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How to Write a Discussion Section | Tips & Examples

Published on August 21, 2022 by Shona McCombes . Revised on July 18, 2023.

Discussion section flow chart

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review and paper or dissertation topic , and making an argument in support of your overall conclusion. It should not be a second results section.

There are different ways to write this section, but you can focus your writing around these key elements:

  • Summary : A brief recap of your key results
  • Interpretations: What do your results mean?
  • Implications: Why do your results matter?
  • Limitations: What can’t your results tell us?
  • Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarize your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example, other interesting articles, frequently asked questions about discussion sections.

There are a few common mistakes to avoid when writing the discussion section of your paper.

  • Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
  • Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
  • Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasize weaknesses or failures.

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Start this section by reiterating your research problem and concisely summarizing your major findings. To speed up the process you can use a summarizer to quickly get an overview of all important findings. Don’t just repeat all the data you have already reported—aim for a clear statement of the overall result that directly answers your main research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

  • The results indicate that…
  • The study demonstrates a correlation between…
  • This analysis supports the theory that…
  • The data suggest that…

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

  • Identifying correlations , patterns, and relationships among the data
  • Discussing whether the results met your expectations or supported your hypotheses
  • Contextualizing your findings within previous research and theory
  • Explaining unexpected results and evaluating their significance
  • Considering possible alternative explanations and making an argument for your position

You can organize your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

  • In line with the hypothesis…
  • Contrary to the hypothesized association…
  • The results contradict the claims of Smith (2022) that…
  • The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is y .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

  • Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
  • Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

  • These results build on existing evidence of…
  • The results do not fit with the theory that…
  • The experiment provides a new insight into the relationship between…
  • These results should be taken into account when considering how to…
  • The data contribute a clearer understanding of…
  • While previous research has focused on  x , these results demonstrate that y .

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what to write in the discussion of a research paper

Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

  • If your sample size was small or limited to a specific group of people, explain how generalizability is limited.
  • If you encountered problems when gathering or analyzing data, explain how these influenced the results.
  • If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

  • The generalizability of the results is limited by…
  • The reliability of these data is impacted by…
  • Due to the lack of data on x , the results cannot confirm…
  • The methodological choices were constrained by…
  • It is beyond the scope of this study to…

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done—give concrete ideas for how future work can build on areas that your own research was unable to address.

  • Further research is needed to establish…
  • Future studies should take into account…
  • Avenues for future research include…

Discussion section example

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In the discussion , you explore the meaning and relevance of your research results , explaining how they fit with existing research and theory. Discuss:

  • Your  interpretations : what do the results tell us?
  • The  implications : why do the results matter?
  • The  limitation s : what can’t the results tell us?

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

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  • How to Write Discussions and Conclusions

How to Write Discussions and Conclusions

The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.

What makes an effective discussion?

When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.

A successful discussion section puts your findings in context. It should include:

  • the results of your research,
  • a discussion of related research, and
  • a comparison between your results and initial hypothesis.

Tip: Not all journals share the same naming conventions.

You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts. 

what to write in the discussion of a research paper

Questions to ask yourself:

  • Was my hypothesis correct?
  • If my hypothesis is partially correct or entirely different, what can be learned from the results? 
  • How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic? 
  • Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies? 
  • How can future research build on these observations? What are the key experiments that must be done? 
  • What is the “take-home” message you want your reader to leave with?

How to structure a discussion

Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:

what to write in the discussion of a research paper

Writing Tips

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results! 

What to do

  • Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations. 
  • Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. 
  • Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research. 
  • State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons? 
  • Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions. 
  • If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided. 
  • Be concise. Adding unnecessary detail can distract from the main findings. 

What not to do

Don’t

  • Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion. 
  • Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper. 
  • Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution. 
  • Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design. 
  • Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research. 

Snippets of Effective Discussions:

Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach

Identifying reliable indicators of fitness in polar bears

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The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

  • Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
  • Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
  • Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
  • Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
  • Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

  • Do not be verbose or repetitive; be concise and make your points clearly
  • Avoid the use of jargon or undefined technical language
  • Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
  • Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
  • If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

  • Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
  • References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
  • Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
  • Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

  • Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
  • Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
  • Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
  • Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
  • Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
  • Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
  • The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

  • Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
  • As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
  • Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
  • Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

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6 Steps to Write an Excellent Discussion in Your Manuscript

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Table of Contents

The discussion section in scientific manuscripts might be the last few paragraphs, but its role goes far beyond wrapping up. It’s the part of an article where scientists talk about what they found and what it means, where raw data turns into meaningful insights. Therefore, discussion is a vital component of the article.  

An excellent discussion is well-organized. We bring to you authors a classic 6-step method for writing discussion sections, with examples to illustrate the functions and specific writing logic of each step. Take a look at how you can impress journal reviewers with a concise and focused discussion section!  

Discussion frame structure   

Conventionally, a discussion section has three parts: an introductory paragraph, a few intermediate paragraphs, and a conclusion¹.  Please follow the steps below:  

Steps to Write an Excellent Discussion in Your Manuscript

1.Introduction—mention gaps in previous research¹⁻ ²

Here, you orient the reader to your study. In the first paragraph, it is advisable to mention the research gap your paper addresses.  

Example: This study investigated the cognitive effects of a meat-only diet on adults. While earlier studies have explored the impact of a carnivorous diet on physical attributes and agility, they have not explicitly addressed its influence on cognitively intense tasks involving memory and reasoning.  

2. Summarizing key findings—let your data speak ¹⁻ ²

After you have laid out the context for your study, recapitulate some of its key findings. Also, highlight key data and evidence supporting these findings.  

Example: We found that risk-taking behavior among teenagers correlates with their tendency to invest in cryptocurrencies. Risk takers in this study, as measured by the Cambridge Gambling Task, tended to have an inordinately higher proportion of their savings invested as crypto coins.  

3. Interpreting results—compare with other papers¹⁻²    

Here, you must analyze and interpret any results concerning the research question or hypothesis. How do the key findings of your study help verify or disprove the hypothesis? What practical relevance does your discovery have?  

Example: Our study suggests that higher daily caffeine intake is not associated with poor performance in major sporting events. Athletes may benefit from the cardiovascular benefits of daily caffeine intake without adversely impacting performance.    

Remember, unlike the results section, the discussion ideally focuses on locating your findings in the larger body of existing research. Hence, compare your results with those of other peer-reviewed papers.  

Example: Although Miller et al. (2020) found evidence of such political bias in a multicultural population, our findings suggest that the bias is weak or virtually non-existent among politically active citizens.  

4. Addressing limitations—their potential impact on the results¹⁻²    

Discuss the potential impact of limitations on the results. Most studies have limitations, and it is crucial to acknowledge them in the intermediary paragraphs of the discussion section. Limitations may include low sample size, suspected interference or noise in data, low effect size, etc.  

Example: This study explored a comprehensive list of adverse effects associated with the novel drug ‘X’. However, long-term studies may be needed to confirm its safety, especially regarding major cardiac events.  

5. Implications for future research—how to explore further¹⁻²    

Locate areas of your research where more investigation is needed. Concluding paragraphs of the discussion can explain what research will likely confirm your results or identify knowledge gaps your study left unaddressed.  

Example: Our study demonstrates that roads paved with the plastic-infused compound ‘Y’ are more resilient than asphalt. Future studies may explore economically feasible ways of producing compound Y in bulk.  

6. Conclusion—summarize content¹⁻²    

A good way to wind up the discussion section is by revisiting the research question mentioned in your introduction. Sign off by expressing the main findings of your study.  

Example: Recent observations suggest that the fish ‘Z’ is moving upriver in many parts of the Amazon basin. Our findings provide conclusive evidence that this phenomenon is associated with rising sea levels and climate change, not due to elevated numbers of invasive predators.  

A rigorous and concise discussion section is one of the keys to achieving an excellent paper. It serves as a critical platform for researchers to interpret and connect their findings with the broader scientific context. By detailing the results, carefully comparing them with existing research, and explaining the limitations of this study, you can effectively help reviewers and readers understand the entire research article more comprehensively and deeply¹⁻² , thereby helping your manuscript to be successfully published and gain wider dissemination.  

In addition to keeping this writing guide, you can also use Elsevier Language Services to improve the quality of your paper more deeply and comprehensively. We have a professional editing team covering multiple disciplines. With our profound disciplinary background and rich polishing experience, we can significantly optimize all paper modules including the discussion, effectively improve the fluency and rigor of your articles, and make your scientific research results consistent, with its value reflected more clearly. We are always committed to ensuring the quality of papers according to the standards of top journals, improving the publishing efficiency of scientific researchers, and helping you on the road to academic success. Check us out here !  

Type in wordcount for Standard Total: USD EUR JPY Follow this link if your manuscript is longer than 12,000 words. Upload  

References:   

  • Masic, I. (2018). How to write an efficient discussion? Medical Archives , 72(3), 306. https://doi.org/10.5455/medarh.2018.72.306-307  
  • Şanlı, Ö., Erdem, S., & Tefik, T. (2014). How to write a discussion section? Urology Research & Practice , 39(1), 20–24. https://doi.org/10.5152/tud.2013.049  

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Writing a scientific paper.

  • Writing a lab report
  • INTRODUCTION

Writing a "good" discussion section

"discussion and conclusions checklist" from: how to write a good scientific paper. chris a. mack. spie. 2018., peer review.

  • LITERATURE CITED
  • Bibliography of guides to scientific writing and presenting
  • Presentations
  • Lab Report Writing Guides on the Web

This is is usually the hardest section to write. You are trying to bring out the true meaning of your data without being too long. Do not use words to conceal your facts or reasoning. Also do not repeat your results, this is a discussion.

  • Present principles, relationships and generalizations shown by the results
  • Point out exceptions or lack of correlations. Define why you think this is so.
  • Show how your results agree or disagree with previously published works
  • Discuss the theoretical implications of your work as well as practical applications
  • State your conclusions clearly. Summarize your evidence for each conclusion.
  • Discuss the significance of the results
  •  Evidence does not explain itself; the results must be presented and then explained.
  • Typical stages in the discussion: summarizing the results, discussing whether results are expected or unexpected, comparing these results to previous work, interpreting and explaining the results (often by comparison to a theory or model), and hypothesizing about their generality.
  • Discuss any problems or shortcomings encountered during the course of the work.
  • Discuss possible alternate explanations for the results.
  • Avoid: presenting results that are never discussed; presenting discussion that does not relate to any of the results; presenting results and discussion in chronological order rather than logical order; ignoring results that do not support the conclusions; drawing conclusions from results without logical arguments to back them up. 

CONCLUSIONS

  • Provide a very brief summary of the Results and Discussion.
  • Emphasize the implications of the findings, explaining how the work is significant and providing the key message(s) the author wishes to convey.
  • Provide the most general claims that can be supported by the evidence.
  • Provide a future perspective on the work.
  • Avoid: repeating the abstract; repeating background information from the Introduction; introducing new evidence or new arguments not found in the Results and Discussion; repeating the arguments made in the Results and Discussion; failing to address all of the research questions set out in the Introduction. 

WHAT HAPPENS AFTER I COMPLETE MY PAPER?

 The peer review process is the quality control step in the publication of ideas.  Papers that are submitted to a journal for publication are sent out to several scientists (peers) who look carefully at the paper to see if it is "good science".  These reviewers then recommend to the editor of a journal whether or not a paper should be published. Most journals have publication guidelines. Ask for them and follow them exactly.    Peer reviewers examine the soundness of the materials and methods section.  Are the materials and methods used written clearly enough for another scientist to reproduce the experiment?  Other areas they look at are: originality of research, significance of research question studied, soundness of the discussion and interpretation, correct spelling and use of technical terms, and length of the article.

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Organizing Academic Research Papers: 8. The Discussion

  • Purpose of Guide
  • Design Flaws to Avoid
  • Glossary of Research Terms
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
  • Extending the Timeliness of a Topic Idea
  • Academic Writing Style
  • Choosing a Title
  • Making an Outline
  • Paragraph Development
  • Executive Summary
  • Background Information
  • The Research Problem/Question
  • Theoretical Framework
  • Citation Tracking
  • Content Alert Services
  • Evaluating Sources
  • Primary Sources
  • Secondary Sources
  • Tertiary Sources
  • What Is Scholarly vs. Popular?
  • Qualitative Methods
  • Quantitative Methods
  • Using Non-Textual Elements
  • Limitations of the Study
  • Common Grammar Mistakes
  • Avoiding Plagiarism
  • Footnotes or Endnotes?
  • Further Readings
  • Annotated Bibliography
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • How to Manage Group Projects
  • Multiple Book Review Essay
  • Reviewing Collected Essays
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Research Proposal
  • Acknowledgements

The purpose of the discussion is to interpret and describe the significance of your findings in light of what was already known about the research problem being investigated, and to explain any new understanding or fresh insights about the problem after you've taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but it does not simply repeat or rearrange the introduction; the discussion should always explain how your study has moved the reader's understanding of the research problem forward from where you left them at the end of the introduction.

Importance of a Good Discussion

This section is often considered the most important part of a research paper because it most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based on the findings, and to formulate a deeper, more profound understanding of the research problem you are studying.

The discussion section is where you explore the underlying meaning of your research , its possible implications in other areas of study, and the possible improvements that can be made in order to further develop the concerns of your research.

This is the section where you need to present the importance of your study and how it may be able to contribute to and/or fill existing gaps in the field. If appropriate, the discussion section is also where you state how the findings from your study revealed new gaps in the literature that had not been previously exposed or adequately described.

This part of the paper is not strictly governed by objective reporting of information but, rather, it is where you can engage in creative thinking about issues through evidence-based interpretation of findings. This is where you infuse your results with meaning.

Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section . San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

  • Do not be verbose or repetitive.
  • Be concise and make your points clearly.
  • Avoid using jargon.
  • Follow a logical stream of thought.
  • Use the present verb tense, especially for established facts; however, refer to specific works and references in the past tense.
  • If needed, use subheadings to help organize your presentation or to group your interpretations into themes.

II.  The Content

The content of the discussion section of your paper most often includes :

  • Explanation of results : comment on whether or not the results were expected and present explanations for the results; go into greater depth when explaining findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning.
  • References to previous research : compare your results with the findings from other studies, or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results than being part of the general research you cited to provide context and background information.
  • Deduction : a claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or recommending best practices.
  • Hypothesis : a more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research].

III. Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

  • Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
  • Use the same key terms, mode of narration, and verb tense [present] that you used when when describing the research problem in the introduction.
  • Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
  • Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequencing of providing this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data. The order of interpreting each major finding should be in the same order as they were described in your results section.
  • A good discussion section includes analysis of any unexpected findings. This paragraph should begin with a description of the unexpected finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each them in the order they appeared as you gathered the data.
  • Before concluding the discussion, identify potential limitations and weaknesses. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of the findings. Avoid using an apologetic tone; however, be honest and self-critical.
  • The discussion section should end with a concise summary of the principal implications of the findings regardless of statistical significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This demonstrates to the reader you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate for your readers the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the meaning of the findings and why you believe they are important. After reading the discussion section, you want the reader to think about the results [“why hadn’t I thought of that?”]. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. Begin this part of the section by repeating what you consider to be your most important finding first.

III.  Relate the Findings to Similar Studies

No study is so novel or possesses such a restricted focus that it has absolutely no relation to other previously published research. The discussion section should relate your study findings to those of other studies, particularly if questions raised by previous studies served as the motivation for your study, the findings of other studies support your findings [which strengthens the importance of your study results], and/or they point out how your study differs from other similar studies. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your prior assumptions or biases.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Describe the generalizability of your results to other situations, if applicable to the method chosen, then describe in detail problems you encountered in the method(s) you used to gather information. Note any unanswered questions or issues your study did not address, and.... VI.  Make Suggestions for Further Research

Although your study may offer important insights about the research problem, other questions related to the problem likely remain unanswered. Moreover, some unanswered questions may have become more focused because of your study. You should make suggestions for further research in the discussion section.

NOTE: Besides the literature review section, the preponderance of references to sources in your research paper are usually found in the discussion section . A few historical references may be helpful for perspective but most of the references should be relatively recent and included to aid in the interpretation of your results and/or linked to similar studies. If a study that you cited disagrees with your findings, don't ignore it--clearly explain why the study's findings differ from yours.

V.  Problems to Avoid

  • Do not waste entire sentences restating your results . Should you need to remind the reader of the finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “The lack of available housing to single women with children in rural areas of Texas suggests that...[then move to the interpretation of this finding].”
  • Recommendations for further research can be included in either the discussion or conclusion of your paper but do not repeat your recommendations in the both sections.
  • Do not introduce new results in the discussion. Be wary of mistaking the reiteration of a specific finding for an interpretation.
  • Use of the first person is acceptable, but too much use of the first person may actually distract the reader from the main points.

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. How to Write an Effective Discussion. Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section . San Francisco Edit, 2003-2008; The Lab Report . University College Writing Centre. University of Toronto; Summary: Using it Wisely . The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion . Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide. Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Overinterpret the Results!

Interpretation is a subjective exercise. Therefore, be careful that you do not read more into the findings than can be supported by the evidence you've gathered. Remember that the data are the data: nothing more, nothing less.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretion of those results, not just the data itself.

Azar, Beth. Discussing Your Findings.  American Psychological Association gradPSYCH Magazine (January 2006)

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if you studied the impact of foreign aid on increasing levels of education among the poor in Bangladesh, it's generally not appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim. If you feel compelled to speculate, be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand the discussion in this way, while others don’t care what your opinion is beyond your efforts to interpret the data.

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General research paper guidelines: discussion, discussion section.

The overall purpose of a research paper’s discussion section is to evaluate and interpret results, while explaining both the implications and limitations of your findings. Per APA (2020) guidelines, this section requires you to “examine, interpret, and qualify the results and draw inferences and conclusions from them” (p. 89). Discussion sections also require you to detail any new insights, think through areas for future research, highlight the work that still needs to be done to further your topic, and provide a clear conclusion to your research paper. In a good discussion section, you should do the following:

  • Clearly connect the discussion of your results to your introduction, including your central argument, thesis, or problem statement.
  • Provide readers with a critical thinking through of your results, answering the “so what?” question about each of your findings. In other words, why is this finding important?
  • Detail how your research findings might address critical gaps or problems in your field
  • Compare your results to similar studies’ findings
  • Provide the possibility of alternative interpretations, as your goal as a researcher is to “discover” and “examine” and not to “prove” or “disprove.” Instead of trying to fit your results into your hypothesis, critically engage with alternative interpretations to your results.

For more specific details on your Discussion section, be sure to review Sections 3.8 (pp. 89-90) and 3.16 (pp. 103-104) of your 7 th edition APA manual

*Box content adapted from:

University of Southern California (n.d.). Organizing your social sciences research paper: 8 the discussion . https://libguides.usc.edu/writingguide/discussion

Limitations

Limitations of generalizability or utility of findings, often over which the researcher has no control, should be detailed in your Discussion section. Including limitations for your reader allows you to demonstrate you have thought critically about your given topic, understood relevant literature addressing your topic, and chosen the methodology most appropriate for your research. It also allows you an opportunity to suggest avenues for future research on your topic. An effective limitations section will include the following:

  • Detail (a) sources of potential bias, (b) possible imprecision of measures, (c) other limitations or weaknesses of the study, including any methodological or researcher limitations.
  • Sample size: In quantitative research, if a sample size is too small, it is more difficult to generalize results.
  • Lack of available/reliable data : In some cases, data might not be available or reliable, which will ultimately affect the overall scope of your research. Use this as an opportunity to explain areas for future study.
  • Lack of prior research on your study topic: In some cases, you might find that there is very little or no similar research on your study topic, which hinders the credibility and scope of your own research. If this is the case, use this limitation as an opportunity to call for future research. However, make sure you have done a thorough search of the available literature before making this claim.
  • Flaws in measurement of data: Hindsight is 20/20, and you might realize after you have completed your research that the data tool you used actually limited the scope or results of your study in some way. Again, acknowledge the weakness and use it as an opportunity to highlight areas for future study.
  • Limits of self-reported data: In your research, you are assuming that any participants will be honest and forthcoming with responses or information they provide to you. Simply acknowledging this assumption as a possible limitation is important in your research.
  • Access: Most research requires that you have access to people, documents, organizations, etc.. However, for various reasons, access is sometimes limited or denied altogether. If this is the case, you will want to acknowledge access as a limitation to your research.
  • Time: Choosing a research focus that is narrow enough in scope to finish in a given time period is important. If such limitations of time prevent you from certain forms of research, access, or study designs, acknowledging this time restraint is important. Acknowledging such limitations is important, as they can point other researchers to areas that require future study.
  • Potential Bias: All researchers have some biases, so when reading and revising your draft, pay special attention to the possibilities for bias in your own work. Such bias could be in the form you organized people, places, participants, or events. They might also exist in the method you selected or the interpretation of your results. Acknowledging such bias is an important part of the research process.
  • Language Fluency: On occasion, researchers or research participants might have language fluency issues, which could potentially hinder results or how effectively you interpret results. If this is an issue in your research, make sure to acknowledge it in your limitations section.

University of Southern California (n.d.). Organizing your social sciences research paper: Limitations of the study . https://libguides.usc.edu/writingguide/limitations

In many research papers, the conclusion, like the limitations section, is folded into the larger discussion section. If you are unsure whether to include the conclusion as part of your discussion or as a separate section, be sure to defer to the assignment instructions or ask your instructor.

The conclusion is important, as it is specifically designed to highlight your research’s larger importance outside of the specific results of your study. Your conclusion section allows you to reiterate the main findings of your study, highlight their importance, and point out areas for future research. Based on the scope of your paper, your conclusion could be anywhere from one to three paragraphs long. An effective conclusion section should include the following:

  • Describe the possibilities for continued research on your topic, including what might be improved, adapted, or added to ensure useful and informed future research.
  • Provide a detailed account of the importance of your findings
  • Reiterate why your problem is important, detail how your interpretation of results impacts the subfield of study, and what larger issues both within and outside of your field might be affected from such results

University of Southern California (n.d.). Organizing your social sciences research paper: 9. the conclusion . https://libguides.usc.edu/writingguide/conclusion

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Study Skills

Writing a discussion section

In the discussion section, you will draw connections between your findings, existing theory and other research. You will have an opportunity to tell the story arising from your findings. 

This page will help you to: 

understand the purpose of the discussion section 

follow the steps required to plan your discussion section 

structure your discussion  

enhance the depth of your discussion 

use appropriate language to discuss your findings.  

Introduction to the discussion section

When you have reached this stage, you might be thinking “All I have to do now is to sum up what I have done, and then make a few remarks about what I did” (as cited in Swales & Feak, 2012, p.263). However, writing a discussion section is not that simple. Read on to learn more.

reflection icon

  Before you continue, reflect on your earlier writing experiences and the feedback you have received. How would you rate your ability in the following skills? Rate your ability from ‘good’ to ‘needs development’. 

Reflect on your answers. Congratulations if you feel confident about your skills. You may find it helpful to review the materials on this page to confirm your knowledge and possibly learn more. Don't worry if you don't feel confident. Work through these materials to build your skills. 

A discussion critically analyses and interprets the results of a scientific study, placing the results in the context of published literature and explaining how they affect the field . 

In this section, you will relate the specific findings of your research to the wider scientific field. This is the opposite of the introduction section, which starts with the broader context and narrows to focus on your specific research topic.  

The discussion will: 

review the findings  

put the findings into the context of the overall research  

tell readers why the research results are important and where they fit in with the current literature 

acknowledge the limitations of the study 

make recommendations for future research.

study skills task icon

Let's review your understanding of the discussion section by identifying what makes a strong discussion.

Planning for a discussion section

Planning for a discussion section starts with analysing your data. For some kinds of research, the analysis cannot be done until your data has been collected. For others, analysing data can happen early as the data already exists in literary texts, archival documents or similar.  

Before starting to write the discussion section, it is important to:  

analyse your data (usually reported in the Results or Findings section) 

select the key issues that are the substance of your research  

relate the findings to the literature and 

plan for the process of going from your specific findings to the broader scientific field.  

Your analysis of the results will inform the Findings or Results section of your thesis or publication. It is the stage where you organise and visualise your data, and identify trends, patterns and causal relationships in the themes.

As the section discusses the key findings without restating the results, it is important to identify the key issues. For example, you should focus on four or five issues that agree or do not agree with your hypothesis or with previously published work. It is also important to include and discuss any unexpected results.

You refer to previous research in your discussion section for explaining your results, confirming how your results support the theories and previous studies, comparing your results with similar studies, or showing how your results contradict similar studies. 

Therefore, papers that you are likely to refer to in your discussion are those that led to: 

your hypothesis  

your experimental design 

your results.

In writing the discussion section, you will start with your research and then broaden your focus to the field or scientific community. This means you will go from narrowest (your specific findings) to broadest (the wider scientific community). You do this by following the six moves: 

Narrowest      Summarising key results   Critically analysing the key results (significance, trends, relationships)  Relating results to the field (relating to previous work)   Relating results to gaps in the field   Speculating about how the field has changed.   Making recommendations for future research.      Broadest

As you can see, your discussion may follow six moves (stages) which broadens the scope of your discussion section. Watch this video to learn how to apply these moves.

what to write in the discussion of a research paper

Structuring your discussion

This section reviews how a discussion section can be organised.

A discussion section usually includes five parts or steps, which are illustrated in the image below. 

In some disciplines, the researcher's argument determines the structure of the presentation and discussion of findings. In other disciplines, the structure follows established conventions. Therefore, it is important for you to investigate the conventions of your own discipline, by looking at theses in your discipline and articles published in your target journals. The discussion section may be: 

in a combined section called Results and Discussion 

in a combined section called Discussion and Conclusion 

in a separate section. 

Your discussion section may be an independent chapter or it might be combined with the Findings chapter. Common chapter headings include:  

Discussion chapter 

Findings and Discussion chapter  

Discussion, Recommendations and Conclusion chapter

Discussion and Conclusion chapter 

It is important to have a good understanding of the expected content of each chapter.  Below is an example of a chapter in which discussion, recommendations and conclusion are combined.

Click on the hotspots to learn more.

This section focuses on useful language for writing your discussion.

Boosters and hedges should be used to demonstrate your confidence in your interpretation of the results. They help you to distinguish between clear and strong results and those that you feel less confident about or that may be open to different interpretations.

 Boosters       Boosters are used to express certainty and confidence.  Hedges       Hedges are used to express possibility and demonstrate a cautious approach to the literature being reviewed.       Maybe   Perhaps   Likely   Possibly   Seems   Appears   To some extent   Some   Somewhat   Suggest       Example:           Clearly   Obviously   Evidently   Undoubtedly   Importantly   Differently           Example:       It is evident that…   The findings clearly demonstrate that…   There is strong evidence…

 Read both sentences. Which one shows more confidence in the results? 

The Dutch supervisors reported using different types of questions more frequently and deliberately than the Chinese supervisors. This difference may have its roots in the underlying educational philosophies. (Adapted from Hu, Rijst, Veen, & Verloop, 2016)  

The findings clearly demonstrate that psychological capital had considerable influence on the 10 employability skills included in the study, and especially on those related to teamwork, self-knowledge and self-management (Adapted from Harper, Bregta & Rundle, 2021) 

The writers of sentence two are more confident in the interpretation of their results.  

Test your knowledge of hedges and boosters by doing the task below. 

It is important to make it clear in your discussion: 

which research has been done by you 

which research has been done by other people 

how they complement each other.

Image 2: Note that present perfect is also used to refer to other studies when you want to emphasise that an area of research is still current and ongoing. Take a look at the example below which uses present perfect to refer to other studies 

Like other studies (e.g., Larcombe et al., 2021; Naylor, 2020) that have shown a strong connection between course experience and wellbeing, our study shows that a significant portion of international students believe that aspects of their immediate environment could be improved to better support their wellbeing.  

More information on tenses in the Discussion section is presented in Language Tip 4 below.  

Below are some useful discussion phrases that were adapted from Paltridge & Starfield (2020) and the APA Discussion phrases guide (7th edition).

You can download this APA discussion phrase guide here and visit the Academic Phrasebank for further phrases and examples. 

Let's look at these extracts and identify the functions of the paragraphs.  

Past, present and present perfect tenses are commonly used in the discussion section.  

  • Past tense is used to summarise the key findings and to refer to the work of previous researchers  
  • Present perfect is used to refer to the work of previous researchers (usually an area of research that is current and on-going rather than one single study) 
  • Present tense is used to interpret the results or describe the significance of the findings  
  • Future  is used to make recommendations for further research or providing future direction 

Below is an example of some paragraphs in a discussion section in which different tenses are used.

The main objective of this article was to examine the role played by psychological capital and employability skills in explaining how final-year students in Business Administration and Management perceived their own employability. The results of our research supported the findings of previous studies (Cooper et al., 2004; Youssef & Luthans, 2007) which showed that psychological capital was an antecedent variable of employability skills. More specifically, our study showed that psychological capital had cons

Test your knowledge of using the right tenses in the discussion section by doing the task below. 

Use this template to plan your discussion.  

The template is an example of a planning tool that will help you develop an overview of the key content that you are going to include in your section. You can download the draft and save it as a Word document once you have finished. 

You may have more or less than 3 key findings that you would like to discuss in your section.  

If you would like more support, visit the Language and Learning Advisors page. 

Butler, K. (2020, 7 April). Breakdown of an ideal discussion of scientific research paper. Scientific Communications . https://butlerscicomm.com/breakdown-of-ideal-discussion-section-research-paper  

Calvo, J. C. A & García, G. M. (2021). The influence of psychological capital on graduates’ perception of employability: the mediating role of employability skills. Higher Education Research & Development , 40(2), 293-308, DOI: 10.1080/07294360.2020.1738350   

Cenamor, J. (2022) To teach or not to teach? Junior academics and the teaching-research relationship. Higher Education Research & Development , 41(5), 1417-1435. DOI: 10.1080/07294360.2021.1933395  

Harper, R.,  Bretag, T & Rundle, K. (2021) Detecting contract cheating: examining the role of assessment type. Higher Education Research & Development, 40(2), 263-278, DOI: 10.1080/07294360.2020.1724899   

Hu, Y., Rijst, R. M., Veen, K & N Verloop, N. (2016) The purposes and processes of master's thesis supervision: a comparison of Chinese and Dutch supervisors. Higher Education Research & Development , 35(5), 910-924, DOI: 10.1080/07294360.2016.1139550  

Humphrey, P. (2015). English language proficiency in higher education: student conceptualisations and outcomes . [Doctoral dissertation, Griffith University]  

Marangell, S., & Baik, C. (2022). International students’ suggestions for what universities can do to better support their mental wellbeing. Journal of International Students, 12(4), 933-954.  

Merga, M., & Mason, S. (2021) Early career researchers’ perceptions of the benefits and challenges of sharing research with academic and non-academic end-users, Higher Education Research & Development , 40(7), 1482-1496, DOI: 10.1080/07294360.2020.1815662  

Paltridge, B., & Starfield, S. (2019). Thesis and Dissertation Writing in a Second Language: A Handbook for Students and their Supervisors (2nd ed.). Routledge.  

Rendle-Short, J. (2009). The Address Term Mate in Australian English: Is it Still a Masculine Term?. Australian Journal of Linguistics, 29(2), 245-268, DOI: 10.1080/07268600902823110  

Did you know CDU Language and Learning Advisors offer a range of study support options?

https://www.cdu.edu.au/library/language-and-learning-support

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How to Write a Discussion Section for a Research Paper

what to write in the discussion of a research paper

We’ve talked about several useful writing tips that authors should consider while drafting or editing their research papers. In particular, we’ve focused on  figures and legends , as well as the Introduction ,  Methods , and  Results . Now that we’ve addressed the more technical portions of your journal manuscript, let’s turn to the analytical segments of your research article. In this article, we’ll provide tips on how to write a strong Discussion section that best portrays the significance of your research contributions.

What is the Discussion section of a research paper?

In a nutshell,  your Discussion fulfills the promise you made to readers in your Introduction . At the beginning of your paper, you tell us why we should care about your research. You then guide us through a series of intricate images and graphs that capture all the relevant data you collected during your research. We may be dazzled and impressed at first, but none of that matters if you deliver an anti-climactic conclusion in the Discussion section!

Are you feeling pressured? Don’t worry. To be honest, you will edit the Discussion section of your manuscript numerous times. After all, in as little as one to two paragraphs ( Nature ‘s suggestion  based on their 3,000-word main body text limit), you have to explain how your research moves us from point A (issues you raise in the Introduction) to point B (our new understanding of these matters). You must also recommend how we might get to point C (i.e., identify what you think is the next direction for research in this field). That’s a lot to say in two paragraphs!

So, how do you do that? Let’s take a closer look.

What should I include in the Discussion section?

As we stated above, the goal of your Discussion section is to  answer the questions you raise in your Introduction by using the results you collected during your research . The content you include in the Discussions segment should include the following information:

  • Remind us why we should be interested in this research project.
  • Describe the nature of the knowledge gap you were trying to fill using the results of your study.
  • Don’t repeat your Introduction. Instead, focus on why  this  particular study was needed to fill the gap you noticed and why that gap needed filling in the first place.
  • Mainly, you want to remind us of how your research will increase our knowledge base and inspire others to conduct further research.
  • Clearly tell us what that piece of missing knowledge was.
  • Answer each of the questions you asked in your Introduction and explain how your results support those conclusions.
  • Make sure to factor in all results relevant to the questions (even if those results were not statistically significant).
  • Focus on the significance of the most noteworthy results.
  • If conflicting inferences can be drawn from your results, evaluate the merits of all of them.
  • Don’t rehash what you said earlier in the Results section. Rather, discuss your findings in the context of answering your hypothesis. Instead of making statements like “[The first result] was this…,” say, “[The first result] suggests [conclusion].”
  • Do your conclusions line up with existing literature?
  • Discuss whether your findings agree with current knowledge and expectations.
  • Keep in mind good persuasive argument skills, such as explaining the strengths of your arguments and highlighting the weaknesses of contrary opinions.
  • If you discovered something unexpected, offer reasons. If your conclusions aren’t aligned with current literature, explain.
  • Address any limitations of your study and how relevant they are to interpreting your results and validating your findings.
  • Make sure to acknowledge any weaknesses in your conclusions and suggest room for further research concerning that aspect of your analysis.
  • Make sure your suggestions aren’t ones that should have been conducted during your research! Doing so might raise questions about your initial research design and protocols.
  • Similarly, maintain a critical but unapologetic tone. You want to instill confidence in your readers that you have thoroughly examined your results and have objectively assessed them in a way that would benefit the scientific community’s desire to expand our knowledge base.
  • Recommend next steps.
  • Your suggestions should inspire other researchers to conduct follow-up studies to build upon the knowledge you have shared with them.
  • Keep the list short (no more than two).

How to Write the Discussion Section

The above list of what to include in the Discussion section gives an overall idea of what you need to focus on throughout the section. Below are some tips and general suggestions about the technical aspects of writing and organization that you might find useful as you draft or revise the contents we’ve outlined above.

Technical writing elements

  • Embrace active voice because it eliminates the awkward phrasing and wordiness that accompanies passive voice.
  • Use the present tense, which should also be employed in the Introduction.
  • Sprinkle with first person pronouns if needed, but generally, avoid it. We want to focus on your findings.
  • Maintain an objective and analytical tone.

Discussion section organization

  • Keep the same flow across the Results, Methods, and Discussion sections.
  • We develop a rhythm as we read and parallel structures facilitate our comprehension. When you organize information the same way in each of these related parts of your journal manuscript, we can quickly see how a certain result was interpreted and quickly verify the particular methods used to produce that result.
  • Notice how using parallel structure will eliminate extra narration in the Discussion part since we can anticipate the flow of your ideas based on what we read in the Results segment. Reducing wordiness is important when you only have a few paragraphs to devote to the Discussion section!
  • Within each subpart of a Discussion, the information should flow as follows: (A) conclusion first, (B) relevant results and how they relate to that conclusion and (C) relevant literature.
  • End with a concise summary explaining the big-picture impact of your study on our understanding of the subject matter. At the beginning of your Discussion section, you stated why  this  particular study was needed to fill the gap you noticed and why that gap needed filling in the first place. Now, it is time to end with “how your research filled that gap.”

Discussion Part 1: Summarizing Key Findings

Begin the Discussion section by restating your  statement of the problem  and briefly summarizing the major results. Do not simply repeat your findings. Rather, try to create a concise statement of the main results that directly answer the central research question that you stated in the Introduction section . This content should not be longer than one paragraph in length.

Many researchers struggle with understanding the precise differences between a Discussion section and a Results section . The most important thing to remember here is that your Discussion section should subjectively evaluate the findings presented in the Results section, and in relatively the same order. Keep these sections distinct by making sure that you do not repeat the findings without providing an interpretation.

Phrase examples: Summarizing the results

  • The findings indicate that …
  • These results suggest a correlation between A and B …
  • The data present here suggest that …
  • An interpretation of the findings reveals a connection between…

Discussion Part 2: Interpreting the Findings

What do the results mean? It may seem obvious to you, but simply looking at the figures in the Results section will not necessarily convey to readers the importance of the findings in answering your research questions.

The exact structure of interpretations depends on the type of research being conducted. Here are some common approaches to interpreting data:

  • Identifying correlations and relationships in the findings
  • Explaining whether the results confirm or undermine your research hypothesis
  • Giving the findings context within the history of similar research studies
  • Discussing unexpected results and analyzing their significance to your study or general research
  • Offering alternative explanations and arguing for your position

Organize the Discussion section around key arguments, themes, hypotheses, or research questions or problems. Again, make sure to follow the same order as you did in the Results section.

Discussion Part 3: Discussing the Implications

In addition to providing your own interpretations, show how your results fit into the wider scholarly literature you surveyed in the  literature review section. This section is called the implications of the study . Show where and how these results fit into existing knowledge, what additional insights they contribute, and any possible consequences that might arise from this knowledge, both in the specific research topic and in the wider scientific domain.

Questions to ask yourself when dealing with potential implications:

  • Do your findings fall in line with existing theories, or do they challenge these theories or findings? What new information do they contribute to the literature, if any? How exactly do these findings impact or conflict with existing theories or models?
  • What are the practical implications on actual subjects or demographics?
  • What are the methodological implications for similar studies conducted either in the past or future?

Your purpose in giving the implications is to spell out exactly what your study has contributed and why researchers and other readers should be interested.

Phrase examples: Discussing the implications of the research

  • These results confirm the existing evidence in X studies…
  • The results are not in line with the foregoing theory that…
  • This experiment provides new insights into the connection between…
  • These findings present a more nuanced understanding of…
  • While previous studies have focused on X, these results demonstrate that Y.

Step 4: Acknowledging the limitations

All research has study limitations of one sort or another. Acknowledging limitations in methodology or approach helps strengthen your credibility as a researcher. Study limitations are not simply a list of mistakes made in the study. Rather, limitations help provide a more detailed picture of what can or cannot be concluded from your findings. In essence, they help temper and qualify the study implications you listed previously.

Study limitations can relate to research design, specific methodological or material choices, or unexpected issues that emerged while you conducted the research. Mention only those limitations directly relate to your research questions, and explain what impact these limitations had on how your study was conducted and the validity of any interpretations.

Possible types of study limitations:

  • Insufficient sample size for statistical measurements
  • Lack of previous research studies on the topic
  • Methods/instruments/techniques used to collect the data
  • Limited access to data
  • Time constraints in properly preparing and executing the study

After discussing the study limitations, you can also stress that your results are still valid. Give some specific reasons why the limitations do not necessarily handicap your study or narrow its scope.

Phrase examples: Limitations sentence beginners

  • “There may be some possible limitations in this study.”
  • “The findings of this study have to be seen in light of some limitations.”
  •  “The first limitation is the…The second limitation concerns the…”
  •  “The empirical results reported herein should be considered in the light of some limitations.”
  • “This research, however, is subject to several limitations.”
  • “The primary limitation to the generalization of these results is…”
  • “Nonetheless, these results must be interpreted with caution and a number of limitations should be borne in mind.”

Discussion Part 5: Giving Recommendations for Further Research

Based on your interpretation and discussion of the findings, your recommendations can include practical changes to the study or specific further research to be conducted to clarify the research questions. Recommendations are often listed in a separate Conclusion section , but often this is just the final paragraph of the Discussion section.

Suggestions for further research often stem directly from the limitations outlined. Rather than simply stating that “further research should be conducted,” provide concrete specifics for how future can help answer questions that your research could not.

Phrase examples: Recommendation sentence beginners

  • Further research is needed to establish …
  • There is abundant space for further progress in analyzing…
  • A further study with more focus on X should be done to investigate…
  • Further studies of X that account for these variables must be undertaken.

Consider Receiving Professional Language Editing

As you edit or draft your research manuscript, we hope that you implement these guidelines to produce a more effective Discussion section. And after completing your draft, don’t forget to submit your work to a professional proofreading and English editing service like Wordvice, including our manuscript editing service for  paper editing , cover letter editing , SOP editing , and personal statement proofreading services. Language editors not only proofread and correct errors in grammar, punctuation, mechanics, and formatting but also improve terms and revise phrases so they read more naturally. Wordvice is an industry leader in providing high-quality revision for all types of academic documents.

For additional information about how to write a strong research paper, make sure to check out our full  research writing series !

Wordvice Writing Resources

  • How to Write a Research Paper Introduction 
  • Which Verb Tenses to Use in a Research Paper
  • How to Write an Abstract for a Research Paper
  • How to Write a Research Paper Title
  • Useful Phrases for Academic Writing
  • Common Transition Terms in Academic Papers
  • Active and Passive Voice in Research Papers
  • 100+ Verbs That Will Make Your Research Writing Amazing
  • Tips for Paraphrasing in Research Papers

Additional Academic Resources

  •   Guide for Authors.  (Elsevier)
  •  How to Write the Results Section of a Research Paper.  (Bates College)
  •   Structure of a Research Paper.  (University of Minnesota Biomedical Library)
  •   How to Choose a Target Journal  (Springer)
  •   How to Write Figures and Tables  (UNC Writing Center)
  • SpringerLink shop

Discussion and Conclusions

Your Discussion and Conclusions sections should answer the question: What do your results mean?

In other words, the majority of the Discussion and Conclusions sections should be an interpretation of your results. You should:

  • Discuss your conclusions in order of  most to least important.
  • Compare  your results with those from other studies: Are they consistent? If not, discuss possible reasons for the difference.
  • Mention any  inconclusive results  and explain them as best you can. You may suggest additional experiments needed to clarify your results.
  • Briefly describe the  limitations  of your study to show reviewers and readers that you have considered your experiment’s weaknesses. Many researchers are hesitant to do this as they feel it highlights the weaknesses in their research to the editor and reviewer. However doing this actually makes a positive impression of your paper as it makes it clear that you have an in depth understanding of your topic and can think objectively of your research.
  • Discuss  what your results may mean  for researchers in the same field as you, researchers in other fields, and the general public. How could your findings be applied?
  • State how your results  extend the findings  of previous studies.
  • If your findings are preliminary, suggest  future studies  that need to be carried out.
  • At the end of your Discussion and Conclusions sections,  state your main conclusions once again .

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how to write a discussion section

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The discussion section of a research paper is where the author analyzes and explains the importance of the study's results. It presents the conclusions drawn from the study, compares them to previous research, and addresses any potential limitations or weaknesses. The discussion section should also suggest areas for future research.

Everything is not that complicated if you know where to find the required information. We’ll tell you everything there is to know about writing your discussion. Our easy guide covers all important bits, including research questions and your research results. Do you know how all enumerated events are connected? Well, you will after reading this guide we’ve prepared for you!

What Is in the Discussion Section of a Research Paper

The discussion section of a research paper can be viewed as something similar to the conclusion of your paper. But not literal, of course. It’s an ultimate section where you can talk about the findings of your study. Think about these questions when writing:

  • Did you answer all of the promised research questions?
  • Did you mention why your work matters?
  • What are your findings, and why should anyone even care?
  • Does your study have a literature review?

So, answer your questions, provide proof, and don’t forget about your promises from the introduction. 

How to Write a Discussion Section in 5 Steps

How to write the discussion section of a research paper is something everyone googles eventually. It's just life. But why not make everything easier? In brief, this section we’re talking about must include all following parts:

  • Answers for research questions
  • Literature review
  • Results of the work
  • Limitations of one’s study
  • Overall conclusion

Indeed, all those parts may confuse anyone. So by looking at our guide, you'll save yourself some hassle.  P.S. All our steps are easy and explained in detail! But if you are looking for the most efficient solution, consider using professional help. Leave your “ write my research paper for me ” order at StudyCrumb and get a customized study tailored to your requirements.

Step 1. Start Strong: Discussion Section of a Research Paper

First and foremost, how to start the discussion section of a research paper? Here’s what you should definitely consider before settling down to start writing:

  • All essays or papers must begin strong. All readers will not wait for any writer to get to the point. We advise summarizing the paper's main findings.
  • Moreover, you should relate both discussion and literature review to what you have discovered. Mentioning that would be a plus too.
  • Make sure that an introduction or start per se is clear and concise. Word count might be needed for school. But any paper should be understandable and not too diluted.

Step 2. Answer the Questions in Your Discussion Section of a Research Paper

Writing the discussion section of a research paper also involves mentioning your questions. Remember that in your introduction, you have promised your readers to answer certain questions. Well, now it’s a perfect time to finally give the awaited answer. You need to explain all possible correlations between your findings, research questions, and literature proposed. You already had hypotheses. So were they correct, or maybe you want to propose certain corrections? Section’s main goal is to avoid open ends. It’s not a story or a fairytale with an intriguing ending. If you have several questions, you must answer them. As simple as that.

Step 3. Relate Your Results in a Discussion Section

Writing a discussion section of a research paper also requires any writer to explain their results. You will undoubtedly include an impactful literature review. However, your readers should not just try and struggle with understanding what are some specific relationships behind previous studies and your results.  Your results should sound something like: “This guy in their paper discovered that apples are green. Nevertheless, I have proven via experimentation and research that apples are actually red.” Please, don’t take these results directly. It’s just an initial hypothesis. But what you should definitely remember is any practical implications of your study. Why does it matter and how can anyone use it? That’s the most crucial question.

Step 4. Describe the Limitations in Your Discussion Section

Discussion section of a research paper isn’t limitless. What does that mean? Essentially, it means that you also have to discuss any limitations of your study. Maybe you had some methodological inconsistencies. Possibly, there are no particular theories or not enough information for you to be entirely confident in one’s conclusions.  You might say that an available source of literature you have studied does not focus on one’s issue. That’s why one’s main limitation is theoretical. However, keep in mind that your limitations must possess a certain degree of relevancy. You can just say that you haven’t found enough books. Your information must be truthful to research.

Step 5. Conclude Your Discussion Section With Recommendations

Your last step when you write a discussion section in a paper is its conclusion, like in any other academic work. Writer’s conclusion must be as strong as their starting point of the overall work. Check out our brief list of things to know about the conclusion in research paper :

  • It must present its scientific relevance and importance of your work.
  • It should include different implications of your research.
  • It should not, however, discuss anything new or things that you have not mentioned before.
  • Leave no open questions and carefully complete the work without them.

Discussion Section of a Research Paper Example

All the best example discussion sections of a research paper will be written according to our brief guide. Don’t forget that you need to state your findings and underline the importance of your work. An undoubtedly big part of one’s discussion will definitely be answering and explaining the research questions. In other words, you’ll already have all the knowledge you have so carefully gathered. Our last step for you is to recollect and wrap up your paper. But we’re sure you’ll succeed!

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How to Write a Discussion Section: Final Thoughts

Today we have covered how to write a discussion section. That was quite a brief journey, wasn’t it? Just to remind you to focus on these things:

  • Importance of your study.
  • Summary of the information you have gathered.
  • Main findings and conclusions.
  • Answers to all research questions without an open end.
  • Correlation between literature review and your results.

But, wait, this guide is not the only thing we can do. Looking for how to write an abstract for a research paper  for example? We have such a blog and much more on our platform.

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Our academic writing service is just a click away. We are proud to say that our writers are professionals in their fields. Buy a research paper and our experts can provide prompt solutions without compromising the quality.

Discussion Section of a Research Paper: Frequently Asked Questions

1. how long should the discussion section of a research paper be.

Our discussion section of a research paper should not be longer than other sections. So try to keep it short but as informative as possible. It usually contains around 6-7 paragraphs in length. It is enough to briefly summarize all the important data and not to drag it.

2. What's the difference between the discussion and the results?

The difference between discussion and results is very simple and easy to understand. The results only report your main findings. You stated what you have found and how you have done that. In contrast, one’s discussion mentions your findings and explains how they relate to other literature, research questions, and one’s hypothesis. Therefore, it is not only a report but an efficient as well as proper explanation.

3. What's the difference between a discussion and a conclusion?

The difference between discussion and conclusion is also quite easy. Conclusion is a brief summary of all the findings and results. Still, our favorite discussion section interprets and explains your main results. It is an important but more lengthy and wordy part. Besides, it uses extra literature for references.

4. What is the purpose of the discussion section?

The primary purpose of a discussion section is to interpret and describe all your interesting findings. Therefore, you should state what you have learned, whether your hypothesis was correct and how your results can be explained using other sources. If this section is clear to readers, our congratulations as you have succeeded.

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How to Write the Discussion Section of a Research Paper

The discussion section of a research paper analyzes and interprets the findings, provides context, compares them with previous studies, identifies limitations, and suggests future research directions.

Updated on September 15, 2023

researchers writing the discussion section of their research paper

Structure your discussion section right, and you’ll be cited more often while doing a greater service to the scientific community. So, what actually goes into the discussion section? And how do you write it?

The discussion section of your research paper is where you let the reader know how your study is positioned in the literature, what to take away from your paper, and how your work helps them. It can also include your conclusions and suggestions for future studies.

First, we’ll define all the parts of your discussion paper, and then look into how to write a strong, effective discussion section for your paper or manuscript.

Discussion section: what is it, what it does

The discussion section comes later in your paper, following the introduction, methods, and results. The discussion sets up your study’s conclusions. Its main goals are to present, interpret, and provide a context for your results.

What is it?

The discussion section provides an analysis and interpretation of the findings, compares them with previous studies, identifies limitations, and suggests future directions for research.

This section combines information from the preceding parts of your paper into a coherent story. By this point, the reader already knows why you did your study (introduction), how you did it (methods), and what happened (results). In the discussion, you’ll help the reader connect the ideas from these sections.

Why is it necessary?

The discussion provides context and interpretations for the results. It also answers the questions posed in the introduction. While the results section describes your findings, the discussion explains what they say. This is also where you can describe the impact or implications of your research.

Adds context for your results

Most research studies aim to answer a question, replicate a finding, or address limitations in the literature. These goals are first described in the introduction. However, in the discussion section, the author can refer back to them to explain how the study's objective was achieved. 

Shows what your results actually mean and real-world implications

The discussion can also describe the effect of your findings on research or practice. How are your results significant for readers, other researchers, or policymakers?

What to include in your discussion (in the correct order)

A complete and effective discussion section should at least touch on the points described below.

Summary of key findings

The discussion should begin with a brief factual summary of the results. Concisely overview the main results you obtained.

Begin with key findings with supporting evidence

Your results section described a list of findings, but what message do they send when you look at them all together?

Your findings were detailed in the results section, so there’s no need to repeat them here, but do provide at least a few highlights. This will help refresh the reader’s memory and help them focus on the big picture.

Read the first paragraph of the discussion section in this article (PDF) for an example of how to start this part of your paper. Notice how the authors break down their results and follow each description sentence with an explanation of why each finding is relevant. 

State clearly and concisely

Following a clear and direct writing style is especially important in the discussion section. After all, this is where you will make some of the most impactful points in your paper. While the results section often contains technical vocabulary, such as statistical terms, the discussion section lets you describe your findings more clearly. 

Interpretation of results

Once you’ve given your reader an overview of your results, you need to interpret those results. In other words, what do your results mean? Discuss the findings’ implications and significance in relation to your research question or hypothesis.

Analyze and interpret your findings

Look into your findings and explore what’s behind them or what may have caused them. If your introduction cited theories or studies that could explain your findings, use these sources as a basis to discuss your results.

For example, look at the second paragraph in the discussion section of this article on waggling honey bees. Here, the authors explore their results based on information from the literature.

Unexpected or contradictory results

Sometimes, your findings are not what you expect. Here’s where you describe this and try to find a reason for it. Could it be because of the method you used? Does it have something to do with the variables analyzed? Comparing your methods with those of other similar studies can help with this task.

Context and comparison with previous work

Refer to related studies to place your research in a larger context and the literature. Compare and contrast your findings with existing literature, highlighting similarities, differences, and/or contradictions.

How your work compares or contrasts with previous work

Studies with similar findings to yours can be cited to show the strength of your findings. Information from these studies can also be used to help explain your results. Differences between your findings and others in the literature can also be discussed here. 

How to divide this section into subsections

If you have more than one objective in your study or many key findings, you can dedicate a separate section to each of these. Here’s an example of this approach. You can see that the discussion section is divided into topics and even has a separate heading for each of them. 

Limitations

Many journals require you to include the limitations of your study in the discussion. Even if they don’t, there are good reasons to mention these in your paper.

Why limitations don’t have a negative connotation

A study’s limitations are points to be improved upon in future research. While some of these may be flaws in your method, many may be due to factors you couldn’t predict.

Examples include time constraints or small sample sizes. Pointing this out will help future researchers avoid or address these issues. This part of the discussion can also include any attempts you have made to reduce the impact of these limitations, as in this study .

How limitations add to a researcher's credibility

Pointing out the limitations of your study demonstrates transparency. It also shows that you know your methods well and can conduct a critical assessment of them.  

Implications and significance

The final paragraph of the discussion section should contain the take-home messages for your study. It can also cite the “strong points” of your study, to contrast with the limitations section.

Restate your hypothesis

Remind the reader what your hypothesis was before you conducted the study. 

How was it proven or disproven?

Identify your main findings and describe how they relate to your hypothesis.

How your results contribute to the literature

Were you able to answer your research question? Or address a gap in the literature?

Future implications of your research

Describe the impact that your results may have on the topic of study. Your results may show, for instance, that there are still limitations in the literature for future studies to address. There may be a need for studies that extend your findings in a specific way. You also may need additional research to corroborate your findings. 

Sample discussion section

This fictitious example covers all the aspects discussed above. Your actual discussion section will probably be much longer, but you can read this to get an idea of everything your discussion should cover.

Our results showed that the presence of cats in a household is associated with higher levels of perceived happiness by its human occupants. These findings support our hypothesis and demonstrate the association between pet ownership and well-being. 

The present findings align with those of Bao and Schreer (2016) and Hardie et al. (2023), who observed greater life satisfaction in pet owners relative to non-owners. Although the present study did not directly evaluate life satisfaction, this factor may explain the association between happiness and cat ownership observed in our sample.

Our findings must be interpreted in light of some limitations, such as the focus on cat ownership only rather than pets as a whole. This may limit the generalizability of our results.

Nevertheless, this study had several strengths. These include its strict exclusion criteria and use of a standardized assessment instrument to investigate the relationships between pets and owners. These attributes bolster the accuracy of our results and reduce the influence of confounding factors, increasing the strength of our conclusions. Future studies may examine the factors that mediate the association between pet ownership and happiness to better comprehend this phenomenon.

This brief discussion begins with a quick summary of the results and hypothesis. The next paragraph cites previous research and compares its findings to those of this study. Information from previous studies is also used to help interpret the findings. After discussing the results of the study, some limitations are pointed out. The paper also explains why these limitations may influence the interpretation of results. Then, final conclusions are drawn based on the study, and directions for future research are suggested.

How to make your discussion flow naturally

If you find writing in scientific English challenging, the discussion and conclusions are often the hardest parts of the paper to write. That’s because you’re not just listing up studies, methods, and outcomes. You’re actually expressing your thoughts and interpretations in words.

  • How formal should it be?
  • What words should you use, or not use?
  • How do you meet strict word limits, or make it longer and more informative?

Always give it your best, but sometimes a helping hand can, well, help. Getting a professional edit can help clarify your work’s importance while improving the English used to explain it. When readers know the value of your work, they’ll cite it. We’ll assign your study to an expert editor knowledgeable in your area of research. Their work will clarify your discussion, helping it to tell your story. Find out more about AJE Editing.

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How to Practice Academic Medicine and Publish from Developing Countries? pp 225–230 Cite as

How to Write the Discussion?

  • Samiran Nundy 4 ,
  • Atul Kakar 5 &
  • Zulfiqar A. Bhutta 6  
  • Open Access
  • First Online: 24 October 2021

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1 Citations

Many authors, and editors, think this is the most difficult part of a paper to write well and have described it variously to be the ‘narrating the story of your research’, ‘the movie or the main scientific script’ and the ‘proof of the pudding’. The idea of a discussion is to communicate to the readers the importance of your observations and the results of all your hard work. In this section, you are expected to infer their meaning and explain the importance of your results and finally provide specific suggestions for future research [1, 2]. The discussion places the outcome into a larger context and mentions the implications of the inferences for theoretical and practical purposes [3].

That then is the first draft and you should never think of having fewer than six drafts Stephen Lock, BMJ editor in chief (1929–…)

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1 What Is the Importance of the Discussion?

Many authors, and editors, think this is the most difficult part of a paper to write well and have described it variously to be the ‘narrating the story of your research’, ‘the movie or the main scientific script’ and the ‘proof of the pudding’. The idea of a discussion is to communicate to the readers the importance of your observations and the results of all your hard work. In this section, you are expected to infer their meaning and explain the importance of your results and finally provide specific suggestions for future research [ 1 , 2 ]. The discussion places the outcome into a larger context and mentions the implications of the inferences for theoretical and practical purposes [ 3 ].

figure a

2 How Should I Structure the Discussion Section?

There are three major portions for the discussion of a manuscript.

The first paragraph should baldly state the key findings of your research. Use the same key concept you gave in the introduction. It is generally not necessary to repeat the citations which have already been used in the Introduction. According to the ‘serial position effect’, themes mentioned at the beginning and end of a paragraph are more likely to be remembered than those in the middle [ 1 ]. However, one should remember that the discussion should not look like a second introduction, and all the ancillary information which has been previously cited should not be repeated [ 4 ].

For example, in a paper on the ‘Role of sulfasalazine in the Chikungunya arthritis outbreak of 2016’, the review may start with, ‘Our key findings suggest that chikungunya arthralgia is a self-limiting disorder. Persistent arthritis was recorded in only 10% of the affected population and in those who received sulfasalazine, clinical improvement both in tender and swollen joints, was recorded in 95% of the subjects’.

The middle portion should consist of the body of the discussion. This section interprets the important results, discusses their implications and explains how your data is similar to or different from those that have been published previously.

Discuss in fair detail studies supporting your findings and group them together, against those offering a different perspective (e.g., Western experience, smaller numbers, non-randomized studies, etc.). An explanation should be offered on how your work is similar to others or how it is different from the others. This should be followed by a review of the core research papers. The results should now be divided thematically and analyzed. The discussion should also contain why the study is new, why it is true, and why it is important for future clinical practice [ 4 , 5 , 6 ].

For the above research mention the clinical features, patterns of joint involvement, how long arthritis persisted, and any role of disease-modifying agents. Have any other researchers found different findings under the same circumstances.

The final paragraph should include a ‘take home message’ (about one or two) and point to future directions for investigation that have resulted from this study.

The discussion can be concluded in two ways:

By again mentioning the response to the research question [ 5 , 7 ]

By indicating the significance of the study [ 2 , 4 ]

You can use both methods to end this section. Most importantly you should remember that the last paragraph of the discussion should be ‘strong, clear, and crisp’ and focus on the main research question addressed in the manuscript. This should be strengthened by the data which clearly states whether or not your findings support your initial hypothesis [ 1 , 5 , 8 , 9 , 10 ].

3 What Are the General Considerations for Writing a Discussion? [ 3 , 10 , 11 ]

Start the discussion with the ‘specific’ problems and move to the ‘general’ implications (Fig. 21.1 ).

The discussion should not look like a mass of unrelated information. Rather, it should be easy to understand and compare data from different studies.

Include only recent publications on the topic, preferably from the last 10 years.

Make certain that all the sources of information are cited and correctly referenced.

Check to make sure that you have not plagiarized by using words quoted directly from a source.

The written text written should be easily understood, crisp, and brief. Long descriptive and informal language should be avoided.

The sentences should flow smoothly and logically.

You need not refer to all the available literature in the field, discuss only the most relevant papers.

figure 1

How a discussion should look. First arrow—Mention your key results/findings; Second arrow—Discuss your results with their explanations\step by step; Third Arrow—Enumerate your studies limitations and strengths; Last arrow—Suggest future directions for investigation

4 Discussion Is Not a War of Words

figure b

5 How Long Should the Discussion in the Manuscript Be?

Most journals do not mention any limits for discussion as long as it is brief and relevant (Fig. 21.2 ). As a rule, ‘The length of the discussion section should not exceed the sum of other parts-introduction, materials and methods, and results’. [ 3 ] In any good article, the discussion section is 3–4 pages, 6–7 paragraphs, or approximately 10 paragraphs, and 1000–1500 words [ 1 , 5 , 8 , 12 ].

figure 2

Discussion pyramid

6 What Should Be Written in the Conclusion Section?

The conclusion is the last paragraph and has the carry-home message for the reader. It is the powerful and meaningful end piece of the script. It states what change has the paper made to science and it also contains recommendations for future studies.

7 Conclusions

Discussion is not a stand-alone section, it intertwines the objectives of the study with how and what was achieved.

The major results are described and compared with other studies.

The author’s own work is critically analysed in comparison with that of others.

The limitations and strengths of the study are highlighted.

Masic I. How to write an efficient discussion? Mediev Archaeol. 2018;72(4):306–7.

Google Scholar  

Bagga A. Discussion: the heart of the paper. Indian Pediatr. 2016;53(10):901–4.

Article   Google Scholar  

Ghasemi A, Bahadoran Z, Mirmiran P, Hosseinpanah F, Shiva N, Zadeh-Vakili A. The principles of biomedical scientific writing: discussion. Int J Endocrinol Metab. 2019;17:e95415.

Zeiger M. Essentials of writing biomedical research papers. Canadian J Stud Discourse Writing. 2000;11:33–6.

Bavdekar SB. Writing the discussion section: describing the significance of the study findings. J Assoc Physicians India. 2015;63:40–2.

PubMed   Google Scholar  

Foote M. The proof of the pudding: how to report results and write a good discussion. Chest. 2009;135(3):866–8.

Alexandrov AV. How to write a research paper? Cerebrovasc Dis. 2004;18(2):135–8.

Annesley TM. The discussion section: your closing argument. Clin Chem. 2010;56(11):1671–4.

Article   CAS   Google Scholar  

Ng KH, Peh WC. Writing the discussion. Singap Med J. 2009;50:458–60.

CAS   Google Scholar  

Coverdale JH, Roberts LW, Balon R, Beresin EV. Writing for academia: Getting your research into print: AMEE guide No. 74. Med Teach. 2013;35:e926–34.

Araujo CG. Detailing the writing of scientific manuscripts: 25–30 paragraphs. Arq Bras Cardiol. 2014;102(2):e21–3.

PubMed   PubMed Central   Google Scholar  

Kearney MH. The discussion section tells us where we are. Res Nurs Health. 2017;40(4):289–91.

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Nundy, S., Kakar, A., Bhutta, Z.A. (2022). How to Write the Discussion?. In: How to Practice Academic Medicine and Publish from Developing Countries?. Springer, Singapore. https://doi.org/10.1007/978-981-16-5248-6_21

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How to write a discussion section?

Writing manuscripts to describe study outcomes, although not easy, is the main task of an academician. The aim of the present review is to outline the main aspects of writing the discussion section of a manuscript. Additionally, we address various issues regarding manuscripts in general. It is advisable to work on a manuscript regularly to avoid losing familiarity with the article. On principle, simple, clear and effective language should be used throughout the text. In addition, a pre-peer review process is recommended to obtain feedback on the manuscript. The discussion section can be written in 3 parts: an introductory paragraph, intermediate paragraphs and a conclusion paragraph. For intermediate paragraphs, a “divide and conquer” approach, meaning a full paragraph describing each of the study endpoints, can be used. In conclusion, academic writing is similar to other skills, and practice makes perfect.

Introduction

Sharing knowledge produced during academic life is achieved through writing manuscripts. However writing manuscripts is a challenging endeavour in that we physicians have a heavy workload, and English which is common language used for the dissemination of scientific knowledge is not our mother tongue.

The objective of this review is to summarize the method of writing ‘Discussion’ section which is the most important, but probably at the same time the most unlikable part of a manuscript, and demonstrate the easy ways we applied in our practice, and finally share the frequently made relevant mistakes. During this procedure, inevitably some issues which concerns general concept of manuscript writing process are dealt with. Therefore in this review we will deal with topics related to the general aspects of manuscript writing process, and specifically issues concerning only the ‘Discussion’ section.

A) Approaches to general aspects of manuscript writing process:

1. what should be the strategy of sparing time for manuscript writing be.

Two different approaches can be formulated on this issue? One of them is to allocate at least 30 minutes a day for writing a manuscript which amounts to 3.5 hours a week. This period of time is adequate for completion of a manuscript within a few weeks which can be generally considered as a long time interval. Fundamental advantage of this approach is to gain a habit of making academic researches if one complies with the designated time schedule, and to keep the manuscript writing motivation at persistently high levels. Another approach concerning this issue is to accomplish manuscript writing process within a week. With the latter approach, the target is rapidly attained. However longer time periods spent in order to concentrate on the subject matter can be boring, and lead to loss of motivation. Daily working requirements unrelated to the manuscript writing might intervene, and prolong manuscript writing process. Alienation periods can cause loss of time because of need for recurrent literature reviews. The most optimal approach to manuscript writing process is daily writing strategy where higher levels of motivation are persistently maintained.

Especially before writing the manuscript, the most important step at the start is to construct a draft, and completion of the manuscript on a theoretical basis. Therefore, during construction of a draft, attention distracting environment should be avoided, and this step should be completed within 1–2 hours. On the other hand, manuscript writing process should begin before the completion of the study (even the during project stage). The justification of this approach is to see the missing aspects of the study and the manuscript writing methodology, and try to solve the relevant problems before completion of the study. Generally, after completion of the study, it is very difficult to solve the problems which might be discerned during the writing process. Herein, at least drafts of the ‘Introduction’, and ‘Material and Methods’ can be written, and even tables containing numerical data can be constructed. These tables can be written down in the ‘Results’ section. [ 1 ]

2. How should the manuscript be written?

The most important principle to be remembered on this issue is to obey the criteria of simplicity, clarity, and effectiveness. [ 2 ] Herein, do not forget that, the objective should be to share our findings with the readers in an easily comprehensible format. Our approach on this subject is to write all structured parts of the manuscript at the same time, and start writing the manuscript while reading the first literature. Thus newly arisen connotations, and self-brain gyms will be promptly written down. However during this process your outcomes should be revealed fully, and roughly the message of the manuscript which be delivered. Thus with this so-called ‘hunter’s approach’ the target can be achieved directly, and rapidly. Another approach is ‘collectioner’s approach. [ 3 ] In this approach, firstly, potential data, and literature studies are gathered, read, and then selected ones are used. Since this approach suits with surgical point of view, probably ‘hunter’s approach’ serves our purposes more appropriately. However, in parallel with academic development, our novice colleague ‘manuscripters’ can prefer ‘collectioner’s approach.’

On the other hand, we think that research team consisting of different age groups has some advantages. Indeed young colleagues have the enthusiasm, and energy required for the conduction of the study, while middle-aged researchers have the knowledge to manage the research, and manuscript writing. Experienced researchers make guiding contributions to the manuscript. However working together in harmony requires assignment of a chief researcher, and periodically organizing advancement meetings. Besides, talents, skills, and experiences of the researchers in different fields (ie. research methods, contact with patients, preparation of a project, fund-raising, statistical analysis etc.) will determine task sharing, and make a favourable contribution to the perfection of the manuscript. Achievement of the shared duties within a predetermined time frame will sustain the motivation of the researchers, and prevent wearing out of updated data.

According to our point of view, ‘Abstract’ section of the manuscript should be written after completion of the manuscript. The reason for this is that during writing process of the main text, the significant study outcomes might become insignificant or vice versa. However, generally, before onset of the writing process of the manuscript, its abstract might be already presented in various congresses. During writing process, this abstract might be a useful guide which prevents deviation from the main objective of the manuscript.

On the other hand references should be promptly put in place while writing the manuscript, Sorting, and placement of the references should not be left to the last moment. Indeed, it might be very difficult to remember relevant references to be placed in the ‘Discussion’ section. For the placement of references use of software programs detailed in other sections is a rational approach.

3. Which target journal should be selected?

In essence, the methodology to be followed in writing the ‘Discussion’ section is directly related to the selection of the target journal. Indeed, in compliance with the writing rules of the target journal, limitations made on the number of words after onset of the writing process, effects mostly the ‘Discussion’ section. Proper matching of the manuscript with the appropriate journal requires clear, and complete comprehension of the available data from scientific point of view. Previously, similar articles might have been published, however innovative messages, and new perspectives on the relevant subject will facilitate acceptance of the article for publication. Nowadays, articles questioning available information, rather than confirmatory ones attract attention. However during this process, classical information should not be questioned except for special circumstances. For example manuscripts which lead to the conclusions as “laparoscopic surgery is more painful than open surgery” or “laparoscopic surgery can be performed without prior training” will not be accepted or they will be returned by the editor of the target journal to the authors with the request of critical review. Besides the target journal to be selected should be ready to accept articles with similar concept. In fact editors of the journal will not reserve the limited space in their journal for articles yielding similar conclusions.

The title of the manuscript is as important as the structured sections * of the manuscript. The title can be the most striking or the newest outcome among results obtained.

Before writing down the manuscript, determination of 2–3 titles increases the motivation of the authors towards the manuscript. During writing process of the manuscript one of these can be selected based on the intensity of the discussion. However the suitability of the title to the agenda of the target journal should be investigated beforehand. For example an article bearing the title “Use of barbed sutures in laparoscopic partial nephrectomy shortens warm ischemia time” should not be sent to “Original Investigations and Seminars in Urologic Oncology” Indeed the topic of the manuscript is out of the agenda of this journal.

4. Do we have to get a pre-peer review about the written manuscript?

Before submission of the manuscript to the target journal the opinions of internal, and external referees should be taken. [ 1 ] Internal referees can be considered in 2 categories as “General internal referees” and “expert internal referees” General internal referees (ie. our colleagues from other medical disciplines) are not directly concerned with your subject matter but as mentioned above they critically review the manuscript as for simplicity, clarity, and effectiveness of its writing style. Expert internal reviewers have a profound knowledge about the subject, and they can provide guidance about the writing process of the manuscript (ie. our senior colleagues more experienced than us). External referees are our colleagues who did not contribute to data collection of our study in any way, but we can request their opinions about the subject matter of the manuscript. Since they are unrelated both to the author(s), and subject matter of the manuscript, these referees can review our manuscript more objectively. Before sending the manuscript to internal, and external referees, we should contact with them, and ask them if they have time to review our manuscript. We should also give information about our subject matter. Otherwise pre-peer review process can delay publication of the manuscript, and decrease motivation of the authors. In conclusion, whoever the preferred referee will be, these internal, and external referees should respond the following questions objectively. 1) Does the manuscript contribute to the literature?; 2) Does it persuasive? 3) Is it suitable for the publication in the selected journal? 4) Has a simple, clear, and effective language been used throughout the manuscript? In line with the opinions of the referees, the manuscript can be critically reviewed, and perfected. [ 1 ]**

Following receival of the opinions of internal, and external referees, one should concentrate priorly on indicated problems, and their solutions. Comments coming from the reviewers should be criticized, but a defensive attitude should not be assumed during this evaluation process. During this “incubation” period where the comments of the internal, and external referees are awaited, literature should be reviewed once more. Indeed during this time interval a new article which you should consider in the ‘Discussion’ section can be cited in the literature.

5. What are the common mistakes made related to the writing process of a manuscript?

Probably the most important mistakes made related to the writing process of a manuscript include lack of a clear message of the manuscript , inclusion of more than one main idea in the same text or provision of numerous unrelated results at the same time so as to reinforce the assertions of the manuscript. This approach can be termed roughly as “loss of the focus of the study” In conclusion, the author(s) should ask themselves the following question at every stage of the writing process:. “What is the objective of the study? If you always get clear-cut answers whenever you ask this question, then the study is proceeding towards the right direction. Besides application of a template which contains the intended clear-cut messages to be followed will contribute to the communication of net messages.

One of the important mistakes is refraining from critical review of the manuscript as a whole after completion of the writing process. Therefore, the authors should go over the manuscript for at least three times after finalization of the manuscript based on joint decision. The first control should concentrate on the evaluation of the appropriateness of the logic of the manuscript, and its organization, and whether desired messages have been delivered or not. Secondly, syutax, and grammar of the manuscript should be controlled. It is appropriate to review the manuscript for the third time 1 or 2 weeks after completion of its writing process. Thus, evaluation of the “cooled” manuscript will be made from a more objective perspective, and assessment process of its integrity will be facilitated.

Other erroneous issues consist of superfluousness of the manuscript with unnecessary repetitions, undue, and recurrent references to the problems adressed in the manuscript or their solution methods, overcriticizing or overpraising other studies, and use of a pompous literary language overlooking the main objective of sharing information. [ 4 ]

B) Approaches to the writing process of the ‘Discussion’ section:

1. how should the main points of ‘discussion’ section be constructed.

Generally the length of the ‘Discussion ‘ section should not exceed the sum of other sections (ıntroduction, material and methods, and results), and it should be completed within 6–7 paragraphs.. Each paragraph should not contain more than 200 words, and hence words should be counted repeteadly. The ‘Discussion’ section can be generally divided into 3 separate paragraphs as. 1) Introductory paragraph, 2) Intermediate paragraphs, 3) Concluding paragraph.

The introductory paragraph contains the main idea of performing the study in question. Without repeating ‘Introduction’ section of the manuscript, the problem to be addressed, and its updateness are analysed. The introductory paragraph starts with an undebatable sentence, and proceeds with a part addressing the following questions as 1) On what issue we have to concentrate, discuss or elaborate? 2) What solutions can be recommended to solve this problem? 3) What will be the new, different, and innovative issue? 4) How will our study contribute to the solution of this problem An introductory paragraph in this format is helpful to accomodate reader to the rest of the Discussion section. However summarizing the basic findings of the experimental studies in the first paragraph is generally recommended by the editors of the journal. [ 5 ]

In the last paragraph of the Discussion section “strong points” of the study should be mentioned using “constrained”, and “not too strongly assertive” statements. Indicating limitations of the study will reflect objectivity of the authors, and provide answers to the questions which will be directed by the reviewers of the journal. On the other hand in the last paragraph, future directions or potential clinical applications may be emphasized.

2. How should the intermediate paragraphs of the Discussion section be formulated?

The reader passes through a test of boredom while reading paragraphs of the Discussion section apart from the introductory, and the last paragraphs. Herein your findings rather than those of the other researchers are discussed. The previous studies can be an explanation or reinforcement of your findings. Each paragraph should contain opinions in favour or against the topic discussed, critical evaluations, and learning points.

Our management approach for intermediate paragraphs is “divide and conquer” tactics. Accordingly, the findings of the study are determined in order of their importance, and a paragraph is constructed for each finding ( Figure 1 ). Each paragraph begins with an “indisputable” introductory sentence about the topic to be discussed. This sentence basically can be the answer to the question “What have we found?” Then a sentence associated with the subject matter to be discussed is written. Subsequently, in the light of the current literature this finding is discussed, new ideas on this subject are revealed, and the paragraph ends with a concluding remark.

An external file that holds a picture, illustration, etc.
Object name is TJU-39-Supp-20-g01.jpg

Divide and Conquer tactics

In this paragraph, main topic should be emphasized without going into much detail. Its place, and importance among other studies should be indicated. However during this procedure studies should be presented in a logical sequence (ie. from past to present, from a few to many cases), and aspects of the study contradictory to other studies should be underlined. Results without any supportive evidence or equivocal results should not be written. Besides numerical values presented in the Results section should not be repeated unless required.

Besides, asking the following questions, and searching their answers in the same paragraph will facilitate writing process of the paragraph. [ 1 ] 1) Can the discussed result be false or inadequate? 2) Why is it false? (inadequate blinding, protocol contamination, lost to follow-up, lower statistical power of the study etc.), 3) What meaning does this outcome convey?

3. What are the common mistakes made in writing the Discussion section?:

Probably the most important mistake made while writing the Discussion section is the need for mentioning all literature references. One point to remember is that we are not writing a review article, and only the results related to this paragraph should be discussed. Meanwhile, each word of the paragraphs should be counted, and placed carefully. Each word whose removal will not change the meaning should be taken out from the text.” Writing a saga with “word salads” *** is one of the reasons for prompt rejection. Indeed, if the reviewer thinks that it is difficult to correct the Discussion section, he/she use her/ his vote in the direction of rejection to save time (Uniform requirements for manuscripts: International Comittee of Medical Journal Editors [ http://www.icmje.org/urm_full.pdf ])

The other important mistake is to give too much references, and irrelevancy between the references, and the section with these cited references. [ 3 ] While referring these studies, (excl. introductory sentences linking indisputable sentences or paragraphs) original articles should be cited. Abstracts should not be referred, and review articles should not be cited unless required very much.

4. What points should be paid attention about writing rules, and grammar?

As is the case with the whole article, text of the Discussion section should be written with a simple language, as if we are talking with our colleague. [ 2 ] Each sentence should indicate a single point, and it should not exceed 25–30 words. The priorly mentioned information which linked the previous sentence should be placed at the beginning of the sentence, while the new information should be located at the end of the sentence. During construction of the sentences, avoid unnecessary words, and active voice rather than passive voice should be used.**** Since conventionally passive voice is used in the scientific manuscripts written in the Turkish language, the above statement contradicts our writing habits. However, one should not refrain from beginning the sentences with the word “we”. Indeed, editors of the journal recommend use of active voice so as to increase the intelligibility of the manuscript.

In conclusion, the major point to remember is that the manuscript should be written complying with principles of simplicity, clarity, and effectiveness. In the light of these principles, as is the case in our daily practice, all components of the manuscript (IMRAD) can be written concurrently. In the ‘Discussion’ section ‘divide and conquer’ tactics remarkably facilitates writing process of the discussion. On the other hand, relevant or irrelevant feedbacks received from our colleagues can contribute to the perfection of the manuscript. Do not forget that none of the manuscripts is perfect, and one should not refrain from writing because of language problems, and related lack of experience.

Instead of structured sections of a manuscript (IMRAD): Introduction, Material and Methods, Results, and Discussion

Instead of in the Istanbul University Faculty of Medicine posters to be submitted in congresses are time to time discussed in Wednesday meetings, and opinions of the internal referees are obtained about the weak, and strong points of the study

Instead of a writing style which uses words or sentences with a weak logical meaning that do not lead the reader to any conclusion

Instead of “white color”; “proven”; nstead of “history”; “to”. should be used instead of “white in color”, “definitely proven”, “past history”, and “in order to”, respectively ( ref. 2 )

Instead of “No instances of either postoperative death or major complications occurred during the early post-operative period” use “There were no deaths or major complications occurred during the early post-operative period.

Instead of “Measurements were performed to evaluate the levels of CEA in the serum” use “We measured serum CEA levels”

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How to Write a Discussion Section | Tips & Examples

Published on 21 August 2022 by Shona McCombes . Revised on 25 October 2022.

Discussion section flow chart

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review , and making an argument in support of your overall conclusion . It should not be a second results section .

There are different ways to write this section, but you can focus your writing around these key elements:

  • Summary: A brief recap of your key results
  • Interpretations: What do your results mean?
  • Implications: Why do your results matter?
  • Limitations: What can’t your results tell us?
  • Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarise your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example.

There are a few common mistakes to avoid when writing the discussion section of your paper.

  • Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
  • Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
  • Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasise weaknesses or failures.

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Start this section by reiterating your research problem  and concisely summarising your major findings. Don’t just repeat all the data you have already reported – aim for a clear statement of the overall result that directly answers your main  research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

  • The results indicate that …
  • The study demonstrates a correlation between …
  • This analysis supports the theory that …
  • The data suggest  that …

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

  • Identifying correlations , patterns, and relationships among the data
  • Discussing whether the results met your expectations or supported your hypotheses
  • Contextualising your findings within previous research and theory
  • Explaining unexpected results and evaluating their significance
  • Considering possible alternative explanations and making an argument for your position

You can organise your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

  • In line with the hypothesis …
  • Contrary to the hypothesised association …
  • The results contradict the claims of Smith (2007) that …
  • The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is x .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

  • Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
  • Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

  • These results build on existing evidence of …
  • The results do not fit with the theory that …
  • The experiment provides a new insight into the relationship between …
  • These results should be taken into account when considering how to …
  • The data contribute a clearer understanding of …
  • While previous research has focused on  x , these results demonstrate that y .

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what to write in the discussion of a research paper

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Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

  • If your sample size was small or limited to a specific group of people, explain how generalisability is limited.
  • If you encountered problems when gathering or analysing data, explain how these influenced the results.
  • If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

  • The generalisability of the results is limited by …
  • The reliability of these data is impacted by …
  • Due to the lack of data on x , the results cannot confirm …
  • The methodological choices were constrained by …
  • It is beyond the scope of this study to …

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done – give concrete ideas for how future work can build on areas that your own research was unable to address.

  • Further research is needed to establish …
  • Future studies should take into account …
  • Avenues for future research include …

Discussion section example

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What’s Included: Research Paper Template

If you’re preparing to write an academic research paper, our free research paper template is the perfect starting point. In the template, we cover every section step by step, with clear, straightforward explanations and examples .

The template’s structure is based on the tried and trusted best-practice format for formal academic research papers. The template structure reflects the overall research process, ensuring your paper will have a smooth, logical flow from chapter to chapter.

The research paper template covers the following core sections:

  • The title page/cover page
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  • Section 2: Literature review 
  • Section 3: Methodology
  • Section 4: Findings /results
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Each section is explained in plain, straightforward language , followed by an overview of the key elements that you need to cover within each section. We’ve also included links to free resources to help you understand how to write each section.

The cleanly formatted Google Doc can be downloaded as a fully editable MS Word Document (DOCX format), so you can use it as-is or convert it to LaTeX.

FAQs: Research Paper Template

What format is the template (doc, pdf, ppt, etc.).

The research paper template is provided as a Google Doc. You can download it in MS Word format or make a copy to your Google Drive. You’re also welcome to convert it to whatever format works best for you, such as LaTeX or PDF.

What types of research papers can this template be used for?

The template follows the standard best-practice structure for formal academic research papers, so it is suitable for the vast majority of degrees, particularly those within the sciences.

Some universities may have some additional requirements, but these are typically minor, with the core structure remaining the same. Therefore, it’s always a good idea to double-check your university’s requirements before you finalise your structure.

Is this template for an undergrad, Masters or PhD-level research paper?

This template can be used for a research paper at any level of study. It may be slight overkill for an undergraduate-level study, but it certainly won’t be missing anything.

How long should my research paper be?

This depends entirely on your university’s specific requirements, so it’s best to check with them. We include generic word count ranges for each section within the template, but these are purely indicative. 

What about the research proposal?

If you’re still working on your research proposal, we’ve got a template for that here .

We’ve also got loads of proposal-related guides and videos over on the Grad Coach blog .

How do I write a literature review?

We have a wealth of free resources on the Grad Coach Blog that unpack how to write a literature review from scratch. You can check out the literature review section of the blog here.

How do I create a research methodology?

We have a wealth of free resources on the Grad Coach Blog that unpack research methodology, both qualitative and quantitative. You can check out the methodology section of the blog here.

Can I share this research paper template with my friends/colleagues?

Yes, you’re welcome to share this template. If you want to post about it on your blog or social media, all we ask is that you reference this page as your source.

Can Grad Coach help me with my research paper?

Within the template, you’ll find plain-language explanations of each section, which should give you a fair amount of guidance. However, you’re also welcome to consider our private coaching services .

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Thus, a white paper author would not “brainstorm” a topic. Instead, the white paper author would get busy figuring out how the problem is defined by those who are experiencing it as a problem. Typically that research begins in popular culture--social media, surveys, interviews, newspapers. Once the author has a handle on how the problem is being defined and experienced, its history and its impact, what people in the trenches believe might be the best or worst ways of addressing it, the author then will turn to academic scholarship as well as “grey” literature (more about that later).  Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position.  Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting, and overlapping perspectives. When people research out of a genuine desire to understand and solve a problem, they listen to every source that may offer helpful information. They will thus have to do much more analysis, synthesis, and sorting of that information, which will often not fall neatly into a “pro” or “con” camp:  Solution A may, for example, solve one part of the problem but exacerbate another part of the problem. Solution C may sound like what everyone wants, but what if it’s built on a set of data that have been criticized by another reliable source?  And so it goes. 

For example, if you are trying to write a white paper on the opioid crisis, you may focus on the value of  providing free, sterilized needles--which do indeed reduce disease, and also provide an opportunity for the health care provider distributing them to offer addiction treatment to the user. However, the free needles are sometimes discarded on the ground, posing a danger to others; or they may be shared; or they may encourage more drug usage. All of those things can be true at once; a reader will want to know about all of these considerations in order to make an informed decision. That is the challenging job of the white paper author.     
 The research you do for your white paper will require that you identify a specific problem, seek popular culture sources to help define the problem, its history, its significance and impact for people affected by it.  You will then delve into academic and grey literature to learn about the way scholars and others with professional expertise answer these same questions. In this way, you will create creating a layered, complex portrait that provides readers with a substantive exploration useful for deliberating and decision-making. You will also likely need to find or create images, including tables, figures, illustrations or photographs, and you will document all of your sources. 

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  • Published: 12 February 2024

A conserved interdomain microbial network underpins cadaver decomposition despite environmental variables

  • Zachary M. Burcham 1 , 2 ,
  • Aeriel D. Belk 1 , 3 ,
  • Bridget B. McGivern   ORCID: orcid.org/0000-0001-9023-0018 4 ,
  • Amina Bouslimani 5 ,
  • Parsa Ghadermazi 6 ,
  • Cameron Martino 7 ,
  • Liat Shenhav 8 , 9 , 10 ,
  • Anru R. Zhang 11 , 12 ,
  • Pixu Shi 11 ,
  • Alexandra Emmons 1 ,
  • Heather L. Deel 13 ,
  • Zhenjiang Zech Xu   ORCID: orcid.org/0000-0003-1080-024X 14 ,
  • Victoria Nieciecki   ORCID: orcid.org/0000-0002-1891-5909 1 , 13 ,
  • Qiyun Zhu   ORCID: orcid.org/0000-0002-3568-6271 7 , 15 , 16 ,
  • Michael Shaffer 4 ,
  • Morgan Panitchpakdi 5 ,
  • Kelly C. Weldon 5 ,
  • Kalen Cantrell   ORCID: orcid.org/0000-0002-6262-1668 17 ,
  • Asa Ben-Hur 18 ,
  • Sasha C. Reed 19 ,
  • Greg C. Humphry 7 ,
  • Gail Ackermann 7 ,
  • Daniel McDonald 7 ,
  • Siu Hung Joshua Chan   ORCID: orcid.org/0000-0002-7707-656X 6 ,
  • Melissa Connor 20 ,
  • Derek Boyd   ORCID: orcid.org/0000-0003-1444-0536 21 , 22 ,
  • Jake Smith 21 , 23 ,
  • Jenna M. S. Watson 21 ,
  • Giovanna Vidoli 21 ,
  • Dawnie Steadman   ORCID: orcid.org/0000-0003-0812-0739 21 ,
  • Aaron M. Lynne 24 ,
  • Sibyl Bucheli 24 ,
  • Pieter C. Dorrestein   ORCID: orcid.org/0000-0002-3003-1030 5 ,
  • Kelly C. Wrighton 4 ,
  • David O. Carter   ORCID: orcid.org/0000-0003-1885-5237 25 ,
  • Rob Knight   ORCID: orcid.org/0000-0002-0975-9019 7 , 17 , 26 , 27 &
  • Jessica L. Metcalf   ORCID: orcid.org/0000-0001-8374-8046 1 , 13 , 28  

Nature Microbiology ( 2024 ) Cite this article

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  • Microbial ecology

Microbial breakdown of organic matter is one of the most important processes on Earth, yet the controls of decomposition are poorly understood. Here we track 36 terrestrial human cadavers in three locations and show that a phylogenetically distinct, interdomain microbial network assembles during decomposition despite selection effects of location, climate and season. We generated a metagenome-assembled genome library from cadaver-associated soils and integrated it with metabolomics data to identify links between taxonomy and function. This universal network of microbial decomposers is characterized by cross-feeding to metabolize labile decomposition products. The key bacterial and fungal decomposers are rare across non-decomposition environments and appear unique to the breakdown of terrestrial decaying flesh, including humans, swine, mice and cattle, with insects as likely important vectors for dispersal. The observed lockstep of microbial interactions further underlies a robust microbial forensic tool with the potential to aid predictions of the time since death.

Decomposition is one of Earth’s most foundational processes, sustaining life through the recycling of dead biological material 1 , 2 . This resource conversion is critical for fuelling core ecosystem functions, such as plant productivity and soil respiration. Microbial networks underpin organic matter breakdown 3 , yet their ecology remains in a black box, obscuring our ability to accurately understand and model ecosystem function, resilience and biogeochemical carbon and nutrient budgets. While DNA-based assessments of decomposer microbial communities have occurred in plant litter 4 , 5 and a few in mammals 6 , 7 , little has been revealed about the microbial ecology of how decomposer microbial communities assemble, interact or function in the ecosystem. Our understanding of how animal remains, or carrion, decompose is in its infancy due to the historical focus on plant litter, which dominates decomposing biomass globally. Nevertheless, an estimated 2 billion metric tons of high-nutrient animal biomass 8 contribute substantially to ecosystem productivity, soil fertility, and a host of other ecosystem functions and attributes 9 , 10 . Carbon and nutrients from carrion biomass can be consumed by invertebrate and vertebrate scavengers, enter the atmosphere as gas, or be metabolized by microbes in situ or via leachate in the surrounding soils 11 , 12 . The proportion of carrion carbon and nutrients entering each resource pool is not well quantified and probably highly variable with substantial contributions to each at an ecosystem scale 2 , 13 . Unlike with plant litter, which is primarily composed of cellulose, animal decomposers must predominantly break down proteins and lipids, which require a vastly different metabolic repertoire. How microbial decomposers assemble to break down these organic compounds is not well understood. For plant litter, it has been proposed that functional redundancy allows different communities of microbes to assemble in any given location 14 and perform similar functions. Alternatively, similar microbial community members, or microbial networks, may assemble across sites to outcompete other community members and thrive on nutrients 15 .

Recent research has demonstrated that microbial community response over the course of terrestrial human cadaver decomposition and across a range of mammals, results in a substantial microbial community change through time that is repeatable across individuals 6 , 7 , 16 , 17 , 18 and appears somewhat similar across different soil types 6 and robust to scavenger activity 16 . These data suggest the potential for universal microbial decomposer networks that assemble in response to mammalian remains. However, it remains unclear how the effects of environmental variability, such as differences in climate, geographic location and season, may affect the assembly processes and interactions of microbial decomposers. Yet understanding and predicting this assembly is important for our understanding of ecosystems and informs practical applications. For example, profiling microbial succession patterns associated with human remains may lead to a novel tool for predicting the postmortem interval (PMI), which has critical societal impact as evidence for death investigations. Within laboratory experiments 6 , 18 , as well as field experiments in single locations 6 , 19 , microbial decomposer community succession is closely linked to PMI at accuracies relevant for forensic applications 6 , 17 , 18 , but these studies do not inform questions of microbial variation across sites, climates and seasons. Consequently, a robust understanding of how microbial ecological patterns of mammalian, and specifically human, decomposition vary is critical for using and improving these important forensic tools. Unlocking the microbial ecology black box for mammal decomposition, or more generally carrion decomposition, could provide actionable knowledge for innovation in agriculture and the human death care industry (for example, composting of bodies) 20 , sustainability (for example, animal mass mortality events) 21 and the forensic sciences (for example, estimating PMI) 22 , as well as guide future research on plant decomposition and maintaining global productivity under anthropogenic change.

To address ecological and forensic research questions on decomposer network assembly and function, we used three willed-body donation anthropological facilities in terrestrial environments across two climate types within the United States (Fig. 1a and Extended Data Fig. 1a,b ) 23 . We asked whether temporal trends in microbial decomposer communities that we previously characterized in a limited experiment using human cadavers at a single geographic location 6 were generalizable across climate, geographic locations and seasons. Over the course of decomposition, we compared the microbial response to decomposition across 36 human bodies within (temperate forest) and between (temperate forest vs semi-arid steppe) climate types. We used multi-omic data (16S and 18S ribosomal (r)RNA gene amplicons, metagenomics and metabolomics) to reveal microbial ecological responses to cadaver decomposition over the first 21 d postmortem (Fig. 1b and Extended Data Fig. 1c ), when decomposition rates are generally fast and dynamic (Fig. 1c , metadata in Supplementary Table 1 ). Here we show that a universal microbial decomposer network assembles despite location, climate and seasonal effects, with evidence of increased metabolic efficiencies to process the ephemeral and abundant lipid- and protein-rich compounds. Key members of the microbial decomposer network are also found associated with swine, cattle and mouse carrion 16 , 24 , 25 , 26 , suggesting that they are not human-specific, but probably general to mammal or animal carrion. Furthermore, the universal microbial network communities underlie a robust microbial-based model for predicting PMI.

figure 1

a , Köppen–Geiger climate map showing ARF and STAFS as ‘temperate without a dry season and hot summer’ and FIRS as ‘arid steppe cold’ adapted from ref. 23 . Thirty-six cadavers in total were placed ( N  = 36), 3 per season for a sum of 12 at each location. b , Upset plot representing the experimental design for the total sample size ( x axis) and number of shared/paired samples ( y axis) for each data type. MetaG, metagenomics; Metab, metabolomics; 18S, 18S rRNA amplicon; 16S, 16S rRNA amplicon. c , Total body score, a visual score of decomposition calculated over the course of decomposition 27 , illustrating how decomposition progresses at each location and by season in triplicate. Dashed lines separate sections of early, active and advanced stages of decomposition as determined by a temperature-based unit of time, accumulated degree day (ADD), calculated by continuously summing the mean daily temperature above 0 °C from left to right. Point transparency increases with days since placement.

Source data

Nutrient-rich cadaver decomposition.

Terrestrial mammalian decomposition is a dynamic process that is partly governed by environmental conditions 1 , 2 . We observed that cadavers placed in the same climate (temperate) decomposed similarly across locations within a season, as determined by a visual total body score (TBS) of decomposition progression (Fig. 1c ) 27 . Cadavers placed in a semi-arid climate (that is, FIRS) generally progressed more slowly through decomposition over the 21 d, which is probably due to decreased temperatures, humidity and precipitation in the semi-arid environment (Extended Data Fig. 1a,b ) 9 , 28 . We observed visual cadaver decomposition progression to be impacted by season, wherein summer was the most consistent across locations (Fig. 1c ). As cadavers and mammalian carrion decompose, they release a complex nutrient pool that impacts the surrounding environment, often resulting in the death and restructuring of nearby plant life 2 , 29 due to generally high inputs of nitrogen 2 , 6 , 9 , 30 , 31 , which is primarily in the form of ammonium 6 , as well as carbon 2 , 6 , 10 , 30 , 31 and phosphorous 9 , 29 . We characterized the cadaver-derived nutrient pool via untargeted metabolomics using liquid chromatography with tandem mass spectrometry (LC–MS/MS) data. Cadaver skin and associated soil metabolite profiles were distinct (Extended Data Fig. 2a,b ). Overall, profiles were largely dominated by likely cadaver-derived lipid-like and protein-like compounds, along with plant-derived lignin-like compounds (Extended Data Fig. 2c,d ). As decomposition progressed, both cadaver-associated soil and skin profiles became enriched in linoleic acids, aleuritic acids, palmitic acids, long-chain fatty acids, fatty amides and general amino acids (Supplementary Tables 2 and 3 ). Furthermore, we estimated a reduction of thermodynamic favourability in the nutrient pool at all locations (Extended Data Fig. 2e,f ), a similar pattern found in the microbial breakdown of plant material in soils 32 . These data suggest that during the first weeks of decomposition, more recalcitrant lipid-like and lipid-derivative nutrients build up within soils as decomposers preferentially utilize labile protein-like resources, but with climate-dependent abundance variations in lipid-like (Extended Data Fig. 2g ) and geographic-dependent variations in protein-like compounds (Extended Data Fig. 2h ). These patterns may also be influenced by the physical properties of soil at each location such as texture, density and stoichiometry.

Cadaver microbial decomposer assembly

The lipid- and protein-rich cadaver nutrient influx is a major ecological disturbance event that attracts scavengers from across the tree of life and initiates the assembly of a specific microbial decomposer community. On the basis of our metabolite data, we hypothesized that soil decomposer microbial communities preferentially shift to efficiently utilize more labile compounds (for example, amino acids from proteins and possibly also carbohydrates such as glycogen, which were not detected via LC–MS/MS metabolomics) and temporarily leave the less-labile compounds (for example, lipids) in the system. By building a metagenome-assembled genome (MAG) database from human decomposition-associated soils (Extended Data Fig. 3a,b and Supplementary Tables 4 – 6 ), we reconstructed genome-scale metabolic models to characterize how potential metabolic efficiencies of soil microbial communities shift in response to three major resources: lipids, amino acids and carbohydrates. Indeed, we found that temperate decomposer metabolic efficiency of labile resources was positively correlated with a temperature-based timeline of decomposition (accumulated degree day (ADD)) (Fig. 2a–c , Extended Data Fig. 3c and Supplementary Tables 7 – 9 ). We found that two MAGs constituted a large portion of the increased amino acid and carbohydrate metabolism efficiencies at temperate locations: Oblitimonas alkaliphila ( Thiopseudomonas alkaliphila ) (Extended Data Fig. 3d ) and Corynebacterium intestinavium (Extended Data Fig. 3e ), respectively. This microbial response is probably an effect of heterogeneous selection (that is, selection driving the community to become different) driving the assemblage of the decomposer community, as heterogeneous selection increases relative to stochastic forces and homogeneous selection during decomposition (Fig. 2d,e , Extended Data Fig. 3f , and Supplementary Tables 10 and 11 ). We further hypothesized that microbe–microbe interactions probably contribute to selection 33 , which we investigated by calculating metabolic competitive and cooperative interaction potentials between our genome-scale metabolic models 34 , 35 . We found that metabolic competition potential initially increased at one temperate and the semi-arid location, suggesting an increase in microbes with similar resource needs (Extended Data Fig. 3g , and Supplementary Tables 12 and 13 ), which was not seen when communities were randomly subsampled within each site and decomposition stage (Extended Data Fig. 3h and Supplementary Table 12 ). Furthermore, we found that communities in temperate climates increased cross-feeding potential (that is, sharing of metabolic products) from early/active to advanced decomposition (Fig. 3a , and Supplementary Tables 12 and 13 ) and had a substantially higher number of cross-feeding exchanges during late decomposition than semi-arid climate communities (Fig. 3b and Supplementary Table 14 ), suggesting the increased potential for metabolic activity. The molecules predicted most for exchange by the models are common by-products of mammalian decomposition 36 , 37 , specifically of protein degradation 38 , and included hydrogen sulfide, acetaldehyde and ammonium, and 56% of the top 25 total exchanged molecules were amino acids. In contrast to temperate locations, semi-arid decomposer communities demonstrated a relatively diminished responsiveness to decomposition stage (Fig. 3c , Extended Data Fig. 4a , and Supplementary Tables 15 and 16 ) and did not significantly shift their metabolism efficiencies (Fig. 2a–c , Extended Data Fig. 3c and Supplementary Tables 7 – 9 ), probably due to a lack of water, which leads to higher metabolic costs 39 , decreased substrate supply 40 and growth 41 . Despite a less measurable microbial response at the semi-arid location, we did detect an increase in cross-feeding potential from early to active decomposition stages, suggesting that the semi-arid community has an increased ability to respond to decomposition nutrients (Fig. 3a , and Supplementary Tables 12 and 13 ) but probably at a smaller scale than temperate locations.

figure 2

a – c , Lipid ( a ), carbohydrate ( b ) and amino acid ( c ) metabolism efficiency as determined by the maximum ATP per C-mol of substrate that can be obtained from each community, plotted against the ADD the community was sampled. ARF n  = 212, STAFS n  = 198 and FIRS n  = 158 biologically independent samples. Data are presented as mean ± 95% confidence interval (CI). Significance was tested with linear mixed-effects models within each location including a random intercept for cadavers with two-tailed ANOVA and no multiple-comparison adjustments. ARF amino acids P  = 6.27 × 10 −23 , STAFS amino acids P  = 6.626 × 10 −10 , STAFS carbohydrate P  = 2.294 × 10 −07 and STAFS lipid P  = 3.591 × 10 −02 . d , Pairwise comparisons to obtain βNTI values focused on successional assembly trends by comparing initial soil at time of cadaver placement to early decomposition soil, then early to active and so on (PL, placement; EA, early; AC, active; AD, advanced) in the 16S rRNA amplicon dataset, showing that strong selection forces are pushing the community to differentiate. ARF n  = 232, STAFS n  = 202 and FIRS n  = 182 biologically independent samples. In boxplots, the lower and upper hinges of the box correspond to the first and third quartiles (the 25th and 75th percentiles); the upper and lower whiskers extend from the hinge to the largest and smallest values no further than 1.5× interquartile range (IQR), respectively; and the centre lines represent the median. The βNTI mean (diamond symbol) change between decomposition stage is represented by connected lines. Dashed lines represent when |βNTI| = 2. A |βNTI| value < 2 indicates stochastic forces (white background) drive community assembly. βNTI values <−2 and >2 indicate homogeneous (blue background) and heterogeneous (yellow background) selection drive assembly, respectively. The width of the violin plot represents the density of the data at different values. Significance was tested with Dunn Kruskal–Wallis H -test, with multiple-comparison P values adjusted using the Benjamini–Hochberg method. e , Representation of heterogeneous selection pressure relative abundance within the total pool of assembly processes increases over decomposition in the 16S rRNA amplicon dataset. Bars were calculated by dividing the number of community comparisons within with βNTI > +2 by the total number of comparisons. * P  < 0.05, ** P  < 0.01 and *** P  < 0.001.

Source Data

figure 3

a , Predicted cross-feeding interactions from MAGs are site-specific and significantly altered over decomposition. ARF n  = 201, STAFS n  = 188 and FIRS n  = 151 biologically independent samples. In boxplots, the lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles); the upper and lower whiskers extend from the hinge to the largest and smallest values no further than 1.5× IQR; the centre lines represent the median. Significance was tested with Dunn Kruskal–Wallis H -test, with multiple-comparison P values adjusted with the Benjamini–Hochberg method. ARF early-active P  = 1.95 × 10 −23 , early-advanced P  = 1.67 × 10 −23 ; STAFS early-active P  = 5.53 × 10 −39 , early-advanced P  = 3.65 × 10 −03 , active-advanced P  = 2.04 × 10 −24 ; FIRS early-active P  = 3.81 × 10 −15 . b , Increased cross-feeding reactions during semi-arid active decomposition and temperate advanced decomposition are summarized to show that compounds such as amino acids (red) are common among the top 25 potential cross-fed molecules from MAGs. c , Phylogenetic turnover in decomposition soil vs control soil shows that temperate climates react quickly to decomposition, while the more arid site does not quickly change (dashed lines represent breaks for early, active (grey shading) and advanced decomposition stages) using the 16S rRNA gene amplicon dataset. ARF n  = 414, STAFS n  = 316 and FIRS n  = 310 biologically independent samples. Data are presented as mean ± 95% CI. Significance was tested using linear mixed-effects models within each location, including a random intercept for cadavers with two-tailed ANOVA and no multiple-comparison adjustments. ARF and STAFS richness P  ≤ 2 × 10 −16 . d , Multi-omic (16S rRNA gene abundances, 18S rRNA gene abundances, MAG abundances, MAG gene abundances, MAG gene functional modules and metabolites) joint-RPCA shows that microbial community ecology is impacted by decomposition stage and geographical location. ** P  < 0.01 and *** P  < 0.001.

We further investigated potential effects of selective environmental conditions via multi-omic, joint robust principal components analysis (joint-RPCA) for dimensionality reduction (see Methods ) 42 , which all (climate, geographic location, season and decomposition stage) significantly shaped the microbial decomposer community ecology (Fig. 3d , Extended Data Fig. 4b–f and Supplementary Table 17 ). Climate (temperate vs semi-arid) along with location (ARF, STAFS, FIRS) significantly shaped the soil microbial community composition (Supplementary Tables 18 – 20 ) and its potential gene function (Supplementary Tables 21 – 22 ). Decomposition soils at temperate sites exhibited strong microbial community phylogenetic turnover (Fig. 3c and Supplementary Table 15 ) and a decrease in microbial richness during decomposition (Extended Data Fig. 4a and Supplementary Table 16 ), while less measurable effects were observed at the semi-arid location (Fig. 3c , Extended Data Fig. 4a , and Supplementary Tables 15 and 16 ). Season appeared to primarily influence soil chemistry as opposed to microbial community composition during decomposition (Supplementary Table 23 ), suggesting possible temperature-associated metabolism changes/limitations of microbial decomposer taxa. Taken together, these data suggest that while stochastic forces play a part in decomposer community assembly, deterministic forces, such as microbial interactions and environmental conditions, also play an important role.

Conserved interdomain soil microbial decomposer network

We discovered a universal network of microbes responding to the cadaver decomposition despite selection effects of climate, location and season on the assembly of the microbial decomposers within the soil. To focus on the universal decomposition effects across locations, we used the joint-RPCA principal component 2 (PC2) scores to generate the universal decomposition network due to their significant change over decomposition stage and reduced impact from location, season and climate (Fig. 4a,b , Extended Data Fig. 4b–f and Supplementary Table 24 ). Therefore, PC2 scores were used to calculate multi-omics of log ratios in late decomposition soil compared to initial and early decomposition soils (Fig. 4c , Extended Data Fig. 4g and Supplementary Table 25 ), which allowed us to identify key co-occurring bacterial and eukaryotic microbial decomposers, bacterial functional pathways and metabolites associated with late decomposition (Fig. 5a , Extended Data Fig. 5 and Supplementary Table 26 ). The organism O. alkaliphila , which is central to the network and a large contributor to the increased amino acid metabolism efficiency at temperate locations (Extended Data Fig. 3d ), may play a key role in terrestrial cadaver decomposition as a controller of labile resource utilization in temperate climates, but little is known about its ecology 43 , 44 , 45 . In addition, most microbial key network decomposers (Fig. 5a ; O. alkaliphila , Ignatzschineria , Wohlfahrtiimonas , Bacteroides , Vagococcus lutrae, Savagea , Acinetobacter rudis and Peptoniphilaceae ) represented unique phylogenetic diversity that was extremely rare or undetected in host-associated or soil microbial communities in American Gut Project (AGP) or Earth Microbiome Project (EMP) data sets (Fig. 5b , Extended Data Fig. 6 , and Supplementary Tables 27 and 28 ). Although the decomposers in the group Bacteroides have previously been assumed to derive from a human gut source 46 , 47 , we find that these are instead probably a specialist group of decomposers distinct from gut-associated Bacteroides (Fig. 5b , Extended Data Fig. 6 , and Supplementary Tables 27 and 28 ). The only strong evidence of key network bacterial decomposers emerging from soil and host-associated environments were in the genera Acinetobacter and Peptoniphilus (Fig. 5b , Extended Data Fig. 6 , and Supplementary Tables 27 and 28 ). We more comprehensively characterized microbial decomposer phylogenetic uniqueness with MAG data, which span previously undescribed bacterial orders, families, genera and species (Extended Data Fig. 3a ). Overall, we find that the soil microbial decomposer network is phylogenetically unique and in extremely low relative abundance in the environment until the cadaver nutrient pool becomes available.

figure 4

a , b , Principal component values show that ( a ) facility variation is primarily explained by principal component 3 (PC3) (that is, least overlap between group scores), while variation caused by ( b ) decomposition stage is explained by PC2. c , Change in log ratio of PC scores within omics datasets (metabolites, MAG abundances, 18S rRNA gene abundances and MAG gene functional modules) from initial soil through advanced decomposition stage soil highlights that decomposition stage progression corresponds to compositional shifts. All data types used the same n  = 374 biologically independent samples. Data are presented as mean ± 95% CI.

figure 5

a , Top 20% correlation values from features responsible for the universal late decomposition log-ratio signal in joint-RPCA PC2 visualized in a co-occurrence network. b , Phylogenetic tree representing ASVs associated with key decomposer nodes from the network placed along the top 50 most abundant ASVs taken from AGP gut, AGP skin, EMP soil and EMP host-associated datasets demonstrates that key decomposers are largely phylogenetically unique. Colour represents taxonomic order (full legend in Extended Data Fig. 6 ); the innermost ring represents decomposer placement, while outer rings represent AGP and EMP ASVs, for which bar height represents ASV rank abundance within each environment. A lack of bars indicates that the ASV was not present within the entire dataset. AGP and EMP ASVs were ranked according to the number of samples they were found in each environment. Decomposer ASVs are numbered clockwise (full taxonomy available in Supplementary Table 27 ).

We hypothesized that specialist decomposer network taxa probably interact to metabolize the nutrient pool, which we explored via estimated cross-feeding capabilities of co-occurring communities. Highlighting the importance of these key taxa, microbial decomposer network members accounted for almost half (42.8%) of predicted late decomposition nutrient exchanges (Figs. 3b and 5a , and Supplementary Table 29 ) with Gammaproteobacteria being prominent as both metabolite donors and receivers. For example, O. alkaliphila has the capability to cross-feed with Ignatzschineria , Acinetobacter , Savagea and Vagococcus lutrae , to which it donates amino acids known to be associated with mammalian decomposition such as aspartate, isoleucine, leucine, tryptophan and valine, along with the lipid metabolism intermediate, sn -Glycero-3-phosphoethanolamine 36 (Supplementary Table 30 ). As a receiver, O. alkaliphilia is predicted to receive essential ferrous ions (Fe 2+ ) from Acinetobacter , Savagea and Vagoccocus along with glutamate, proline and lysine from Ignatzschineria . Further, putrescine, a foul-smelling compound produced during decomposition by the decarboxylation of ornithine and arginine, and arginine/ornithine transport systems were universal functions within our network (Fig. 5a ). Cross-feeding analysis identified multiple potential ornithine and/or arginine exchangers, such as Ignatzschineria , Savagea , Wohlfahrtiimonas and O. alkaliphilia (Supplementary Table 31 ). Putrescine is an interdomain communication molecule probably playing an important role in assembling the universal microbial decomposer network by signalling scavengers such as blow flies 48 , which disperse decomposer microbes, as well as directly signalling other key microbial decomposers, such as fungi 49 , 50 , 51 .

Fungi play an essential role in the breakdown of organic matter; however, their processes and interdomain interactions during cadaver decomposition remain underexplored. Our network analysis identified multiple fungal members that are co-occurring with bacteria, belonging to the Ascomycota phylum (Fig. 5a )—a phylum known for its role in breaking down organic matter 6 , 44 , 52 , 53 . In particular, Yarrowia and Candida are known for their ability to utilize lipids, proteins and carbohydrates 44 , 53 , and both have one of their highest correlations with O. alkaliphila (Fig. 5a and Supplementary Table 25 ). The ability of Yarrowia and Candida to break down lipids and proteins during decomposition may serve as interdomain trophic interactions that allow O. alkaliphila to utilize these resources 44 . For example, Yarrowia and Candida genomes contain biosynthesis capabilities for arginine and ornithine that, if excreted, could be taken up by O. alkaliphilia . The complete genome of O. alkaliphilia (Genbank accession no. CP012358 ) contains the enzyme ornithine decarboxylase, which is responsible for converting ornithine to the key compound putrescine 43 .

Machine learning reveals a predictable microbial decomposer ecology

The assembly of a universal microbial decomposer network suggests the potential to build a robust forensics tool. We demonstrate that the PMI (calculated as ADD) can be accurately predicted directly from microbiome-normalized abundance patterns via random forest regression models (Fig. 6a ). High-resolution taxonomic community structure was the best predictor of PMI (Fig. 6b ), particularly normalized abundances of the 16S rRNA gene at the SILVA database level-7 taxonomic rank (L7) of the skin decomposer microbes (Fig. 6a–c ). Interestingly, 3 out of 4 of the skin-associated decomposer taxa that were most informative for the PMI model had similar normalized abundance trends over decompositions for bodies at all locations, suggesting that skin decomposers are more ubiquitous across climates than soil decomposers (Fig. 6d and Extended Data Fig. 7 ). We hypothesize that this is due to the human skin microbiome being more conserved between individuals than the soil microbiome is between geographic locations 54 . In fact, both skin and soil 16S rRNA-based models had the same top taxon as the most important predictor, Helcococcus seattlensis (Fig. 6d and Extended Data Fig. 7 ). H. seattlensis is a member of the order Tissierellales and family Peptoniphilaceae, both of which were key nodes within the universal decomposer network. In line with our hypothesis, H. seattlensis on the skin showed more-similar abundance trends for cadavers decomposing across both climate types, while H. seattlensis trends in the soil were primarily measurable at temperate locations (Fig. 6e and Extended Data Fig. 8 ). We found that normalized abundances of important soil taxa previously established to be in our universal decomposer network had strong climate signals, further suggesting a diminished responsiveness in semi-arid climates, such as temperate-climate responses with H. seattlensis , O. alkaliphila , Savagea sp., Peptoniphilus stercorisuis , Ignatzschineria sp. and Acinetobacter sp. (Extended Data Fig. 8c,d ). However, we found that the three most important PMI model soil taxa, Peptostreptococcus sp., Sporosarcina sp. and Clostridiales Family XI sp., had increased detection with decomposition in both semi-arid and temperate climates (Extended Data Fig. 8c,d ), suggesting that while strong climate-dependent fluctuations exist, there are microbial members that respond more ubiquitously to decomposition independent of climate. In addition, microbiome-based models and a TBS-based model had comparable average mean absolute errors (MAE) (Extended Data Fig. 9a ); however, 16S rRNA microbiome-based model predictions were on average closer to the actual observed values (that is, smaller average residual values), suggesting a higher accuracy (Fig. 6c and Extended Data Fig. 9a ). Lastly, we confirmed the model accuracy and reliability of PMI prediction using 16S rRNA amplicon data with an independent test set of samples that were collected at a different time from cadavers at locations and climates not represented in our model. We discovered that we could accurately predict the true PMIs of samples better than samples with randomized PMIs at all independent test set locations (Extended Data Fig. 9b,c and Supplementary Table 32 ), confirming the generalizability and robustness of our models in predicting new data from multiple geographies and climates with an accuracy useful for forensic death investigations.

figure 6

a , Cross-validation errors of multi-omic data sets. 16S and 18S rRNA gene data were collapsed to SILVA taxonomic level 7 (L7) and 12 (L12). Boxplots represent average prediction MAE in ADD of individual bodies during nested cross-validation of 36 body dataset. 16S rRNA soil face, soil hip, skin face and skin hip datasets contain n  = 600, 616, 588 and 500 biologically independent samples, respectively. 18S rRNA soil face, soil hip, skin face and skin hip datasets contain n  = 939, 944, 837 and 871 biologically independent samples, respectively. Paired 16S rRNA+18S rRNA soil face, soil hip, skin face and skin hip datasets contain n  = 440, 450, 428 and 356 biologically independent samples, respectively. MAG datasets contain n  = 569 biologically independent samples. Metabolite soil hip and skin hip datasets contain n  = 746 and 748 biologically independent samples, respectively. b , Mean absolute prediction errors are lowest when high-resolution taxonomic data are used for model training and prediction. Data represented contain the same biologically independent samples as in a . In boxplots in a and b , the lower and upper hinges of the boxplot correspond to the first and third quartiles (the 25th and 75th percentiles); the upper and lower whiskers extend from the hinge to the largest and smallest values no further than 1.5× IQR; the centre lines represent the median; the diamond symbol represents the mean. c , Linear regressions of predicted to true ADDs to assess model prediction accuracy show that all sampling locations significantly predict ADD. Data represented contain the same biologically independent samples as in a . Data are presented as mean ± 95% CI. Black dashed lines represent ratio of predicted to real ADD predictions at 1:1. The coloured solid lines represent the linear model calculated from the difference between the predicted and real ADD. d , The most important SILVA L7 taxa driving model accuracy from the best-performing model derived from 16S rRNA gene amplicon data sampled from the skin of the face. e , Comparison of abundance changes of the top important taxon, Helcococcus seattlensis , in skin reveals that low-abundance taxa provide predictive responses. Data plotted with loess regression and represent the same biologically independent samples as in a . Data are presented as mean ± 95% CI. Bact., bacterial; Avg., average; Marg., marginal.

We provide a genome-resolved, comprehensive view of microbial dynamics during cadaver decomposition and shed light on the assembly, interactions and metabolic shifts of a universal microbial decomposer network. We found that initial decomposer community assembly is driven by stochasticity, but deterministic forces increase over the course of decomposition, a finding in agreement with other conceptual models of microbial ecology 33 , 55 , 56 , 57 . These processes led to a decomposer network consisting of phylogenetically unique taxa emerging, regardless of season, location and climate, to synergistically break down organic matter. The ubiquitous decomposer and functional network revealed by our multi-omic data suggests that metabolism is coupled to taxonomy, at least to some extent, for cadaver decomposition ecology. However, the overall composition of microbial decomposer communities did vary between different climates and locations, indicating that some functional redundancy also probably exists. In a study of agricultural crop organic matter decomposition (straw and nutrient amendments), researchers similarly demonstrated that although functional redundancy probably plays a role, key microbial taxa emerge as important plant decomposers 15 , and a meta-analysis of microbial community structure–function relationships in plant litter decay found that community composition had a large effect on mass loss 58 . In terms of climatic controls over cadaver decomposition, temperate locations had a more measurable microbial response (for example, phylogenetic turnover, potential cross-feeding) in soils than the arid location in our study, and plant studies support the idea that climate is a strong determinant of decomposition rates and microbial activity 59 .

Despite the lesser response in the arid location, cadaver decomposer microbial ecologies were similar, suggesting that while climate may act as a strong control, microbial community composition follows similar assembly paths. We find evidence that key interdomain microbial decomposers of cadavers (that is, fungi and bacteria) emerge in diverse environments and probably utilize resource partitioning and cross-feeding to break down a nutrient pulse that is rich in lipids, proteins and carbohydrates. This process would be consistent with dogma within leaf litter ecology that fungal decomposers are typically specialized decomposers of complex substrates while bacteria serve as generalists that decompose a broader nutritional landscape 60 . Thus, we hypothesize that fungi (such as Yarrowia and Candida ) assist in the catabolism of complex, dead organic matter (such as lipids and proteins) into simpler compounds (such as fatty acids and amino acids), which are utilized by bacterial community members, (such as O. alkaliphila ) capable of efficiently metabolizing these by-products. This division of labour coupled with microbial interactions drives the assembly of the microbial decomposer community, in a process reminiscent of ecological dynamics observed in leaf litter decomposition 60 .

We suspect that key network microbial decomposers are probably not specific to decomposition of human cadavers and are, in part, maintained or seeded by insects. Key cadaver bacterial decomposers O. alkaliphila , Ignatzschineria , Wohlfahrtiimonas , Bacteroides , Vagococcus lutrae , Savagea , Acinetobacter rudis and Peptoniphilaceae have been detected in terrestrial decomposition studies of swine, cattle and mice (Supplementary Table 33 ) 16 , 24 , 25 , 26 , and a subset detected in aquatic decomposition 61 . Most key network bacterial decomposers, including the well-known blow fly-associated genera Ignatzschineria and Wohlfahrtiimonas 62 , were rare or not detected in a lab-based mouse decomposition study 6 in which insects were excluded (Supplementary Table 33 ). However, a different lab-based study that excluded blow flies but included carrion beetles 26 detected a subset of these key microbial decomposers, suggesting a role for microbe–insect interactions and dispersal by insects 26 , 48 , 63 . Further evidence implicating insects as important vectors is that all key network bacterial decomposers presented here have been detected on blow flies (Supplementary Table 28 ) 6 , 64 . Furthermore, Ascomycota fungal members, such as Yarrowia and Candida , have been previously detected in association with human, swine and mouse remains 6 , 26 , 44 , 53 . Yarrowia can be vertically transmitted from parent to offspring of carrion beetle 63 and may facilitate beetle consumption of carrion. Taken together, these findings suggest that key microbial decomposer taxa identified in this study of human cadavers are probably more generalizable carrion decomposers and are likely inoculated, at least partly, by insects.

We demonstrate the potential practical application of microbiome tools in forensic science by leveraging microbial community succession patterns and machine learning techniques for accurately predicting PMI. Importantly, the predictive models showcase their generalizability by accurately predicting the PMIs of independent test samples collected from various geographic locations and climates, including for test samples collected from a climate region not represented in the training set of the model. The best-performing model was able to accurately predict PMI within ~±3 calendar days during internal validation and on an independent test set (Supplementary Tables 34 and 35 ), which is a useful timeframe for forensic sciences, enabling investigators to establish crucial timelines and aiding in criminal investigations. Prediction errors are probably due to intrinsic (for example, BMI/total mass) 19 , 24 , 65 and/or extrinsic (for example, scavengers, precipitation) 19 , 26 factors not accounted for in the model, but should be a future area of research for model improvement. For example, total mass has been previously shown not to affect microbial decomposer composition in swine 24 ; however, ref. 19 found that Gammaproteobacteria relative abundance correlated with BMI of humans. Within our study, in which cadavers had highly variable initial total masses (Supplementary Table 1 ), Acinetobacter and Ignatzschineria (within Gammaproteobacteria) were important features in our PMI models, suggesting that it is probably robust to BMI (Extended Data Fig. 7 ). In addition, scavenging by invertebrates and vertebrates is another factor that can affect not only the decomposer microbial composition (for example, carrion beetles) 26 but also the microbes themselves which can shape the scavenger community via volatile organic compounds (for example, repel vertebrates but attract insects 48 , 66 ). A better understanding of which intrinsic and extrinsic factors directly affect microbes that are important features for predicting PMI will be an important next step.

Our improved understanding of the microbial ecology of decomposing human cadavers and its more general implications for the crucial and rarely studied carrion nutrient pool is critical for revising concepts of what should be included in carbon and nutrient budgets and the models used to forecast ecosystem function and change 11 . New insight on the role of carrion decomposition in fuelling carbon and nutrient cycling is needed for conceptual and numerical models of biogeochemical cycles and trophic processes 11 ; this study informs how the assembly and interactions among decomposer microbial communities facilitate the turnover and exchange of resources, and begins unlocking one of the remaining black boxes of ecosystem ecology. Finally, these findings may contribute to society by providing potential for a new forensic tool and for potentially modulating decomposition processes in both agricultural and human death industries via the key microbial decomposers identified here.

Site and donor selection

Outdoor experiments on 36 human cadavers were conducted at three willed-body donation facilities: Colorado Mesa University Forensic Investigation Research Station (FIRS), Sam Houston State University Southeast Texas Applied Forensic Science (STAFS) Facility and University of Tennessee Anthropology Research Facility (ARF). Before the start of the project, a meeting was held at STAFS to demonstrate, discuss and agree on sampling protocols. The Institutional Review Board and the Protection of Human Subjects Committee either determined that review was not required or granted exempt status for donors at each respective facility since the proposed research does not involve human donors as defined by federal regulations. Three deceased human donors were placed supine and unclothed on the soil surface in the spring, summer, fall and winter over the years 2016 and 2017 at each facility ( N  = 36). Bodies were placed on soil with no known previous human decomposition. Before placement, STAFS performed minimal removal of vegetation including raking of leaves and removal of shrubbery, and bodies placed at STAFS were placed in cages made of 1 cm × 1 cm wire fences and wooden frames to prevent vertebrate scavenging. The ARF and FIRS did not remove vegetation or place bodies under cages as standard protocol. Furthermore, bodies were placed no closer than 2.5 m between sternum midpoints. Collection date for each donor can be found in the sample metadata, in addition to cause of death if known, initial condition, autopsy status, weight before placement, age in years if known, estimated age if not known, sex, donor storage type, days donor was stored, time since death to cooling and placement head direction (Supplementary Table 1 ). Donor weight was taken at time of intake at ARF and FIRS but is a self-reported measure either by the donor before death or a family member at STAFS. During daily sampling, daily ambient average temperature and humidity, TBS 27 , scavenging status and insect status were recorded if available or applicable. Human bodies were fully exposed to all weather elements and invertebrate scavengers. Inclusion criteria for the remains were specified before the start of the experiment and required that the remains were in the fresh stage of decomposition and had not been frozen (and not extensively cooled) or autopsied before placement at the facility.

Decomposition metric calculations

The Köppen–Geiger climate classification system characterizes both the ARF and STAFS facilities as temperate without a dry season and hot summer (Cfa) and the FIRS facility as a cold semi-arid steppe (BSk) 23 . Average daily temperatures were collected from the National Centers for Environmental Information (NCEI) website ( https://www.ncei.noaa.gov/ ) and monthly total precipitation accumulation over the course of the study was collected from the Weather Underground website ( https://www.wunderground.com/ ) from local weather stations: Grand Junction Regional Airport Station, McGhee Tyson Airport Station and Easterwood Airport Station. Reference 27 TBS quantifies the degree to which decomposition has occurred in three main areas (head, trunk and limbs) 27 . The user assigned values to represent the progress of decomposition on the basis of visual assessment of the cadaver and added these values to generate a TBS at the time of sampling. A maximum score was assigned for each area when the cadaver has reached dry skeletal remains. ADD was estimated using the weather data provided by the NCEI. Degree day on the day of placement was not included, and a base temperature of 0 °C was used. ADD was calculated by adding together all average daily temperatures above 0 °C for all previous days of decomposition, as in ref. 27 , and subtracting the base temperature of 0 °C.

Sample collection and DNA extraction

We sampled the skin surface of the head and torso near the hip along with gravesoils (soils associated with decomposition) associated with each skin site over 21 d of decomposition. Control soil samples were taken of the same soil series and horizon that are not associated with body decomposition (known past or present) from areas within or just outside each facility. We collected swabs of 756 non-decomposition soil (controls), 756 gravesoil near the hip, 756 gravesoil near the face, 756 hip skin and 756 face skin samples ( N  = 3,780). All site samples (skin surface, gravesoil and control soil) were taken using sterile dual-tipped BD SWUBE applicator (REF 281130) swabs as described in ref. 18 , and immediately frozen after each sampling event and kept frozen at −20 °C. Samples were shipped to CU Boulder or Colorado State University overnight on dry ice and immediately stored at −20 °C upon arrival and until DNA extraction. Skin and soil DNA was extracted from a single tip of the dual-tipped swabs using the PowerSoil DNA isolation kit 96-htp (MoBio Laboratories), according to standard EMP protocols ( http://www.earthmicrobiome.org/ ).

Amplicon library preparation and sequencing

Bacterial and archaeal communities were characterized using 16S rRNA gene regions while eukaryotic communities were characterized using 18S rRNA gene regions as universal markers, for all successful skin and soil DNA extracts ( n  = 3,547). To survey bacteria and archaea, we used the primer set 515f (5′GTGYCAGCMGCCGCGGTAA) and 806rb (5′GGACTACNVGGGTWTCTAAT) that targets these domains near-universally 67 , 68 , with barcoded primers allowing for multiplexing, following EMP protocols 69 . To survey microbial eukaryotes, we sequenced a subregion of the 18S rRNA gene using the primers 1391f_illumina (5′GTACACACCGCCCGTC) and EukBr_illumina (5′TGATCCTTCTGCAGGTTCACCTAC) targeting the 3′ end of the 18S rRNA gene. 18S rRNA gene primers were adapted from ref. 70 and target a broad range of eukaryotic lineages. We have successfully generated and analysed data using these gene markers previously 6 , 18 . Primers included error-corrected Golay barcodes to allow for multiplexing while preventing misassignment. PCR amplicons were quantified using Picogreen Quant-iT (Invitrogen, Life Technologies) and pooled from each sample to equimolar ratio in a single tube before shipping to the UC San Diego genomics laboratory for sequencing. For both amplicon types, pools were purified using the UltraClean PCR clean-up kit (Qiagen). 16S rRNA pools were sequenced using a 300-cycle kit on the Illumina MiSeq sequencing platform and 18S rRNA gene pools were sequenced using a 300-cycle kit on the Illumina HiSeq 2500 sequencing platform (Illumina). Samples within a sample type (skin vs soil) were randomly assigned to a sequencing run to prevent potential batch effects. Blank DNA extraction and PCR negative controls were included throughout the entire process from DNA extraction to PCR amplification to monitor contamination ( n  = 592 negative controls).

Shotgun metagenomic library preparation and sequencing

Extracted DNA from a subset of hip-associated soil samples ( n  = 756), soil controls ( n  = 9), blank controls ( n  = 102) and no-template PCR controls ( n  = 15) were chosen to undergo shallow shotgun sequencing to provide in-depth investigation of microbial dynamics within decomposition soil (Supplementary Table 4 ). Our standard protocol followed that of ref. 71 and was optimized for an input quantity of 1 ng DNA per reaction. Before library preparation, input DNA was transferred to 384-well plates and quantified using a PicoGreen fluorescence assay (ThermoFisher). Input DNA was then normalized to 1 ng in a volume of 3.5 μl of molecular-grade water using an Echo 550 acoustic liquid-handling robot (Labcyte). Enzyme mixes for fragmentation, end repair and A-tailing, ligation and PCR were prepared and added at 1:8 scale volume using a Mosquito HV micropipetting robot (TTP Labtech). Fragmentation was performed at 37 °C for 20 min, followed by end repair and A-tailing at 65 °C for 30 min. Sequencing adapters and barcode indices were added in two steps, following the iTru adapter protocol 72 . Universal adapter ‘stub’ adapter molecules and ligase mix were first added to the end-repaired DNA using the Mosquito HV robot and ligation performed at 20 °C for 1 h. Unligated adapters and adapter dimers were then removed using AMPure XP magnetic beads and a BlueCat purification robot (BlueCat Bio). A 7.5 μl magnetic bead solution was added to the total adapter-ligated sample volume, washed twice with 70% ethanol and then resuspended in 7 μl molecular-grade water.

Next, individual i7 and i5 indices were added to the adapter-ligated samples using the Echo 550 robot. Because this liquid handler individually addresses wells and we used the full set of 384 unique error-correcting i7 and i5 indices, we generated each plate of 384 libraries without repeating any barcodes, eliminating the problem of sequence misassignment due to barcode swapping (61, 62). To ensure that libraries generated on different plates could be pooled if necessary and to safeguard against the possibility of contamination due to sample carryover between runs, we also iterated the assignment of i7 to i5 indices per run, such that each unique i7:i5 index combination is only repeated once every 147,456 libraries 72 . A volume of 4.5 μl of eluted bead-washed ligated samples was added to 5.5 μl of PCR master mix and PCR-amplified for 15 cycles. The amplified and indexed libraries were then purified again using AMPure XP magnetic beads and the BlueCat robot, resuspended in 10 μl of water and 9 μl of final purified library transferred to a 384-well plate using the Mosquito HTS liquid-handling robot for library quantitation, sequencing and storage. All samples were then normalized on the basis of a PicoGreen fluorescence assay for sequencing.

Samples were originally sequenced on an Illumina HiSeq 4000; however, due to some sequencing failures, samples were resequenced on the Illumina NovaSeq 6000 platform. To ensure that we obtained the best sequencing results possible, we assessed both sequencing runs and added the best-performing sample of the two runs to the final analysis (that is, if sample X provided more reads from the HiSeq run than the NovaSeq run, we added the HiSeq data from that sample to the final analysis and vice versa). Samples were visually assessed to ensure that no batch effects from the two sequencing runs were present in beta diversity analysis. A list of which samples were pulled from the HiSeq vs NovaSeq runs can be found in the sample metadata under the column ‘best_MetaG_run’, with their corresponding read count under ‘MetaG_read_count’ (Supplementary Table 1 ). In total, 762 samples were sequenced, with 25 coming from the HiSeq run and 737 samples coming from the Novaseq run. Raw metagenomic data had adapters removed and were quality filtered using Atropos (v.1.1.24) 73 with cut-offs of q  = 15 and minimum length of 100 nt. All human sequence data were filtered out by aligning against the Genome Reference Consortium Human Build 38 patch release 7 (GRCh37/hg19) reference database released in 21 March 2016 (ncbi.nlm.nih.gov/assembly/GCF_000001405.13/) and removing all data that matched the reference from the sequence data. Alignment was performed with bowtie2 (v.2.2.3) 74 using the --very-sensitive parameter, and the resulting SAM files were converted to FASTQ format with samtools (v.1.3.1) 75 and bedtools (v.2.26.0) 76 . Metagenomic samples were removed from the analysis if they had <500 k reads. Final metagenomic sample numbers were 569 hip-adjacent soil, 5 soil controls, 102 blank controls and 15 no-template controls.

Metabolite extraction and LC–MS/MS data generation

To investigate the metabolite pools associated with decomposition skin and gravesoils, we performed metabolite extraction on the second tip of the dual-tipped swabs collected from the skin and soil associated with the hip sampling location to ensure all datasets are paired. Skin and soil swab samples were extracted using a solution of 80% methanol. Briefly (with all steps performed on ice), swabs were placed into a pre-labelled 96-well DeepWell plate where A1–D1 were used for a solvent blank and E1–H1 were used for blank clean swabs with extraction solvent added. Swab shafts were cut aseptically and 500 μl of solvent (80% methanol with 0.5 μM sulfamethazine) was added. The DeepWell plate was covered and vortexed for 2 min, followed by 15 min in a water sonication bath. Next, samples were incubated at 4 °C for 2 h, followed by a 12 h incubation at −20 °C. Swab tips were then removed from the solvent and samples were lyophilised. Untargeted metabolomics LC–MS/MS data were generated from each sample. Two types of dataset were generated from each sample: MS1 data for global and statistical analysis and MS/MS data for molecular annotation. Molecular annotation was performed through the GNPS platform https://gnps.ucsd.edu/ . Molecules were annotated with the GNPS reference libraries 77 using accurate parent mass and MS/MS fragmentation pattern according to level 2 or 3 of annotation defined by the 2007 metabolomics standards initiative 78 . If needed and if the authentic chemical standard was available, MS/MS data were collected from the chemical standard and compared to MS/MS spectra of the molecule annotated from the sample (level 1 of annotation).

Amplicon data processing

After data generation, amplicon sequence data were analysed in the Metcalf lab at Colorado State University using the QIIME2 analysis platform v.2020.2 and v.2020.8 (ref. 79 ). In total, 4,139 samples were sequenced, including 592 DNA extraction blank negative and no-template PCR controls. Sequencing resulted in a total of 89,288,561 16S rRNA partial gene reads and 1,543,472,127 18S rRNA partial gene reads. Sequences were quality filtered and demultiplexed using the pre-assigned Golay barcodes. Reads were 150 bp in length. 18S rRNA gene sequences had primers (5′GTAGGTGAACCTGCAGAAGGATCA) removed using cutadapt to ensure that the variable length of the 18S region was processed without primer contamination. Sequences were then classified into amplicon sequence variants (ASVs) in groups of samples that were included on the same sequencing run so the programme could accurately apply the potential error rates from the machine using the Deblur denoising method (v.2020.8.0) 80 . Feature tables and representative sequences obtained from denoising each sequencing run were then merged to create a complete dataset for each amplicon method. Taxonomic identifiers were assigned to the ASVs using the QIIME feature-classifier classify-sklearn method 81 . For the 16S rRNA gene data, these assignments were made using the SILVA 132 99% classifier for the 515fb/806rb gene sequences. ASVs that were assigned to chloroplast or mitochondria (non-microbial sequences) were filtered out of the dataset before continuing analysis. For 18S rRNA data, the RESCRIPt (v.2022.8.0) plugin was used to extract the full 12-level taxonomy from sequences matching the primers from the SILVA 138 99% database, to dereplicate the extracted sequences and to train a classifier to assign labels to ASVs in the feature table 82 . This taxonomy was used to filter out any ASVs that were assigned to Archaea, Streptophyta, Bacteria, Archaeplastida, Arthropoda, Chordata, Mollusca and Mammalia, as well as those that were unassigned, resulting in 5,535 ASVs at a total frequency of 772,483,701. DNA extraction negative and no-template PCR control samples were analysed to determine that contamination within the samples was minimal. Most control samples were low abundance and below the threshold used for rarefaction. The few controls that were above the rarefaction threshold clustered distantly and separately from true samples on principal coordinate analysis (PCoA) and had low alpha diversities, hence samples above the rarefaction depth were considered minimally contaminated and acceptable for analyses. Subsequently, DNA extraction negative and no-template PCR control samples were removed from the dataset and future analyses.

Microbial diversity metrics were generated from both amplicon types using the QIIME2 phylogenetic diversity plugin. The phylogenetic trees were constructed for each amplicon type individually using the fragment-insertion SEPP method 83 against the SILVA 128 99% reference tree. Alpha diversity metrics were calculated using the number of observed features as ASV richness and Faith’s phylogenetic diversity formulas. Statistical comparisons were made using the pairwise Kruskal–Wallis H -test with a Benjamini–Hochberg multiple-testing correction at an alpha level of 0.05 (ref. 84 ). To evaluate beta diversity, the generalized UniFrac method weighted at 0.5 was used to calculate dissimilarity 85 . Statistical comparisons were made using permutational analysis of variance (PERMANOVA) with a multiple-testing correction and an alpha level of 0.05 (ref. 86 ). Taxonomy and alpha diversity visualizations were created using ggplot2 and the viridis package in R 87 , 88 . Beta diversity principal coordinates plots were constructed using the Emperor (v.2022.8.0) plugin in QIIME2 (ref. 89 ). Linear mixed-effects models were used to evaluate the contribution of covariates to a single dependent variable and to test whether community alpha diversity metrics (for example, ASV richness) and beta diversity distances (for example, UniFrac distances) were impacted by decomposition time (that is, ADD) and sampling location (that is, decomposition soil adjacent to the hip and control soil). The response variables were statistically assessed over ADD with sampling site (that is, decomposition soil vs control soil) as an independent variable (fixed effect) and a random intercept for individual bodies to account for repeated measures using the formula: diversity metric ≈ ADD × sampling site + (1|body ID).

Detection of key decomposers in other decomposition studies

16S rRNA gene amplicon sequence data files from refs. 6 , 24 , 25 , 64 , 69 , 90 , 91 were obtained from QIITA 92 under study IDs 10141–10143, 1609, 13114, 10317, 13301 and 11204, respectively. Data obtained from QIITA 92 had been previously demultiplexed and denoised using Deblur 80 and are available on the QIITA 92 study page. Data from ref. 16 were obtained from the NCBI Sequence Read Archive under BioProject PRJNA525153 . Forward reads were imported into QIIME2 (v.2023.5) 79 , demultiplexed and denoised using Deblur (v.1.1.1) 80 . Data from ref. 26 were obtained from the Max Planck Society Edmond repository ( https://edmond.mpdl.mpg.de/dataset.xhtml?persistentId=doi:10.17617/3.UV4FBN ). Forward reads were imported into QIIME2 (v.2023.5) 79 and demultiplexed. Primers (5′ GTGCCAGCMGCCGCGGTAA) were removed using cutadapt (v.4.4) 93 and the data were denoised using Deblur (v.1.1.1) 80 . ASVs from all studies were assigned taxonomy using a naïve Bayes taxonomy classifier trained on the V4 (515f/806r) region of SILVA 138 99% operational taxonomic units (OTUs). Data tables were imported into Jupyter notebooks (Jupyter Lab v.4.0.5) 94 for further analysis (Python v.3.8.16). A search for the 35 universal PMI decomposer ASVs was conducted within each dataset. This search matched exact ASVs in our dataset to other datasets but did not match similar ASVs that may be classified as the same taxon. The relative abundance of each decomposer ASV was first averaged across all samples within a specific metadata category. The average relative abundances were then summed across each decomposer genus. Prevalence tables were constructed by summing the number of samples across a specific metadata category in which each universal decomposer ASV was present. The presence of Wohlfahrtiimonas was found in the ref. 26 dataset; however, these ASVs were not exact sequence matches to our universal Wohlfahrtiimonas decomposers and probably represent insect-associated strains (Supplementary Table 33 ; Wohlfahrtiimonadaceae column). We searched within the remaining studies for the presence of other ASVs assigned to the Wohlfahrtiimonas genus or ASVs that were assigned to the Wohlfahrtiimonadaceae family but these were unidentified at the genus level. Average relative abundances were calculated as described above.

Community assembly mechanism determination

To investigate the ecological processes driving bacterial assembly, we quantitatively inferred community assembly mechanisms by phylogenetic bin-based null model analysis of 16S rRNA gene amplicon data as described in refs. 95 , 96 . Longitudinal turnover in phylogenetic composition within the decomposition soil between successional stages was quantified using the beta nearest taxon index (βNTI), where a |βNTI| value <+2 indicates that stochastic forces drive community assembly and a value >+2 indicates less than or greater than expected phylogenetic turnover by random chance (deterministic forces). βNTI values <−2 correspond to homogeneous selection and values >+2 correspond to heterogeneous selection. Homogeneous selection refers to communities that are more similar to each other than expected by random chance, while heterogeneous selection refers to communities that are less similar to each other than expected by random chance. Deterministic forces include selection factors such as environmental filtering and biological interactions, while stochastic forces include random factors such as dispersal, birth–death events and immigration.

MAGs generation and classification

To maximize assembly, metagenomes were co-assembled within sites using MEGAHIT (v.1.2.9) 97 with the following flags: –k-min 41 (see Supplementary Tables 4 – 6 for a list of samples used to generate metagenomic data, co-assembly statistics, GTDB taxonomic classification and TPM-normalized count abundance of MAGs within each sample). Assembled scaffolds >2,500 kb were binned into MAGs using MetaBAT2 (v.2.12.1) 98 with default parameters. MAG completion and contamination were assessed using checkM (v.1.1.2) 99 . MAGs were conservatively kept in the local MAG database if they were >50% complete and <10% contaminated. MAGs were dereplicated at 99% identity using dRep (v.2.6.2) 100 . MAG taxonomy was assigned using GTDB-tk (v.2.0.0, r207) 101 . Novel taxonomies were determined as the first un-named taxonomic level in the GTDB classification string (see Supplementary Table 5 for MAG quality and taxonomy information). MAGs and co-assemblies were annotated using DRAM (v.1.0.0) 102 (Supplementary Table 5 ; https://doi.org/10.5281/zenodo.7843104 ). From 575 metagenomes, we recovered 1,130 MAGs, of which 276 were medium or high quality, and dereplicated these at 99% identity into 257 MAGs. This MAG set encompassed novel bacterial orders ( n  = 3), families ( n  = 9), genera ( n  = 28) and species ( n  = 158), providing genomic blueprints for microbial decomposers dominated by Gammaproteobacteria and Actinobacteriota (Supplementary Table 5 ).

MAG and gene abundance mapping

To determine the abundance of the MAGs in each sample, we mapped reads from each sample to the dereplicated MAG set using bowtie2 (v.2.3.5) 74 with the following flags: -D 10 -R 2 -N 1 -L 22 -i S,0,2.50. Output sam files were converted to sorted BAM files using samtools (v.1.9) 75 . BAM files were filtered for reads mapping at 95% identity using the reformat.sh script with flag idfilter=0.95 from BBMap (v.38.90) ( https://sourceforge.net/projects/bbmap/ ). Filtered BAM files were input to CoverM (v0.3.2) ( https://github.com/wwood/CoverM ) in genome mode to output transcripts per million (TPM). To determine the abundance of genes across samples, we clustered the gene nucleotide sequences from the annotated assemblies output by DRAM using MMseqs2 (release 13) easy-linclust (v4e23d5f1d13a435c7b6c9406137ed68ce297e0fc) 103 with the following flags: –min-seq-id 0.95–alignment-mode 3–max-seqs 100000. We then mapped reads to the cluster representative using bowtie2 (ref. 74 ) and filtered them to 95% identity as described above for the MAGs. To determine gene abundance, filtered bams were input to coverM in contig mode to output TPM. Bacterial MAG feature tables were imported into QIIME2 (v.2020.8) 79 . Bacterial features that were not present for a total of 50 times and were found in less than six samples were removed from the dataset to reduce noise. Bacterial feature tables were collapsed at the phylum, class, order, family, genus and species GTDB taxonomic levels. Community diversity was compared between the MAG and 16S rRNA ASV feature tables to ensure that both data types demonstrate the same biological signal. Each table was filtered to contain samples with paired 16S rRNA and metagenomic data (that is, samples with both metagenomic and 16S rRNA data). Bray–Curtis dissimilarity matrices were calculated for the TPM-normalized MAG abundance table and rarified 16S rRNA ASV table. Procrustes/PROTEST 104 , 105 and Mantel tests were performed between the PCoA ordinations and distance matrices, respectively 106 . Results showed that the datasets were not significantly different from each other and confirmed their shared biological signal (Extended Data Fig. 10 ).

Metabolic interaction simulations

Higher-order (20 microbial members) co-occurrence patterns were calculated from the MAG relative frequency tables of each decomposition stage (that is, early, active, advanced) for each facility using HiOrCo (v.1.0.0) (cut-off 0.001) ( https://github.com/cdanielmachado/HiOrCo ). HiOrCo provides 100 iterations of co-occurring MAG communities to improve simulation accuracy. No significantly co-occurring MAGs were detected at the FIRS facility during advanced decomposition; therefore, we continued the analyses using only early and active decomposition stages at FIRS. CarveMe (v.1.5.1) 107 was used to construct genome-scale metabolic models (GEMs) from each MAG using default parameters ( https://github.com/cdanielmachado/carveme ). GEMs from each co-occurring MAG community were input as a microbial community into SMETANA (v1.0.0) ( https://github.com/cdanielmachado/smetana ) to compute several metrics that describe the potential for metabolic cooperative and competitive interactions between community members as described in refs. 34 , 35 . Metrics include metabolic interaction potential (MIP), metabolic resource overlap (MRO), species coupling score (SCS), metabolite uptake score (MUS), metabolite production score (MPS) and SMETANA score. MIP calculates how many metabolites the species can share to decrease their dependency on external resources. MRO is a method of assessing metabolic competition by measuring the overlap between the minimal nutritional requirements of all member species on the basis of their genomes. SCS is a community size-dependent measurement of the dependency of one species in the presence of the others to survive. MUS measures how frequently a species needs to uptake a metabolite to survive. MPS is a binary measurement of the ability of a species to produce a metabolite. The individual SMETANA score is a combination of the SCS, MUS and MPS scores and gives a measure of certainty of a cross-feeding interaction (for example, species A receives metabolite X from species B). Simulations were created on the basis of a minimal medium, calculated using molecular weights, that supports the growth of both organisms, with the inorganic compounds hydrogen, water and phosphate excluded from analysis. A random null model analysis was performed to ensure that changes in co-occurring MAGs within each site and decomposition are driving interaction potential changes. For each site and decomposition stage, 100 20-member communities were generated by random selection without replacement using random.sample(). Simulations to calculate MIP and MRO were performed as above. A detailed investigation into the potential molecules being cross-fed was performed on the late stages of decomposition for each facility: temperate-climate advanced decomposition and semi-arid active decomposition stages.

Metabolic efficiency simulations

Metabolic models and the Constraint Based Reconstruction and Analysis (COBRA) toolbox (v.3.0) 108 were used to simulate differences in metabolic capabilities between samples that are spatiotemporally different. A general base growth medium, M 0 , containing a list of carbohydrates, amino acids, lipids and other vitamins and minerals adapted from a previous study 109 was used. From this base medium, carbohydrate-rich, M 1 , amino acid-rich, M 2 , and lipid-rich, M 3 , media were defined. The carbohydrate-rich medium includes all compounds in the base medium but allows for higher uptake of carbohydrates than proteins and lipids, and vice versa. The COBRA toolbox 108 in MATLAB was used to optimize overall ATP production from M 1 , M 2 and M 3 for each individual MAG in an aerobic condition. This assumption was made because the topsoil conditions in which decomposition happens are relatively aerobic. The calculated maximum ATP yields can be interpreted as the maximum capability of each MAG in extracting ATP from the growth media. Finally, the weighted average of total ATP production from the GEMs in a sample was calculated by multiplying the relative abundance of each MAG by the maximum total ATP production and summing over all of the GEMs in a sample 110 .

Molecular networking and spectral library search

A molecular network was created using the Feature-Based Molecular Networking (FBMN) workflow (v.28.2) 111 on GNPS ( https://gnps.ucsd.edu ; ref. 77 ). The mass spectrometry data were first processed with MZMINE2 (v.2.53) 112 and the results were exported to GNPS for FBMN analysis. The precursor ion mass tolerance was set to 0.05 Da and the MS/MS fragment ion tolerance to 0.05 Da. A molecular network was then created where edges were filtered to have a cosine score above 0.7 and >5 matched peaks. Furthermore, edges between two nodes were kept in the network if and only if each of the nodes appeared in each other’s respective top 10 most similar nodes. Finally, the maximum size of a molecular family was set to 100, and the lowest-scoring edges were removed from molecular families until the molecular family size was below this threshold. The spectra in the network were then searched against GNPS spectral libraries 77 , 111 . All matches kept between network spectra and library spectra were required to have a score above 0.7 and at least 6 matched peaks.

Metabolite formula and class prediction

Spectra were downloaded from GNPS and imported to SIRIUS (v.4.4) 113 containing ZODIAC 114 for database-independent molecular formula annotation under default parameters. Formula annotations were kept if the ZODIAC score was at least 0.95 and at least 90% of the MS/MS spectrum intensity was explained by SIRIUS as described by the less-restrictive filtering from ref. 114 . A final list of formula identifications was created by merging ZODIAC identifications with library hits from GNPS (Supplementary Table 36 ). In the cases where a metabolite had both a ZODIAC predicted formula and an assigned library hit, the library hit assignment took precedence. The final formula list contained 604 formula assignments. Organic compound composition was examined in van Krevelen diagrams and assigned to major biochemical classes on the basis of the molar H:C and O:C ratios 115 . Since classification based on molecular ratio does not guarantee that the compound is part of a specific biochemical class, compounds were labelled as chemically similar by adding ‘-like’ to their assigned class (for example, protein-like). Furthermore, compound formulas were used to calculate the nominal oxidation state of carbon on the basis of the molecular abundances of C, H, N, O, P and S as described in ref. 116 (Supplementary Tables 37 and 38 ).

Metabolite feature table processing

The metabolite feature table downloaded from GNPS was normalized using sum normalization, then scaled with pareto scaling 117 and imported in QIIME2 (v.2022.2) 79 . This table contains all library hits, metabolites with predicted formulas and unannotated metabolites. PCoA clustering with Bray–Curtis and Jaccard distances confirmed clustering of processing controls separate from soil and skin samples. Five soil samples were removed for clustering with processing controls. Processing controls were removed from the dataset; then metabolites absent from a minimum of 30 samples were removed to reduce noise. Bray–Curtis and Jaccard beta diversity group comparisons were performed between soil and skin samples using PERMANOVA (perm. = 999). The metabolite feature table was filtered to contain metabolites with chemical formulas based on GNPS library hits and/or predicted chemical formulas from ZODIAC. Differential abundance analyses were performed on these tables from the cadaver-associated soil and skin to test metabolite log-ratio change over decomposition stage using initial, day 0 samples as the reference frame, utilizing the Analysis of Composition of Microbiomes with Bias Correction (ANCOM-BC) 118 QIIME2 (v.2022.2) plugin.

The complete methodology including mathematical formulas for joint-RPCA can be found in Supplementary Text . Briefly, before joint factorization, we first split the dataset into training train and testing sample sets from the total set of shared samples across all input data matrices. The datasets included in this analysis were 16S rRNA gene abundances, 18S rRNA gene abundances, MAG abundances, MAG gene abundances, MAG gene functional modules and metabolites from the hip-adjacent decomposition soil. Each matrix was then transformed through the robust-centred-log-ratio transformation (robust-clr) to centre the data around zero and approximate a normal distribution 42 , 119 . Unlike the traditional clr transformation, the robust-clr handles the sparsity often found in biological data without requiring imputation. The robust-clr transformation was applied to the training and test set matrices independently. The joint factorization used here was built on the OptSpace matrix completion algorithm, which is a singular value decomposition optimized on a local manifold 42 , 119 . A shared matrix was estimated across the shared samples of all input matrices. For each matrix, the observed values were only computed on the non-zero entries and then averaged, such that the minimized shared estimated matrices were optimized across all matrices. The minimization was performed across iterations by gradient descent. To ensure that the rotation of the estimated matrices was consistent, the estimated shared matrix and the matrix of shared eigenvalues across all input matrices were recalculated at each iteration. To prevent overfitting of the joint-factorization, cross-validation of the reconstruction was performed. In this case, all the previously described minimization was performed on only the training set data. The test set data were then projected into the same space using the training set data estimated matrices and the reconstruction of the test data was calculated. Through this, it can be ensured that the minimization error of the training data estimations also minimizes that of the test set data, which is not incorporated into these estimates on each iteration. After the training data estimates were finalized, the test set samples were again projected into the final output to prevent these samples from being lost. The correlations of all features across all input matrices were calculated from the final estimated matrices. Finally, here we treated the joint-RPCA with only one input matrix as the original RPCA 119 but with the additional benefit of the addition of cross-validation for comparison across other methods.

Multi-omics ecological network visualization

The datasets included in this analysis were 18S rRNA gene abundances, MAG abundances, MAG gene functional modules and metabolites from the hip-adjacent decomposition soil. log ratios were generated using the joint-RPCA PC2 scores, chosen on the basis of the sample ordination, to rank each omics feature on the basis of association with either initial non-decomposition and early decomposition soil or late decomposition (that is, active and advanced) soil time periods. The log ratios are the log ratio of the sum of the top N -features raw-counts/table-values over the sum of the bottom N ranked features raw-counts/table-values, based on the PC2 loadings produced from the ordinal analysis since these were observed to change the most by decomposition stage. To prevent sample drop out in the log ratio due to sparsity, as described in refs. 120 , 121 , between 2 and 1,500 numerator and denominator features for each omic were summed such that at least 90% of the sample were retained: metagenomics (MAGs) N -features = 30 (99.2%), 18S N -features = 1,499 (90.1%), metagenomics (gene modules) N -features = 26 (100%) and metabolomics N -features = 238 (100%). The joint-RPCA correlation matrix was subset down to the total initial day zero, early, active or advanced decomposition-associated features used in the log ratios to generate the network visualizations. Only the top 20% of correlations between selected nodes were retained to reduce noise in generating the network visualization.

Phylogenetic tree generation

Redbiom (v.0.3.9) 122 was used to search for all publicly available AGP 90 and EMP 69 studies for samples containing at least 100 counts of a key decomposer. The AGP samples were further filtered to only include gut and skin environments and the EMP samples were limited to only include soil and host environment. Next, the top 50 most abundant ASVs were taken from each environment along with the key decomposers and placed on a phylogenetic tree using Greengenes2 (release 2022.10) 123 . The ASVs were then ranked according to the number of samples they were found in and visualized using EMPress (v.1.2.0) 124 .

Random forest regression modelling

Processed features tables from each ‘omic data type were used for random forest regression modelling with nested cross-validation (CV) to test ADD prediction power. Data were subset so that models were trained and tested for each sampling location separately (for example, soil adjacent to the hip, soil adjacent to the face, skin of the hip and skin of the face). Data were pre-processed for models using calour (v.2018.5.1) ( http://biocore.github.io/calour/index.html ) and models were trained/tested using scikit-learn (v.0.24.2) 125 . Features with an abundance of zero in the dataset after filtering were removed. The facilities at which sampling was performed were included as features in the model to determine whether geographical location is important for modelling. Samples from individual bodies were grouped together to prevent samples from a body being split between train and test sets to help prevent overfitting. Nested CV was performed to thoroughly test the accuracy and generalizability of the models. Hyperparameters tested for optimization were: max_depth = [None, 4], max_features = [‘auto’, 0.2] and bootstrap = [True, False]. Nested CV was made of an outer CV loop and an inner CV loop. The outer loop was created by a LeaveOneGroupOut split wherein samples from one of the 36 bodies were set aside for model validation after the inner CV loop completes. The remaining 35 bodies were used for RandomForestRegressor (n_estimators = 500) model training with the inner CV loop. The inner CV loop performed a LeaveOneGroupOut split as well so that 34 bodies were used to train a model, which was tested on the samples from the one withheld body in the inner CV loop. This inner CV was repeated until all 35 bodies within the inner loop were used as a test body once to determine which hyperparameters were best for prediction. The best-performing inner CV model was then used to predict the samples from the 36th body that was withheld at the outer CV loop, which now acts as a validation test set. Model accuracy was determined by calculating the MAE of the predicted ADD relative to the actual ADD of all the validation body samples. The prediction of the samples from the 36th body, which was completely withheld from the training of the model, allowed us to reduce overfitting and gain an estimate of the model accuracy. The entire nested CV process was repeated until each body was used as the outer CV loop validation body one time (that is, 36 iterations). The resulting 36 mean absolute errors of each body were used for determining model accuracy, generalizability and which data type performed the best. To ensure that we were using the complete dataset to determine the important taxa driving the models, the best-performing hyperparameters (bootstrap=False, max_depth=None, max_features=0.2) were used to train a RandomForestRegressor (n_estimators = 1,000) model to extract the important features. Important features were ranked by their relative importance on a scale from 0–1, where the sum of all importances equals 1. A random forest model using TBS from each sampling day as training data for ADD prediction was trained and tested using the same methodology to compare microbiome-based models to a more traditional method of assessing decomposition progression.

Lastly, we confirmed the accuracy and reliability of postmortem interval prediction with an independent test set of samples collected from bodies not represented in our models. The independent test set was collected from hip-adjacent soil and skin of the hip locations across three facilities (ARF, Forensic Anthropology Research Facility in San Marcos, Texas (FARF) and Research on Experimental and Social Thanatology in Quebec, Canada (REST)) (Supplementary Table 39 ). The independent test set was made up of temporal samples taken from each facility. ARF and REST samples consisted of three bodies with three timepoints taken from each body at each facility. At each timepoint, a soil sample was swabbed within the purge and outside the purge, and a skin sample was swabbed from the hip. One ARF body (B3.D4) did not have purge during the first timepoint; therefore, this sample was not collected. FARF provided samples from four bodies. Two bodies (2021.04 and 2021.45) had the same sampling procedure as ARF and REST, while the other two bodies (2021.39 and 2021.44) did not have purge during the first sampling timepoint; hence samples were not collected. Samples were collected, shipped, stored, DNA extracted and 16S rRNA V4 sequenced using the previously described methods. After data generation, amplicon sequence data were analysed in the Metcalf lab using QIIME2 (v.2020.8) 79 . Sequences were quality filtered and demultiplexed using the pre-assigned Golay barcodes. Reads were 150 bp in length. Sequences were then classified into ASVs using the deblur denoising method 80 . Taxonomic identifiers were assigned to the ASVs using the QIIME feature-classifier classify-sklearn method 81 using the SILVA 132 99% classifier for the 515fb/806rb gene sequences. ASVs that were assigned to chloroplast or mitochondria (non-microbial sequences) were filtered out of the dataset before continuing analysis. Data were rarified to 5,000 reads per sample and collapsed to the SILVA database 7-rank taxonomic level (L7). Feature tables were split into soil and skin data; then the validation data table was matched to the original dataset so that sampling location and features were the same (that is, using only taxa found in hip-adjacent soil in both datasets). A random forest regressor model (n_estimators=1000, max_depth=None, bootstrap=False, max_features=0.2) was built and fitted to predict the validation samples’ true ADD measurement. Randomly assigned ADDs were used as a null model.

Statistics and reproducibility

From March 2016 to December 2017, 36 human cadavers were sampled daily starting on the day of placement through 21 d of decomposition. The study encompasses three geographically distinct anthropological research facilities, and 3 cadavers were placed at each facility for each of the four seasons. Swab samples were collected from soil directly adjacent to the hip, face and a control, non-decomposition location. Swab samples were also collected from skin located on the hip and the face. No statistical method was used to predetermine sample size. The samples were randomized during processing. The investigators were not blinded to allocation during experiments and outcome assessment. Samples were excluded if not enough DNA was extracted, sequenced or if sequence quality was poor. Negative controls were included during DNA/metabolite extraction, amplification and library preparation. Linear statistical modelling was performed with linear mixed-effects models to a single dependent variable, and response variables were statistically assessed over ADD with a random intercept for individual bodies to account for repeated measures. Group comparisons were performed using Dunn Kruskal–Wallis H -test with multiple-comparison P values adjusted using the Benjamini–Hochberg method, two-tailed analysis of variance (ANOVA) with no multiple-comparison adjustments, or PERMANOVA with a multiple-testing correction. Differential abundance analyses were performed using ANCOM-BC 118 with initial, day 0 samples as the reference frame. Procrustes/PROTEST 104 , 105 and Mantel tests were performed between PCoA ordinations and distance matrices, respectively 106 .

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Raw amplicon and metagenomic sequencing data and sample metadata are available on the QIITA open-source microbiome study management platform under study 14989 and ENA accession PRJEB62460 ( ERP147550 ). Dereplicated MAGs and DRAM output can be found publicly on Zenodo ( https://doi.org/10.5281/zenodo.7843104 ; https://zenodo.org/record/7938240 ) and NCBI BioProject PRJNA973116 . The mass spectrometry data were deposited on the MassIVE public repository (accession numbers: MSV000084322 for skin samples and MSV000084463 for soil samples). The molecular networking job can be publicly accessed at https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=1c73926f2eb5409985cc2e136062db2f . The GNPS database was accessed through https://gnps.ucsd.edu/ . The GreenGenes2 database can be found at https://ftp.microbio.me/greengenes_release/ . SILVA databases can be found at https://www.arb-silva.de/documentation/release-1381/ . The Earth Microbiome Project data and American Gut Project data can be found on EBI under accessions ERP125879 and ERP012803 , respectively. 16S rRNA gene amplicon sequence data files from refs. 6 , 24 , 25 , 64 , 69 , 90 , 91 were obtained from QIITA 92 under study IDs 10141–10143 (ref. 6 ), 1609 (refs. 24 , 25 ), 13114 (ref. 69 ), 10317 (ref. 90 ), 13301 (ref. 64 ) and 11204 (ref. 91 ). Data from ref. 16 were obtained from the NCBI Sequence Read Archive under BioProject PRJNA525153 . Data from ref. 26 were obtained from the Max Planck Society Edmond repository ( https://edmond.mpdl.mpg.de/dataset.xhtml?persistentId=doi:10.17617/3.UV4FBN ). The GTDB data can be accessed at https://data.gtdb.ecogenomic.org/releases/ . Source data are provided with this paper.

Code availability

Analysis code, intermediate files and metadata are publicly available on Github ( https://github.com/Metcalf-Lab/2023-Universal-microbial-decomposer-network ). The complete mathematical algorithms for Joint-RPCA can be found in Supplementary Text .

Swift, M. J., Heal, O. W. & Anderson, J. M. Decomposition in Terrestrial Ecosystems (Blackwell Scientific, 1979).

Carter, D. O., Yellowlees, D. & Tibbett, M. Cadaver decomposition in terrestrial ecosystems. Naturwissenschaften 94 , 12–24 (2007).

Article   CAS   PubMed   Google Scholar  

Wagg, C., Schlaeppi, K., Banerjee, S., Kuramae, E. E. & van der Heijden, M. G. A. Fungal–bacterial diversity and microbiome complexity predict ecosystem functioning. Nat. Commun. 10 , 4841 (2019).

Article   PubMed   PubMed Central   Google Scholar  

Schroeter, S. A. et al. Microbial community functioning during plant litter decomposition. Sci. Rep. 12 , 7451 (2022).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Strickland, M. S., Lauber, C., Fierer, N. & Bradford, M. A. Testing the functional significance of microbial community composition. Ecology 90 , 441–451 (2009).

Article   PubMed   Google Scholar  

Metcalf, J. L. et al. Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351 , 158–162 (2016).

Pechal, J. L. et al. The potential use of bacterial community succession in forensics as described by high throughput metagenomic sequencing. Int. J. Leg. Med. 128 , 193–205 (2014).

Article   Google Scholar  

Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115 , 6506–6511 (2018).

Parmenter, R. R. & MacMahon, J. A. Carrion decomposition and nutrient cycling in a semiarid shrub–steppe ecosystem. Ecol. Monogr. 79 , 637–661 (2009).

Barton, P. S., Cunningham, S. A., Lindenmayer, D. B. & Manning, A. D. The role of carrion in maintaining biodiversity and ecological processes in terrestrial ecosystems. Oecologia 171 , 761–772 (2013).

Barton, P. S. et al. Towards quantifying carrion biomass in ecosystems. Trends Ecol. Evol. 34 , 950–961 (2019).

Putman, R. J. Flow of energy and organic matter from a carcase during decomposition: decomposition of small mammal carrion in temperate systems 2. Oikos 31 , 58–68 (1978).

Article   CAS   Google Scholar  

DeVault, T. L., Brisbin, I. L. Jr & Rhodes, O. E. Jr Factors influencing the acquisition of rodent carrion by vertebrate scavengers and decomposers. Can. J. Zool. 82 , 502–509 (2004).

Aneja, M. K. et al. Microbial colonization of beech and spruce litter—influence of decomposition site and plant litter species on the diversity of microbial community. Microb. Ecol. 52 , 127–135 (2006).

Banerjee, S. et al. Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biol. Biochem. 97 , 188–198 (2016).

Dangerfield, C. R., Frehner, E. H., Buechley, E. R., Şekercioğlu, Ç. H. & Brazelton, W. J. Succession of bacterial communities on carrion is independent of vertebrate scavengers. PeerJ 8 , e9307 (2020).

Johnson, H. R. et al. A machine learning approach for using the postmortem skin microbiome to estimate the postmortem interval. PLoS ONE 11 , e0167370 (2016).

Metcalf, J. L. et al. A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system. eLife 2 , e01104 (2013).

Singh, B. et al. Temporal and spatial impact of human cadaver decomposition on soil bacterial and arthropod community structure and function. Front. Microbiol. 8 , 2616 (2017).

Hong, E. S., Bang, S. H., Kim, Y.-H. & Min, J. Treatment of livestock carcasses in soil using Corynebacterium glutamicum and lysosomal application to livestock burial. Environ. Health Toxicol. 33 , e2018009 (2018).

Fey, S. B. et al. Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events. Proc. Natl Acad. Sci. USA 112 , 1083–1088 (2015).

Metcalf, J. L. Estimating the postmortem interval using microbes: knowledge gaps and a path to technology adoption. Forensic Sci. Int. Genet. 38 , 211–218 (2019).

Beck, H. E. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5 , 180214 (2018).

Weiss, S., Carter, D. O., Metcalf, J. L. & Knight, R. Carcass mass has little influence on the structure of gravesoil microbial communities. Int. J. Leg. Med. 130 , 253–263 (2015).

Carter, D. O., Metcalf, J. L., Bibat, A. & Knight, R. Seasonal variation of postmortem microbial communities. Forensic Sci. Med. Pathol. 11 , 202–207 (2015).

Shukla, S. P. et al. Microbiome-assisted carrion preservation aids larval development in a burying beetle. Proc. Natl Acad. Sci. USA 115 , 11274–11279 (2018).

Megyesi, M. S., Nawrocki, S. P. & Haskell, N. H. Using accumulated degree-days to estimate the postmortem interval from decomposed human remains. J. Forensic Sci. 50 , 618–626 (2005).

Connor, M., Baigent, C. & Hansen, E. S. Measuring desiccation using qualitative changes: a step toward determining regional decomposition sequences. J. Forensic Sci. 64 , 1004–1011 (2019).

Towne, E. G. Prairie vegetation and soil nutrient responses to ungulate carcasses. Oecologia 122 , 232–239 (2000).

Vass, A. A., Bass, W. M., Wolt, J. D., Foss, J. E. & Ammons, J. T. Time since death determinations of human cadavers using soil solution. J. Forensic Sci. 37 , 1236–1253 (1992).

Coe, M. The decomposition of elephant carcases in the Tsavo (East) National Park, Kenya. J. Arid Environ. 1 , 71–86 (1978).

Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K. & Paul, E. The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob. Change Biol. 19 , 988–995 (2013).

Gralka, M., Szabo, R., Stocker, R. & Cordero, O. X. Trophic interactions and the drivers of microbial community assembly. Curr. Biol. 30 , R1176–R1188 (2020).

Zelezniak, A. et al. Metabolic dependencies drive species co-occurrence in diverse microbial communities. Proc. Natl Acad. Sci. USA 112 , 6449–6454 (2015).

Machado, D. et al. Polarization of microbial communities between competitive and cooperative metabolism. Nat. Ecol. Evol. 5 , 195–203 (2021).

DeBruyn, J. M. et al. Comparative decomposition of humans and pigs: soil biogeochemistry, microbial activity and metabolomic profiles. Front. Microbiol. 11 , 608856 (2020).

Keenan, S. W., Schaeffer, S. M., Jin, V. L. & DeBruyn, J. M. Mortality hotspots: nitrogen cycling in forest soils during vertebrate decomposition. Soil Biol. Biochem. 121 , 165–176 (2018).

Carbonero, F., Benefiel, A. C., Alizadeh-Ghamsari, A. H. & Gaskins, H. R. Microbial pathways in colonic sulfur metabolism and links with health and disease. Front. Physiol. 3 , 448 (2012).

Parr, W. R. G. J. Water Potential Relations in Soil Microbiology (Soil Science Society of America, 1981).

Stark, J. M. & Firestone, M. K. Mechanisms for soil moisture effects on activity of nitrifying bacteria. Appl. Environ. Microbiol. 61 , 218–221 (1995).

Manzoni, S., Taylor, P., Richter, A., Porporato, A. & Ågren, G. I. Environmental and stoichiometric controls on microbial carbon-use efficiency in soils. New Phytol. 196 , 79–91 (2012).

Martino, C. et al. A novel sparse compositional technique reveals microbial perturbations. mSystems 4 , e00016–e00019 (2019).

Drobish, A. M. et al. Oblitimonas alkaliphila gen. nov., sp. nov., in the family Pseudomonadaceae, recovered from a historical collection of previously unidentified clinical strains. Int. J. Syst. Evol. Microbiol. 66 , 3063–3070 (2016).

Ashe, E. C., Comeau, A. M., Zejdlik, K. & O’Connell, S. P. Characterization of bacterial community dynamics of the human mouth throughout decomposition via metagenomic, metatranscriptomic, and culturing techniques. Front. Microbiol. 12 , 689493 (2021).

Dong, N. et al. Prevalence, transmission, and molecular epidemiology of tet(X)-positive bacteria among humans, animals, and environmental niches in China: an epidemiological, and genomic-based study. Sci. Total Environ. 818 , 151767 (2022).

Cobaugh, K. L., Schaeffer, S. M. & DeBruyn, J. M. Functional and structural succession of soil microbial communities below decomposing human cadavers. PLoS ONE 10 , e0130201 (2015).

Keenan, S. W. et al. Spatial impacts of a multi-individual grave on microbial and microfaunal communities and soil biogeochemistry. PLoS ONE 13 , e0208845 (2018).

Tomberlin, J. K. et al. Interkingdom responses of flies to bacteria mediated by fly physiology and bacterial quorum sensing. Anim. Behav. 84 , 1449–1456 (2012).

Shi, Z. et al. Putrescine is an intraspecies and interkingdom cell–cell communication signal modulating the virulence of Dickeya zeae . Front. Microbiol. 10 , 1950 (2019).

Valdés-Santiago, L. & Ruiz-Herrera, J. Stress and polyamine metabolism in fungi. Front. Chem. 1 , 42 (2013).

PubMed   Google Scholar  

Tofalo, R., Cocchi, S. & Suzzi, G. Polyamines and gut microbiota. Front. Nutr. 6 , 16 (2019).

Challacombe, J. F. et al. Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis. BMC Genomics 20 , 976 (2019).

Fu, X. et al. Fungal succession during mammalian cadaver decomposition and potential forensic implications. Sci. Rep. 9 , 12907 (2019).

Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109 , 21390–21395 (2012).

Dini-Andreote, F., Stegen, J. C., van Elsas, J. D. & Salles, J. F. Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc. Natl Acad. Sci. USA 112 , E1326–E1332 (2015).

Zhou, J. & Ning, D. Stochastic community assembly: does it matter in microbial ecology? Microbiol. Mol. Biol. Rev . https://doi.org/10.1128/mmbr.00002-17 (2017).

Zhou, J. et al. Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc. Natl Acad. Sci. USA 111 , E836–E845 (2014).

Waring, B., Gee, A., Liang, G. & Adkins, S. A quantitative analysis of microbial community structure–function relationships in plant litter decay. iScience 25 , 104523 (2022).

Aerts, R. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79 , 439–449 (1997).

Purahong, W. et al. Life in leaf litter: novel insights into community dynamics of bacteria and fungi during litter decomposition. Mol. Ecol. 25 , 4059–4074 (2016).

Pechal, J. L., Crippen, T. L., Cammack, J. A., Tomberlin, J. K. & Benbow, M. E. Microbial communities of salmon resource subsidies and associated necrophagous consumers during decomposition: potential of cross-ecosystem microbial dispersal. Food Webs 19 , e00114 (2019).

Hyde, E. R., Haarmann, D. P., Petrosino, J. F., Lynne, A. M. & Bucheli, S. R. Initial insights into bacterial succession during human decomposition. Int. J. Leg. Med. 129 , 661–671 (2015).

Vogel, H. et al. The digestive and defensive basis of carcass utilization by the burying beetle and its microbiota. Nat. Commun. 8 , 15186 (2017).

Deel, H. L. et al. The microbiome of fly organs and fly–human microbial transfer during decomposition. Forensic Sci. Int. 340 , 111425 (2022).

Mason, A. R. et al. Body mass index (BMI) impacts soil chemical and microbial response to human decomposition. mSphere 7 , e0032522 (2022).

Burkepile, D. E. et al. Chemically mediated competition between microbes and animals: microbes as consumers in food webs. Ecology 87 , 2821–2831 (2006).

Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6 , 1621–1624 (2012).

Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems https://doi.org/10.1128/msystems.00009-15 (2016).

Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551 , 457–463 (2017).

Amaral-Zettler, L. A., McCliment, E. A., Ducklow, H. W. & Huse, S. M. A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA genes. PLoS ONE 4 , e6372 (2009).

Sanders, J. G. et al. Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads. Genome Biol. 20 , 226 (2019).

Glenn, T. C. et al. Adapterama I: universal stubs and primers for 384 unique dual-indexed or 147,456 combinatorially-indexed Illumina libraries (iTru & iNext). PeerJ 7 , e7755 (2019).

Didion, J. P., Martin, M. & Collins, F. S. Atropos: specific, sensitive, and speedy trimming of sequencing reads. PeerJ 5 , e3720 (2017).

Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9 , 357–359 (2012).

Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25 , 2078–2079 (2009).

Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26 , 841–842 (2010).

Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 34 , 828–837 (2016).

Sumner, L. W. et al. Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 3 , 211–221 (2007).

Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37 , 852–857 (2019).

Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems 2 , e00191-16 (2017).

Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6 , 90 (2018).

Robeson, M. S. 2nd et al. RESCRIPt: reproducible sequence taxonomy reference database management. PLoS Comput. Biol. 17 , e1009581 (2021).

Janssen, S. et al. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems 3 , e00021-18 (2018).

Kruskal, W. H. & Wallis, W. A. Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc. 47 , 583–621 (1952).

Chen, J. et al. Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics 28 , 2106–2113 (2012).

Anderson, M. J. A new method for non‐parametric multivariate analysis of variance. Austral Ecol. 26 , 32–46 (2001).

Google Scholar  

Wickham, H. Ggplot2. Wiley Interdiscip. Rev. Comput. Stat. 3 , 180–185 (2011).

R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).

Vázquez-Baeza, Y., Pirrung, M., Gonzalez, A. & Knight, R. EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience 2 , 16 (2013).

McDonald, D. et al. American Gut: an open platform for citizen science microbiome research. mSystems 3 , e00031-18 (2018).

Kodama, W. A. et al. Trace evidence potential in postmortem skin microbiomes: from death scene to morgue. J. Forensic Sci. 64 , 791–798 (2019).

Gonzalez, A. et al. Qiita: rapid, web-enabled microbiome meta-analysis. Nat. Methods 15 , 796–798 (2018).

Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17 , 10–12 (2011).

Kluyver, T. et al. in Positioning and Power in Academic Publishing: Players, Agents and Agendas (eds Loizides, F. & Scmidt, B.) 87–90 (IOS Press, 2016).

Stegen, J. C. et al. Quantifying community assembly processes and identifying features that impose them. ISME J. 7 , 2069–2079 (2013).

Stegen, J. C., Lin, X., Fredrickson, J. K. & Konopka, A. E. Estimating and mapping ecological processes influencing microbial community assembly. Front. Microbiol. 6 , 370 (2015).

Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31 , 1674–1676 (2015).

Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7 , e7359 (2019).

Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25 , 1043–1055 (2015).

Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 11 , 2864–2868 (2017).

Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36 , 1925–1927 (2019).

Shaffer, M. et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48 , 8883–8900 (2020).

Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35 , 1026–1028 (2017).

Gower, J. C. Generalized procrustes analysis. Psychometrika 40 , 33–51 (1975).

Jackson, D. A. PROTEST: a PROcrustean Randomization TEST of community environment concordance. Écoscience 2 , 297–303 (1995).

Peres-Neto, P. R. & Jackson, D. A. How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129 , 169–178 (2001).

Machado, D., Andrejev, S., Tramontano, M. & Patil, K. R. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 46 , 7542–7553 (2018).

Heirendt, L. et al. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0. Nat. Protoc. 14 , 639–702 (2019).

Bittinger, K. et al. Bacterial colonization reprograms the neonatal gut metabolome. Nat. Microbiol. 5 , 838–847 (2020).

Chan, S. H. J., Simons, M. N. & Maranas, C. D. SteadyCom: predicting microbial abundances while ensuring community stability. PLoS Comput. Biol. 13 , e1005539 (2017).

Nothias, L.-F. et al. Feature-based molecular networking in the GNPS analysis environment. Nat. Methods 17 , 905–908 (2020).

Pluskal, T., Castillo, S., Villar-Briones, A. & Oresic, M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 11 , 395 (2010).

Dührkop, K. et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat. Methods 16 , 299–302 (2019).

Ludwig, M. et al. Database-independent molecular formula annotation using Gibbs sampling through ZODIAC. Nat. Mach. Intell. 2 , 629–641 (2020).

Kim, S., Kramer, R. W. & Hatcher, P. G. Graphical method for analysis of ultrahigh-resolution broadband mass spectra of natural organic matter, the van Krevelen diagram. Anal. Chem. 75 , 5336–5344 (2003).

Boye, K. et al. Thermodynamically controlled preservation of organic carbon in floodplains. Nat. Geosci. 10 , 415–419 (2017).

van den Berg, R. A., Hoefsloot, H. C. J., Westerhuis, J. A., Smilde, A. K. & van der Werf, M. J. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics 7 , 142 (2006).

Lin, H. & Peddada, S. D. Analysis of compositions of microbiomes with bias correction. Nat. Commun. 11 , 3514 (2020).

Keshavan, R. H., Montanari, A. & Oh, S. Matrix completion from a few entries. IEEE Trans. Inf. Theory 56 , 2980–2998 (2010).

Fedarko, M. W. et al. Visualizing ’omic feature rankings and log-ratios using Qurro. NAR Genom. Bioinform. 2 , lqaa023 (2020).

Martino, C. et al. Context-aware dimensionality reduction deconvolutes gut microbial community dynamics. Nat. Biotechnol. 39 , 165–168 (2021).

McDonald, D. et al. redbiom: a rapid sample discovery and feature characterization system. mSystems 4 , e00215–e00219 (2019).

McDonald, D. et al. Greengenes2 unifies microbial data in a single reference tree. Nat. Biotechnol. https://doi.org/10.1038/s41587-023-01845-1 (2023).

Cantrell, K. et al. EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic data sets. mSystems 6 , e01216–e01220 (2021).

Pedregosa, F., Varoquaux, G. & Gramfort, A. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12 , 2825–2830 (2011).

Download references

Acknowledgements

Foremost, we thank the willed-body donors for their contribution to science; A. Esterle, K. Otto, H. Archer, C. Carter, R. Reibold, L. Burcham, J. Prenni and the CSU Writes programme for technical and resource contributions; A. Buro, V. Rodriguez, M. Sarles, A. Hartman and A. Uva at SHSU for field contributions. Opinions or points of view expressed here represent a consensus of the authors and do not necessarily represent the official position or policies of the US Department of Justice. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the US Government. Funding was provided by the National Institutes of Justice (2016-DN-BX-0194, J.L.M.; 2015-DN-BX-K016, J.L.M.; GRF STEM 2018-R2-CX-0017, A.D.B.; GRF STEM 2018-R2-CX-0018, H.L.D.), the Canadian Institute for Advanced Research Global Scholar Program (J.L.M.), National Science Foundation Early Career Award (1912915, K. C. Wrighton) and National Institutes of Health T32 Training Award (T32GM132057, V.N.).

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Zachary M. Burcham, Aeriel D. Belk, Alexandra Emmons, Victoria Nieciecki & Jessica L. Metcalf

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Zachary M. Burcham

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Contributions

Z.M.B., D.O.C., R.K., K. C. Wrighton and J.L.M. conceptualized the project. Z.M.B., A.D.B., B.B.M., A.B., C.M., H.L.D., M.P., K. C. Weldon, G.C.H., G.A., M.C., D.B., J.S., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, D.O.C., R.K. and J.L.M. contributed to data curation. Z.M.B., A.D.B., B.B.M., P.G., C.M., L.S., A.R.Z., P.S., A.E., H.L.D., V.N., M.S., K.C. and D.M. conducted formal analysis. K. C. Wrighton, D.O.C., R.K. and J.L.M. acquired funding. A.B., M.P., K. C. Weldon, M.C., D.B., J.S., J.M.S.W., G.V., D.S., A.M.L. and S.B. contributed to project investigation. Z.M.B., A.D.B., B.B.M., A.B., P.G., C.M., L.S., A.R.Z., P.S., Z.Z.X., V.N., Q.Z., M.S., M.P., K. C. Weldon, K.C., A.B.-H., S.H.J.C., M.C., D.B., J.S., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, D.O.C., R.K. and J.L.M. developed the methodology. Z.M.B., M.C., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, D.O.C., R.K. and J.L.M. administered the project. S.H.J.C., M.C., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, D.O.C. and R.K. provided resources. Z.M.B., A.D.B., B.B.M., P.G., C.M., L.S., A.R.Z., P.S., Z.Z.X., M.S., K.C., A.B.-H., D.M. and P.C.D. developed software. S.H.J.C., M.C., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, D.O.C. and R.K. supervised the project. Z.M.B., A.D.B., B.B.M., P.G., C.M., M.C., G.V., D.S., A.M.L., S.B., P.C.D., K. C. Wrighton, R.K. and J.L.M. conducted data validation. Z.M.B., A.D.B., B.B.M., P.G., C.M., A.E. and S.C.R. worked on visualization. Z.M.B., A.D.B., A.E., B.B.M., S.C.R., D.O.C. and J.L.M. wrote the original draft. Z.M.B., A.D.B., B.B.M., P.G., C.M., H.L.D., S.C.R., D.M., M.C., S.B., P.C.D., K. C. Wrighton, D.O.C., R.K. and J.L.M. reviewed and edited the manuscript.

Corresponding author

Correspondence to Jessica L. Metcalf .

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Competing interests.

P.C.D. consulted in 2023 for DSM animal health, is a consultant and holds equity in Sirenas and Cybele Microbiome, and is founder and scientific advisor and has equity in Ometa Labs LLC, Arome and Enveda (with approval by UC San Diego). R.K. is affiliated with Gencirq (stock and SAB member), DayTwo (consultant and SAB member), Cybele (stock and consultant), Biomesense (stock, consultant, SAB member), Micronoma (stock, SAB member, co-founder) and Biota (stock, co-founder). The other authors declare no competing interests.

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Extended data

Extended data fig. 1 study information..

Average a ) temperature data and b ) total precipitation per location over experiment with cadaver placement dates. Temperature data was collected from local weather stations reported to the National Centers for Environmental Information. Total monthly precipitation data was collected from Weather Underground. The vertical line represents the date of placement and line color denotes the season the body placement is considered to have been placed. c ) Upset plot illustrating the intersections between sample and omic types after extractions, processing and quality filtering that were used for further analyses. MetaG = metagenomics, Metab = metabolomics, 18S = 18S rRNA amplicon, and 16S = 16S rRNA amplicon.

Extended Data Fig. 2 Metabolome Comparison.

Principal coordinate analysis (PCoA) of a ) Jaccard and b ) Bray-Curtis distances of all unique metabolites and all metabolomic samples show cadaver skin and cadaver-associated soil are significantly different community profiles. n = 1503 biologically independent samples. Significance was determined by PERMANOVA (permutations = 999). Van Krevelen diagram showed a strong presence of lipid-like, protein-like, and lignin-like classes within c ) cadaver-associated soils and d ) cadaver skin. Metabolites that matched database chemical formulas or had a significantly predicted chemical formula were assigned a Van Krevelen organic compound classification by their hydrogen:carbon and oxygen:carbon molar ratios. Colors correspond to organic compound classification. Nominal oxidation state of carbon (NOSC) scores for cadaver-associated e ) soil and f ) cadaver skin metabolites with assigned chemical formulas show significant decrease of thermodynamic favorability at all geographical locations over decomposition time measured by accumulated degree days (ADD). Soil: ARF n = 251, STAFS n = 250, and FIRS n = 245 biologically independent samples. Skin: ARF n = 250, STAFS n = 249, and FIRS n = 249 biologically independent samples. Data are presented as mean values +/− 95% CI. Significance measured with linear mixed-effects models within each location and adding a random intercept for cadavers with two-tailed ANOVA and no multiple comparison adjustments. g ) Lipid-like metabolites show an increased abundance in cadaver-associated soils over decomposition measured by accumulated degree days (ADD) and significantly increase in temperate soils. h ) Protein-like metabolites are less abundant than lipid-like metabolites in cadaver-associated soils over decomposition measured by accumulated degree days (ADD) and significantly decrease in STAFS soil. ARF n = 251, STAFS n = 250, and FIRS n = 245 biologically independent samples. Data are presented as mean values +/− 95% CI. Significance measured with linear mixed-effects models within each location and adding a random intercept for cadavers with two-tailed ANOVA and no multiple comparison adjustments. Metabolite abundance normalized by center log ratio transformation.

Extended Data Fig. 3 Community Assembly.

Sankey diagram of the a ) 257 99% dereplicated, medium to high quality MAGs with Genome Taxonomy Database classifications and b ) the average MAG abundances (given as transcript per million, TPM) at each decomposition stage within each location. Proteobacteria and Bacteroidota representation increases with decomposition while Actinobacteria representation decreases at each location. This MAG set encompassed novel bacterial orders (n=3), families (n=9), genera (n=28), and species (n=158). Proteobacteria is the highest represented phylum. c ) Spearman correlation of the maximum ATP per C-mol for lipids, carbohydrates, and amino acids over ADD at each location represented by circle size. Metabolism efficiency is correlated with ADD in temperate climates. ARF n = 212, STAFS n = 198, and FIRS n = 158 biologically independent samples. Significance measured with linear mixed-effects models within each location and adding a random intercept for cadavers and denoted as p<0.05 (*), p<0.01 (**), and p<0.001 (***). ARF: Amino Acids p = <2e-16, STAFS: Amino Acids p = 1.18e-06, and Carbohydrate p = 4.22e-04. d ) The amino acid metabolism efficiency of the total community that can be attributed to O. alkaliphila and e ) the carbohydrate metabolism efficiency of the total community that can be attributed to C. intestinavium increase over decomposition at temperate locations as a product of the genome’s metabolism efficiency and relative abundance. Data plotted with loess regression as mean values +/− 95% CI. ARF n = 212, STAFS n = 198, and FIRS n = 158 biologically independent samples. f ) Pairwise comparisons to obtain beta nearest taxon index (βNTI) values focused on successional assembly trends by comparing initial non-decomposition soil to early decomposition soil then early to active, etc. (PL = placement, EA = early, AC = active, AD = advanced) in the 16S rRNA amplicon dataset. Relative abundance of assembly forces reveals that heterogeneous selection (βNTI > +2) pressure increases and homogenous selection (βNTI < -2) decreases over decomposition. Stochastic forces are a constant driver of community assembly (+2 > βNTI > -2). g ) Predicted metabolic competition from metagenome-assembled genomes are site-specific and significantly altered over decomposition. STAFS: early-active p = 3.42e-11, early-advanced p = 1.23e-11, active-advanced p = 7.85-41, FIRS: early-active p = 0.042. h ) Predicted metabolic cooperation and competition from metagenome-assembled genomes randomly subsampled into 20-member communities within each site and decomposition serves as a null model comparison signifying the importance of MAG co-occurrence. ARF n = 201, STAFS n = 188, and FIRS n = 151 biologically independent samples. The lower and upper hinges of the boxplot correspond to the first and third quartiles (the 25th and 75th percentiles). The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge, and the lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. The center of the boxplot is represented by the median. Significance measured with Dunn Kruskal-Wallis H-test with multiple comparison p-values adjusted with the Benjamini-Hochberg method as denoted by p<0.05 (*), p<0.01 (**), and p<0.001 (***).

Extended Data Fig. 4 Multi-omic Integration.

a ) ASV richness comparison between decomposition soil and control soil over the decomposition time frame reveals that bacterial richness decreases significantly at temperate locations. ARF n = 414, STAFS n = 316, and FIRS n = 310 biologically independent samples. Significance measured with linear mixed-effects models within each location and adding a random intercept for cadavers with two-tailed ANOVA and no multiple comparison adjustments. ARF and STAFS richness p = <2e-16. Denoted as p<0.05 (*), p<0.01 (**), and p<0.001 (***). b ) Multi-omic joint-RPCA shows that microbial community ecology is impacted by season and geographical location. Multi-omic Joint-RPCA incorporates soil 16S rRNA, 18S rRNA, metabolomic, and metagenome-assembled genome data. All data types used the same n = 374 biologically independent samples. Multi-omics joint-RPCA principal component scores show that c ) facility variation is primarily explained by principal component 3 (PC3) and PC4, d ) decomposition stage is primarily explained by PC2, e ) season is primarily explained by PC1, and f ) climate is primarily explained by PC3 and PC4 as described by the least overlap of PC values between groups. g ) PC2 from the multi-omics joint-RPCA scores for each geographical location over decomposition stages shows the temperate climate locations are the most dynamic in their microbial ecology. Multi-omic Joint-RPCA incorporates soil 16S rRNA, 18S rRNA, metabolomic, and metagenome-assembled genome data. All data types used the same n = 374 biologically independent samples. Data in panel g are presented as mean values +/− 95% CI.

Extended Data Fig. 5 Universal Initial Non-Decomposition And Early Decomposition Soil Network.

Top 20% of correlations between selected nodes for the universal initial non-decomposition and early decomposition soil log-ratio signal in Joint-RPCA PC2 visualized in co-occurrences network. All data types used the same n = 374 biologically independent samples.

Extended Data Fig. 6 Decomposer ASVs Placed in Current Databases.

Phylogenetic tree representing ASVs associated with the key decomposer nodes from the network placed along within the top 50 most abundant ASVs taken from AGP gut, AGP skin, EMP soil, and EMP host-associated datasets demonstrates key decomposers are largely phylogenetically unique. Innermost ring represents decomposer placement while outer rings represent AGP and EMP ASVs, for which bar height represents ASV rank prevalence within each environment. AGP and EMP ASVs were ranked according to the number of samples they were found in each environment. A lack of bars represents that the ASV was not present within the dataset. Decomposer ASVs are numbered clockwise with full taxonomy available in Supplementary Table 27 .

Extended Data Fig. 7 Important Features for 16S rRNA Random Forest Models.

The 20 most important SILVA level-7 taxa as determined in the 16S rRNA random forest regression models for predicting postmortem interval shows that many of the same taxa appear important for model prediction within all sample types, but some differences do emerge.

Extended Data Fig. 8 Longitudinal Abundances of Important Features.

The 6 most important SILVA level-7 taxa as determined in the 16S rRNA data from the a ) skin of the face, b ) skin of the hip, c ) soil associated with the hip, and d ) soil associated with the face for random forest regression models for predicting postmortem interval. Data plotted by the taxa and the normalized abundance change over ADD at each geographic location. Data plotted with loess regression and 16S rRNA soil face, soil hip, skin face, and skin hip datasets contain n = 600, 616, 588, and 500 biologically independent samples, respectively. Data are presented as mean values +/− 95% CI.

Extended Data Fig. 9 16S rRNA Random Forest Model Validation.

a ) Total body scores (TBS) used to train a random forest model for prediction of PMI (ADD) shows that TBS scores can predict PMI relatively accurately based on a low MAE but have higher variability in their predictions as represented by a higher residual value than microbiome-based models. Models built from 16S rRNA data using SILVA level-7 taxa from the skin and soil associated with the hip were validated with b ) an independent test set of samples that were collected from cadavers at locations and climates not represented in our model and c ) the same data where samples were given randomly assigned ADDs within the range of true ADDs to serve as a null model. Significance measured with linear mixed-effects models within each location and adding a random intercept for cadavers with two-tailed ANOVA and no multiple comparison adjustments. Data are presented as mean values +/− 95% CI.

Extended Data Fig. 10 Diversity Comparison between 16S rRNA and Metagenomic Data.

PCoA ordination plots of Bray-Curtis dissimilarity matrices calculated from paired rarefied 16S rRNA feature abundances (left) and TPM-normalized MAG abundances (right) from the soil adjacent to the hip. Procrustes/PROTEST and mantel tests were performed between the PCoA ordinances and distance matrices, respectively. n = 480 biologically independent samples, respectively.

Supplementary information

Supplementary information.

Legends for Supplementary Tables 1–9, 14–16 and 25–39. Supplementary Tables 10–13 and 17–24, and Text.

Reporting Summary

Supplementary tables.

Supplementary Table 1. Sample metadata. Table includes data taken during intake and over the course of the study. Table 2. ANCOM-BC differential abundance analysis results of cadaver skin metabolite log-ratio change over decomposition stages. Initial day 0 samples were used as the reference level and the intercept. Results include log-ratio changes of day 0 metabolites to early, active and advanced decomposition stages, P values, Holm–Bonferroni-corrected P values ( Q values), standard errors and W values. Table 3. ANCOM-BC differential abundance analysis results of cadaver-associated soil metabolite log-ratio change over decomposition stages. Initial day 0 samples were used as the reference level and the intercept. Results include log-ratio changes of day 0 metabolites to early, active and advanced decomposition stages, P values, Holm–Bonferroni-corrected P values ( Q values), standard errors and W values. Table 4. List of samples used to generate shotgun metagenomic data. Table 5. Assembly statistics and GTDB taxonomic classification of genomic bins (metagenome-assembled genomes; MAGs) co-assembled from the metagenomic samples. Table includes completeness and contamination of each MAG. Table 6. TPM-normalized count abundance of MAGs within metagenomic samples. Table 7. Linear mixed-effects model statistics for testing response variable change of ATP per C-mol amino acids calculated from metagenomic data over ADD at each facility and a random intercept for each individual body to account for repeated measures to test whether the metabolism efficacy shifts within each facility. Formula: ‘ATPm ≈ ADD + (1|body ID)’. Table 8. Linear mixed-effects model statistics for testing response variable change of ATP per C-mol carbohydrates calculated from metagenomic data over ADD at each facility and a random intercept for each individual body to account for repeated measures to test whether the metabolism efficacy shifts within each facility. Formula: ‘ATPm ≈ ADD + (1|body ITable 9. Linear mixed-effects model statistics for testing response variable change of ATP per C-mol lipids calculated from metagenomic data over ADD at each facility and a random intercept for each individual body to account for repeated measures to test whether the metabolism efficacy shifts within each facility. Formula: ‘ATPm ≈ ADD + (1|body ID)’. Table 14. Number of predicted exchanges for cross-fed compounds at each facility during late decomposition. Late decomposition was defined as the advanced decomposition stage at STAFS and ARF and the active decomposition stage at FIRS. Table 15. Linear mixed-effects model statistics for testing response variable change of Generalized UniFrac PC1 distances calculated from 16S rRNA gene data over ADD at each facility with sampling site (that is, soil adjacent to hip vs soil control) as an independent variable (fixed effect) and a random intercept for each individual body to account for repeated measures. The models measure the sampling site and ADD variables individually and the interaction between the variables. The interaction between the variables was used to test whether the sampling sites respond differently to decomposition. Formula: ‘diversity metric ≈ ADD × sampling site + (1|body ID)’. Table 16. Linear mixed-effects model statistics for testing response variable change of ASV richness calculated from 16S rRNA gene data over ADD at each facility with sampling site (that is, soil adjacent to hip vs soil control) as an independent variable (fixed effect) and a random intercept for each individual body to account for repeated measures. The models measure the sampling site and ADD variables individually and the interaction between the variables. The interaction between the variables was used to test whether the sampling sites respond differently to decomposition. Formula: ‘diversity metric ≈ ADD × sampling site + (1|body ID)’. Table 25. Joint-RPCA PC2 correlations calculated between network feature nodes that correspond with late (that is, active and advanced) decomposition soil. Table 26. Joint-RPCA PC2 correlations calculated between network feature nodes in initial, non-decomposition and early decomposition soil. Table 27. 16S rRNA gene ASVs assigned to the same taxonomy as decomposer network taxa. Table includes the phylogenetic tree labels in Fig. 4e, 150-bp-long ASVs and trimmed 100-bp-long ASVs used to explore ASV presence in other studies. Table 28. Presence of universal decomposers in possible human and terrestrial source environments in a few other studies. Table shows the average relative abundance of each decomposer ASV across each sample type. Average relative abundances were then summed for each decomposer genus. Table 29. Cross-feeding statistics for MAGs predicted as cross-feeders during late decomposition. Table includes GTDB taxonomic classification, number of reactions each MAG was considered the compound receiver and/or donor, and the percent responsible for all donations and acceptances during late decomposition. Late decomposition was defined as the advanced decomposition stage at STAFS and ARF and the active decomposition stage at FIRS. Table 30. Cross-feeding exchanges for Oblitimonas alkaliphila during late decomposition. Oblitimonas alkaliphila was not a predicted cross-feeder at FIRS during this timeframe. Table includes MAG ID and taxonomic classification of genomes involved in exchange, compounds exchanged and computed interaction metrics. Table 31. Cross-feeding exchanges for l -arginine or ornithine during late decomposition. Table includes MAG ID and taxonomic classification of genomes involved in exchange, compounds exchanged and computed interaction metrics. Table 32. Model validation results from predicting an independent test set of samples using the 16S rRNA gene at the SILVA database level-7 taxonomic rank random forest regression models for the skin of the hip and soil adjacent to the hip. Errors are represented by MAE in ADD. Table 33. Presence of universal decomposers in a few other studies focused on mammalian decomposition environments. A search for the 35 universal PMI decomposer ASVs was conducted within each dataset. The relative abundance of each decomposer ASV was first averaged across all samples within a specific metadata category. The average relative abundances were then summed across each decomposer genus. Prevalence tables were constructed by summing the number of samples across a specific metadata category in which each universal decomposer ASV was present. Table 34. The average ADD per calendar day calculated for each cadaver at each facility. The average ADD per calendar day was calculated by dividing the final maximum ADD values by the total number of days (that is, 21). The average ADD per day was calculated for each cadaver, season and facility, each climate type and as a study-wide average. Table 35. The average ADD per calendar day calculated for each cadaver at each facility for the independent test set. The average ADD per calendar day was calculated by dividing the final maximum ADD values by the total number of sampling days. The average ADD per day was calculated for each cadaver, facility and as a study-wide average. Table 36. Metabolite identification information for metabolites that had a predicted chemical formula or matched to a compound in the database library. When available, chemical formulas in the database library took precedence over predicted chemical formulas for calculating NOSC and major biochemical classes based on the molar H:C and O:C ratios. Table 37. Soil metabolite feature table normalized with sum normalization then scaled with pareto scaling. Table includes chemical formulas and major biochemical classes based on the molar H:C and O:C ratios. Table 38. Skin metabolite feature table normalized with sum normalization then scaled with pareto scaling. Table includes chemical formulas and major biochemical classes based on the molar H:C and O:C ratios. Table 39. Sample metadata for the machine learning independent test set. Table includes data taken during intake and over the course of the study.

Source Data for Figs. 1–6, Extended Data Figs. 1–6 and Extended Data Fig. 9

SD for Fig. 1. Sample type counts and sample metadata. SD for Fig. 2. ATP per C-mol for each substrate by sample and pairwise beta-NTI calculations. SD for Fig. 3. SMETANA MIP and MRO score calculations, predicted cross-fed metabolites, Faith’s PD calculations and joint-RPCA distance matrix/ordination. SD for Fig. 4. Joint-RPCA distance matrix/ordination and multi-omic log ratios. SD for Fig. 5. Late decomposition multi-omic correlations. SD for Fig. 6. Random forest predictions, 16S rRNA model important features and 16S rRNA SILVA-L7 feature table. SD for ED Fig. 1. Site weather data. SD for ED Fig. 2. Metabolite feature table, chemical formulas and Van Krevelen metabolite classifications. SD for ED Fig. 3. MAG taxonomy and feature table, amino acid and carbohydrate ATP per C-mol per MAG and sample. SD for ED Fig. 4. 16S rRNA calculated richness. SD for ED Fig. 5. Initial/early decomposition multi-omic correlations. SD for ED Fig. 6. Top rank taxa for phylogenetic tree comparing ASVs found during decomposition and in the EMP and AGP datasets. SD for ED Fig. 9. 16S rRNA random forest validation predictions

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Burcham, Z.M., Belk, A.D., McGivern, B.B. et al. A conserved interdomain microbial network underpins cadaver decomposition despite environmental variables. Nat Microbiol (2024). https://doi.org/10.1038/s41564-023-01580-y

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Selecting the right topic is crucial. It’s the seed from which your term paper will grow. Aim for a topic that is not only interesting to you but also appropriate for the scope of the assignment and your academic level. 

It should be specific enough to be manageable but broad enough to allow for comprehensive research. 

If you find yourself stuck at this stage, consult your professor or peers for suggestions. They can offer perspectives that might not have occurred to you.

3. Conducting Thorough Research

Conducting Thorough Research

Research is the backbone of your term paper. Begin by consulting a variety of sources, including books, academic journals, and reputable websites. Libraries, both physical and digital, are treasure troves of information. 

Utilize databases such as JSTOR or Google Scholar to find relevant academic papers. As you research, keep meticulous records of your sources. This will make citing your references easier and ensure your paper is grounded in credible information.

4. Crafting an Outline

An outline is your roadmap, guiding you through the writing process. It helps organize your thoughts and structure your paper logically. Start with a broad overview, then break down the main sections into more detailed subsections. 

This will help you identify areas that need more research or sections that are too complex and need simplification. An effective outline ensures that every part of your paper serves the overall argument or thesis statement.

5. Writing the Draft

Writing the Draft

With your outline in hand, it’s time to start writing. The introduction should hook the reader, present your thesis statement , and outline the structure of your paper. Each body paragraph should focus on a single idea or piece of evidence, supporting your thesis. 

Use transitions to smoothly navigate from one idea to the next, maintaining a coherent flow throughout. The conclusion should tie everything together, reinforcing your thesis and highlighting the significance of your findings.

The writing process is iterative. Don’t aim for perfection on the first draft. Focus on getting your ideas down on paper; refinement comes later.

6. Revising and Editing

The difference between a good term paper and a great one often lies in the revision stage. Start by reviewing your paper for content and structure. 

Ensure each paragraph contributes to your thesis and that your argument flows logically. Then, move on to editing for clarity, coherence, and conciseness. Pay attention to grammar, punctuation, and style. 

Tools like Grammarly or the Hemingway Editor can be invaluable but don’t rely on them completely. A manual review is irreplaceable.

Finally, check your citations and references. They should adhere to the required format, whether it’s APA , MLA, or Chicago. This not only lends credibility to your paper but also avoids the pitfalls of plagiarism.

7. Handling Feedback

Seek Feedback from Your Professor

If possible, seek feedback from your professor or peers before the final submission. They can offer insights you might have missed and suggest improvements. Be open to criticism; it’s an opportunity for growth, not a personal attack. Use the feedback to refine your paper further.

8. Final Touches and Submission

Before submitting your paper, give it one last review. Check for any errors you might have missed and ensure that it meets all the assignment requirements. Submit your paper with confidence, knowing you’ve put in your best effort.

How Can I Narrow Down a Broad Topic for My Term Paper?

Narrowing down a broad topic requires a bit of brainstorming and preliminary research. Start by reading general sources about your topic to identify specific themes, trends, or issues that interest you. 

Then, consider how these specific angles relate to the broader topic. It can also be helpful to discuss your ideas with your professor or classmates to gain different perspectives. Finally, formulate a research question or thesis statement that reflects the narrowed focus. This approach ensures your topic is manageable and tailored to the assignment’s scope.

What Strategies Can I Use if I’m Struggling to Find Sources for My Topic?

If you’re struggling to find sources, try altering your search terms or using synonyms to expand your search. Consult with a librarian, who can offer expert guidance on searching databases and may suggest resources you hadn’t considered. 

How Do I Balance My Own Ideas with Research Findings in My Term Paper?

How Do I Balance My Own Ideas with Research Findings in My Term Paper?

To balance your own ideas with research findings, start by clearly stating your thesis or main argument. Use research findings to support your ideas, citing evidence that backs up your points. However, don’t just present the research; analyze it. 

Discuss how the evidence supports your thesis, what it means in the context of your argument, and any limitations or counterarguments. Your own analysis and synthesis of the research are what will make your term paper unique and insightful.

Can I Include Visuals in My Term Paper, and How Should I Do So?

Yes, visuals such as graphs, charts, and images can be included in your term paper to support your arguments or illustrate complex ideas. Ensure that each visual is clearly labeled (e.g., Figure 1, Table 1) and accompanied by a caption explaining what it shows.

Refer to the visuals in your text to guide the reader’s attention to them at relevant points in your argument. Always cite the source of the visual in accordance with the citation style you are using.

How Do I Handle Contradictory Evidence in My Term Paper?

Handling contradictory evidence is a crucial part of demonstrating critical thinking . Present the contradictory evidence fairly and objectively, then provide an analysis that explains why it does not undermine your thesis. 

You can argue that the evidence is flawed, outdated, or limited in scope. Alternatively, you can acknowledge the complexity of the issue and refine your thesis to accommodate the nuanced view that emerges from considering all evidence. This approach shows that you have engaged deeply with the material and strengthens your argument.

How Long Should I Spend on Each Stage of Writing My Term Paper?

How Long Should I Spend on Each Stage of Writing My Term Paper?

The time spent on each stage of writing a term paper can vary based on the length of the paper, the complexity of the topic, and your own working style. A balanced approach might involve spending 20% of your time on choosing a topic and conducting initial research, 30% on in-depth research and organizing your findings, 25% on writing the first draft, and 25% on revising, editing, and finalizing the paper.

Adjust these percentages based on your specific needs and deadlines. Remember, starting early and allocating time for each stage can help reduce stress and improve the quality of your work.

Final Words

Writing a term paper is a substantial academic endeavor, but it’s also a deeply rewarding one. It challenges you to think critically, research deeply, and express your thoughts clearly and coherently. By following these steps, you equip yourself with a structured approach to tackle this challenge head-on. 

Remember, academic writing is a skill honed over time. Each term paper is an opportunity to improve, learn, and grow as a scholar. Embrace the process, and you’ll find yourself not just surviving but thriving in the academic world.

  • Academic Writing , Assignment , Education , Research , Students , Term Paper , Tips

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IMAGES

  1. How to Write a Discussion Section

    what to write in the discussion of a research paper

  2. How to Write Discussions and Conclusions

    what to write in the discussion of a research paper

  3. (PDF) How to Write an Effective Discussion in a Research Paper; a Guide

    what to write in the discussion of a research paper

  4. How to Write a Discussion Essay

    what to write in the discussion of a research paper

  5. How to Write a Discussion Essay

    what to write in the discussion of a research paper

  6. A Guide on Writing A Discussion Section Of A Research Paper

    what to write in the discussion of a research paper

VIDEO

  1. Workshop on how to write a research paper. Registration Link in comments #research #lawstudent #law

  2. How to Write a Discussion Section in a Research Paper (SECRET framework)

  3. how to write discussion and conclusion of Research article or paper

  4. L 28 Part 2 How to write ‘Discussion’ section in your Manuscript

  5. Research Paper Methodology

  6. Writing A Research Paper: Discussion

COMMENTS

  1. How to Write a Discussion Section

    The discussion section is where you delve into the meaning, importance, and relevance of your results.. It should focus on explaining and evaluating what you found, showing how it relates to your literature review and paper or dissertation topic, and making an argument in support of your overall conclusion.It should not be a second results section.. There are different ways to write this ...

  2. How to Write Discussions and Conclusions

    Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and ...

  3. 8. The Discussion

    The discussion section is often considered the most important part of your research paper because it: Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;

  4. PDF Discussion Section for Research Papers

    The discussion section is one of the final parts of a research paper, in which an author describes, analyzes, and interprets their findings. They explain the significance of those results and tie everything back to the research question(s). In this handout, you will find a description of what a discussion section does, explanations of how to ...

  5. 6 Steps to Write an Excellent Discussion in Your Manuscript

    1.Introduction—mention gaps in previous research¹⁻². 2. Summarizing key findings—let your data speak¹⁻². 3. Interpreting results—compare with other papers¹⁻². 4. Addressing limitations—their potential impact on the results¹⁻². 5. Implications for future research—how to explore further¹⁻².

  6. Research Guides: Writing a Scientific Paper: DISCUSSION

    Show how your results agree or disagree with previously published works. Discuss the theoretical implications of your work as well as practical applications. State your conclusions clearly. Summarize your evidence for each conclusion. "Discussion and Conclusions Checklist" from: How to Write a Good Scientific Paper.

  7. PDF 7th Edition Discussion Phrases Guide

    Papers usually end with a concluding section, often called the "Discussion.". The Discussion is your opportunity to evaluate and interpret the results of your study or paper, draw inferences and conclusions from it, and communicate its contributions to science and/or society. Use the present tense when writing the Discussion section.

  8. Organizing Academic Research Papers: 8. The Discussion

    Organization and Structure. Keep the following sequential points in mind as you organize and write the discussion section of your paper: Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate]. Use the ...

  9. General Research Paper Guidelines: Discussion

    Discussion Section. The overall purpose of a research paper's discussion section is to evaluate and interpret results, while explaining both the implications and limitations of your findings. Per APA (2020) guidelines, this section requires you to "examine, interpret, and qualify the results and draw inferences and conclusions from them ...

  10. Writing a discussion section

    A discussion critically analyses and interprets the results of a scientific study, placing the results in the context of published literature and explaining how they affect the field.. In this section, you will relate the specific findings of your research to the wider scientific field. This is the opposite of the introduction section, which starts with the broader context and narrows to focus ...

  11. How to Write a Discussion Section for a Research Paper

    Begin the Discussion section by restating your statement of the problem and briefly summarizing the major results. Do not simply repeat your findings. Rather, try to create a concise statement of the main results that directly answer the central research question that you stated in the Introduction section.

  12. How to Write a Discussion Section

    The discussion chapter is where you delve into the meaning, importance and relevance of your results. There are many different ways to write the discussion s...

  13. Discussion and Conclusions

    However doing this actually makes a positive impression of your paper as it makes it clear that you have an in depth understanding of your topic and can think objectively of your research. Discuss what your results may mean for researchers in the same field as you, researchers in other fields, and the general public.

  14. PDF How to Write an Effective Discussion

    paper. There are elements of the discussion that should be included and other things that should be avoided. Always write the discussion for the reader; remember that the focus should be to help the reader understand the study and that the highlight should be on the study data. Key words: publishing; writing; manuscripts, medical; communication.

  15. Discussion Section of a Research Paper: Guide & Example

    Step 2. Answer the Questions in Your Discussion Section of a Research Paper. Writing the discussion section of a research paper also involves mentioning your questions. Remember that in your introduction, you have promised your readers to answer certain questions. Well, now it's a perfect time to finally give the awaited answer.

  16. How to Write the Discussion Section of a Research Paper

    The discussion section provides an analysis and interpretation of the findings, compares them with previous studies, identifies limitations, and suggests future directions for research. This section combines information from the preceding parts of your paper into a coherent story. By this point, the reader already knows why you did your study ...

  17. How to Write the Discussion?

    Zeiger M. Essentials of writing biomedical research papers. Canadian J Stud Discourse Writing. 2000;11:33-6. Google Scholar Bavdekar SB. Writing the discussion section: describing the significance of the study findings. J Assoc Physicians India. 2015;63:40-2. PubMed Google Scholar Foote M. The proof of the pudding: how to report results and ...

  18. Writing a discussion section: how to integrate substantive and

    Consequently, suggestions on writing a discussion often remain vague by hardly addressing the role of the assumptions that have (often implicitly) been made when designing a study, analyzing the data and interpreting the results. ... research papers. We illustrate this through the personal roles that a statistician (i.e. methods expert) and a ...

  19. How to write a discussion section?

    The discussion section can be written in 3 parts: an introductory paragraph, intermediate paragraphs and a conclusion paragraph. For intermediate paragraphs, a "divide and conquer" approach, meaning a full paragraph describing each of the study endpoints, can be used. In conclusion, academic writing is similar to other skills, and practice ...

  20. (PDF) How to Write an Effective Discussion in a Research Paper; a Guide

    Discussion is mainly the section in a research paper that makes the readers understand the exact meaning of the results achieved in a study by exploring the significant points of the research, its ...

  21. How to Write a Discussion Section

    Table of contents. What not to include in your discussion section. Step 1: Summarise your key findings. Step 2: Give your interpretations. Step 3: Discuss the implications. Step 4: Acknowledge the limitations. Step 5: Share your recommendations. Discussion section example.

  22. (PDF) How to Write an Effective Discussion

    The discussion section, a systematic critical appraisal of results, is a key part of a research paper, wherein the authors define, critically examine, describe and interpret their findings ...

  23. How to Write a Strong Discussion Section

    How do you Write a Strong Discussion Section? How do you get started? How do you actually "discuss"? My first few papers had very weak discussions sections....

  24. Free Research Paper Template (Word Doc & PDF)

    If you're preparing to write an academic research paper, our free research paper template is the perfect starting point. In the template, we cover every section step by step, with clear, straightforward explanations and examples.. The template's structure is based on the tried and trusted best-practice format for formal academic research papers. The template structure reflects the overall ...

  25. Researching the White Paper

    Unlike a school research paper, the author does not set out to argue for or against a particular position, and then devote the majority of effort to finding sources to support the selected position. Instead, the author sets out in good faith to do as much fact-finding as possible, and thus research is likely to present multiple, conflicting ...

  26. Finding Sources for Your Paper

    When you click "Define Your Search," you are presented with options you must select before you can type your search terms: Books (print + ebooks) will search the OneSearch system. Articles will search the OneSearch system for articles in journals, newspapers, and magazines.. Videos will search the OneSearch system for streaming videos and DVDs. Books + Articles + Videos will search OneSearch ...

  27. A conserved interdomain microbial network underpins cadaver

    Recent research has demonstrated that microbial community response over the course of terrestrial human cadaver decomposition and across a range of mammals, results in a substantial microbial ...

  28. Full article: A critical review of GenAI policies in higher education

    Two research assistants were involved in the search. One examined universities ranked 1-10, while the other focused on universities ranked 11-20. After the individual search, the two research assistants reviewed each other's results to validate the data. The author cross-checked a sample (around 30%) of their work.

  29. How to Write a Term Paper: 8 Expert Tips for Academic Success 2024

    The time spent on each stage of writing a term paper can vary based on the length of the paper, the complexity of the topic, and your own working style. A balanced approach might involve spending 20% of your time on choosing a topic and conducting initial research, 30% on in-depth research and organizing your findings, 25% on writing the first ...

  30. TOEFL TestReady

    No other English language test provider has a prep offering like this — designed for you, with you. TOEFL ® TestReady ™ combines the best TOEFL iBT prep offerings with exclusive features and deeper insights to enhance your English communication skills. All feedback, recommendations, personalized insights and tips are developed by the same teams that write and produce the TOEFL iBT test.