Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management?

Jamie C. Tam; Sean M. Lucey; Alida Bundy; Sarah Gaichas; Robert Gamble

doi:10.1371/journal.pone.0328505

Peer Review History

Original SubmissionApril 9, 2025
Decision Letter - Athanassios C. Tsikliras, Editor PONE-D-25-18645Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management?PLOS ONE Dear Dr. Tam, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the minor points raised during the review process (note that one of the reviewers made comments directly on the pdf file). Please submit your revised manuscript by Jul 13 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I have completed my review for the manuscript entitled “Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management? (PONE-D-25-18645)” This is a very well-written, conceptually strong, and timely manuscript that contributes meaningfully to the literature on ecosystem-based management (EBM). The authors systematically explore the relationship between model complexity and output reliability in qualitative network models (QNMs) by comparing multiple simplified versions of a well-established quantitative model (Rpath). The core idea, identifying a “sweet spot” of model complexity, is both scientifically interesting and practically useful, especially for decision-makers and stakeholders in resource management contexts. In particular, the study provides an elegant way to balance model interpretability, time/resource efficiency, and robustness, which are often in tension in real-world applications of EBM. This work addresses a real need in applied marine systems modeling, where ecosystem managers often work under constraints that preclude full quantitative modeling. Its relevance aligns with broader ecosystem modelling priorities from ICES and EBM literature that supports multi-model and stakeholder-inclusive approaches. The manuscript is well structured, methods are clearly explained, and the results are robust and ecologically plausible. With a few clarifications and refinements, this work will make a strong contribution. General comments The manuscript builds toward identifying an optimal complexity level, but never formally defines what “sweet spot” means (i.e., balance between simplicity and agreement with a quantitative reference). It would be beneficial to include a sentence like: “We define the sweet spot of model complexity as the lowest complexity level that yields agreement with a quantitative model sufficient to support robust scientific inference.” It would be useful to justify the thresholds for removing linkages in QNM10-50. Providing a rationale grounded in prior work, or at least show a sensitivity check to validate that 10% increments are informative. Defining a result as positive/negative if ≥600 out of 1000 simulations show consistent direction is a bit arbitrary. I would suggest explaining this as a “majority rule” threshold or provide statistical reasoning (e.g., 95% confidence threshold would be 975+ under binomial assumptions). The interpretation of mixed vs. neutral needs more rigor. These are currently treated as categorical, yet they reflect different aspects: low effect size vs. high variance. I would suggest considering reporting proportion of runs with positive/negative results for all nodes to clarify this distinction. Reviewer #2: The article titled “Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management?” by Tam et al. compares quantitative and qualitative ecosystem models to discuss the optimal level of model complexity for effective Ecosystem-Based Management advice. The study is an insightful methodological exercise that demonstrates scientific rigor. Thus, I only have few minor comments that are reported in the form of in-text comments in the attached pdf file. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #1: Yes: Ioannis Keramidas Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. Attachments Attachment Submitted filename: PONE-D-25-18645_reviewer.pdf https://doi.org/10.1371/journal.pone.0328505.r001
Revision 1
23 Jun 2025 Author Response To Athanassios C. Tsikliras, Please find our enclosed revised Research Article for PLOS ONE, “Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management?”, by Tam et al., for submission [PONE-D-25-18645]. Alongside this response to reviewers, is: ● A marked up copy of the MS that highlights changes to the original version. ● An unmarked version as the revised “Manuscript”. Thank you for the time and effort to edit and review this paper. The comments have made it much stronger. We confirm that this manuscript has not been published elsewhere, nor is it under consideration by another journal. All authors have approved the manuscript and agree with the submission to PLOS ONE. Sincerely, Jamie C. Tam, PhD Response to Reviewer #1 (Ioannis Keramidas) Thank you for your thorough and constructive review. We appreciate your thoughtful assessment of this manuscript and we were happy that you agreed with the need for practical research to support the operationalization of ecosystem models into decision making. Please see the responses to your questions below and have included text clearly labeled in the marked version of the MS. It would be useful to justify the thresholds for removing linkages in QNM10-50. Providing a rationale grounded in prior work, or at least show a sensitivity check to validate that 10% increments are informative. Although we agree that a sensitivity might be useful to better understand the specific level to which the linkage strength would impact the overall model, the attempt here was to use a systematic reduction of link strengths rather than to examine thresholds or breakdown points of the model. As we used estimates of diet and mortality from the original Rpath model (which have varying levels of estimation defined in the pedigree table) to determine the linkage strengths, we wanted to consider the practicality of how to use this information to build qualitative models without an existing quantitative ecosystem model. Thus, we attempted to classify major vs moderate vs weak interactions at reasonable increments that would be feasible to estimate interactions under data depauperate scenarios. We determined that 6 qualitative models seemed like a balanced number to examine in this study. Removing linkages above 50% interaction would result in some lost model elements (functional groups) that would no longer be linked. We have made some adjustments in the text at lines 162-166 to clarify these points. Defining a result as positive/negative if ≥600 out of 1000 simulations show consistent direction is a bit arbitrary. I would suggest explaining this as a “majority rule” threshold or provide statistical reasoning (e.g., 95% confidence threshold would be 975+ under binomial assumptions). Thank you for this advice. We have included in the text that this was a “majority rule” threshold, as we wanted to depict 50/50 confidently. A difference of 6 runs (e.g. 506) did not seem indicative of a true change, but within 100 (e.g. 600) we felt more confident about the change. This was agreed by consensus by the authors as subject matter experts. We have also included more examples of published work that make similar delineations without using a statistical threshold. Changes were made at lines 227-229. The interpretation of mixed vs. neutral needs more rigor. These are currently treated as categorical, yet they reflect different aspects: low effect size vs. high variance. I would suggest considering reporting proportion of runs with positive/negative results for all nodes to clarify this distinction. The results in Figure 3 do show the scale of the results for each model element from each perturbation (size of the points are based on the number of simulation results out of 1000) as we wanted to be transparent about these results. We determined that neutral responses were no change for the node, while mixed nearly equal positive and negative results. We have made these results publicly available in the github that we have now included as part of the supplements. In the text we have made it clearer that these results are reflecting different aspects of not reacting (neutral) vs reacting in different directions (mixed) to reflect the low effects sizes vs high variances, respectively in lines 326-374. Response to Reviewer #2 Thank you for your thoughtful review. We appreciate your attention to detail in providing the comments in line. In the text, we have resolved typos, but respond to your in-line comments below: ● Line 131: Link complexity are the same from Rpath to QNM0 Figure 2. Main differences between the base model and the qualitative model is one has link strength, one retains just the direction (positive or negative) as shown in Figure 1. We have adjusted the figure caption to reflect these points. ● Line 153: The values are for individual linkages so representing the relationship between one model element to another model element which represents linkages either as prey and/or predator. ● Line 186-187: We cannot sum the biomass of the fishery as is done for other model elements because fisheries don’t have biomass. We summarized the fishery catch in this way so that it is similarly treated as other functional groups (model elements). ● Line 190: Yes there was no perturbation applied to the first 10 years of the Ecosense runs. ● Line 235: changed to “out of” (typo!) ● Line 318: We realized we were inconsistent here to the previous paragraph where we presented similar results. To remain consistent and avoid confusion, we included “or” in the bracket. This should reflect that the results are mirrored, we discuss positive (or negative). This is to keep the results more concise while remaining accurate. ● Lines 440-448: we removed some of the results details in this section of the discussion to avoid being overly repetitive. ● Line 478: Although fishery is treated here similarly to a functional group, we did not notice much difference in the way that perturbations to the fishery impacted the models compared to other perturbations. We wanted to note here that components with similar linkage structure to seals would not be well examined with the models used in this study. ● Line 491: Yes. We would consider an ensemble model as a possibility, but here considering data depauperate scenarios we thought suites of models might be more appropriate. ● Line 475: Included suggested reference Attachments Attachment Submitted filename: PONE-D-25-18645 Response to Reviewer.docx https://doi.org/10.1371/journal.pone.0328505.r002
Decision Letter - Athanassios C. Tsikliras, Editor Is there a “sweet spot” of model complexity for qualitative models used in Ecosystem-Based Management? PONE-D-25-18645R1 Dear Dr. Tam, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. 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If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: N/A ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I would like to thank the authors for addressing the comments thoroughly and thoughtfully. The clarifications provided on the rationale for linkage reduction thresholds and the use of the “majority rule” criterion strengthen the methodological transparency of the manuscript. I find the revisions satisfactory and believe the manuscript is now suitable for publication. Reviewer #2: I thank the authors for considering my minor comments. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #1: Yes: Ioannis Keramidas Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0328505.r003
Formally Accepted
Acceptance Letter - Athanassios C. Tsikliras, Editor PONE-D-25-18645R1 PLOS ONE Dear Dr. Tam, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Athanassios C. Tsikliras Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0328505.r004

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