PONE-D-22-25181Assessing Settlement Dynamics in the Central Salish Sea, a Bayesian ApproachPLOS ONE

Dear Dr. Rorabaugh,

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 points raised during the review process. Both reviewers indicate that your work has promise to be an important contribution to understanding demographic trends in your study area. However, they also indicate the need for fairly substantial revisions and additions. Reviewer 1 indicates the need for much more contextual information. I agree. When I first read your manuscript, I thought it read like a section/chapter in a much larger report rather than a stand alone journal article. Reviewer 2 indicates the need for corrections in your discussion of kernel density estimates. As implemented in OxCal KDEs are not strictly Bayesian: "Because the KDE method is in itself frequentist, this is not a purely Bayesian approach" (Bronk Ramsey 2017:1819). To better place KDEs in context, I suggest that you read: Crema, Enrico R. "Statistical inference of prehistoric demography from frequency distributions of radiocarbon dates: a review and a guide for the perplexed." Journal of Archaeological Method and Theory (2022): 1-32. As Reviewer 2 indicates there are Bayesian approaches to analyzing compiled radiocarbon dates for demographic modeling. Baydem is one possibility, but you do not need to do so for this paper. You do need to correct the sentence on assumptions about underlying distributions. Finally the paper needs a careful proofread. As both reviewers indicate there are partial sentences throughout.

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Reviewers' comments:

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Comments to the Author

1. 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: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

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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

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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

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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: The author has compiled 538 radiocarbon dates from 142 archaeological sites across northwestern Washington State. The dates are grouped into three regions in order to compare demographic trends between them and also with other demographic models existing to the north, in British Columbia, Canada. Utilizing and comparing marine shell dates was also an objective of this study.

The compilation and analysis of these radiocarbon dates has the potential to be a significant contribution, but this study, as is, provides only a cursory and uncritical summary of the data, description of the results, and discussion of demographic trends. More contextual information is necessary for anything beyond the most basic modelling of demography. As it is, a reader would have a challenging time trying to evaluate the appropriateness of the research questions or the validity of the interpretations because no background information in offered on the nature of the c14 dated sites, or the known settlement history of the region. Readers unfamiliar with the region would reasonably wonder how the analysis of the compiled c14 dates relates to earlier research in the region, and advances understanding of key anthropological or historical questions.

Another concern with this study is that there is no effort to look at the settlement patterning over time, to detect if the types of sites or the distribution of sites changed in relation to one another, the environment, new technologies and settlement forms/size, or demographic trends. There is no discussion of factors that might help to explain some of the modelled ups and down in the KDE.

I am not qualified to determine if the marine reservoir corrections have been applied appropriately, but more details would be helpful, and critical analysis of the methods should also be provided considering the ongoing uncertainty and regional variability with using shell dates.

The KDE seem to indicate some interesting trends that are generally consistent with those of other studies, but again, there is not sufficiently detailed results to know what the significance of this might be. Where the models indicate differing trends, there is also not discussion of why this might be.

This manuscript contains many sentence fragments (including the first line of the introduction) and some repetition. Other sections are too brief to be clear to the reader. A background section that might provide useful context for interpretations and discussion is missing.

Altogether, I’d like to see a research paper along these lines published, but would expect it to be thoroughly re-worked, from the intro to the conclusion.

Reviewer #2: This paper updates Taylor et al.'s 2011 paper, exploring population growth dynamics of the Pacific Northwest using the temporal distributions of radiocarbon datasets as proxies for the increasing and decreasing abundance of the archaeological record over time, i.e. the so-called "dates as data" approach. The present manuscript expands on Taylor et al.'s previous work in two noteworthy ways: first, it expands the geographic scope and consequently the sample size of the radiocarbon datasets used by Taylor et al., including adding inland sites from Washington State. Second, it replaces the summed probability distribution (SPD) approach used by Taylor et al. for describing temporal distributions of data points with a kernel density estimation (KDE) approach. Specifically, the author applies the KDE functions introduced to OxCal by Bronk Ramsey (2017), which have the appeal of being (relatively) easily applied by OxCal users without requiring any extensive programming on the user's part.

In general, I think this manuscript makes a novel and nontrivial contribution to our demographic-archaeological knowledge of the Pacific Northwest, and I do hope that it will be published for this reason. I also think that OxCal's KDE functionality supersedes both the SPD approach and other "composite kernel density estimation" alternatives suggested by others reviewed in the submission (e.g. Brown 2017). There is one alternative approach on offer---finite mixture modeling---that is founded on even strong theoretical and methodological principles than OxCal's KDE approach, which I discuss further below, but I will leave it to the author to decide whether the added effort to pursue finite mixture models over a KDE models is worth it; OxCal's KDE functions are still great tools.

One thing I would strongly recommend is that the author give the manuscript a new round of revisions with fresh eyes especially for broken grammar. Most of the paper is clearly written, but I did encounter a handful of sentence fragments, primarily sentence subjects lacking their predicates. Make sure every sentence ends.

Grammar aside, I do have one important critique of the manuscript that I think will need to be addressed before it is published: the author's characterization of kernel density estimation (KDE) as a Bayesian method is incorrect. In fact, KDE is not readily available to standard likelihood based approaches to model-fitting---whether maximum likelihood estimation (MLE; Silverman 1986: 25-26, 110-119; Simonoff 1996: 64-70) or Bayesian inference (Bouveyron et al. 2019: 92-93)---because tuning the KDE model's single free parameter ("bandwidth") in a likelihood-based way leads to the statistical problem of degeneracy: the likelihood function approaches infinity as the strictly positive bandwidth parameter approaches 0. In the case of KDE and other finite mixture models (FMMs), this degeneracy problem sometimes goes under the label "the collapsing variance problem" (Murphy 2012: 357-359), and it is unavoidable in the case of KDE. While it is true in general that OxCal comprises a diverse set of tools for radiocarbon data analysis that are Bayesian in a strict sense, this is not the case for OxCal's recently added KDE operations, a fact about which Bronk Ramsey (2017) is quite explicit. Instead, in order to operationalize KDE, OxCal's almost-but-not-quite-Bayesian approach replaces the proper likelihood function required by Bayes' Rule with a leave-one-out predictive probability function (Bronk Ramsey 2017: Eqs. 5 and 9). (A similar approach has been applied to MLE approaches to KDE; Silverman 1986: 52-55.) On one hand, this substitution "works" because the out-of-sample predictive probability function behaves in a manner similar to likelihood functions, increasing and decreasing over the parameter space depending on how suitable different parameter values are for the data under analysis. On the other hand, these out-of-sample predictive probabilities still should not be mistaken for likelihoods in the strict sense, so their substitution is of questionable theoretical merit. In my opinion, this choice is especially problematic for Bayesian inference because this substitution sacrifices the logical axioms that give this inferential framework, especially Bayes' Rule, its principled foundations. Nevertheless, a certain amount of pragmatic justification does exist for their use as a hack when proper likelihoods just won't work (Silverman 1986: 52-55), so I wouldn't insist that we abandon OxCal's KDE functions altogether. Even so, they are not Bayesian.

In any case, the author will need to make one of two changes to address and resolve this issue:

(1) The simpler solution would be editorial: remove or qualify any characterization of KDE as Bayesian, including in the paper title, key words, abstract, and main body of the text. This would require no new analysis on the author's part but merely a more accurate characterization of what the author has already done.

(2) Alternatively, if the author really wishes to do something that is truly Bayesian, he should consider a new round of analysis, replacing his KDE models with FMMs that can be approached in a Bayesian way. As it turns out, KDE models are an extreme case of FMMs, in which there are as many mixture components as there are data points and in which all kernels or mixture components share the same bandwidth. However, unlike KDE models specifically, FMMs more generally *are* available to Bayesian inference in the strict sense, particularly if there are fewer kernels/mixture components than there are data points. The collapsing variance problem mentioned earlier is still a possibility particularly for FMMs with large numbers of mixture components, but this problem can be mitigated in a Bayesian framework using regularizing priors (Fraley and Raftery 2007; Bouveyron 2019: 92-95) and/or posterior maximization rather than likelihood maximization (Murphy 2012: 357-359). Additionally, using FMMs with relatively few mixture components usually out-performs KDEs when applied as density estimates to the same data, particularly if different kernels/mixture components are allowed to have different bandwidths (Fraley and Raftery 2002; Gelman et al. 2013: 535). Unfortunately, OxCal has not yet implemented functions for finite mixture modeling. To my knowledge, the only prepackaged program capable of fitting such models is the 'baydem' package for R described by Price et al. (2021). If the author wishes to apply a truly Bayesian approach to the task at hand and is knowledgeable about how to use R (including loading packages from Github), I don't see any alternative at present to using 'baydem'.

One further, minor note: the author makes the assertion that "KDE is a non-parametric method and does not require assumptions of a particular underlying distribution, unlike parametric Bayesian approaches or summed probability distributions." Two thirds of this statement are true, but it is incorrect to say that summed probability distributions require assumptions of a particular underlying distribution. When producing SPDs, one can but need not make any such assumptions, and in fact in most cases users of SPDs do not do so.

References

Bouveyron, C., Celeux, G., Murphy, T. B., and Raftery, A. E. 2019. Model-based Clustering and Classification for Data Science With Applications in R. Cambridge University Press, Cambridge.

Bronk Ramsey, C. 2017. Methods for summarizing radiocarbon datasets. Radiocarbon 59(6): 1809-1833.

Fraley, C., and Raftery, A.E. 2002. Model-Based Clustering, Discriminant Analysis, and Density Estimation. Journal of the American Statistical Association 97(458): 611-631.

Fraley, C., and Raftery, A.E. 2007. Bayesian Regularization for Normal Mixture Estimation and Model-Based Clustering. Journal of Classification 24: 155-188.

Gelman, A., Carlin, J. B., Stern, H.S., Dunson, D. B., Vehtari, A., and Rubin, D.B. 2013. Bayesian Data Analysis, 3rd ed. CRC Press, Boca Raton.

Murphy, K. P. 2012. Machine Learning: A Probabilistic Perspective. The MIT Press, Cambridge, MA.

Price, M.H., Capriles, J. M., Hoggarth, J. A., Bocinsky, R. K., Ebert, C. E., and Jones, J. H. 2021. End-to-end Bayesian analysis for summarizing sets of radiocarbon dates. Journal of Archaeological Science 135: 105473.

Silverman, B.W. 1986. Density Estimation for Statistics and Data Analysis. Chapman & Hall/CRC, Boca Raton.

Simonoff, J.S. 1996. Smoothing Methods in Statistics. Springer, New York.

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Reviewer #1: No

Reviewer #2: Yes: William Brown

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PONE-D-22-25181R1Assessing Population Dynamics in the Central Salish SeaPLOS ONE

Dear Dr. Rorabaugh,

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 points raised during the review process. Per the two reviews, your manuscript needs more work before it will be acceptable for publications. You will need to take all of the comments and suggestions into account when making revisions.

Please submit your revised manuscript by Feb 16 2023 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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• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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Academic Editor

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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: (No Response)

Reviewer #2: (No Response)

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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: Partly

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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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: (No Response)

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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: No

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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: The author’s removal of the term “settlement” from the title of the manuscript helps to clarify the focus of this paper on population, but the rest of the edits do not address the principal issues that I identified.

As originally noted, the manuscript (from the first paragraph of the introduction) pre-supposes that readers will have an understanding of the paleo demography of the San Juan Islands and Salish Sea. I think that more work is required to demonstrate how this study contributes to the study of population dynamics in the region.

In the second paragraph of the introduction the author outlines the geographic divisions for analysis, but no rationale is provided. I wonder why the radiocarbon dates from the San Juan islands are analyzed separately from the adjoining mainland? Based on historical and cultural factors the data could just as easily be grouped. I think that the geographic divisions make intuitive sense, but this could be elaborated on, especially because the relationship between the islands and the mainland seems to be importation to some of the conclusions (ie. an influx of people from the mainland to the islands).

The author added a general overview of the region with an emphasis on hereditary social inequality. It’s not clear how this all ties in with the research questions. I would have expected context relating to populations/demography, archaeological perspectives on the growth and distribution of various localized or regional populations. Or perhaps on population movements, since this is proposed in the study. Some parts of this overview would also need to be expanded on to provide adequate background information for non-regional archaeologists.

The research questions also pre-suppose that the reader has existing familiarity with the region (ie., Clark’s 2013 idea that the Fraser Delta was a regional core) and previous San Juan Island research in particular.

the first couple lines of the second paragraph of the research questions section seem unrelated to the rest of the paper.

Methodology: It’s not clear how complete this compilation of radiocarbon dates is? This would be useful to know. Also when was the data compiled (ie. how up-to-date is it)?

Figure 3. Many of the sites look like they are in the middle of the ocean. Must be a mapping error.

Map figures: It seems important to represent the riverways, since nearly all the mainland sites are oriented to them.

KDE plot figures. It’s hard for the reader to evaluate the differences between Marine vs. Terrestrial data or even the regions because the timescales on the plots are different. Ideally, they could be plotted together, with variances statistically represented.

The results sections are all very brief and could be described more clearly so that the reader can get a better sense of how the KDE plots might relate to population dynamics.

In the discussion the author seems to suggest that the San Juan population dynamics reflect an “influx” of people around 2,600 – 2,200 cal BP and notes that it is too simplistic to focus on resource intensification as either a driving force or result of greater populations. Because there is no discussion of demography in this manuscript, it does not seem warranted to conclude that changes in the KDE were the result of an influx of people rather than in-place demographic growth (which I would assume is the viewpoint of the Indigenous communities). The author’s critques of other models (Croes and Hackenburger 1988 and Clark 2013) are not clearly refuted with the presented data or described in a way that can be evaluated. Also, in effect, the author seems to be describing the same sort of expansion idea, only from the Skagit River/delta to the San Juan Islands.

Overall the discussion should be developed and expanded so that readers can understand the contributions of the study, and how it advances other recent explorations of this same topic. One study that the author should consider is the recent Prentiss et al. 2022 study on population dynamics comparing the middle Fraser and lower Fraser regions (Divergent population dynamics in the middle to late Holocene lower Fraser valley and mid-Fraser canyon, British Columbia).

Issues with punctuation and spelling persist. There is a grammatical issue with the first sentence of the abstract.

Reviewer #2: I am fully satisfied that all of the theoretical and substantive issues I raised in my first review have been addressed. That being said, I noted the need for some further copy editing in my initial review as well, and unfortunately some important editorial problems persist in the manuscript, including in the abstract. I will list those that I think undermine the reader experience most, in order of appearance. Because the manuscript lacks page or line numbers, I will have to use the section name and paragraph number within each section to orient the author for the purpose of correction:

Abstract: The grammar is broken in the sentence "Recent developments in radiocarbon dating have enabled archaeologists to re-examination of question of population dynamism in the Salish Sea". I suggest revising "re-examiniation of question" to "reexamine the question"

Abstract: The words "that the" should be dropped from the following passage: "The expanded sample suggests that the patterns of population growth from 3200-2800 cal BP ...". Also, consider changing "patterns" to "a pattern"

Section: Introduction, Para. 2: "beingutilized" should be "being utilized"

Section: Research questions, para. 1: "If the case" should be "If this is the case"

Section: Database, para. 1: This is a run-on sentence: "An aim of this study was to critically assess uncertainties in marine dates, shell and bone dates with marine diet contributions were included." I think the logical connector "so" needs to be added after the comma. Alternatively, change the comma to a period and begin the new sentence that follows with "Consequently."

Section: Kernel density estimation, para. 2: typo: "methofd" should be "method"

Section: Discussion, para. 6: Revisit the grammar and punctuation of this sentence: "While an FMM study of individual sites is more in line with previous site-level radiocarbon analyses previously done in the region, can provide new insights to specific site histories and would be complementary to a settlement pattern analysis approach."

Additionally, I disagree with the implication that an FMM would be more inline with intra-site analysis than inter-site analyses. On one hand, it is true that finite mixture modeling is very often used as a method for model-based cluster analysis (e.g., see Bouveyrone et al. 2019 cited in my first round of review). Consequently, I would agree with the author that FMMs would be well-suited to the task of disentangling palimpsests of radiocarbon data at an intra-site level. On the other hand, FMMs can also be used simply as nonparametric density estimators. In fact, as I noted in my first review, FMM includes KDE as a special, extreme case. In this case, the mixture components are not interpreted as representing latent subpopulations in a mixed population but merely as tools for inducing flexible distributional structures in the density estimators. Consequently, FMMs are just as well suited for modeling regional dynamics in settlement patterns and demographic change as they are for disentangling latent clusters in mixed populations. This is actually the application that Price has in mind in developing the R 'bayesdem' package.

Section: Discussion, para. 7: This sentence needs some serious editorial reworking: "2. The marine and terrestrial sample lacks some finer structure seen in terrestrial only sample but broad patterns relatively consistent, ...". Perhaps it could be revised to something like "The combined marine and terrestrial sample lacks the fine distributional structures seen in the terrestrial-only sample, but broad patterns are consistent between the two, ..."

Section: Discussion, para. 7: The word "be" is missing between "not" and "problematic" in the following passage: "3. While shell date error terms may obscure fine structure, reservoir corrections themselves may not problematic."

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Reviewer #1: No

Reviewer #2: Yes: William A. Brown

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PONE-D-22-25181R2Assessing Population Dynamics in the Central Salish SeaPLOS ONE

Dear Dr. Rorabaugh,

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 points raised during the review process. Thank you for making the revisions to the manuscript. Both reviewers are satisfied that the revisions have addressed their concerns. Reviewer 1 identifies some minor issues that you should consider when making your final revisions prior to publication.

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PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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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: Partly

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: (No Response)

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: Overall, I find that this manuscript has improved considerably from the original submission, but there are still a few changes/additions that would ideally be addressed before publication.

One issue is that there is no discussion on population growth overall, starting with radiocarbon evidence for people living in inland, then on the coast, then on the islands. I’m not clear why there is no real mention of the broader trends as indicated by the radiocarbon dates. The discussion focuses-in on only a couple peaks (mostly related to the Islands). This is fine of course, but it’s not explained why some peaks are emphasized more than others, or over the general trends.

At one point the author notes that there is in-situ population growth in NW coastal Washington between 3,200 – 2,800 cal BP. People were living in this area long before this time though…was this earlier time characterized by something other than in-situ growth? I think that this is only confusing because there is not a more general review discussion on longer-term population trends.

In the San Juan results section the first peak is described as being between 2,400 – 2,200 cal BP. In the discussion it’s reported as starting at 2,600 cal BP. Which is more accurate?

So, even though people have been living on the San Juan islands since before 3,000 years ago, the argument is that the First Ancestor of the Lummi people may have arrived around 2,600/2,400 cal BP because there is an increase in population at this time?

I also wonder about the word choice of “influx” to describe this significant event in tribal history. Influx makes it sound like the First Ancestor is coming from somewhere nearby (like the mainland, as was suggested in the second version). Typically though, these oral histories are explicit about the ancestors coming from the sky, and that they are the original settlers in a new area.

The figures are better than before, but could still be improved with place names (ie., coastal and riverine water bodies) to help orient the reader.

Figure 1. “Stolo” is the only name provided for a cultural group on the Canadian side of the map, and it’s use is inaccurate. I suggest sticking with linguistic groupings at this geographic scale.

Reviewer #2: (No Response)

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Reviewer #1: No

Reviewer #2: Yes: William Brown

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Assessing Population Dynamics in the Central Salish Sea, Pacific Northwest Coast of North America

PONE-D-22-25181R3

Dear Dr. Rorabaugh,

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.

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Kind regards,

John P. Hart, Ph.D.

Academic Editor

PLOS ONE

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