PONE-D-21-39491Predicting biomass of resident kōkopu (Galaxias) populations using local habitat compositionPLOS ONE

Dear Dr. Crichton,

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.I have now received two reviews of your manuscript. Your manuscript got many general but also quite some specific comments that you need to consider before we move forward in the publication process. I found that the potential of this manuscript critically depends on how your arguments can meet the reviewers comments. A major concern raised by both reviewers was that species identity was not included in the models. Although there is a large overlap in microhabitat it is still plausible that the different species have different ecological requirements. Both reviewers have given suggestions on how this can be dealt with. Another concern regards the representativeness of your results both to other systems and rivers entailing kökopu populations but also to other freshwater species. In your response letter you need to include point by point how you dealt with the reviewers' comments.

Please submit your revised manuscript by Apr 08 2022 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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We look forward to receiving your revised manuscript.

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Peter Eklöv

Academic Editor

PLOS ONE

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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: Yes

Reviewer #2: Partly

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

Reviewer #1: Yes

Reviewer #2: No

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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: No

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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 manuscript “Predicting biomass of resident kōkopu (Galaxias) populations using local habitat composition” evaluates the relationship among biomass of three endemic species of Galaxias and five instream habitat characteristics in New Zealand streams. I think the study is very well conducted and well written, and it is of great contribution to the field. This research is not only important for conservation of the species under study, but can also be used as a model to understand what drives variation in stream fish populations elsewhere. In general, I have mostly minor comments to the manuscript. My main concern is about the not inclusion of species identity in the models; all the three species are regarded as a single population in the models, which may be an issue because one may expect at least little differences in microhabitat selection. I think that adding the species identity as a random variable in the models will make the study more compelling and convincing to the readers.

Title: I would suggest to use “local habitat characteristics' ' instead “composition”, as composition is more related to the content (like for a chemical compound or for a fish assemblage).

Abstracts: Is it a riverine or stream fish? Or a lake? Maybe state the type of freshwater habitat.

Introduction:

L60-74: Regarding this, you may want to check Dala-Corte & De Fries (2018) study, which investigates very similar questions.

Dala-Corte, R. B., & De Fries, L. (2018). Inter and intraspecific variation in fish body size constrains microhabitat use in a subtropical drainage. Environmental Biology of Fishes, 101(7), 1205-1217.

L66. Give an example for what you mean with “same local environment”.

L119: “habitat characteristics”. Review it elsewhere in the text.

L119: State again which are these 3 species.

L119-131: This paragraph is almost entirely a methods paragraph, I would move to methods.

L133: I recommend “kokopu fish populations of three species endemic to New Zealand streams”.

L133: There is no need to state the use of AIC here, leave it to methods only. AIC is a widely known statistical approach.

L136-142: Congratulations for the predictions.

Methods

L173-193: Were the individuals identified to species-level during the field?

Data analysis

L195: I think the author should include the species identity in the models (at least as a random variable). I know that the three species may largely overlap their microhabitat selection, readers will still think that it is very plausible that the different species have slightly different ecological requirements and behaviors. For instance, see Dala-Corte and De Fries (2018).

Results

Table 1. Tables should not have these horizontal lines in the middle.

L246: Like you did with large kokopu, start the small kokopu paragraph stating the results for the AIC models.

L256-258: Actually, looking at the deltaAICc (smaller than 2), you do not have strong support to say that the model 1S is better than the 4S. So theoretically you should say that the best model is the 4S, which is the most simple. Yet, it is important to discuss the model 1S too.

Table 2. Since you may be interested in the effect size of all the explanatory variables, you may want to inform the relative importance of the variables using the Summed Akaike Weights (SW) of all the models. See Burnham and Anderson (2002) and Giam and Olden (2016) if you have interest.

Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New York.

Giam X, Olden JD (2016) Quantifying variable importance in a multi-model inference framework. Methods Ecol Evol 7:388–397

Discussion

You may want to expand your comparisons to other studies with stream fish besides those with kokopu and trouts. For example, see Dala-Corte and De Fries (2018).

L283-292: You may want to recall the readers who are the kokopu species you studied.

L347. Ok, it iwas not locally important, but give an emphasis in this conclusion that upstream forest cover may be essential and probably explain your results.

L357-359: Ok, so benthic insects may be an important feeding resource. Make it clearer.

L348-365. Indeed, I think that local riparian forest may be more important in driving refuge for small fish than in predicting the local input of terrestrial invertebrates, because upstream riparian forest may provide plenty of drifting terrestrial invertebrates to the pools.

L367-373. You may want to take into consideration that the negative relationship between total bank cover and small kokopu biomass may just reflect that large kokopus displace the small ones from sites with more bank cover. In other words, an increase in bank cover may not be a conflict of interests for habitat restoration between large and small kokopus. If streams had no bank cover, you could probably don’t see any kokopu at all. To assess this one must sampling long stream reaches with few or no bank cover at all.

Reviewer #2: Dear Authors,

In my view, the basic premise of this manuscript – the need for better understanding and characterisation of ontogenetic variations in physical habitat preferences – is sound. However, I feel that there are a few aspects of this study that need to be tackled more substantively before it is ready for publication.

Conceptually, I see the value in pursuing the development of predictive models of fish biomass to support species management. As such, I see this as a valuable endpoint for this study. However, to strengthen the credibility and hence uptake of such models, in my view there needs to be greater transparency around the underlying data and assumptions that have been made. Furthermore, there is a need for validation and consideration of the transferability of the resulting models.

The study offers a valuable dataset on kōkopu habitat utilisation from multiple rivers on the west coast of the South Island of New Zealand. It is predicated on an assumption of potential habitat separation between ‘small’ and ‘large’ individuals arising from competitive displacement of smaller individuals from preferred habitats as indicated by previous studies. Below I make a few observations regarding the study methodology and some of the assumptions that I feel need addressing within the manuscript.

Firstly, it is indicated that the fish surveys took place during May and June (L147). This coincides with the spawning season of these species, yet the potential implications of this in terms of fish behaviour and habitat choice (and hence representativeness/transferability of these data and models) are not addressed in the manuscript. Mature individuals are known to aggregate prior to spawning and can undertake spawning migrations. Consequently, how representative are these observations (particularly for the ‘large’ group) of ‘normal’ habitat use and hence how transferable are the models?

Secondly, observations for the three kōkopu species have been pooled, based on an assumption that they regularly co-exist and have similar habitat requirements (L121). Broadly speaking, yes, they all typically display an association with pool habitats and some degree of overlap in distribution does occur. However, I would suggest that there’s sufficient evidence to indicate a degree of spatial separation in the distribution of the three species (particularly beyond the South Island west coast rivers) broadly correlating with distance inland and elevation (giants lower gradient closer to the sea, bandeds low-mid gradients and further inland, shortjaws mid-higher gradients further inland still). I would also think there is some potential for differentiation in micro-habitat use between the species. Consequently, I feel there is a need to account for this potential in the analyses or at least demonstrate the assumption is sound. One of the benefits of the more modern mixed models as you have used here is that it would be simple to include species as a predictor variable and check the validity of this assumption. You show no data on the proportional make up of your observations between the species, nor information on equivalence (or not) of size classes between the species. Likewise, there is no exploration of whether there is any spatial or microhabitat separation between the species (e.g. do shortjaws inhabit larger pools than bandeds?). Much of this would be fairly straightforward to illustrate graphically. With respect to species management, these factors are crucial to understand and be confident about for ensuring the validity and credibility of your models for informing management actions.

Thirdly, and somewhat linked to the above, how representative are the west coast river systems and kōkopu populations of other rivers and kōkopu populations across New Zealand, and hence, how transferable are the results to elsewhere in the country?

Fourthly, is there an interaction between pool size and pool depth? Intuitively I would expect the potential for some statistical redundancy between these two variables. It would be good to see this addressed. Likewise, how about between any of the other predictor variables? How closely correlated are they? Similarly, does the apparent correlation between smaller individuals and forest cover simply reflect a preference for smaller streams (and hence greater chance of canopy closure)?

Finally, and this is in my view a particularly critical omission, there is no cross-validation of the statistical models. Good practice in this sort of study would typically see some form of model validation undertaken and reported. For example, using a proportion of the dataset to train the model and a separate portion of the dataset to test and quantify model predictive performance. The addition of this sort of approach would help to provide possible end users greater confidence in the relevance and transferability of the model for real world application.

More generally, I felt that the introduction was biased towards pelagic, drift-feeding species, without really acknowledging that some of the statements regarding energetic benefits of pool feeding etc may not be as generalisable as could be inferred. You also jump into some fairly bold statements about statistical models in your opening paragraph (e.g. L42) that in my view aren’t as well justified as they could be and perhaps need a bit more introductory context.

One specific comment about your choice of sampling for determining mean pool depth – why only measure depths along one axis of the pool? Can you be sure that is representative of the mean pool depth? Do you have a reference for this method ahead of others (e.g. 10 random depth measurements or 5 on each axis)? I would have thought there was quite a bit of depth variation in the longitudinal axis.

In the discussion (and throughout), I think it would be good to consider your terminology with respect to habitat use/requirements/preference. These three terms have different meanings to me – habitat use being the habitats that fish are using (i.e. where you find them when you look for them), habitat preference being where they would most like to be if the habitat was available, and habitat requirements being habitats that are required to fulfil a particular function. These can all be the same, but could also all be distinct. You talk, for example, about small and large kōkopu having different habitat ‘requirements’ (e.g. L288). Do they really require different habitats? Or do they, as you allude to later, have overlapping fundamental niches but different realised niches (L317-318) due to competition for ‘preferred’ space? Or perhaps there is a genuine spatial segregation of small and large kōkopu habitats, with the distribution of smaller fish skewed towards smaller, lower order streams, and larger fish in larger, main stem streams, that may be more indicative of differing habitat preferences/requirements? I think this could be explored in more depth through your analysis, for example by illustrating the random effects of site to show how these relationships may vary by stream size. I know this may seem somewhat pedantic, but there are crucial distinctions in these terms and what they may mean from a management/restoration perspective, so it’s important to be precise about what you mean.

I feel there is real promise in this manuscript, and it is generally well written, but as identified above I do feel there is still some work to achieve the impact that befits the hard work that has gone into collecting these data.

Best of luck with the manuscript.

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PONE-D-21-39491R1Predicting biomass of resident kōkopu (Galaxias) populations using local habitat characteristicsPLOS ONE

Dear Dr. Crichton,

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. I have received a second review from one of the reviewers and as you can this reviewer is happy with the development of this manuscript after the first round of review. However, the reviewer has also some additional comments that need to be resolved before we can proceed in the publication process. Please, indicate in your response letter, point by point, how you have dealt with this reviewer's comments.

Please submit your revised manuscript by Aug 07 2022 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.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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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.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Peter Eklöv

Academic Editor

PLOS ONE

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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 #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 #2: Partly

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

Reviewer #2: No

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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 #2: Yes

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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 #2: Yes

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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 #2: Dear Authors,

The changes made to the manuscript in response to the initial reviews are positive and validate the comments from both reviewers regarding the need to account for the separate species in your models.

The basic premise of this manuscript remains sound, and it is based on a strong empirical foundation. The species-specific models have improved the value and credibility of this work, but in my view there remain some questions regarding the structure of your statistical models and, potentially, their transferability that need to be addressed.

Firstly, in my view it is not appropriate to include the biomass of other species as random effect – this should be treated as a fixed effect because, as you state, it is included to account for the direct effect of competitive exclusion.

Secondly, it appears that you are treating all sampled reaches as independent sites, even though they are nested within catchments and hence subject to correlated effects. In my view this is potentially an inappropriate treatment of pseudo-replication and the spatial structuring of reaches by catchment needs to be accounted for in your formulation of your site random effect (e.g. reaches need to be nested within catchments).

Thirdly, I am not yet sufficiently convinced of the transferability of your models to areas beyond the geographical and environmental space within which the data have been collected. The west coast rivers of New Zealand have a fairly unique character – short, steep rivers, high rainfall, glacial derived flows, relatively intact catchments (at least compared to a lot of New Zealand). I think that compared to places like the Waituna (see Greer et al 2012) or central Waikato (see Franklin et al 2015) strongholds for giant kokopu, or Coromandel (see West et al 2005) or Auckland (see McEwan et al 2009) strongholds for banded kokopu, there are substantial differences in the stream type, flow regimes, and habitat structure where these species are resident. Similarly, there are relatively few places elsewhere in New Zealand where all three kokopu species co-occur in the same way (see Yungnickel 2017). These models may represent the realised niche in this region, but given the different habitat structures and relative differences in species composition and dominance in other regions, I don’t think you provide sufficient evidence to be able to claim that the realised niche elsewhere would be equivalent and thus that your models are transferable. I would like to see some evidence to support this claim – for example how do the environmental gradients you have sampled compare to other regions? While it does not cover extrapolation of mixed effects models, the paper by Booker & Whitehead (2018) may be of interest in this respect.

Fourthly, your site random effect accounts for around half of the variation in biomass in your models of both banded and giant kokopu. Given the general spatial structuring of kokopu species with distance inland and elevation, this is not surprising. However, it again raises the question of transferability of your models to other sites. Why not reduce some of this random error tied to site by explicitly accounting for distance inland/elevation (I appreciate there’s some correlation there!) and potentially other landscape scale variables as fixed effects in a way that will make the results more transferable? Similar approaches using landscape scale predictors have been used to predict fish probability of occurrence across the New Zealand river network previously (e.g. Leathwick et al 2005), so it seems logical that a similar approach here to cover off the broader biogeographical drivers before accounting for local scale variations in biomass associated with the site level variables should be explored.

It is my view that these issues of model structure and transferability need to be better addressed to strengthen this manuscript and improve the usefulness of the models. A few more specific comments follow:

1. I remain unconvinced that your surveys coinciding with spawning season for these species could not have impacted their distribution/behaviour. The Charteris et al manuscript you cite as a justification that kokopu spawn in situ explicitly states that the giant kokopu from that study site migrated out of the reach and then returned following spawning. Similar observations have been observed for giant kokopu by David & Closs 2002. I appreciate that the Franklin et al 2015 paper showed giant kokopu spawned in situ, but this reflects the current level of uncertainty regarding spawning behaviour in spawning kokopu – it’s rarely been documented comprehensively but there’s enough evidence to suggest both aggregation of fish within areas and movement between reaches for spawning.

2. Some previous studies of giant kokopu have demonstrated clear seasonal variation in activity and microhabitat use (e.g. David & Closs 2003). Please address this in your discussion – what does the timing of your surveys mean for the applicability of these models?

3. In all of your tables I think you mistakenly use BK instead of BC to indicate your bank cover fixed effect. If this is not a mistake, I suggest using a different abbreviation for bank cover given that BK is also used to mean banded kokopu in the paper.

4. In your discussion I think it would be helpful to consider what additional value your models have over existing models of fish distribution available for New Zealand (e.g. Leathwick et al 2005). Please compare and contrast the relative strengths and weaknesses of these approaches and, therefore, the suitable contexts for their application.

I remain convinced that there is real promise in this manuscript and with some further work it will merit the hard work that has gone in to collecting the data.

References:

Booker, D. J. and A. L. Whitehead (2018). "Inside or Outside: Quantifying Extrapolation Across River Networks." Water Resources Research 54(9): 6983-7003.

David, B. O. and G. P. Closs (2002). "Behavior of a Stream-Dwelling Fish before, during, and after High-Discharge Events." Transactions of the American Fisheries Society 131(4): 762-771.

David, B. O. and G. P. Closs (2003). "Seasonal variation in diel activity and microhabitat use of an endemic New Zealand stream-dwelling galaxiid fish." Freshwater Biology 48(10): 1765-1781.

Franklin, P. A., et al. (2015). "First observations on the timing and location of giant kōkopu (Galaxias argenteus) spawning." New Zealand Journal of Marine and Freshwater Research 49(3): 419-426.

Greer, M. J. C., et al. (2012). "Complete versus partial macrophyte removal: the impacts of two drain management strategies on freshwater fish in lowland New Zealand streams." Ecology of Freshwater Fish 21(4): 510-520.

Leathwick, J. R., et al. (2005). "Using multivariate adaptive regression splines to predict the distributions of New Zealand's freshwater diadromous fish." Freshwater Biology 50(12): 2034-2052.

McEwan, A. J. and M. K. Joy (2009). "Differences in the distributions of freshwater fishes and decapod crustaceans in urban and forested streams in Auckland, New Zealand." New Zealand Journal of Marine and Freshwater Research 43(5): 1115-1120.

West, D. W., et al. (2005). "Growth, diet, movement, and abundance of adult banded kokopu (Galaxias fasciatus) in five Coromandel, New Zealand streams." New Zealand Journal of Marine and Freshwater Research 39(4): 915-929.

Yungnickel, M.R. (2017) New Zealand’s whitebait fishery: spatial and temporal variation in species composition and morphology. MSc Thesis, University of Canterbury.

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Reviewer #2: No

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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.

PONE-D-21-39491R2Predicting biomass of resident kōkopu (Galaxias) populations using local habitat characteristicsPLOS ONE

Dear Dr. Crichton,

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.

It appears most of the comments concerns raised in previous submissions have been addressed. However, the authors have only made critical counterpoints to some (in their response to reviewers) and these editorial changes remain to be fully addressed or rebutted.  These are minor points and should be able to be easily addressed by the authors without much trouble. Please refer to your "response to reviewers" for editorial remarks that you have chosen not to change.

Please submit your revised manuscript by Nov 19 2022 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.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
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Reviewer #2: (No Response)

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Reviewer #2: Partly

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Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #2: Dear Authors,

It is great to see the ongoing improvements to this manuscript in response to prior review comments. It retains its strong empirical foundation and in acknowledging and addressing some of the limitations around transferability and application relative to other species distribution modelling approaches I think now gives a more balanced view of its applied value. However, I believe you have not appropriately addressed the errors in the structure of your statistical models as highlighted by previous reviews.

The structure of the model (in terms of what is included as fixed v random effects) should not be determined by convenience to support a desired narrative. It must be dictated by the protocols of the statistical methodology. In that respect, you must include the biomass of other species as a fixed effect. It is a continuous variable, the value of which has real meaning, and as such can only be treated as a fixed effect. My understanding is that random effects must be factors and that the levels of those factors should effectively be ‘meaningless’ in so far that you can use any set of labels and it doesn’t change the interpretation of what it means (e.g. labelling sites 1, 2, 3 versus A, B, C). As such, I’m not even sure how you’ve included biomass as a random variable as it presumably would have had to be converted to a factor somehow (maybe high/medium/low?), but even if you’ve done this the factor labels have meaning – they’re ordered – and so do not meet the normal rules of defining a random effect. I appreciate that this may appear ‘inconvenient’ for how you are wanting to frame your narrative, but assuming that biomass is retained as a significant fixed effect in your models, then I think it can potentially help with the transferability of the models – it would allow someone who is trying to apply the model in the real world to set biomass of a species at zero, if for example, it was known not to co-exist at the site. Similarly, you could provide median and/or confidence intervals around your observed biomass values that someone wishing to use the model could utilise to get an understanding of the range of biomass in the target species given the local habitat conditions. My key point is that just by including biomass of competing species as a fixed effect, it doesn’t negate the value of the model – in fact I would argue it strengthens the potential utility because it allows users to more appropriately recognise uncertainty.

Another component of your GLMM that you need to address is the treatment of site/reach. Your use of the term ‘site’ as the term in the model appears to have created some confusion; to most people at first glance this would be interpreted as the lowest level of replication, but I think in this case this is what you term a ‘reach’. The prior review comments remain valid in this respect in so far that it would be most appropriate for ‘reach’ to be nested within ‘site’ within your model formulation. This will appropriately address the spatial structuring of your data and currently inappropriate treatment of pseudo-replication.

More generally, I feel that the comments made in the previous review around the uncertainty of the potential impacts of spawning remain valid – I appreciate your responses, but you rightly acknowledge that there remains considerable uncertainty over the role of migratory movements around spawning. As such, I feel that you could provide a more balanced acknowledgement of this in your manuscript. It’s not a fundamental flaw, but there appears to be enough evidence to suggest that particularly for giant kokopu, at least in some streams, they likely undertake spawning migrations and at the moment you largely dismiss this possibility – just be honest about the uncertainty.

I feel that there is a strong manuscript here, but please don’t ignore good statistical practice for the sake of fulfilling a particular narrative. Likewise, it is always advisable to provide a balanced and honest discussion of the limitations/uncertainty in your work – this improves its credibility and is not something to be afraid of.

Best of luck with completing your manuscript.

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Reviewer #2: No

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Predicting biomass of resident kōkopu (Galaxias) populations using local habitat characteristics

PONE-D-21-39491R3

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