Commercial fishing amplifies impacts of increasing temperature on predator-prey interactions in marine ecosystems

Domain: biology
Published: 2026-01-19
Editorial outcome: minor_revision

Abstract
Predator-prey interactions determine food web structure, energy flux, and ecosystem stability. Increasing temperatures and commercial fishing both alter body size distributions that underpin predator-prey interactions, but empirical evidence of their individual and combined effects is limited. We study how the predator to prey body mass ratio (PPMR) changes as a function of temperature and fishing effort in over 50,000 predator stomachs collected across the Northeast Atlantic over 35 years. PPMR increases with temperature, an effect that is exacerbated by greater fishing effort, driven by intraspecific decreases in prey body mass in heavily fished areas. To compensate for smaller prey (both within and across species) in warmer waters and areas of high fishing, predators target the largest prey available to them, but this is insufficient to alter the community-wide increase in PPMR. Higher PPMR is associated with weaker trophic interactions that dampen strong oscillatory dynamics but could also reduce energy transfer efficiency within ecosystems, both of which can affect ecosystem stability. These results could help underpin ecosystem-based management and sustainable fisheries by providing estimates of how future climate warming might interact with fishing to affect energy flux through marine food webs.

Introduction
Marine food webs are highly size structured, consisting of many small organisms and few large organisms1,2. Trophic interactions tend to involve larger consumers eating smaller resources due to gape limitation and the lower risk of injury or wasted energy3–5. The size-structuring of marine food webs has given rise to their historical conceptualisation as trophic pyramids where the vast majority of biomass and productivity is concentrated at lower trophic levels made up of smaller organisms (e.g., plankton, small fish) with decreasing biomass and productivity at higher trophic levels that consist of larger intermediate and top predators (e.g., large fish, marine mammals)6. Thus, body mass is considered a master trait due to the constraints it imposes on trophic relations and is a useful tool for gaining insight into and modelling trophic interactions2,7. For instance, the relative sizes of predators and their prey measured via predator-prey mass ratios (PPMR) are a key constraint on how energy flows through ecosystems8–10.

Predator-prey interactions act as highways of energy flow, creating avenues whereby the direct and indirect effects of species can propagate throughout entire ecosystems11–15. Trophic interactions are vulnerable to global environmental change16,17, but the intricacies of the response are less well known18–20. Marine ecosystems exhibit large natural variability in temperature due to latitude, seasonality, and depth, but climate change is causing relatively rapid increases in sea surface temperatures (SST) beyond this natural variability21,22. For example, SST in the Northeast Atlantic has increased by as much as 0.5°C in the last century23, which has been linked to changes in biodiversity and food web structure16,24–26. Warmer waters are known to favour smaller species due to temperature dependencies of distribution, physiology, and productivity27,28. Decreasing body mass is recognised as a ubiquitous response to increasing temperature, which can be due to physiological drivers such as increased metabolic demands keeping species smaller and the age at maturity lower29,30, or through changes in community composition that favour smaller species28,31.

Commercial fishing is a global anthropogenic pressure ubiquitous in marine ecosystems, particularly in the Northeast Atlantic, where the biomass of many fish species has declined dramatically over the past century19,32,33. Similar to the observed impacts of increasing temperatures, fishing also results in an increase in the relative abundance of smaller species, as commercial fishing practices are well known to target larger fish due to their commercial value24,34. By selecting for larger fish, commercial fisheries also impact the age-structure of fish communities35,36. Commercial fishing has a heterogeneous distribution in space and time and could therefore lead to complex effects on trophic interactions when combined with changes in temperature. For example, the combination of commercial fishing and increasing temperature has been shown to alter the recruitment, abundance, distribution, body condition, prey availability, and spawning success of marine organisms26,37,38. Despite the growing body of evidence highlighting the impacts of both commercial fishing and temperature on the size structuring of marine food webs, few studies have investigated the potential for complex interacting effects of these drivers on PPMR.

It is important to address this because current models that forecast fish stocks under climate change use a fixed PPMR39, not accounting for the physiological and compositional plasticity of species when exposed to environmental stressors.

To improve our predictive capacity, it is important to first understand the historical variation in PPMR across large-scale gradients of temperature and commercial fishing pressure. PPMR is an excellent predictor of the identity and strength of predator-prey interactions and thus for quantifying ecosystem energy flux3,40. Physiological and compositional changes, such as decreasing body mass and fluctuating species richness and prey availability, driven by increasing temperature and targeted fishing practices, could alter PPMR, which in turn has the potential to rewire whole food webs41,42 and disrupt ecosystem functioning and stability1,9,26. Altered PPMR at the community-level is thus likely to be underpinned by disproportionate changes in the relative size of predators and their prey driven either by physiological mechanisms, such as altered metabolism or growth leading to a systematic reduction in body size of many species in the community (i.e. intraspecific processes), or compositional mechanisms, such as systematic changes in the number of small or large species within the community (i.e. interspecific processes). Disentangling the relative importance of these mechanisms is key to understanding and forecasting the effects of temperature and commercial fishing on the size-structure of trophic interactions.

Here, we employ a space-for-time substitution to quantify PPMR across spatial gradients of temperature and fishing effort, which could help predict how energy fluxes in the Northeast Atlantic may respond to future global change. Given that PPMR has a negative relationship with body mass1,43,44, a reduction in the mean body size of the community at higher temperatures and/or commercial fishing pressure should lead to an increase in PPMRs since smaller predators consume relatively smaller prey. We test the following hypotheses: (1) PPMR is positively related to temperature and fishing; (2) PPMR values are highest where temperature and fishing are both high; (3) increases in PPMR are related to both physiological processes (e.g., altered metabolic rate, which may underpin changes in body mass) and compositional processes (changes in taxonomic composition). The central goal of our study was to empirically quantify change in PPMR along a temperature gradient and test how this was affected by commercial fishing effort. Given how critical PPMR is in determining energy flux through marine food webs and their stability10,19,45, this understanding could be critical for improving projections of fish stocks and optimising multi-species fisheries management under future scenarios of climate change and commercial fishing.

Results
Effects of increasing temperature and fishing effort on PPMR
Across the Northeast Atlantic, there was a significant increase in PPMR with increasing temperature (t = 23.29; p < 0.001, R2 = 0.45; Fig. 1a, b). This suggests that predators and their prey diverged in size at higher temperatures (Fig. 1b). PPMR was predicted to increase by 30% across the temperature gradient, or 1.8% per 1°C. Latitude was a major contributor to the effect of temperature on PPMR, with less contribution of season and water column depth (Fig. S1). The increase in PPMR was amplified in areas with more commercial fishing, with a significant interactive effect of temperature and fishing effort on PPMR (t = 2.99, p = 0.003, R2 = 0.48, Fig. 1c, d). PPMR increased at both high and low fishing effort, but the increase in PPMR with increasing temperature was more pronounced in areas that were more heavily fished (Fig. 1d). In areas of low commercial fishing, PPMR was predicted to increase by 22% across the temperature gradient, or 1.3% per 1°C, whereas in areas of high commercial fishing, PPMR was predicted to increase by 82% across the temperature gradient, or 4.8% per 1°C.

Effects of only temperature on body mass, prey count, and prey richness
There was no significant effect of temperature on the mean body mass of the predators sampled (t = 1.93, p = 0.053, Fig. 2a), i.e., using the larger dataset without fishing effort data included. Mean predator body mass was also relatively consistent at the species level across the entire temperature gradient, with no significant effect of temperature on 82% of predator species, accounting for 99% of predator biomass (Table 1, Table S1). In contrast, there was a significant decrease in the mean body mass of prey individuals with increasing temperature (t = -7.58, p < 0.001, R2 = 0.83, Fig. 2b), indicating that reductions in prey body mass were a primary driver of the increase in PPMR with increasing temperature. Note that we refer to “prey” here as any organism found in the diet of the fish predators, even if those species could be predators themselves. At the species level, there was a decrease in mean individual prey body mass with increasing temperature for 58% of prey species, accounting for 77% of prey biomass (Table 1, Table S2), indicating that intraspecific responses to increasing temperature played a major role in determining the observed changes in PPMR.

The prey count (t = -4.91, p < 0.001, R2 = 0.64, Fig. 2c) and prey species richness (t = -6.42, p < 0.001, R2 = 0.82, Fig. 2d) within predator stomachs significantly increased with increasing temperature. There was a significant interaction between prey size class and temperature for both prey count (t = 13.07, p = <0.001, R2 = 0.64, Fig. 2c) and prey species richness (t = 27.43, p < 0.001, R2 = 0.82, Fig. 2d). Here, predators increasingly targeted larger prey from a bigger pool of species as temperature increased. However, the nMDS analysis did not indicate any strong relationship between the size of the prey taxa consumed and mean temperature (Fig. 2e), indicating no clear evidence for compositional changes contributing to the decrease in mean prey body mass with increasing temperature.

Interactive effects of temperature and fishing effort on body mass, prey count, and prey richness
The consistency of sampled predator body mass across the temperature gradient was maintained despite additional impacts of commercial fishing, with no significant interactive effect of temperature and fishing effort (t = -0.71, p = 0.478, Fig. 3a). There was a significant interactive effect of temperature and commercial fishing on individual prey body mass (t = -9.92, p < 0.001, R2 = 0.83; Fig. 3b), however, with an increase in prey body mass at low fishing effort and a decline in prey body mass at high fishing effort (Fig. 3b). Fishing effort also significantly altered the positive relationship between prey count and temperature (t = 15.0, p < 0.001, R2 = 0.79, Fig. 3c), with a reduction in the number of prey of all sizes consumed with increasing temperature at low fishing effort, but an increase in the number of prey of all sizes consumed with increasing temperature at high fishing effort.

There was a significant interactive effect of temperature and commercial fishing on prey species richness (t = 5.19, p < 0.001, R2 = 0.84, Fig. 3d). Here, there was a greater increase in prey species richness with temperature as prey size class increased and as fishing effort increased. The nMDS plot showed a tendency for larger prey taxa to be found in areas of increased commercial fishing, although mean fishing effort only accounted for 4% of the variation in body size (R2 = 0.04, Fig. 3e). Mean prey body mass was also not strongly associated with mean temperature or fishing effort.

Methods
The study relies on historical stomach-content records publicly available from the Cefas Data Hub79, Copernicus80–82 and the JRC Data catalogue83. No new animal sampling was undertaken, and therefore, ethical approval and informed consent were not required. Data were used in accordance with institutional and national regulations.

Study region
The fish stomach survey data for this study were collected from 1981-2016 in an area of the Northeast Atlantic spanning 35° of latitude and 70° of longitude, incorporating the Bay of Biscay, Celtic Sea, North Sea, Norwegian Sea, and Greenland Sea (Fig. 1a). The geographic area has a temperate climate in the south and a polar climate to the north7. The region provides ecosystem goods and services to large populations across many countries in western Europe, including valuable commercial fish stocks, with mature oil and gas fields, rapidly developing offshore wind infrastructure and important carbon sinks7,84,85. The Northeast Atlantic thus experiences some of the strongest anthropogenic impacts globally26,73,86. Extensive and often coordinated international research has also been conducted, providing extensive datasets and sampling records87.

Stomach content dataset
Observations of PPMR were taken from the Dapstom stomach content database79. We utilise a total of 313,953 individual observations from 53,444 individual stomachs of 88 unique predator species. These observations were made on 1,862 different research hauls across the Northeast Atlantic (44°N to 79.5°N and 28.5 E° to 41.9°W) from 1981 to 2016. Predators were always identified to species level, with prey identified to the highest possible taxonomic level, i.e., species where possible, but often to family level. All prey species were considered (i.e., both fish and invertebrates). Fullness of stomach or level of digestibility were not considered, and so the estimates of body mass PPMR may be subject to some associated uncertainty. Additional variables taken from the database included the prey abundance per predator stomach (prey count), the geographical coordinates, and the year and month each sample was collected. These variables were included in the study as any change in PPMR can be driven by multiple and not mutually exclusive processes, e.g., changes in predator body size, prey body size, predator behaviour to select different-sized prey, or the behaviour of prey to avoid predation based on their body size.

Biomass-weighted PPMR was calculated for each individual predator using the following equation (1)60:

PPMR = Mi / (1/n * sum(Mj))

where Mi is the body mass of predator species i, Mj is the body mass of prey taxon j, and n is the total abundance of prey in the stomach. Wet weight (g) was defined as body mass.

Sea surface temperature dataset
Daily sea surface temperature (SST) data (°C) from both satellite and in situ observations were extracted from the Copernicus open access data repository80–82. Throughout the rest of the study, SST is simply referred to as temperature. The spatial resolution of the temperature data was 0.05° longitude x 0.05° latitude and covered every month from 1981 to 2016. The average temperature (°C) was calculated per month and matched to PPMR data sampled in the following month to account for any lag effects (i.e., if a predator’s stomach contents were sampled in May 1992, then the corresponding temperature would be the monthly average of April 1992). Other environmental variables used for modelling purposes included salinity, chlorophyll (ug/l), and the average water column depth (m), which were taken from the ICES open-source data portal (ICES Data Portal, Dataset on Ocean Hydro-Chemistry, Extracted June 12, 2023. ICES, Copenhagen). These ecologically relevant variables were included as they could cause background variation in PPMR. The mean of each environmental variable was calculated for each month of every year (1981–2016) and matched to the following month of PPMR data. The longitude and latitude coordinates were to four decimal points. Due to spatio-temporal limitations in the environmental data layers available, 43% of PPMR observations did not have corresponding salinity or chlorophyll data.

Commercial fishing effort dataset
We make use of the Scientific, Technical and Economic Committee for Fisheries (STECF) trawling effort dataset, available from the JRC Data catalogue, because of its extensive coverage in space and time, which corresponded with our PPMR observations (STECF, 2017). The STECF data provides annual fishing hours per ICES rectangle (0.5° latitude by 1° longitude) across areas of the Northeast Atlantic. We downloaded the data for the region 49.25°N to 63.25°N and 7.5°W to 12.5°E, covering the period 2002 to 2022. The data is a compilation of member state submissions in response to the Data Collection Framework (DCF) Fishing Effort Regimes Data Call in 201783. The STECF dataset used in this study included data from Belgium, Denmark, the Netherlands, the United Kingdom, France, Germany, and Sweden. Fishing effort was matched to the PPMR observations based on the year and the ICES rectangle in which the sampling took place. This resulted in 131,767 PPMR observations in the Northeast Atlantic from 2002–2016 with a corresponding measure of fishing effort in hours per year (Fig. 1c). For visualisation purposes, the fishing effort data were divided into three bins, each containing an equal number of observations, and the median of each bin was calculated for fitting regression lines to plots. An overview of the data construction can be found in Fig. S2.

Statistical analysis
All statistical analyses were conducted using R v4.2.288. A mixed effects model was used to test the relationship between temperature and either PPMR, predator body mass (g), prey body mass (g), prey abundance per predator stomach (prey count), or prey species richness per predator stomach. The response variables were log10 transformed to meet the assumptions of normality, homogeneity, and independence of residuals (Fig. S3). The model included the fixed effect of mean temperature (°C, continuous variable) and random effects for chlorophyll (ug/l, continuous), salinity (‰, continuous), depth (m, continuous), number of years since the start of the study period (continuous), ICES rectangle (categorical), season (categorical), predator species identity (categorical), and predator stomach identity (categorical).

The same five response variables (PPMR, predator body mass, prey body mass, prey count, and prey species richness) were then separately included in models containing main and interactive effects of mean temperature (°C, continuous variable) and mean commercial fishing effort (hours per year, continuous variable) for the subset of data that included information on fishing effort. The response variables were again log10 transformed to meet the assumptions of normality, homogeneity, and independence of residuals (Fig. S4). The random effect structure remained the same as above. For all models, linear and polynomial versions were compared using Akaike’s Information Criterion (AIC), with the linear models found to be the best fit in seven out of ten comparisons (Table S3).

Lastly, nMDS ordination plots were constructed for both the full temperature dataset and the fishing effort data subset. Prey were aggregated into families for consistency and to help with model convergence, and plotted against mean temperature, prey body mass, and fishing effort vectors.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "I have very much enjoyed reading the manuscript addressing how the interaction between gradients in temperature and intensive fishery affect the predator-prey body-mass ratios of fish predators. The question targeted is highly relevant and considers the interplay between various anthropogenic stressors. The manuscript is well written and the methodological and statistical procedures are presented with all detail necessary to understand or replicate the study. Most of my initial points, after giving the manuscript a quick read, such as effects of spatial autocorrelation and non-linearity in the relationships have been covered in the method section. I was highly impressed with the rigor how this analysis has been carried out. Therefore, I have only very few points, and I hope that they are helpful.\n\nP1: The study is based on a space for time substitution. The temperature gradient arises from large natural variability in temperature due to latitude, depth, and seasonality (line 49). I would encourage the authors to also test for the effects of the underlying variables (latitude, depth, seasonality). This not meant to replace the statistical tests in the main manuscript but it would be great to see the results as a supplement to understand which of these factors is the main underlying driver.\n\nP2: The authors have used mixed models with a variety of random effects. I was wondering why predator identity has not been used as a random effect. Of course, this can only be done for predators with sufficient replication across the temperature gradient but it would be important to show that these are effects of temperature not affected by any turnover in predator identity.\n\nP3: I like how the results are presented in the figures. Nevertheless, I would like to get a better feel for the quantitative effects. I would like to see some numbers on what is the predicted average change in PPMR on the temperature gradient between five and twenty degrees Celsius.\n\nP4: In Fig 1d, the interaction effect and the model predict that intensive fishery increases PPMR at high and decreases it at low temperatures. Is this reality or a model artefact? If this is a model artefact, a non-linear model might do a better job despite not being favored by AIC selection.\n\nA minor point: line 103: I would not call a change in body mass a physiological effect.\n\nI hope that these points are useful. As always, I have signed my review and I am happy to discuss these points if anything should be unclear.\n\nSigned\nUlrich Brose", "reviewer_2": "The authors leverage an outstanding dataset, probably the most extensive of its kind globally, to investigate a key parameter of size-spectrum models: predator-prey mass ratios. This comprehensive data encompasses both temperature and fishing-pressure gradients, allowing for two potential drivers of fish body size variation in the region to be assessed.\n\nKey results include:\nThere is a significant increase in PPMR with increasing temperature (regardless of fishing pressure).\nThe authors next state that there is an interaction effect between temperature and fishing pressure which amplifies the increase in PPMR with temperature.\nThe mean size of predators was not related to temperature (regardless of fishing pressure).\nTemperature was significantly related to the mean prey size, and interrelated variables: prey count and prey species richness.\n\nThe above findings are based on mixed effects models of five response variables (i) log10(PPMR), (ii) predator body mass (g), (iii) prey body mass (g), (iv) prey abundance per predator stomach (prey count), and (v) prey species richness per predator stomach. The predictor variables included: (1) fixed effect of mean temperature (°C), random slopes of (2) chlorophyll, (3) salinity, (4) depth, along with random intercepts of (5) stomach contents data source, (6) year since start of study period, (7) ICES rectangle, (8) predator species identity. These response variables were then re-tested in a model that included the interaction between temperature and commercial fishing effort. The authors state that polynomial and linear models were compared using AIC, and that linear models consistently outperformed polynomial alternatives.\n\nWhile the authors use the well-established approach of linear mixed effects to study the space-for-time patterns of the above variables, there are a few areas that the authors could improve. Mostly these are related to demonstrating the validity of their results and careful interpretation.\n\nThe dataset they draw on is publicly available, but the code used for analyses to derive the results was not, this would be beneficial for others and would help with repeatability, transparency, interpretation, and for testing the generality of their results. Also which R package was used for these analyses?\n\nGreater clarity of the data and statistical model structure - is each data point an individual predator-prey link? It is not always clear if the authors are referring to the mean individual across all species sampled or the species - often the term “individual species” is used, which is confusing and misleading given the random effect of species in the model. The flowchart in the supplement is helpful but would be improved with these additional details. Also, it should be explained in the methods what the later shown statistics are being used to test for. For example, Table S1 is provided to show that predator and prey body sizes do not significantly change with temperature - at the species level, again the nesting in the different tests is not fully clear and should be explicit. Table S1 seems to show predator species not prey as specified in the caption and text. In a size-based view of the world, predators are also prey depending on body size.\n\nPredictor variables: Was fullness of stomach considered or level of digestibility? (level of digestibility can make prey sizes inaccurate). Were the prey types considered only fish ( as is often the case) or all measured prey (e.g. invertebrates)?\n\nThe spatial pattern of high, medium, and low categories of fishing effort used for visualisation (Figure 1) seems almost random - how were these different levels of effort determined (were they based on quantiles or a cluster analysis or just arbitrarily chosen?).\n\nIt would be helpful to show the residual/diagnostic plots of the model in the supplement. The model predictions shown in Figure 3b at low temperatures and high fishing don’t really have any data points, and this is the pattern that drives the interaction term. Appreciate that polynomials were tested, how was model selection carried out? Seeing diagnostics for the mixed effects models would help (e.g. recommendations here: https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12577).\n\nAlso, please show results in supplement to support this statement: “For all models, linear and polynomial versions were compared using Akaike’s Information Criterion (AIC), but the linear models were consistently found to be the best fit and thus are presented here.”\n\nOverall, while the paper is well-presented, with potentially wide-reaching findings, I find it difficult to assess the validity of these findings in the present version, and therefore whether commercial fishing is really amplifying the PPMR - temperature relationship, without these further details.\n\nMore specific comments\nLine 15 - 17\nThe abstract is very well written, excepting this one line where it is unclear whether the same species are found at warm and colder waters, or whether the sentence is referring to different species. The last part of the sentence would be fine if the first bit of the sentence was clear.\n\nLine 33\nI would avoid starting sentences with ‘their’ as it is an ambiguous word, ‘trophic’ could be a better word in this case.\n\nLine 34\nThe use of “lower risk”. I think know what you mean, but this is very vague. I am not sure it would be clear to others, perhaps ‘lower risk of injury or wasted energy’.\n\nLine 40\n“Super trait”. Master is often used, but I wonder if you are choosing ‘super’ to avoid the use of ‘master’, which is up to you.\n\nLine 42\nNot sure ‘moreover’ is appropriate here (given the sentences leading up to it).\n\nLine 50\nThis is where ‘moreover’ would be appropriate as it is sort of piling more onto the previous sentences. “However” would be appropriate if the previous sentences were contradictory, which they are not.\n\nLine 51\n“natural thermal ranges” of what? Please specify what the natural thermal ranges are of, otherwise it is vague.\n\nLine 56 - 57\n1) Not solely, it can also be brought about by species redistributions,\nsee Cheung et al., 2013 and others,\nand possibly through trophic guild-temperature trends, see\nCoghlan AR, Blanchard JL, Wotherspoon S, Stuart‐Smith RD, Edgar GJ, Barrett N, Audzijonyte A. Mean reef fish body size decreases towards warmer waters. Ecology Letters. 2024 Feb;27(2):e14375.\n2) The TSR is only one mechanism by which ‘shrinking’ body sizes might be brought about, the way this is written it appears to be the sole reason, which is not the case. Moreover the evidence for the TSR is currently contradictory due to discrepancies in study methodology:\nhttps://www.authorea.com/doi/full/10.22541/au.171813253.384000\n3) Mortality could also be a driver, not just changes in growth\nA solution could be to mention these other potential drivers: e.g. “due to ecological drivers such as changes in species or trophic guild composition, or physiological drivers such as changes in asymptotic body sizes”\n\nLine 62\nI do not think that higher temperatures “favour” smaller species, it is a consequence of temperature. Perhaps: “similar to the observed impacts of increasing temperatures, fishing also results in an increase in the relative abundance of smaller-bodied fish, as commercial fishing….etc”. But perhaps in a more concise way.\n\nLine 77 - 79\nThis sentence is quite convoluted, I wonder if it could be made more clear and concise.\n\nLine 98\nThis sentence is unclear: you need to state “increasing” or “decreasing” before the thing changing, perhaps reword the sentence to describe the relationship as either positive or negative, whichever suits.\n\nLine 108 - 109\nI think this is unlikely to be used in short forecasts - I think the term projection is more appropriate here, e.g. referring to modelling work that supports EBFM and uses PPMR in parameterisation.\n\nLine 113 - 120\nThis section was very clear and nicely explained, good job.\n\nLine 133 - 134\nBefore or after accounting for fishing effects? Please clarify here\n\nLine 134\n“Predator body mass”: Is this the mean or maximum? I am assuming mean, but please restate that. I assume this is without accounting for differences in fishing pressure along the temperature gradient, even if it is equal along the gradient just say “after accounting for fishing pressure”\n\nLine 139\nIt is unclear to me how predator and prey species were defined and whether there was overlap, so this is difficult to interpret.\n\nLine 143\nI would not put “physiological responses” here, there could be other mechanisms at play. No need to draw conclusions, just say “intraspecific responses” then if you want to discuss physiological mechanisms bring that explanation into the discussion.\n\nLine 146\nBefore or after or without accounting for fishing pressure?\n\nLine 177-178\nThis result is why it would be helpful to clarify ‘before accounting for fishing pressure’ in the above. Is there a relationship between fishing pressure and temperature across your sites? If not this would be helpful to know.\n\nLine 196\nFigure 3: If you made the geom_points slightly more transparent, or the lines layered on top of them a slightly darker shade of their current colours, it may be easier to see the lines. As it is the ‘large prey size’ at ‘low fishing’ in ‘panel C’ is very hard to see.\nMoreover, it is confusing that you use a solid line to represent the small prey size class in panel C, when you use a solid line elsewhere to represent other things. Perhaps use a dotted line instead for panel C. Keep using the solid lines as you do in the other plots (where they do not specifically relate to small prey).\nPanel d: was commercial fishing only analysed as a continuous variable for this one test and elsewhere it was categorical?\nYou also only indicate low and high in the figure, but in the caption describe a ‘medium’ level?\nI find the part where you describe the trendlines confusing, especially as it comes before describing panel e, perhaps describe this where you describe each panel.\nPanel e: you have “prey weight class” and “prey body mass” both on this figure. How are they different? Is one species-based? Is one the binned version of the other?\n\nLine 221\nInstead of just “climate change” can you be more specific and say “increased water temperature”?\n\nLine 226\nYou don’t present time series data though, so rather than saying your study provides “information on the historical variation” you might better say your study provides “potential insights into past variation”\n\nLine 228-229\n“, given the long timescales over which ecosystems have been exposed to these conditions .” I am not sure what this means and you do not need it.\n\nLine 231\nInstead of “wholesale” perhaps use “overall”?\n\nLine 236\nPossibly “increase” instead of “increased”\n\nLine 239 -242\nThis is the Temperature Size Rule (TSR) for which there is contradictory evidence.\n\nLine 242-244\nI would not say “more easily” carte blanche. Arguably, larger individuals thermoregulate more easily in cooler conditions, and less easily in warmer conditions – so how easily thermoregulation occurs for a given body size depends on the conditions and this is key. This is stated throughout the cited paper. You could say, “Furthermore, when close to the upper limits of their thermal ranges, smaller individuals thermoregulate more efficiently than larger individuals as they are better able to lose excess heat due to their larger SA:V (citation). This has led to many authors predicting a general decrease in the body sizes of ectotherms with climate-driven warming (citation)”.\n\nLine 249\nThe relationship between PPMR and size-spectrum slopes also varies with temperature and may be driven by compositional and structural shifts within ecosystems with temperature. No need to cite, but this may be of interest:\nCommunity size structure varies with predator–prey size relationships and temperature across Australian reefs. Coghlan et al. (2022) Ecology and Evolution, Volume 12, Issue 4 e8789.\n\nLine 253\n“the distribution of small and large taxa was still similar” in trying to interpret this sentence I am wondering if the mean size of prey items remained the same as a result. If this is so, it would be good to add here, if not, this is also valuable information.\n\nLine 251\n“. In other words, while the taxonomic composition of prey may have changed from colder to warmer waters, the distribution of small and large taxa was still similar. The sampled predators did respond to the community-wide intraspecific decrease in prey body mass at higher temperatures and fishing effort by selecting the largest individuals available to them”\nThese sentences seem contradictory. What specifically do you mean by ‘distribution,’ is this a size distribution? Does the prey minimum and maximum size range change? It may be valuable to describe how the mean size changed without the size distribution changing.\nMy current understanding from this sentence is that the taxonomic composition changed, the size distribution remained the same, yet the mean size decreased.\nI think this needs to be laid out more clearly for the reader.\n\nLine 257\nWhat do you mean by “increased importance” specifically? Do you mean “increased proportion”? “Importance” is vague. I feel like this paper would benefit from a conceptual diagram showing what is happening in terms of prey availability in the environment, versus what is happening in the diet. There is a lot going on with changing prey size, taxonomic composition, size distributions, and what is being observed in a generalised predator’s diet. It is a really challenging result to summarise, I do not envy the task! But it is very valuable work and when presented more clearly will be a very valuable paper in the field. Being very clear and precise in the language used and the results described, even to the point of repetition, will really help make these results accessible to readers. Referring to figures when describing the results will also be very useful and I am surprised this was not done in this section. Even if some figures are supplementary, they will no doubt help with clarity and should be referred to.\n\nLine 266\n“Driver” instead of “force”? Optional\n\nLine 269 - 271\n“which underpinned the increase in PPMR in areas of high commercial fishing” before or after accounting for changes in temperature?\n\nLine 289\nPrey species or prey individuals? This needs to be clarified in every sentence involving the word prey as you could be referring to one or the other, you discuss both in the paper. Here it isn’t clear which\n\nLine 289\n“regardless of temperature...” this is a confusing sentence, so helps to reiterate, if this is indeed what you mean\n\nLine 290-291\nI am not sure what this sentence means, or how it would cause larger prey body sizes. Please elaborate or remove. Perhaps lead with the following hypothesis as that seems to have a bit more solidity (you cite and explain it better). What do you mean by “catch well”?\n\nLine 291 - 295\nI think what this (“top down”) means is “the selective removal of the largest individuals in the community may release large prey individuals from the risk of predation, should they outgrow the gape-limitations of their predators [Mixhitalis or someone], or become more costly to catch (larger fish have faster swim speeds [cite] and are more likely to escape predators [cite]).” I think you could afford to elaborate a little more here.\nIf you mean some other form of top-down control, I think that could also be explained. This is if you are talking about individuals not species, which has not been clarified. If species, you need to elaborate why/how you think top-down control could be manifesting, rather than vaguely refer to it.\n\nLine 293\n“The latter” is ambiguous. If you mean “top-down control” please just repeat this, it really helps with clarity.\n\nLine 296\n“community-wide reduction in individual prey body mass” Is this the mean or maximum prey body mass? Please be specific.\n\nLine 298\nAbove you say that there was “reduced predation on larger prey species” here you say there is increased predation on them? I suspect I am missing something, which may sbe due to this paragraph being a little unclear.\n\nLine 302\n“with no change in body mass across the temperature gradient” even after accounting for changes in fishing pressure? Or with no change in “temperature or fishing pressure”? It’s important to know what the other variable is doing because you mention that there is an interaction.\n\nLines 302 - 305:\nWhat does this mean? Please explain the sampling bias.\nCould it be due to, specifically, the trawls “allowing individuals of the largest body size to escape” or something? What do you mean by “no control on the prey composition included”, perhaps, “some prey are more likely to escape the trawl, such as [some fish] which burrow into the sand at the trawls approach. Should [these species] comprise more of the prey in certain areas, we would miss [this component] in our sampling. However, previous [BRUV or something] surveys have shown the abundance of [these prey] is the same throughout our sampling region, so we don’t think this potential bias is likely to impact our findings…” or something. I do not imagine this is actually a bias you faced as I am unfamiliar with your ecosystem, but hopefully you can see how the potential bias is described and then combated. This can be brief but you do need to elaborate on it.\nAlternatively, perhaps you mean: “this could be a consequence of the selective removal of [species] from this part of the region where they are commercially valuable (being not targeted elsewhere). Should these species be larger in this area, [the trend we observed] may be masked by the impacts of fishing.”\nOr “we expect [the species] targeted by fishing to be more abundant/larger in the heavily fished areas, so it is possible that a compensatory effect is occurring, masking the impact of temperature”. Or something along those lines.\n\nLine 305 -\nAbove you say there was no change, I believe you mean, “regardless of fishing pressure there was no change with temperature” up there, I’ll make a note, but this needs to be clarified each time. You know this data back-to-front and it is a great analysis on an amazing dataset, but it has the potential to be very confusing for the reader if things are not reiterated and clarified. Some of these things are: whether you controlled for (or ignoring) one factor or another (e.g. temperature or fisheries”, whether you are talking about prey species or individuals, and reiterating you are talking about the community [mean] body size or the species [max] body size, etc. where appropriate.\n\nLine 307-309 -\nHere you clarify that there is an interaction effect. Perhaps state this as the first sentence above. “Due to the interaction effect between fishing and temperature, we cannot interpret the effects of temperature on the body size etc without accounting for shifts in fishing pressure.” Be super clear from the go.\n\nLine 309-312 -\n“The original hypothesis whereby PPMR would increase in the Northeast Atlantic due to increased temperature was only substantiated by a decrease in prey body mass, not predator body mass as anticipated”.\nThis is a key result. I feel like this could be stated earlier and have its own paragraph.\n\nLine 312 - An alternative, perhaps more clear way to say this:\nHowever, there was an interaction effect between pred body size and fisheries impact, such that when fisheries was included we did see the anticipated reduction in pred body mass with temperature”\n\nLine 314-316 - This sentence sort of comes out of no-where and could be better off in the conclusion.\n\nLine 317 - 319 - Change “An increase” to “Increasing” and “can be associated” to “is” and the language becomes more active, plus you save words\n\nLine 319-320 - I found this sentence very confusing, what is “absolute trophic energy”? Do you mean fewer steps in the food chain, thus less energy lost through “trophic transfer inefficiencies”?\n\nLine 320-322 - Elaborate, i.e., flexible foraging or generalised predation can prevent the over-dominance or over-predation of particular prey species under different environmental conditions, leading to imbalances in ecosystem structuring.\n\nLine 322 - As you are expanding on the above sentence, do not use “furthermore” as it suggests to the reader that you are introducing a new, additional point.\n\nLine 324 - This is essentially what I suggested you write two comments above, but with more jargon. It is along the lines of what I suggested, but you introduce “secondary extinctions” and then do not going into it, so perhaps remove that and keep it simple. Also try to keep relevant sentences together in the paragraph to avoid jumping around.\n\nLine 331 - What does this mean? Lower energy efficiency causes weak interactions? Are you referring to trophic transfer efficiency? Because that is an artifact of weak interactions and not a cause. Perhaps you mean “Given energetic variation in prey, generalised predation may lead to predators selectively targeting larger individuals (of any prey species) in order to ensure energetic requirements are met per feeding attempt”\n\nLine 335 - 337 - This sentence is unexpected, I am not sure whether this paragraph is discussing trophic transfer efficiency, or optimal foraging, because it seems to do a bit of both. Perhaps separate paragraphs for those two topics?\n\nLine 339 -I would not say that it constrains, rather predicts\n\nLine 339 It can also be used to estimate the community size spectra\nhttps://onlinelibrary.wiley.com/doi/full/10.1002/ece3.8789", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "*** Note that original reviewers’ comments are in bold. Our responses are numbered\nsequentially, written in plain font, and contain quotations to the revised text in italics with line\nnumbers corresponding to the revised version of the manuscript ***\nReviewer #1 (Remarks to the Author):\nI have very much enjoyed reading the manuscript addressing how the interaction\nbetween gradients in temperature and intensive fishery affect the predator-prey body-\nmass ratios of fish predators. The question targeted is highly relevant and considers the\ninterplay between various anthropogenic stressors. The manuscript is well written and\nthe methodological and statistical procedures are presented with all detail necessary to\nunderstand or replicate the study. Most of my initial points, after giving the manuscript\na quick read, such as effects of spatial autocorrelation and non-linearity in the\nrelationships have been covered in the method section. I was highly impressed with the\nrigor how this analysis has been carried out. Therefore, I have only very few points, and\nI hope that they are helpful.\nResponse #1: Thank you for the kind words and positive overall impression of our manuscript.\nWe appreciate the constructive feedback you have given us below and hope we have\nsatisfactorily addressed all of your points.\nP1: The study is based on a space for time substitution. The temperature gradient arises\nfrom large natural variability in temperature due to latitude, depth, and seasonality (line\n49). I would encourage the authors to also test for the effects of the underlying variables\n(latitude, depth, seasonality). This not meant to replace the statistical tests in the main\nmanuscript but it would be great to see the results as a supplement to understand which\nof these factors is the main underlying driver.\nResponse #2: Thank you for this excellent suggestion. We now include plots of PPMR as a\nfunction of latitude, season, and depth in our new Figure S1 and we note in the main results\nthat latitude is the major contributor to the temperature effect on PPMR.\nLn109: “Latitude was a major contributor to the effect of temperature on PPMR, with less\ncontribution of season and water column depth (Fig. S1).”\n(PPMR). (a) There was a significant increase in log PPMR with increasing latitude (t =\n10 260508\n27.83, p < 0.001, R2 = 0.73). (b) There was no significant effect of season on log PPMR\n10\n(F = 1.88, p = 0.171). (c) There was no significant effect of depth on log10 PPMR (t\n3,50433 64886\n= 0.92, p = 0.361).\nP2: The authors have used mixed models with a variety of random effects. I was\nwondering why predator identity has not been used as a random effect. Of course, this\ncan only be done for predators with sufficient replication across the temperature gradient\nbut it would be important to show that these are effects of temperature not affected by\nany turnover in predator identity.\nResponse #3: There is good replication for all the predator species included in the analysis and\nso we actually did use predator species identity as a random effect in our mixed effects models.\nWe made the oversight of omitting stomach identity (i.e. the identity of individual predators)\nfrom the random effects structure though, so have now updated this in the revised manuscript.\nWe think this helps to account for the non-independence of multiple prey sizes in the stomach\ncontents of each individual predator.\nLn435: “The model included the fixed effect of mean temperature (°C, continuous variable)\nand random effects for chlorophyll (ug/l, continuous), salinity (‰, continuous), depth (m,\ncontinuous), number of years since the start of the study period (continuous), ICES rectangle\n(categorical), season (categorical), predator species identity (categorical), and predator\nstomach identity (categorical).”\nP3: I like how the results are presented in the figures. Nevertheless, I would like to get a\nbetter feel for the quantitative effects. I would like to see some numbers on what is the\npredicted average change in PPMR on the temperature gradient between five and twenty\ndegrees Celsius.\nResponse #4: This is a great suggestion thank you. The predicted mean increase in PPMR\nacross the temperature gradient without accounting for commercial fishing was 30 %, but it\nwas 22 % in areas of low commercial fishing and 82 % in areas of high commercial fishing.\nWe added this information to the revised manuscript.\nLn107: “PPMR was predicted to increase by 30 % across the temperature gradient, or 1.8 %\nper 1 °C.”\nLn115: “In areas of low commercial fishing, PPMR was predicted to increase by 22 % across\nthe temperature gradient, or 1.3 % per 1 °C, whereas in areas of high commercial fishing,\nPPMR was predicted to increase by 82 % across the temperature gradient, or 4.8 % per 1 °C.”\nP4: In Fig 1d, the interaction effect and the model predict that intensive fishery increases\nPPMR at high and decreases it at low temperatures. Is this reality or a model artefact? If\nthis is a model artefact, a non-linear model might do a better job despite not being favored\nby AIC selection.\nResponse #5: We actually did test for non-linearity in all our models, using AIC to compare\nbetween a linear or polynomial fitting. After updating our models to include a random effect\nfor predator stomach identity, we find that the linear model was the better fit in 7 of 10 cases\n(including the key interactive effect of temperature and commercial fishing on PPMR). We\nnow include a table of AIC comparisons in the supporting information.\noptimal model (AIC value > 2 units lower) is highlighted in bold in each case.\nModel Response variable Linear Polynomial\nPPMR ~ temperature PPMR 254903.3 255022.9\nPredator mass 5301.242 5308.293\nPrey mass 143835.6 143831.4\nPrey count 114131.7 468990.4\nPrey richness -85829.94 -86088.3\nPPMR ~ temperature × fishing effort PPMR 246904.1 246939.1\nPredator mass 10427.64 29361.44\nPrey mass 137925.1 137996.6\nPrey count 113464.7 468703.9\nPrey richness -80542.45 -80906.26\nA minor point: line 103: I would not call a change in body mass a physiological effect.\nResponse #6: We have updated the phrasing to indicate that the physiological process\nunderpinning a change in body mass might be altered metabolic rate.\nLn95: “…increases in PPMR are related to both physiological processes (e.g. altered\nmetabolic rate, which may underpin changes in body mass) and compositional processes\n(changes in taxonomic composition).”\nI hope that these points are useful. As always, I have signed my review and I am happy\nto discuss these points if anything should be unclear. Signed Ulrich Brose\nResponse #7: Again, many thanks for your constructive review and taking the time to read over\nour work.\nReviewer #2 (Remarks to the Author):\nThe authors leverage an outstanding dataset, probably the most extensive of its kind\nglobally, to investigate a key parameter of size-spectrum models: predator-prey mass\nratios. This comprehensive data encompasses both temperature and fishing-pressure\ngradients, allowing for two potential drivers of fish body size variation in the region to be\nassessed. Key results include: There is a significant increase in PPMR with increasing\ntemperature (regardless of fishing pressure). The authors next state that there is an\ninteraction effect between temperature and fishing pressure which amplifies the increase\nin PPMR with temperature. The mean size of predators was not related to temperature\n(regardless of fishing pressure). Temperature was significantly related to the mean prey\nsize, and interrelated variables: prey count and prey species richness. The above findings\nare based on mixed effects models of five response variables (i) log10(PPMR), (ii)\npredator body mass (g), (iii) prey body mass (g), (iv) prey abundance per predator\nstomach (prey count), and (v) prey species richness per predator stomach. The predictor\nvariables included: (1) fixed effect of mean temperature (C), random slopes of (2)\nchlorophyll, (3) salinity, (4) depth, along with random intercepts of (5) stomach contents\ndata source, (6) year since start of study period, (7) ICES rectangle, (8) predator species\n3\nidentity. These response variables were then re-tested in a model that included the\ninteraction between temperature and commercial fishing effort. The authors state that\npolynomial and linear models were compared using AIC, and that linear models\nconsistently outperformed polynomial alternatives. While the authors use the well-\nestablished approach of linear mixed effects to study the space-for-time patterns of the\nabove variables, there are a few areas that the authors could improve. Mostly these are\nrelated to demonstrating the validity of their results and careful interpretation.\nResponse #8: Thank you for the comprehensive summary of our key findings and the\ntremendous care and attention with which you have reviewed our paper. We appreciate all the\nhelpful comments and suggestions, which we have taken on board in our revision. Please see\nour detailed responses to each point below.\nThe dataset they draw on is publicly available, but the code used for analyses to derive\nthe results was not, this would be beneficial for others and would help with repeatability,\ntransparency, interpretation, and for testing the generality of their results. Also which R\npackage was used for these analyses?\nResponse #9: We wholeheartedly agree, and it was our attention to upload all R code and\nassociated datasets to the publicly available University of Essex Research Data Repository\nupon acceptance of the article, as we have done with all our recent publications. We have made\nthem available as supplementary files for review if it is helpful to see them sooner. It should\nbe noted that some models require high computing power due to the size of the dataset.\nGreater clarity of the data and statistical model structure - is each data point an\nindividual predator-prey link? It is not always clear if the authors are referring to the\nmean individual across all species sampled or the species - often the term “individual\nspecies” is used, which is confusing and misleading given the random effect of species in\nthe model. The flowchart in the supplement is helpful but would be improved with these\nadditional details. Also, it should be explained in the methods what the later shown\nstatistics are being used to test for. For example, Table S1 is provided to show that\npredator and prey body sizes do not significantly change with temperature - at the species\nlevel, again the nesting in the different tests is not fully clear and should be explicit. Table\nS1 seems to show predator species not prey as specified in the caption and text. In a size-\nbased view of the world, predators are also prey depending on body size.\nResponse #10: Every data point is an observation of prey size in the diet of a predator, meaning\nthat there can be multiple PPMR values for each predator if it contains multiple prey individuals\nin its diet. We now note this in the flowchart (now Figure S2). We have also updated our models\nto include a random effect for predator stomach identity on the advice of Reviewer #1 (see\nResponse #3), which did not result in any major changes to the patterns described in the original\nmanuscript. Table S1 did actually contain temperature-size responses for both predator and\nprey, with the heading for prey found further down the table. To avoid confusion, we have now\nsplit this into two tables: one for predators and one for prey. We also now more clearly define\nwhat we mean by predators and prey at the first relevant point in the results.\nLn140: “Note that we refer to “prey” here as any organism found in the diet of the fish\npredators, even if those species could be predators themselves.”\ndigestibility can make prey sizes inaccurate). Were the prey types considered only fish (\nas is often the case) or all measured prey (e.g. invertebrates)?\nResponse #11: All prey types were measured, but fullness of stomach or digestibility were not\nconsidered in the database. We have added a comment on these points to the methods.\nLn377: “All prey species were considered (i.e. both fish and invertebrates). Fullness of stomach\nor level of digestibility were not considered and so the estimates of body mass may be subject\nto some associated uncertainty.”\nThe spatial pattern of high, medium, and low categories of fishing effort used for\nvisualisation (Figure 1) seems almost random - how were these different levels of effort\ndetermined (were they based on quantiles or a cluster analysis or just arbitrarily\nchosen?).\nResponse #12: The fishing effort data are not normally distributed and so dividing them into\nthree evenly sized bins would have led to a bias in the number of observations in each category.\nAccordingly, the fishing data was divided into three categories with an equal number of\nobservations in each bin and then a median value of fishing effort was calculated from each\nbin. We have added an explanation into the methods.\nLn424: “For visualisation purposes, the fishing effort data was divided into three bins each\ncontaining an equal number of observations, and the median of each bin was calculated for\nfitting regression lines to plots.”\nIt would be helpful to show the residual/diagnostic plots of the model in the supplement.\nThe model predictions shown in Figure 3b at low temperatures and high fishing don’t\nreally have any data points, and this is the pattern that drives the interaction term.\nAppreciate that polynomials were tested, how was model selection carried out? Seeing\ndiagnostics for the mixed effects models would help (e.g. recommendations here:\nhttps://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12577).\nResponse #13: We have added diagnostic plots for the two main models (our new Figures S3\nand S4) to show that they conform to the assumptions of normality, homogeneity, and\nindependence of residuals, with no obvious patterns observed against any of the covariates (see\nexample from Figure S3 below). We feel it may be overkill to add diagnostic plots for every\nmodel (an additional eight supporting figures with ten panels each, which may overwhelm\nreaders), but we are happy to include these if the editor recommends it.\nresiduals, (b) scatterplot of fitted vs residual values, and (c-k) scatterplots of residuals vs each\ncovariate in the model.\nAlso, please show results in supplement to support this statement: “For all models, linear\nand polynomial versions were compared using Akaike’s Information Criterion (AIC), but\nthe linear models were consistently found to be the best fit and thus are presented here.”\nResponse #14: We have included a new Table S3 containing AIC comparisons of all linear and\npolynomial models (see Response #5). After including predator stomach identity as a random\neffect, the polynomial model was a better fit in 3 out of 10 cases. We have included this fitting\nin all relevant figures and updated our results text accordingly. The overall story remains\nvirtually unchanged (though see Response #58 for one minor update).\nOverall, while the paper is well-presented, with potentially wide-reaching findings, I find\nit difficult to assess the validity of these findings in the present version, and therefore\nwhether commercial fishing is really amplifying the PPMR - temperature relationship,\nwithout these further details.\nResponse #15: We hope our changes in the revised manuscript have increased confidence in\nthe results that we present. Thank you for helping to increase the robustness of our study.\nMore specific comments\nLine 15 – 17. The abstract is very well written, excepting this one line where it is unclear\nwhether the same species are found at warm and colder waters, or whether the sentence\nis referring to different species. The last part of the sentence would be fine if the first bit\nof the sentence was clear.\nResponse #16: We have clarified that smaller prey size occurs both within and across species.\nLn15: “To compensate for smaller prey (both within and across species) in warmer waters and\nareas of high fishing…”\ncould be a better word in this case.\nResponse #17: Changed as suggested.\nLine 34. The use of “lower risk”. I think know what you mean, but this is very vague. I\nam not sure it would be clear to others, perhaps ‘lower risk of injury or wasted energy’.\nResponse #18: Changed as suggested.\nLine 40. “Super trait”. Master is often used, but I wonder if you are choosing ‘super’ to\navoid the use of ‘master’, which is up to you.\nResponse #19: Changed to “master”.\nLine 42. Not sure ‘moreover’ is appropriate here (given the sentences leading up to it).\nResponse #20: Changed to “for instance”.\nLine 50. This is where ‘moreover’ would be appropriate as it is sort of piling more onto\nthe previous sentences. “However” would be appropriate if the previous sentences were\ncontradictory, which they are not.\nResponse #21: Our logic was that the preceding sentence noted how marine ecosystems exhibit\nlarge natural variation in temperature regimes, but the rapid rate of climate change still pushes\nthem beyond this natural variability. We have joined the two sentences to make the link clearer\nand replaced “however” with “but”.\nLn41: “Marine ecosystems exhibit large natural variability in temperature due to latitude,\nseasonality, and depth, but climate change is causing relatively rapid increases in sea surface\ntemperatures (SST) beyond this natural variability21,22.”\nLine 51. “natural thermal ranges” of what? Please specify what the natural thermal\nranges are of, otherwise it is vague.\nResponse #22: Changed to “beyond this natural variability” and joined up with the previous\nsentence to make the connection to what we were talking about clearer (see Response #21).\nLine 56 – 57. 1) Not solely, it can also be brought about by species redistributions,\nsee Cheung et al., 2013 and others,\nand possibly through trophic guild-temperature trends,\nsee Coghlan AR, Blanchard JL, Wotherspoon S, Stuart‐Smith RD, Edgar GJ, Barrett N,\nAudzijonyte A. Mean reef fish body size decreases towards warmer waters. Ecology\nLetters. 2024 Feb;27(2):e14375.\nResponse #23: This is an excellent point and actually feeds into our later arguments that\nchanges in body size could be driven by either physiological or compositional mechanisms.\nWe now acknowledge that changes in community composition can also lead to a reduction in\nbody mass.\nLn48: “Decreasing body mass is recognised as a ubiquitous response to increasing\ntemperature, which can be due to physiological drivers such as increased metabolic demands\n7\nkeeping species smaller and the age at maturity lower7,29, or through changes in community\ncomposition that favour smaller species28,30.”\n2) The TSR is only one mechanism by which ‘shrinking’ body sizes might be brought\nabout, the way this is written it appears to be the sole reason, which is not the case.\nMoreover the evidence for the TSR is currently contradictory due to discrepancies in\nstudy methodology: https://www.authorea.com/doi/full/10.22541/au.171813253.384000\nResponse #24: We cannot access the link you recommended because the page cannot be found.\nWe don’t explicitly mention the TSR here or at any point in the manuscript though. Your\nsuggested change in the previous point (see Response #23) means that we now acknowledge\nmultiple mechanisms for shrinking body mass with increasing temperature, so we think there\nshould be no issue here.\n3) Mortality could also be a driver, not just changes in growth. A solution could be to\nmention these other potential drivers: e.g. “due to ecological drivers such as changes in\nspecies or trophic guild composition, or physiological drivers such as changes in\nasymptotic body sizes”\nResponse #25: We have integrated a version of this suggestion into the text (see Response #23).\nLine 62. I do not think that higher temperatures “favour” smaller species, it is a\nconsequence of temperature. Perhaps: “similar to the observed impacts of increasing\ntemperatures, fishing also results in an increase in the relative abundance of smaller-\nbodied fish, as commercial fishing….etc”. But perhaps in a more concise way.\nResponse #26: We have made the recommended change.\nLine 77 – 79. This sentence is quite convoluted, I wonder if it could be made more clear\nand concise.\nResponse #27: We have streamlined the first two sentences of this paragraph to improve clarity.\nLn71: “To improve our predictive capacity, it is important to first understand the historical\nvariation in PPMR across largescale gradients of temperature and commercial fishing\npressure.”\nLine 98. This sentence is unclear: you need to state “increasing” or “decreasing” before\nthe thing changing, perhaps reword the sentence to describe the relationship as either\npositive or negative, whichever suits.\nResponse #28: We don’t quite understand the confusion because the sentence already included\ndirectionality throughout, rather than referring to changes. Nevertheless, we have rephrased the\nbeginning as a negative relationship to hopefully make it clearer.\nLn89: “Given that PPMR has a negative relationship with body mass1,42,43, a reduction in the\nmean body size of the community at higher temperatures and/or commercial fishing pressure\nshould lead to an increase in PPMR since smaller predators consume relatively smaller prey.”\nLine 108 – 109. I think this is unlikely to be used in short forecasts - I think the term\nprojection is more appropriate here, e.g. referring to modelling work that supports\nEBFM and uses PPMR in parameterisation.\nLine 113 – 120. This section was very clear and nicely explained, good job.\nResponse #30: Thank you!\nLine 133 – 134. Before or after accounting for fishing effects? Please clarify here\nResponse #31: We have relabelled the section as “Effects of only temperature on body mass,\nprey count, and prey richness”. We have also clarified at the end of the first sentence that these\nanalyses were performed “using the larger dataset without fishing effort data included”.\nLine 134. “Predator body mass”: Is this the mean or maximum? I am assuming mean,\nbut please restate that. I assume this is without accounting for differences in fishing\npressure along the temperature gradient, even if it is equal along the gradient just say\n“after accounting for fishing pressure”\nResponse #32: Done.\nLine 139. It is unclear to me how predator and prey species were defined and whether\nthere was overlap, so this is difficult to interpret.\nResponse #33: There was indeed overlap, so we have added a sentence to clarify (Ln140; see\nResponse #10).\nLine 143. I would not put “physiological responses” here, there could be other\nmechanisms at play. No need to draw conclusions, just say “intraspecific responses” then\nif you want to discuss physiological mechanisms bring that explanation into the\ndiscussion.\nResponse #34: Done.\nLine 146. Before or after or without accounting for fishing pressure?\nResponse #35: We have clarified that this analysis was done “using the larger dataset without\nfishing effort data included”.\nLine 177-178. This result is why it would be helpful to clarify ‘before accounting for\nfishing pressure’ in the above. Is there a relationship between fishing pressure and\ntemperature across your sites? If not this would be helpful to know.\nResponse #36: And we now do that, as recommended (see Responses #31 and #33).\nLine 196. Figure 3: If you made the geom_points slightly more transparent, or the lines\nlayered on top of them a slightly darker shade of their current colours, it may be easier\nto see the lines. As it is the ‘large prey size’ at ‘low fishing’ in ‘panel C’ is very hard to\nsee.\nResponse #37: We have made the suggested changes, please see the new Figure 3 below.\n10\npredator body mass (g), b, log prey body mass (g), c, log prey count (number of individuals\n10 10\nper stomach) and d, log species richness (number of species per stomach) in the Northeast\nvariable, but for the purposes of visualisation, low (45 – 566 hours per year), medium (576 –\n878 hours per year), and high (903 – 3,479 hours per year) levels of fishing effort are indicated\nin the figure. Trend lines based on the predicted values of the mixed effects model were plotted\nfor low (a: y = 1.6 + 0.026x; b: y = -1.1 + 0.0039x) and high commercial fishing (a: y = 1.8\n+ 0.0081x; b: y = 1.9 + 0.003x). The results of c, log prey count and d, log species richness\n10 10\nwere further categorised into prey weight classes by small (0-0.072 g); medium (0.072 – 1.25\ng) and large (1.25 – 2,137 g) prey body mass. (c: low fishing effort and small species: y = 2.5\n– 0.14x; high fishing effort and small species: y = -1.1 + 0.23x; low fishing effort and large\nspecies: y = 2.3 – 0.12x; high fishing effort and large species: y = -1.1 + 0.25x; d: low fishing\neffort and small species: y = 0.67 – 4.3×10-17x –0.00027x2; high fishing effort and small\nspecies: y = 0.59 – 3.5×10-17x + 0.0023x2; low fishing effort and large species: y = 0.69 –\n2.3×10-17x + 7×10-4x2; high fishing effort and large species: y = 0.63 – 5.8×10-17x + 0.0033x2).\ne, nMDS illustrating the weak effects of temperature and fishing effort on the size of prey taxa,\nwith temperature and body mass vectors orthogonal to one another and a weak correlation\nbetween body mass and commercial fishing effort (R2 = 0.04). The colour and size of the points\nrepresents the size classes of the prey taxa.\nMoreover, it is confusing that you use a solid line to represent the small prey size class in\npanel C, when you use a solid line elsewhere to represent other things. Perhaps use a\ndotted line instead for panel C. Keep using the solid lines as you do in the other plots\n(where they do not specifically relate to small prey).\nconfusing due to the number of data points behind the trend line. We also tried different types\nof dashed lines but found it to be similarly confusing. We believe that leaving a solid line is\nthe best option.\nPanel d: was commercial fishing only analysed as a continuous variable for this one test\nand elsewhere it was categorical? You also only indicate low and high in the figure, but\nin the caption describe a ‘medium’ level?\nResponse #39: Commercial fishing effort was always analysed as a continuous variable and\nwe simply use the categories of low, medium, and high effort as a tool to visualise the patterns.\nWe note this in the legend for Figures 1 and 3 (i.e. the same approach was also adopted for the\nanalysis of PPMR). We now also specify in the methods that commercial fishing effort was\ntreated as a continuous variable.\nLn440: “The same five response variables (PPMR, predator body mass, prey body mass, prey\ncount, and prey species richness) were then separately included in models containing main and\ninteractive effects of mean temperature (°C, continuous variable) and mean commercial fishing\neffort (hours per year, continuous variable) for the subset of data that included information on\nfishing effort.”\nI find the part where you describe the trendlines confusing, especially as it comes before\ndescribing panel e, perhaps describe this where you describe each panel.\nResponse #40: We tried moving the trendline information after each panel letter, but we felt it\nbecame even more confusing. We need to first explain that commercial fishing effort was\nvisualised at low, medium, and high levels, and that prey count and richness were further\ncategorised by small, medium, and large prey sizes before presenting the regression lines.\nPanel e: you have “prey weight class” and “prey body mass” both on this figure. How are\nthey different? Is one species-based? Is one the binned version of the other?\nResponse #41: Yes, prey weight class is a binned version of prey body mass, with the\nspecification of bin sizes noted in the figure caption. The prey weight classes were included in\nthe nMDS to visualise any potential groupings by prey weight within the data, but a continuous\nvector of body masses was fitted to test for the amount of variability in community composition\nexplained by prey body mass (very low in both Figures 2e and 3e).\nLine 221. Instead of just “climate change” can you be more specific and say “increased\nwater temperature”?\nResponse #42: Done.\nLine 226. You don’t present time series data though, so rather than saying your study\nprovides “information on the historical variation” you might better say your study\nprovides “potential insights into past variation”\nResponse #43: We made the suggested change.\nLine 228-229. “, given the long timescales over which ecosystems have been exposed to\nthese conditions .” I am not sure what this means and you do not need it.\nwarming experiment. Therefore, ecosystems have been chronically exposed to their given\ntemperature regimes for many decades (and thus generations) of their constituent organisms,\nwhich are likely to experience adaptation to those environmental conditions. We have clarified\nthis in the text.\nLn231: “…i.e. organisms may be thermally adapted after many generations at higher\ntemperatures, which is not possible to study in short-term experiments involving acute\ntemperature exposures.”\nLine 231. Instead of “wholesale” perhaps use “overall”?\nResponse #45: Done\nLine 236. Possibly “increase” instead of “increased”\nResponse #46: Changed\nLine 239 -242. This is the Temperature Size Rule (TSR) for which there is contradictory\nevidence.\nResponse #47: We acknowledge that there can be exceptions, referencing a recent paper by\nWootton et al. showing how warming does not have to elevate metabolism if there is sufficient\ntime for acclimation, and that reductions in body size can instead emerge from increased\ninvestment into reproduction.\nLn245: “…though note there are exceptions to this general rule52.”\nLine 242-244. I would not say “more easily” carte blanche. Arguably, larger individuals\nthermoregulate more easily in cooler conditions, and less easily in warmer conditions –\nso how easily thermoregulation occurs for a given body size depends on the conditions\nand this is key. This is stated throughout the cited paper. You could say,\n“Furthermore, when close to the upper limits of their thermal ranges, smaller individuals\nthermoregulate more efficiently than larger individuals as they are better able to lose\nexcess heat due to their larger SA:V (citation). This has led to many authors predicting a\ngeneral decrease in the body sizes of ectotherms with climate-driven warming (citation)”.\nResponse #48: We agree and really appreciate your description. We have included the first\nsentence above in the revised manuscript (Ln245).\nLine 249. The relationship between PPMR and size-spectrum slopes also varies with\ntemperature and may be driven by compositional and structural shifts within ecosystems\nwith temperature. No need to cite, but this may be of interest: Community size structure\nvaries with predator–prey size relationships and temperature across Australian reefs.\nCoghlan et al. (2022) Ecology and Evolution, Volume 12, Issue 4 e8789.\nResponse #49: We are familiar with this paper and now refer to the associated link between\nPPMR and size spectra at two points in the revised manuscript.\nLn330: “This highlights how temperature can interact with factors like PPMR and the\nassociated indirect changes to trophic interaction strengths to alter entire community size\nspectra77.”\ntrophic interactions, governs how energy flows through ecosystems1,2,13, can estimate\ncommunity size-spectrum77 and as a result, is a fundamental input into size-based models of\necosystem dynamics such as the Allometric Diet Breadth Model2,3.”\nLine 253. “the distribution of small and large taxa was still similar” in trying to interpret\nthis sentence I am wondering if the mean size of prey items remained the same as a result.\nIf this is so, it would be good to add here, if not, this is also valuable information.\nResponse #50: We address this comment in more detail in the next response.\nLine 251. “. In other words, while the taxonomic composition of prey may have changed\nfrom colder to warmer waters, the distribution of small and large taxa was still similar.\nThe sampled predators did respond to the community-wide intraspecific decrease in prey\nbody mass at higher temperatures and fishing effort by selecting the largest individuals\navailable to them”. These sentences seem contradictory. What specifically do you mean\nby ‘distribution,’ is this a size distribution? Does the prey minimum and maximum\nsize range change? It may be valuable to describe how the mean size changed without the\nsize distribution changing. My current understanding from this sentence is that the\ntaxonomic composition changed, the size distribution remained the same, yet the mean size\ndecreased. I think this needs to be laid out more clearly for the reader.\nResponse #51: Prey body mass decreased with increasing temperature, but this was driven by\nsystematic within-species reductions in body mass, rather than changes in taxonomic\ncomposition that were biased towards smaller taxa (across-species reductions in body mass).\nWe have tried to clarify this by replacing the word “distribution” with “number”, highlighting\nthat the driver of decreasing prey body mass is “within rather than across species” and stressing\nthat there is an “intraspecific decrease in prey body mass”.\nLn256: “In other words, while the taxonomic composition of prey species may have changed\nfrom colder to warmer waters, the number of small and large taxa was still similar. Despite\nthe similar size composition of prey species across the temperature gradient, there was a\ncommunity-wide intraspecific decrease in prey body mass at higher temperatures and fishing\neffort (Table S2), i.e. driven by reductions in size within rather than across species. The\nsampled predators responded to the intraspecific decrease in prey body mass by selecting the\nlargest individuals available to them (Fig. 2c) and a greater diversity of large prey (Fig. 2d),\nwhich could be a result of optimal foraging in order to maintain energetic requirements60.”\nLine 257. What do you mean by “increased importance” specifically? Do you mean\n“increased proportion”? “Importance” is vague. I feel like this paper would benefit from\na conceptual diagram showing what is happening in terms of prey availability in the\nenvironment, versus what is happening in the diet. There is a lot going on with changing\nprey size, taxonomic composition, size distributions, and what is being observed in a\ngeneralised predator’s diet. It is a really challenging result to summarise, I do not envy\nthe task! But it is very valuable work and when presented more clearly will be a very\nvaluable paper in the field. Being very clear and precise in the language used and the\nresults described, even to the point of repetition, will really help make these results\naccessible to readers. Referring to figures when describing the results will also be very\nuseful and I am surprised this was not done in this section. Even if some figures are\nsupplementary, they will no doubt help with clarity and should be referred to.\nnot have access to any data on prey availability in the environment, so we cannot produce such\na conceptual figure. We do however refer back to key results figures throughout the discussion\nnow, as recommended.\nLine 266. “Driver” instead of “force”? Optional\nResponse #53: Done\nLine 269 – 271. “which underpinned the increase in PPMR in areas of high commercial\nfishing” before or after accounting for changes in temperature?\nResponse #54: After accounting for temperature. The sentence was changed to reflect that.\nLn275: “In particular, commercial fishing magnified the reduction in the body mass of prey\nspecies with increasing temperature (Fig. 3b), which underpinned the increase in PPMR in\nwarmer waters with more fishing.”\nLine 289. Prey species or prey individuals? This needs to be clarified in every sentence\ninvolving the word prey as you could be referring to one or the other, you discuss both in\nthe paper. Here it isn’t clear which\nResponse #55: We have deleted that sentence in the revised manuscript, but we also reviewed\nthe manuscript with this comment in mind and changed Ln257 as well to refer to “prey\nspecies”.\nLine 289. “regardless of temperature...” this is a confusing sentence, so helps to reiterate,\nif this is indeed what you mean\nResponse #56: This entire paragraph has been deleted in the revised manuscript (see Response\n#58).\nLine 290-291. I am not sure what this sentence means, or how it would cause larger prey\nbody sizes. Please elaborate or remove. Perhaps lead with the following hypothesis as that\nseems to have a bit more solidity (you cite and explain it better). What do you mean by\n“catch well”?\nResponse #57: We acknowledge that this sentence was confusing and so we have now deleted\nit.\nLine 291 – 295. I think what this (“top down”) means is “the selective removal of the\nlargest individuals in the community may release large prey individuals from the risk of\npredation, should they outgrow the gape-limitations of their predators [Mixhitalis or\nsomeone], or become more costly to catch (larger fish have faster swim speeds [cite] and\nare more likely to escape predators [cite]).” I think you could afford to elaborate a little\nmore here. If you mean some other form of top-down control, I think that could also be\nexplained. This is if you are talking about individuals not species, which has not been\nclarified. If species, you need to elaborate why/how you think top-down control could be\nmanifesting, rather than vaguely refer to it.\nResponse #58: In updating our models with predator stomach identity as a random effect, we\nno longer find that prey size is consistently larger at high levels of fishing effort. Previously,\n14\nthis result was dominated by a cluster of points around 10 °C, which related to many individual\nprey measurements in the diet of only a few predator individuals. Our new model structure\ndownweights this bias and provides a result that makes more sense for the greater reduction in\nPPMR with increasing temperature at high levels of fishing effort. This paragraph on altered\ntop-down control is no longer relevant, so we have deleted it.\nLine 293. “The latter” is ambiguous. If you mean “top-down control” please just repeat\nthis, it really helps with clarity.\nResponse #59: As noted in the previous comment, we have now deleted this paragraph.\nLine 296. “community-wide reduction in individual prey body mass” Is this the mean or\nmaximum prey body mass? Please be specific.\nResponse #60: We have now deleted this sentence.\nLine 298. Above you say that there was “reduced predation on larger prey species” here\nyou say there is increased predation on them? I suspect I am missing something, which\nmay sbe due to this paragraph being a little unclear.\nResponse #61: We agree that the paragraph was a little unclear and we have now deleted it as\nexplained in Response #58.\nLine 302. “with no change in body mass across the temperature gradient” even after\naccounting for changes in fishing pressure? Or with no change in “temperature or fishing\npressure”? It’s important to know what the other variable is doing because you mention\nthat there is an interaction.\nResponse #62: We have updated the text and also refer to appropriate figures to clarify the\nresults we mean.\nLn293: “The sampled Northeast Atlantic predators in this study were seemingly more resilient\nto increasing temperature, with no change in body mass across the temperature gradient (Fig.\n2a) or in response to fishing (Fig. 3a).”\nLines 302 - 305:\nWhat does this mean? Please explain the sampling bias.\nCould it be due to, specifically, the trawls “allowing individuals of the largest body size to escape”\nor something? What do you mean by “no control on the prey composition included”,\nperhaps, “some prey are more likely to escape the trawl, such as [some fish] which burrow\ninto the sand at the trawls approach. Should [these species] comprise more of the prey in\ncertain areas, we would miss [this component] in our sampling. However, previous\n[BRUV or something] surveys have shown the abundance of [these prey] is the same\nthroughout our sampling region, so we don’t think this potential bias is likely to impact\nour findings…” or something. I do not imagine this is actually a bias you faced as I am\nunfamiliar with your ecosystem, but hopefully you can see how the potential bias is\ndescribed and then combated. This can be brief but you do need to elaborate on it.\nAlternatively, perhaps you mean: “this could be a consequence of the selective removal\nof [species] from this part of the region where they are commercially valuable (being not\ntargeted elsewhere). Should these species be larger in this area, [the trend we observed]\nmay be masked by the impacts of fishing.”\nOr “we expect [the species] targeted by fishing to be more abundant/larger in the heavily\nfished areas, so it is possible that a compensatory effect is occurring, masking the impact\nof temperature”. Or something along those lines.\nResponse #63: We now clarify what we mean by potential biases in the sampling of the\npredators and the prey in the study.\nLn295: “The consistency in predator body mass could be due to sampling bias of the survey\ntrawls targeting larger, commercially important fish species, i.e. smaller species not captured\nby the trawls may also be predators in the wider food web, and so the lack of temperature effect\non predator body size is largely constrained to organisms in the 1 to 10,000 g size range. The\ntrawls had no control over the prey composition included, i.e. since the prey in the stomach\ncontents were selectively sampled through feeding by the predators.”\nLine 305 - Above you say there was no change, I believe you mean, “regardless of fishing\npressure there was no change with temperature” up there, I’ll make a note, but this needs\nto be clarified each time. You know this data back-to-front and it is a great analysis on\nan amazing dataset, but it has the potential to be very confusing for the reader if things\nare not reiterated and clarified. Some of these things are: whether you controlled for (or\nignoring) one factor or another (e.g. temperature or fisheries”, whether you are talking\nabout prey species or individuals, and reiterating you are talking about the community\n[mean] body size or the species [max] body size, etc. where appropriate.\nResponse #64: We have done our best to ensure that we clarify throughout whenever we are\ntalking about one or both main explanatory variables, prey species or individuals, and\ncommunity- or species-level body size. Thank you as well for the suggestion to refer to results\nfigures throughout the discussion, which we think will also help to avoid confusion about our\nmeaning (see Response #52).\nLine 307-309 - Here you clarify that there is an interaction effect. Perhaps state this as\nthe first sentence above. “Due to the interaction effect between fishing and temperature,\nwe cannot interpret the effects of temperature on the body size etc without accounting for\nshifts in fishing pressure.” Be super clear from the go.\nResponse #65: In addressing Response #62, we now specify at the beginning of the paragraph\nthat there is no effect of temperature or fishing effort, and we refer to the results figures\ncorresponding to our logic at each point. We hope this makes things much clearer now.\nLine 309-312 - “The original hypothesis whereby PPMR would increase in the Northeast\nAtlantic due to increased temperature was only substantiated by a decrease in prey body\nmass, not predator body mass as anticipated”. This is a key result. I feel like this could be\nstated earlier and have its own paragraph.\nResponse #66: We prefer to keep the current order of the discussion, but we have created a new\nparagraph discussing the importance of this key result and placing it in the context of the wider\nliterature.\nLn302: “Our original hypothesis that PPMR would increase with temperature in the Northeast\nAtlantic was underpinned by the expectation of widespread reductions in body mass in warmer\nwaters (i.e. for both predators and prey). Given the observed negative relationship between\nPPMR and body size1,42,43, a community with a smaller average body mass should thus have a\nlarger PPMR. This hypothesis was only substantiated by a decrease in prey body mass (Fig.\n16\n2b), not also predator body mass as anticipated (Fig. 2a; Fig. 3a). Thus, the overall increase\nin PPMR with temperature was driven by a different mechanism to our expectation, i.e.\ncontrasting effects of temperature on large and small organisms leading to a divergence in\ntheir size ratio. Differential effects of temperature on the body size of trophic groups have\nrecently been described in coastal reef ecosystems, with a similar reduction in the size of\nsmaller fish with increasing temperature and no change in larger piscivores30. This highlights\nthe importance of further research to explore the underlying mechanisms to improve our\nunderstanding of how warming may affect different food web compartments and thus overall\nfunctioning and stability.”\nLine 312 - An alternative, perhaps more clear way to say this:\nHowever, there was an interaction effect between pred body size and fisheries impact, such that when fisheries was\nincluded we did see the anticipated reduction in pred body mass with temperature”\nResponse #67: After updating our analyses, there is no longer an interactive effect of\ntemperature and fishing effort on predator body mass, simplifying the conclusions. We now\nnote that predator body mass does not decrease “across the temperature gradient (Fig. 2a) or\nin response to fishing (Fig. 3a)”, citing the corresponding results figure for additional clarity.\nLine 314-316 - This sentence sort of comes out of no-where and could be better off in the\nconclusion.\nResponse #68: We rewrote this entire section (see Response #66) and so the sentence has now\nbeen deleted.\nLine 317 - 319 - Change “An increase” to “Increasing” and “can be associated” to “is”\nand the language becomes more active, plus you save words\nResponse #69: Thanks, we made these recommended changes.\nLine 319-320 - I found this sentence very confusing, what is “absolute trophic energy”?\nDo you mean fewer steps in the food chain, thus less energy lost through “trophic transfer\ninefficiencies”?\nResponse #70: We deleted this fragment and instead explain that weak interactions “can help\nto buffer against the destabilising, oscillatory dynamics of strong trophic interactions73.”\nLine 320-322 - Elaborate, i.e., flexible foraging or generalised predation can prevent the\nover-dominance or over-predation of particular prey species under different\nenvironmental conditions, leading to imbalances in ecosystem structuring.\nResponse #71: We have added the recommended explanation.\nLine 322 - As you are expanding on the above sentence, do not use “furthermore” as it\nsuggests to the reader that you are introducing a new, additional point.\nResponse #72: “Furthermore” was deleted from the sentence.\nLine 324 - This is essentially what I suggested you write two comments above, but with\nmore jargon. It is along the lines of what I suggested, but you introduce “secondary\nextinctions” and then do not going into it, so perhaps remove that and keep it simple. Also\ntry to keep relevant sentences together in the paragraph to avoid jumping around.\nLine 331 - What does this mean? Lower energy efficiency causes weak interactions? Are\nyou referring to trophic transfer efficiency? Because that is an artifact of weak\ninteractions and not a cause. Perhaps you mean “Given energetic variation in prey,\ngeneralised predation may lead to predators selectively targeting larger individuals (of\nany prey species) in order to ensure energetic requirements are met per feeding attempt”\nResponse #74: We realise it was confusing to introduce the concept of energetic efficiency here\nand so have removed it. The sentence now reads “On the other hand, weak per capita\ninteractions can also result in species needing to consume more or larger prey to meet their\nenergetic requirements60, leading to stronger population-level interaction strengths.”\nLine 335 - 337 - This sentence is unexpected, I am not sure whether this paragraph is\ndiscussing trophic transfer efficiency, or optimal foraging, because it seems to do a bit of\nboth. Perhaps separate paragraphs for those two topics?\nResponse #75: We have removed all reference to energy efficiency in this paragraph to avoid\nconfusion and instead focus our arguments on the implications of altered PPMR for interaction\nstrength and stability. We hope this is clearer.\nLine 339 - I would not say that it constrains, rather predicts\nResponse #76: We would prefer to not use the word “predict” as it is already used within the\nsentence. We instead changed the word “constrains” to “governs”.\nLine 339. It can also be used to estimate the community size spectra\nhttps://onlinelibrary.wiley.com/doi/full/10.1002/ece3.8789\nResponse #77: Added, as recommended (Ln330; see Response #49).\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nResponse #78: Many thanks for supporting this initiative for early career researchers and for\nyour contribution to the very helpful suggestions made as part of this review, which have\nsubstantially improved our manuscript.\n18"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I have been reading the revision of this manuscript with great pleasure. I have seen that all my points have been addressed in a very thorough manner and I highly appreciate the high scientific standard of the response and the revision. In my view, the comments by all reviewers have helped to strengthen the conclusion of the manuscript. I have thus no further remarks and I am sure that this will be a very impactful publication."}, "author_response": ""}]

Decision letter