Thermal sensitivity of field metabolic rate predicts differential futures for bluefin tuna juveniles across the Atlantic Ocean

Domain: earth_science
Published: 2023-11-27
Editorial outcome: minor_revision

Abstract
Changing environmental temperatures impact the physiological performance of fishes, and consequently their distributions. A mechanistic understanding of the linkages between experienced temperature and the physiological response expressed within complex natural environments is often lacking, hampering efforts to project impacts especially when future conditions exceed previous experience. In this study, we use natural chemical tracers to determine the individual experienced temperatures and expressed field metabolic rates of Atlantic bluefin tuna (Thunnus thynnus) during their first year of life. Our findings reveal that the tuna exhibit a preference for temperatures 2–4°C lower than those that maximise field metabolic rates, thereby avoiding temperatures warm enough to limit metabolic performance. Based on current IPCC projections, our results indicate that historically-important spawning and nursery grounds for bluefin tuna will become thermally limiting due to warming within the next 50 years. However, limiting global warming to below 2°C would preserve habitat conditions in the Mediterranean Sea for this species. Our approach, which is based on field observations, provides predictions of animal performance and behaviour that are not constrained by laboratory conditions, and can be extended to any marine teleost species for which otoliths are available.

Introduction
Predicting the effects of climate change on the physiological performance and distribution of organisms is one of ecology’s greatest challenges1,2. This is particularly true for commercially exploited and highly migratory marine fishes, where the species’ distribution extends across multiple management jurisdictions and the high seas, and where species’ life history ecology and physiology make them vulnerable to global warming3–9. Changes in the abundance and distributions of fish populations under future climate scenarios can be predicted from historic covariances between climate variables and species distributions6,8,9. However, future scenarios may not be analogous to past experiences, leading to low confidence in predictions of species distributions and performance1,2,10. Mechanistic approaches linking temperature directly to physiological performance offer greater potential for predicting responses of fish populations to climate change, but disaggregating climatic and fishery processes can be challenging2,11.

Responses of individual organisms to external conditions typically have an energetic expression because of changes in behaviour and energy partitioning, and/or in the availability or accessibility of resources2,12. Organisms are limited by their ability to acquire and metabolise resources at sufficient rates to meet the energetic requirements of their physiological system13, and to do so efficiently enough to compete with other organisms for resources12. Environmental temperature is a major driver influencing energetic costs and organism performance, especially for ectothermic species12–17. Identifying the thermal niche for maximum performance, and the thermal threshold beyond which temperature limits metabolic performance, offers a mechanistic tool to predict population responses to climate change, particularly where thermal thresholds are identified based on observations of individuals from the population under study in their specific natural context2,4,13,17–19. Relatively acute thermal variations presented in laboratory experiments may exaggerate effects on physiological performance compared to those expressed in wild individuals and populations exposed to fluctuating temperature ranges over multiple generations20–22. The realised niche constraining a population may also differ from the species’ fundamental niche as limits to performance are potentially affected by the phenotypic plasticity of the population2,12,23,24 and the specific combination of ecological conditions encountered19. Finally, physiological niches defining performance vary across life stages25. In fish, early life stages experience high mortality, and small differences in mortality can translate into large cohort effects26. Early life stages often favour warm waters allowing maximum growth rates, but these waters may be close to species’ thermal tolerance limits, so that environmental warming is most likely to impact populations of marine fishes through thermal limitation of performance during early life stages and spawning25 Accurate and context-specific predictions of the response of individuals to temperature change, therefore, require knowledge of the thermal sensitivity of physiological performance as realised in wild conditions in the environmental context under study2.

The total, time-integrated metabolic rate expressed by an organism operating in the wild is termed field metabolic rate (FMR). The FMR expressed by an individual reflects a combination of respiratory potential and access to resources27. Field metabolic rate is, arguably, the most ecologically relevant measure of whole organism metabolism, particularly in the context of the thermal niche. FMR captures the total energetic cost of operating in the natural environment given the accessibility of resources and accounting for energetic trade-offs available to the individual within its phenotypic, ecological and life stage context28,29; however, measuring field metabolic rate in wild fishes is challenging28.

In teleost fishes, FMR and temperature can be estimated retrospectively from the stable isotope composition of otoliths; hard, calcareous structures located in the inner ear of bony fishes, also known as ear stones23,24,27,30–32. Briefly, carbon precipitated into the aragonitic otolith structure is derived from two sources, dissolved inorganic carbon (DIC) from ambient seawater, and carbon released from the cellular respiration of food29–35. Total blood carbonate concentrations are physiologically regulated to maintain optimum pH and increases in the rate of respiration of food (metabolic rate) result in an increased proportion of respiratory carbon in the total blood-carbonate pool. In marine waters the two carbon sources are isotopically distinct, as δ13C values of DIC typically range between −1 and 2‰, whereas δ13C values of animals within marine food webs rarely exceed −10‰24,27,34. The proportion of respiratory carbon in a carbon-containing bio-material (C resp) can therefore be estimated from isotopic mass balance (see supplementary materials for an extended explanation). Simultaneously, the isotopic composition of oxygen in otoliths provides a record of experienced temperature based on the well-established thermal sensitivity of equilibrium fractionation of oxygen isotopes during aragonite precipitation35–38. Consequently, each otolith provides a record of the temperature experienced by an individual fish and the associated field metabolic rates sustained by the fish averaged over a time period dependent on the amount of otolith material sampled. If physiological performance in the field is influenced by the temperature experienced by individual fish, temperature and FMR otolith proxies across a population will describe field thermal performance curves22,24,39. Otolith stable isotope data can, therefore, be used to infer the distribution of temperatures experienced by individuals, and to describe thermal performance curves for absolute field metabolic rate24. The temperature most frequently observed within a population of free-ranging individuals describes the preferred temperature (T pref) within the thermal habitat available to the population, while the temperature corresponding to the maximum observed C resp value indicates the point at which physiological performance becomes thermally limited (T lim)(Fig. 1). The range of metabolic rates expressed at any given temperature has also been inferred as a field equivalent of maximum aerobic scope24,39.

Here we apply otolith isotope-derived field performance metrics to focus on Atlantic bluefin tuna (Thunnus thynnus Linnaeus, 1758, here on ABFT) in the first year of life (i.e. age 0 or young of the year fish). We infer preferred otolith temperatures for ABFT and identify threshold temperatures beyond which field physiological performance in the first year of life is thermally limited. From these data, we assess the likely trajectories of tuna production in the two main spawning grounds (western Atlantic and Mediterranean Sea) until end century (2100) under differing emission scenarios.

ABFT is an important species for the global economy and cultural heritage, being fished in the Mediterranean Sea from pre-Roman times40,41, and currently sustaining a fishery with a global dockside value (estimated in 2018) of 360 million US$ and an end value of 1.1 billion US$42. ABFT is a pelagic marine species that inhabits mainly the temperate waters of the north Atlantic Ocean and adjacent seas40. ABFT is the largest of the tuna species and adult fish are top predators with a significant role in marine food web structure and dynamics43,44. ABFT can perform large-scale migrations between cold-water foraging grounds in the north Atlantic Ocean and warm oligotrophic spawning grounds, to which they seem to display homing behaviour and spawning site fidelity43,44. Since the mid 1970s, ABFT has been managed as two management units, separated by the 45°W meridian, reflecting the separation in spawning grounds41. Eastern populations spawn in the Mediterranean Sea from May to June in the eastern Mediterranean Sea and from June to July in the central and western Mediterranean Sea.

Results
Over the time period of the sample, the proportion of adult tuna with an assigned origin to the warmer western population has fallen consistently for adult tuna caught in the western and central North Atlantic, but has fluctuated with no overall trend for fish caught in the eastern North Atlantic. By 2010, fewer than 25% of fish from any of the capture locations are assigned to a western origin (Supp. Fig. S1).

Experienced temperatures
In regionally endothermic fishes, the temperature recorded by the otolith reflects the body temperature, which may be elevated over ambient waters as endothermic capability develops during ontogeny. Time averaged temperatures experienced by individual juvenile ABFT inferred from otolith δ18O values were between 24–27°C (95% range) for fish with an inferred or known origin in the Mediterranean Sea and 26–30°C for fish inferred or known to derive from the western North Atlantic population. Population modal temperatures (T pref) for sampled life stages were consistently between 25 and 26°C (Table 1). Otolith-inferred preferred temperatures were consistent with data from larval and adult distributions of ABFT in spawning locations which indicate ~24–27°C as preferred seawater temperatures48,59,70–72, implying that average body temperatures are not strongly elevated above ambient waters during the first year of life. The physiological thermal limit for adult ABFT is considered to be 30°C58, and both larval and adult ABFT are not commonly recorded from waters >30°C43,60. The small number of ABFT recording inferred otolith temperatures >30°C may imply either higher critical thermal tolerance for juvenile ABFT, or fish experiencing waters with unexpectedly high δ18O values.

Field metabolic rates
C resp values derived from δ13C values of otoliths ranged between 0.3 and 0.6, with a median of 0.48 and an inter-quartile range of 0.045. These are among the highest C resp values so far recorded for marine fishes73, as expected for highly active young of the year ABFT. Assuming that the linear form of the calibration between C resp and oxygen consumption rates27 holds across species, these values are equivalent to oxygen consumption rates between 300 and 650 mgO2 Kg−1h−1 with a median value of 465 mgO2 Kg−1h−1. These values are consistent with existing measurements of oxygen consumption rates for juvenile Pacific bluefin tuna and ABFT, with mean routine metabolic rates of 460 mgO2 Kg−1h−1 reported in free swimming southern bluefin tuna (T. maccoyii) at 19°C74. Routine metabolic rates reported for Pacific bluefin tuna at 20–25°C range between 175 and 500 mgO2 Kg−1h−1 with higher values observed at higher swimming speeds48 and in fish after feeding75. While the relative consistency in estimated oxygen consumption rates across studies is encouraging, we restrict subsequent analyses to C resp values to avoid additional and unconstrained uncertainty associated uncertainty associated with converting C resp values to oxygen consumption rates.

Monte Carlo sampling produced mean 95% confidence intervals of 0.034 for individual C resp values and 1.95°C for individual inferred temperatures (Fig. 3). Field metabolic rates (based on C resp values) covary systematically with water temperature across the entire dataset (Fig. 3A–D). The relationship between experienced temperature and C resp values (the thermal performance curve for FMR) is non-linear, increasing with temperature until around 28°C (Table 1). The sign of the relationship between temperature and C resp is inverted at the slope break. Field metabolic rates are, therefore, maximised at average otolith temperatures of ~28°C (i.e. T lim). Above this temperature, the metabolic performance of juvenile ABFT is compromised.

Age-0 (young of the year) ABFT sampled from across the Mediterranean show relatively high C resp values (Fig. 3A), and recorded temperatures approaching the maximum expected for Mediterranean waters, but still rarely exceeding 28°C. Age-1 (yearling) ABFT (Fig. 3B), particularly those sampled from the western North Atlantic, yielded time averaged experienced temperatures in excess of 28°C more frequently than seen in otolith cores from adult ABFT sampled after year 2 (Fig. 3C, D). Consequently, parabolic relationships between temperature and C resp values are more clearly expressed in yearling ABFT. The quadratic model vertex and breakpoint temperatures are similar for populations of subyearling and yearling fish and for yearling fish caught in eastern (Mediterranean Sea, Bay of Biscay) or western (eastern seaboard of the USA) Atlantic waters (Supplementary data). The lowest inferred experienced temperatures are seen in the fish where otolith sampling targeted only the earliest life stages (first 3 months of life), likely reflecting dominance of Mediterranean-origin fish in these samples. C resp values for otolith samples representing the first 3 months of life are relatively high when considering the equivalent experienced temperature, consistent with relatively high mass-specific metabolic rates in younger, smaller fish, and potentially high feeding rates during the first 3 (summer) months of life (Fig. 3A, C). Interquartile ranges of expressed C resp values also vary with integer increments of experienced temperature. Where sufficient samples are available across a broad range in experienced temperatures, inter-quartile ranges of FMR are maximised between T pref and T lim (Fig. 3E, Table 1).

Waters in the Gulf of Mexico, the southern Gulf Stream and the Levantine Sea (eastern Mediterranean) currently exceed the 28°C threshold value for summer (July to September) and whole-year averaged temperatures (Supp. Fig. S3), consistent with physiological modelling implying negative oxygen balance for adult ABFT in the Gulf of Mexico59,60. We used an ensemble of future climate projections from 23 climate models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6)76. From these data, we estimated the time taken for waters across the species range to reach the 28°C threshold under different CMIP6 shared socio-economic pathway (SSP) scenarios up to 2100. In all scenarios, sea surface temperatures increase more in the Mediterranean Sea than the Gulf of Mexico (Fig. 4). Under the SSP1-2.6 scenario emphasising sustainability and maintaining mean warming below 2°C by 210077, seasonally averaged sea surface temperatures do not exceed 28°C in the Mediterranean Sea nor in Slope Sea regions but do exceed 28°C in the Levantine Sea. Under SSP scenario 5–8.5 reflecting a global policy of continued expansion of fossil fuel use resulting in global temperature rise by 2100 exceeding 4.5°C, average summer sea surface temperatures in most of the eastern half of the Mediterranean Sea exceed the 28°C threshold by around 2048 (i.e. around 25 years from the time of writing), and virtually the whole Mediterranean Sea exceeds thermally limiting temperatures for juvenile ABFT by 2100. Intermediate SSP scenarios 2–4.5 and 3–7.0 both predict restriction of juvenile tuna habitat in the Mediterranean Sea by mid-century; however, under SSP 2–4.5, warming stabilises by 2100 whereas in SSP 3-7.0, warming continues.

Methods
Sampling details
ABFT otoliths are routinely analysed to determine δ13C and δ18O values to assign region of origin through ICCAT’s Atlantic-Wide Research Programme for Bluefin Tuna (GBYP)63–69,86, and we draw on these data to infer aspects of tuna ecophysiology. The core region of otoliths representing growth during the first year of life is removed by micro-milling. Sample preparation and analysis methods are described in detail elsewhere63–69. The dataset contains otoliths of juvenile and adult bluefin tuna captured in the Mediterranean Sea, western US and different regions of the North Atlantic Ocean (Fig. 2). The majority of the data (3985 out of 4776) samples were from fish greater than 2 years of age at capture, most caught as adults, mainly due to fishery management agreements prohibiting catch of fish smaller than 30 kg or 115 cm except for some traditional fisheries. Young of year and yearling samples were obtained through ICCAT’s GBYP research initiative to validate otolith chemical markers for region of origin analysis63,64. For adult-caught fish, spawning-origin (western or Mediterranean Sea population) was inferred from otolith δ13C and δ18O values64. The portion of the otolith milled for fish caught at ages greater than age-2 corresponds to growth from hatching until the end of the first winter, as well as any later growth contaminating the sample, and samples are derived from fish surviving to adulthood. 571 samples were taken from fish captured between age-1 and age-2, 559 of these samples from dedicated sampling to validate regional otolith markers63,64. These fish were caught at the end of the first year of life and the sampled otolith aragonite includes material deposited during both summer and winter growth. Finally, 220 age-0 fish were sampled from the Mediterranean Sea, and sampling for these fish represents growth during the summer period only. Within the full dataset, a smaller subset of 367 tuna otoliths was sampled to record δ13C and δ18O values of the otolith portion approximately corresponding to the first 3 months of growth. This group of sampled fish includes 138 of the 220 sampled age-0 fish, 3 age-1 fish, and 181 age-2+ fish caught in the western North Atlantic, Mediterranean Sea and central North Atlantic Ocean. The otolith portions sampled for these 367 fish includes only summer growth. A summary of the samples is shown in Table 1 and full data are provided in the appendix.

Instrument, calibration and standards details
The δ13C and δ18O values from otolith aragonite (δ13C oto and δ18O oto) were determined using an automated carbonate preparation device (KIEL-III; Thermo Fisher Scientific.) coupled to a gas chromatograph-isotope ratio mass spectrometer (Finnigan MAT 252; Thermo Fisher Scientific) at the University of Arizona. Powdered otolith samples (ca. 40–80 μg) were reacted with dehydrated phosphoric acid under vacuum at 70°C. The isotope ratio measurement was calibrated based on repeated measurements of National Bureau of Standards (NBS) NBS-19 and NBS-18, with 6 standards run for every 40 samples; precision was ±0.08‰ (SD) and ±0.11‰ (SD) for δ13C and δ18O, respectively. δ13C oto and δ18O oto values are reported relative to the Vienna Pee Dee Belemnite (VPDB) scale after comparison to an in house laboratory standard calibrated to VPDB. Note that no acid fractionation correction has been applied for differences between aragonite and calcite. Calibration is based on direct comparison to calcite standards.

Data analysis Methods
Estimating temperature and C resp. δ13C oto and δ18O oto values from the compiled dataset were converted to experienced SST and C resp values drawing on estimates of the isotopic composition of oxygen in ambient water (δ18O w), carbon in dissolved inorganic carbonate (δ13C DIC) and carbon in tuna diet (δ13C diet).

Published estimates of seawater δ18O (δ18O water) values in the Gulf of Mexico, southern Gulf Stream and western Mediterranean Sea vary around 0.9 to 1.4‰, consistent with monthly sampled δ18O water values in the Balearic Sea, while the highly evaporitic eastern Mediterranean Sea records higher values up to 2‰ but more typically around 1.5‰87–91. Given that sampled otolith tissues integrate over either 3 months or a year of life92 with no additional independent details on the likely location of individuals, we estimate distributions of δ18O water values with a mean of 1.0‰ for western origin fish and 1.2‰ for Mediterranean origin fish with a 95% confidence range spanning 0.2‰ in both cases.

Otolith temperatures reflect the temperature at which the otolith was grown. In ectothermic fishes, body temperature is the same as ambient water, but in fishes with regional endothermy capacity such as ABFT, body temperatures recorded by the otolith may be elevated over ambient water. The ontogenetic development of elevated body temperature in ABFT is not fully known. In Pacific BFT, body temperatures are elevated over ambient water at body sizes of c. 25 cm79, and decoupling between body and ambient temperatures increases with age as enhanced endothermic capacity enables fish to exploit cooler waters, and potentially excludes larger fish from warmer water. The early onset of endothermic capability in PBFT potentially implies some elevation of body temperature in ABFT of the body sizes sampled in this study. However, we note that otolith temperatures recorded in ABFT span a wide range of >10°C, and record systematically warmer otolith temperatures in fish of western compared to eastern origin, implying that thermoregulatory capacity is limited at the body size sampled, and that otolith temperatures vary with ambient water temperature. Throughout we refer to ‘otolith temperatures’ which reflect the body temperature during otolith growth.

Estimates of δ13C DIC values are available to be estimated from published δ13C DIC values. We add no additional uncertainty as in δ13C oto values, reflecting well as isotope-enabled global biogeochemical models94 and direct sampling90,95. Consequently, we estimated likely δ13C DIC values as 1‰ (95% confidence range 0.75‰–1.25‰) for both eastern and western-origin fish. δ13C diet values were estimated as −18.5‰ (95% confidence range −17.5‰–19.5‰)96,97. We are not aware of estimates of isotopic fractionation in C between diet and respiratory CO2 in fishes. Some isotopic fractionation between diet carbon and respiratory CO2 is expected, but any such fractionation cannot be large as the corresponding isotopic spacing between diet and muscle protein in fishes is typically c. 1–2‰. Given that any fractionation factor would be uniformly applied, and minor compared to the c. 18‰ difference in δ13C values between respiratory CO2 and DIC, we do not add a fractionation term.

Otoliths were sampled over a range of 16 years (1996–2012), requiring consideration of changes in carbon isotope compositions due to increased drawdown of isotopically light anthropogenic carbon (Suess Effect). Consequently δ13C oto estimates were adjusted to 2019, by applying a progressive correction of −0.025‰ per year based on the inferred birth year69. Adult ABFT have thermoregulatory capacity, elevating core body and brain temperatures above ambient water temperatures, however, thermoregulatory capacity is not thought to develop completely until after the first year of life55,57,79, and this is reflected in the correspondence between δ18O oto values and water temperatures observed in ABFT captured in waters of known temperature66. Consequently, temperatures experienced in the first year of life were inferred from δ18O oto values and estimates of δ18O water using an otolith isotope thermometry relationship derived from Pacific bluefin tuna98:

T = (δ18O oto − δ18O water) / 0.27(0.016) + 5.193(0.12) (1)

Numbers in parentheses are confidence intervals around statistically-inferred variables

C resp values were estimated following27:

C resp = 1 − (δ13C diet − δ13C oto) / (δ13C diet − δ13C DIC) (2)

Note that this approach follows previous work24,27,30–32 assuming a total fractionation factor between carbon sources and otolith aragonite (ε) not different from 0 based on experimental work in fishes99. Non-zero fractionation of carbon isotopes between dissolved carbonate and aragonite has been suggested for synthetic aragonite precipitation100 and assumed in estimates of proportions of respiratory carbon in otoliths23 providing the total fractionation is fixed (and independent of metabolic rate), the actual term used does not influence the inferred relationship between temperature and C resp values.

We applied Monte Carlo sampling to account for uncertainty in inferred C resp values and estimated temperatures arising from estimates of δ13C values of diet and DIC, δ18O water values and measurement uncertainty, reflecting measurement uncertainty and error on the coefficients of the otolith temperature equation. We randomly drew values for temperature coefficients in Eq. (1) from a normal distribution and applied common temperature equation coefficients within each of 100 replicates. For all individuals within in the 100 replicates, we randomly drew values for δ13C DIC, δ13C diet, δ13C oto, δ18O oto and δ18O water from normally distributed populations with means set either to measured values (δ18O oto, δ13C oto) or best estimates (δ13C diet, δ13C DIC, δ18O water) and standard deviations informed from analytical error or ranges in published values (all central values and confidence intervals used for MC sampling are given in Table 2). The average 95% confidence intervals around individual temperature and C resp values accounting for uncertainty in the estimated parameter variables were 1.9°C and 0.034 respectively. Subsequent analyses are performed on the full resampled dataset. C resp values are a proxy for metabolic rate, but to allow comparison with other datasets, conversions between C resp values and oxygen consumption rates have been developed for cod and Australian snapper27,30. Calibrations have not been validated across wider taxa, however as a first approximation, we applied the linear form of the calibration equation27 to present estimates of tuna FMR in units of oxygen consumption rate.

Quantifying thermal sensitivity of C resp and identifying breakpoints. Our a priori expectation is that field metabolic rate (C resp values) will covary positively with temperature. If a thermal optimum is reached or exceeded, the relationship will become parabolic (i.e. a thermal performance curve) with a vertex or breakpoint indicating the optimal temperature. We therefore modelled the relationship between C resp values and experienced temperature inferred from δ18O oto values with linear models with a quadratic term. We also applied segmented linear regression and breakpoint analyses55 to identify potential metabolic performance threshold temperatures and the thermal sensitivity of C resp values. The explanatory value of using segmented regression compared to linear models was tested using the Davies’ test implemented within the R package ‘segmented’101. The distribution of estimates of T lim based on both breakpoint and quadratic linear model fits across the Monte Carlo simulations is shown in Table 1. The range of C resp values expressed at a given temperature has been inferred to reflect the field-realised aerobic scope27,39. As the total range of expressed values within a population is related to the population size, we draw on the inter-quartile range as a more robust metric of population distribution, and limited inferences to cases with more than 15 observations for any given inferred integer temperature value. All data and code are included in the supplementary materials.

Projecting climate impacts. T lim reflects a threshold temperature beyond which metabolic performance is impaired. If waters regularly exceed T lim during early juvenile life stages we expect reduced growth, increased mortality and reductions in stock size. We draw on CMIP6 model products to produce model ensemble predictions of the likely time period when summer or whole year median SST exceed identified metabolic threshold temperatures under varied shared socio economic pathway (SSP) scenarios77. We use 23 climate models from CMIP6 project to produce an ensemble mean state for every year’s summer (JAS) sea surface temperature for the future (from years 2016–2100) for the four socioeconomic pathways (described in Supplementary materials Table S2). The list of models, corresponding institutions and nominal horizontal resolution are given in Table S1. Results presented here were calculated as ensemble means, with checking to ensure that no individual models were extreme outliers likely to bias the results. Models often exhibited significant biases in ocean SST relative to present day observations. To account for this bias when determining the point at which the ensemble mean crosses the threshold values, we first removed the year 2016 values from each of the future model years and then added these anomalies to observed 2016 values (HadlSST)102, creating a bias-corrected SST time series.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This paper addresses an important topic and utilizes a very impressive dataset. However, I\ndo not recommend publication of the paper as currently written. There are many aspects of\nthe paper that are not addressed with clarity and it is thus difficult to interpret the results.\nMost notably, the paper does not start with a clear description of the early life history and\nmovement patterns of bluefin and the results and writing are often confusing and in some\ncases inaccurate. Below. I elaborate further on this.\nThe methodology (Line 482) mentions that “thermoregulatory capacity is not thought to\ndevelop completely until after the first year of life.” While “complete” development may not\noccur, there is field data on the early decoupling of the ambient temperature and body\ntemperature for Pacific bluefin tuna (Kitagawa et al 2022-Rapid endothermal development\nof juvenile Pacific bluefin tuna. Frontiers in Physiology). Specifically, starting at about 25 cm\nin size and during their first summer growth period body temperature starts to be elevated.\nThis is within the size/age range that appears to be pertinent to the results in this paper.\nThe paper should elaborate more about how this ties in to the work done here. Is the\n“temperature experienced by individuals” the body temperature or the ambient\ntemperature? Does the methodology used include the portion of the otolith corresponding\nto a size at which body temperature can be maintained above ambient temperature?\nMuch more precision and clarity is required in the explanation of the early life history of\nbluefin tuna from each of the spawning grounds and the uncertainty in that early life\nhistory. As the manuscript is currently written there are clear errors and assumptions that\nare not supported by the data.\n• With respect to spawning grounds the manuscript mentions the Slope Sea, but is\ninconsistent in how it addresses the relevance of this spawning ground. In most places the\nmanuscript assumes only the Gulf of Mexico and Mediterranean are relevant. There is\nuncertainty and a limited amount of data about the relative contribution of spawning\ngrounds\nin the western Atlantic. However, the available larval data indicates the Slope Sea\nand Gulf of Mexico are of a similar scale, and there are other analyses that collaborate this,\nthough certainly there is not a consensus. This is highly relevant to the results in the paper,\nand the work should more clearly discuss this issue rather than simply providing a citation\nand then moving on to interpret the data within the framework of primarily spawning in the\nGulf of Mexico. How would the results be interpreted if spawning was more widespread in\nthe western Atlantic? I also believe it is relevant to include the Slope Sea in Figure 4\ntemperature trends.\n• For this paper it is important to understand the temporal/seasonal distribution of different\nearly life stages of bluefin tuna in the western Atlantic. In many cases the paper makes the\nassumption that individuals are not moving from spawning grounds in the early life stages.\nBetween the larval stage and their second summer, 12-18 months later, there is a scarcity of\ninformation on distribution, but the information that is available indicates that fish move\nout of the Gulf of Mexico and enter the Atlantic. In the late-summer and early fall, the\nAtlantic off the northeast US is where a majority of bluefin young of the year have been\ncaught to my knowledge. I may not be familiar with all of the data but I am not aware of\nmany bluefin young of the year caught in the Gulf of Mexico in the September timeframe. The\nanalyses assume that average summer conditions (July-September) in the Gulf of\nMexico are important and thus they are a focus of the analyses. Does this really match what\nwe know about bluefin distributions during this time period? On line 186 it states that\n“juvenile fish spend up to a year in these nursery waters” with citations 49 and 50 provided.\nMy understanding is both of those papers deal with the larval stage and say little about the\npost-larval stage.\n• There is a need for precision in this manuscript in many places. For example, Line 260\nstates “Age-1 (yearling) ABFT particularly those sampled from the Gulf of Mexico.” I do not\nbelieve that any of these fish were actually sampled from the Gulf of Mexico. If they match\nwhat is in the supplemental material of Rooker et al 2014, then they were sampled off the\nnortheast U.S. The actual location these individuals were spawned is unknown within the\nwestern Atlantic. They could have originated from the Gulf of Mexico or from the Slope Sea\noff the northeast U.S.\n• In the Gulf of Mexico, the spawning season is primarily late April-early June consistent\nwith the preferred spawning temperatures. Many adult fish arrive in the Gulf of Mexico\nmonths before that when waters are typically colder than preferred spawning\ntemperatures. One hypothesis is that fish will spawn earlier under climate change, but the\ntemperature experienced by larvae will not be affected. I think this alternate hypothesis\nshould also be mentioned. Right now, the paper is making a strong conclusion that western\norigin fish will decline in the future.\nSpecific comments:\nLines 194-197: These sentences cite the 2022 assessment report to state that the Eastern\nstock has recovered over the past decade (i.e. since 2010) and then say consequentially the\neastern contribution has increased with a reference to a figure that only shows data through\n2010. There is a mismatch between the timing of the assessment estimated recovery and\nthe otolith data that ends at 2010, but the text make it seem that the two are concurrent\nand related.\nSupplemental Line 16-17: The water temperatures they are associated with are not 21-24C.\nThe max is 28. The minimum is somewhere between 20 and 24 depending on the author\nand methodology.\nSupplemental Lines 20-21: Does the Muhling et al paper really deal with juveniles? I don’t\nthink that is a proper citation to say juveniles are in the Gulf of Mexico up to 29C. Is there\nany data on the juvenile distribution in the Gulf of Mexico. There is some limited data from\nbird feeding studies of the timing and sizes of fish in the Straits of Florida. In general the\nauthors should probably define what they consider to be the transition (i.e. size/age)\nbetween the larval and juvenile stage and then they should be consistent and precise in the\nuse of this terminology.\nSupplemental Lines 22: “Eastern ABFT mature earlier and at larger body size” The wording\nhere is I presume not what the author intended. Additionally, there is a debate as to\nwhether there is a difference in maturity between the west and east. The author should\ncheck the report from the ICCAT reproductive workshop report.\nSupplemental Line 26: differences in growth rates between western and eastern\npopulations. What is the citation for this? Stewart 2022 stated that they: “found that there\nwas no significant difference in growth parameters between individuals assigned to\ngenetically distinct spawning stocks.”\nFigure 2: The color scale on this figure makes it difficult to resolve some of the more subtle\ntemperature patterns. In particular, a lot of the text is dealing with temperatures above 20\nC, but the scale goes all the way to 0 C, thus obscuring the patterns. I am particularly curious\nwhere the line is for >28 C waters.\nLine 218: Seasonal averaged water temperature. In reading this through it is not clear what\nthis term refers to. Average between which days of the year? Does a value >28C or >30C\neven make sense based on what we know about the distribution of individuals at different\nlife stages.", "reviewer_2": "Trueman and colleagues provide an interesting example of how isotopic analyses of fish\notoliths (ear bones) can be used to reconstruct temperature histories as well as aspects of\nphysiological growth constraints of different life stages of Atlantic bluefin tuna. Fisheries\necologists are starting to use these innovative measurements to reveal a lot about the\nenvironments experienced by highly migratory species of fish. The spatial scale of the\npresent study (Gulf of Mexico, Atlantic Ocean and Mediterranean Sea) is impressive. The\ndifference in environmental (temperature) characteristics of the two main spawning areas\n(GoM and MS) provide interesting contrasts for future climate-driven changes in habitat\nsuitability. The projections have clear fisheries management of an important, transboundary\nfishery.\nI have provided a number of suggested edits and comments directly onto the manuscript\n(word doc). Please be sure to find this attachment.\nThree points.\n1) it is important to recognize and visualize the uncertainty in the Tpref and Cresp\nmeasurements. The dome-shaped curves suggest no error in these measurements.\n2) Related to point 1, the ensemble CMIP6 projections were bias corrected but no statistical\ndownscaling was attempted. The CMIP6 projections may not need to be downscaled given\nthe relatively coarse (basin-scale) resolution of the presentation. It would be interesting for\nthe authors to comment on this.\n3) one of the main figures (projections of change in year when an average summer\ntemperature of 18 deg C is surpassed) is confusing. It almost appears as though the color\nscale was reversed. It is difficult to see the spawning area in the Mediterranean - perhaps\nwhite boxes / lines can be used instead of black.\nBuilding mechanistic models (based on physiology) is important when making projections of\nclimate change impacts, particularly under no-analog futures. This work on Atlantic bluefin\ntuna is a good example of such a study.\nMyron A. Peck", "reviewer_3": "Trueman et al review\nThis interesting study used tuna otolith stable isotopes to estimate field metabolic rates\n(carbon) and thermal preferences (oxygen) of several life stages of Atlantic bluefin. They\nanalyzed a large dataset of samples across many years and modeled the experienced\ntemperatures and field metabolic rates. Monte Carlo resampling was used to assess the\nvariability of model estimates and model parameters. They also used climate models to\nassess how thermal habitats might change overtime and how that relates to the valuable\ntuna fishery. Overall, they found bluefin tuna prefer lower temperatures than those\npredicted by metabolic theory. Gulf of Mexico habitats may become too warm for optimal\ngrowth and survival, but habitats in the Mediterranean may increase. The interesting\nconclusions are supported by the data presented, but some of the supplemental material is\nmissing from the manuscript and I suggest some more methodical details are expanded\nupon. Overall, this is a very interesting and creative paper and I would support publication\nwith some minor revisions.\nBelow, I offer some thoughts to consider as I reviewed the paper.\nAbstract\nLine 52: ‘ectothermic species…’ bluefin may be considered endothermic due to the regional\ngeneration of heat.\nLine 58: ’thermal limiting temperatures’ – clarify warmer or increased temperatures\nLine 60: ‘..next 50 years…’ expand here the expectations for next 50 years that temps will\nincrease in some regions. Also, the ability to limit global warming to below 2C is very\nunlikely so I suggest avoiding this statement or rewording\nLine 62: ‘based on field observations. AND numerous biological assumptions\nIntro\nLine 94: wild individuals do experience fluctuating temperatures, but also seek out thermal\npreferences behaviorally\nLine 104-105: environmental warming will affect performance if confined/limited to space,\nbut mobile fishes will seek out and find thermal preferences\nLine 107: thermal histories will also rely on the precision and accuracy of the method used\nto assess experienced temperature, and what integrated time scale it represents\nLine 126: ‘… isotopically distinct… maybe provide some more detail here and define how in\nterms of decreased or increased 13C/12C ratios.. maybe average or median values of sea\nwater (DIC) and respiratory carbon\nLine 156: …infer preferred field temperatures…this is very much dependent on the\nconsistency of the amount of otolith aragonite samples (e.g. months to years). More detail\non the consistency of the various micromill raster sizes and drill bit areas and sample masses\nwould be more convincing\nLine 157: .. first year of life thermally limited. Tuna grow rapidly within the first year of life,\nand the otolith morphology changes significantly. The diameter and dimensions of a tuna\notolith would change dramatically within 6 to 12 to 18 months. Thus, micromilling the\naragonite with difference drill paths would result in the aggregation of different timescales.\nThis can be resolved with more detail on the dimensions of drilled otoliths cores used for\nSIA. It is plausible that the first year of life temperature experience (and otolith growth) is\nvariable and complex.\nLine 177-178: how does regional endothermy (warmer temps) affect blood and endolymph\ndynamics related to otolith biomineralization (i.e. protein and enzyme function, crystal\nformation)? The intro cites ectothermic fish species often, yet this study focuses on\nendothermic bluefin tuna\nLine 213 Figure 2A: Temperature map from 2021 – what is the time span and temperature\ntrend of the 4,776 samples used in study? Figure 2B of the sectioned otolith shows that the\nmicro milling path was very different, encompassing the full first year or only the first three\nmonths of life. These are very different time scales and that should be clarified. One way to\ntest if the micromill path size had any influence on isotope values would be to compare the\n1-year data to the 3-month data for C and O with a simple boxplots or t-tests. That could be\npresented in the supplemental material.\nLine 287: the climate projections seem very ‘hand-wavy’ in my opinion. This is not my\nexpertise so I am not sure how valid the climate projection models are\nLine 274: The supplemental figure Fig S2 was missing in the materials?\nLine 316: the temperature experience by a fish can be mediated daily. Diving to deep depths\nand cooler waters to slow stomach digestion after feeding at surface, would be an example.\nThe behavioral depth distribution of fish important to consider in broad otolith signatures\nthat integrate monthly experiences. This is considered later on line 335\nLine 324: mortality – is there a lethal temperature where bluefin would be unable to sustain\ncellular processes?\nLine 419: citation 52 repeated twice. Also, was the same raster path size, area and depth\nused for all otoliths?\nLine 440: did not see the appendix in the supplemental?\nLine 467: water 18O – was the decided value a median or mean? Please clarify how that was\ndecided\nLine 474: diet 13C – are the assumed diet values based on juvenile or adult fish? Would you\nexpect there to be a difference in 13C between juveniles and adult and perhaps between\nthe Med and Gulf? Was a fractionation factor applied to estimate 13C diet? Providing a little\nmore detail here would be helpful, perhaps in the supplement\nLine 512: The font size and style seem different in Table 2. Very nice to see the Monte Carlo\nresampling to assess the effect of variation in model parameters. Well done!\nLine 536: Did not see supplemental Figure 4? In fact, there was only 1 supplemental figure\npresent so that need to be corrected."}, "author_response": "We would like to thank the 3 reviewers for their considered, insightful and constructive\ncomments. We have attempted to address all comments raised and agree that the\nmanuscript is significantly improved. Below we outline the responses made:\nReviewer 1\nThis paper addresses an important topic and utilizes a very impressive dataset. However, I\ndo not recommend publication of the paper as currently written. There are many aspects of\nthe paper that are not addressed with clarity and it is thus difficult to interpret the results.\nMost notably, the paper does not start with a clear description of the early life history and\nmovement patterns of bluefin and the results and writing are often confusing and in some\ncases inaccurate. Below. I elaborate further on this.\nThe methodology (Line 482) mentions that “thermoregulatory capacity is not thought to\ndevelop completely until after the first year of life.” While “complete” development may not\noccur, there is field data on the early decoupling of the ambient temperature and body\ntemperature for Pacific bluefin tuna (Kitagawa et al 2022-Rapid endothermal development of\njuvenile Pacific bluefin tuna. Frontiers in Physiology). Specifically, starting at about 25 cm\nin size and during their first summer growth period body temperature starts to be elevated.\nThis is within the size/age range that appears to be pertinent to the results in this paper. The\npaper should elaborate more about how this ties in to the work done here. Is the\n“temperature experienced by individuals” the body temperature or the ambient temperature?\nDoes the methodology used include the portion of the otolith corresponding to a size at which\nbody temperature can be maintained above ambient temperature?\nResponse: We thank the reviewer(s) for this important comment - we have added the\nfollowing text to the data analysis methods:\nOtolith temperatures reflect the temperature at which the otolith was grown. In\nectothermic fishes, body temperature is the same as ambient water, but in fishes with\nregional endothermy capacity such as ABFT, body temperatures recorded by the otolith\nmay be elevated over ambient water. The ontogenetic development of elevated body\ntemperature in ABFT is not fully known. In Pacific BFT, body temperatures are elevated\nover ambient water at body sizes of c.25cm79, and decoupling between body and\nambient temperatures increases with age as enhanced endothermic capacity enables\nfish to exploit cooler waters, and potentially excludes larger fish from warmer water.\nThe early onset of endothermic capability in PBFT potentially implies some elevation of\nbody temperature in ABFT of the body size sampled in this study. However, we note\nthat otolith temperatures recorded in ABFT span a wide range of >10ºC, and record\nsystematically warmer otolith temperatures in fish of western compared to eastern\norigin, implying that thermoregulatory capacity is limited at the body size sampled, and\nthat otolith temperatures vary with ambient water temperature. Throughout we refer\nto ‘otolith temperatures’ which reflect the body temperature during otolith growth.\nand later in the discussion, we have added the text below outlining the implication of early\nonset body water elevation to our projections:\nThe onset and ontogenetic development of thermoregulatory capacity in ABFT is\nuncertain. As thermoregulatory capacity develops and body temperatures become\nelevated, the 28 degree thermal limit for body temperatures will be met under cooler\nambient water temperatures. Our projections of thermal limitation of juvenile ABFT\nbased on median summer water temperatures of 28 degrees are therefore conservative,\napplying directly to smaller juveniles where body temperatures match water\ntemperatures. Thermal limitation of ABFT may be exaggerated beyond our projections if\nelevated body temperatures develop rapidly during ABFT ontogeny.\nMuch more precision and clarity is required in the explanation of the early life history of\nbluefin tuna from each of the spawning grounds and the uncertainty in that early life history.\nAs the manuscript is currently written there are clear errors and assumptions that are not\nsupported by the data.\n• With respect to spawning grounds the manuscript mentions the Slope Sea, but is\ninconsistent in how it addresses the relevance of this spawning ground. In most places the\nmanuscript assumes only the Gulf of Mexico and Mediterranean are relevant. There is\nuncertainty and a limited amount of data about the relative contribution of spawning grounds\nin the western Atlantic. However, the available larval data indicates the Slope Sea and Gulf\nof Mexico are of a similar scale, and there are other analyses that collaborate this, though\ncertainly there is not a consensus. This is highly relevant to the results in the paper,\nand the work should more clearly discuss this issue rather than simply providing a citation\nand then moving on to interpret the data within the framework of primarily spawning in the\nGulf of Mexico. How would the results be interpreted if spawning was more widespread in\nthe western Atlantic? I also believe it is relevant to include the Slope Sea in Figure 4\ntemperature trends.\nResponse: We acknowledge that we should have been clearer about the potential\ndistribution of juvenile ABFT especially in the western populations. The reviewer correctly\ndraws attention to the lack of clear evidence for long-term residence of YOY bluefin tuna\nwithin the Gulf of Mexico (as opposed to the western North Atlantic (Florida current / Slope\nSea).\nWe have revised the text throughout to remove explicit reference to the Gulf of Mexico as\nthe assumed spawning site or location of early juvenile fish for the Western population. We\nnote that spawning may occur both within the GOM and in the Slope Sea - and that juvenile\ngrowth likely occurs outside of GOM with the Gulf Stream / Florida Current and slope sea\narea. We note however that the location of juveniles is not central to our identification of\nthermally limiting temperatures. We identify the (otolith) temperatures recorded by these\nfish and the resulting expressed FMR. We conclude that any waters warmer than 28C will\nexceed Tlim for age0 BFT - whether in the GOM or broader warm gulf stream waters. Our\nprojections of the distribution of potentially limiting sea surface temperatures cover the\nentire north Atlantic and therefore also refer to all currently known or assumed regions\ncritical for spawning and growth in the first year of life.\nWe have also now addressed in the text the presence of potential spawning grounds as\nderived from the literature where presence of ABT larvae has been reported, including the\nSlope Sea. We acknowledge that the Slope Sea might be an additional important spawning\nground but at the present time there is no direct evidence on the importance of this\n“newly” discovered spawning ground relative to the Gulf of Mexico and the Mediterranean\nSea, and its contribution to the population dynamics is still undetermined. In the revised\nversion we refer to eastern and western spawning grounds / populations (with the western\nspawning population including both the GOM and the Slope Sea. We have also revised Fig.2\nto reflect this).\n• For this paper it is important to understand the temporal/seasonal distribution of different\nearly life stages of bluefin tuna in the western Atlantic. In many cases the paper makes the\nassumption that individuals are not moving from spawning grounds in the early life stages.\nBetween the larval stage and their second summer, 12-18 months later, there is a scarcity of\ninformation on distribution, but the information that is available indicates that fish move out\nof the Gulf of Mexico and enter the Atlantic. In the late-summer and early fall, the Atlantic off\nthe northeast US is where a majority of bluefin young of the year have been caught to my\nknowledge. I may not be familiar with all of the data but I am not aware of many bluefin\nyoung of the year caught in the Gulf of Mexico in the September timeframe. The analyses\nassume that average summer conditions (July-September) in the Gulf of Mexico are\nimportant and thus they are a focus of the analyses. Does this really match what we know\nabout bluefin distributions during this time period? On line 186 it states that “juvenile fish\nspend up to a year in these nursery waters” with citations 49 and 50 provided. My\nunderstanding is both of those papers deal with the larval stage and say little about the post-\nlarval stage.\nResponse: As above, we have revised text throughout to clarify that while distributions of\nyoung of year tune form the western spawning population are unclear, it is likely that fish\nexit the Gulf of Mexico during the time period sampled in the otolith analyses. As above we\nhave revised text throughout to clarify this. But also point out that the location of the\nindividuals is not critical to our identification of the thermally limiting (otolith) temperature.\n• There is a need for precision in this manuscript in many places. For example, Line 260\nstates “Age-1 (yearling) ABFT particularly those sampled from the Gulf of Mexico.” I do not\nbelieve that any of these fish were actually sampled from the Gulf of Mexico. If they match\nwhat is in the supplemental material of Rooker et al 2014, then they were sampled off the\nnortheast U.S. The actual location these individuals were spawned is unknown within the\nwestern Atlantic. They could have originated from the Gulf of Mexico or from the Slope Sea\noff the northeast U.S.\nResponse: This is correct and we have revised the text to refer to \"eastern and western\nnurseries\" to remedy this issue. We also state that the isotopic composition of each bluefin\ntuna from the western spawning population was shaped by ambient conditions in both the\nGulf of Mexico and NE U.S.\n• In the Gulf of Mexico, the spawning season is primarily late April-early June consistent\nwith the preferred spawning temperatures. Many adult fish arrive in the Gulf of Mexico\nmonths before that when waters are typically colder than preferred spawning temperatures.\nOne hypothesis is that fish will spawn earlier under climate change, but the temperature\nexperienced by larvae will not be affected. I think this alternate hypothesis should also be\nmentioned. Right now, the paper is making a strong conclusion that western origin fish will\ndecline in the future.\nResponse: We agree that changes in phenology could be an adaptation to warming waters,\nparticularly addressing acute thermal(+oxygen) stress on spawning adults – but post-larval\njuvenile fish in the Gulf of Mexico / Florida Strait will still encounter water temperatures in\nexcess of the identified thermally limiting temperature of 28 degrees. Therefore while\nearlier spawning has clear potential benefit for spawning adults, it is not clear what effect it\nwould have in terms of limiting exposure of post -larval juveniles to thermally limiting\ntemperatures.\nSpecific comments:\nLines 194-197: These sentences cite the 2022 assessment report to state that the Eastern\nstock has recovered over the past decade (i.e. since 2010) and then say consequentially the\neastern contribution has increased with a reference to a figure that only shows data through\n2010. There is a mismatch between the timing of the assessment estimated recovery and\nthe otolith data that ends at 2010, but the text make it seem that the two are concurrent\nand related.\nResponse: “Consequently” has been removed.\nSupplemental Line 16-17: The water temperatures they are associated with are not 21-24C.\nThe max is 28. The minimum is somewhere between 20 and 24 depending on the author and\nmethodology.\nResponse: text corrected\nSupplemental Lines 20-21: Does the Muhling et al paper really deal with juveniles? I don’t\nthink that is a proper citation to say juveniles are in the Gulf of Mexico up to 29C. Is there\nany data on the juvenile distribution in the Gulf of Mexico. There is some limited data from\nbird feeding studies of the timing and sizes of fish in the Straits of Florida. In general the\nauthors should probably define what they consider to be the transition (i.e. size/age) between\nthe larval and juvenile stage and then they should be consistent and precise in the use of this\nterminology.\nResponse: We have refined the text to refer to larval and juvenile tuna as we do not have\nclear understanding of the timing / age of exit from the Gulf of Mexico\nSupplemental Lines 22: “Eastern ABFT mature earlier and at larger body size” The wording\nhere is I presume not what the author intended. Additionally, there is a debate as to whether\nthere is a difference in maturity between the west and east. The author should check the\nreport from the ICCAT reproductive workshop report.\nResponse: Authors agree that this issue could be further developed\nDifferences in size at maturity between the two spawning grounds have been reported; in\nthe Gulf of Mexico, maturity is assumed to be achieved in fish no younger than nine years\nold or 185 cm curved fork length, while in the Mediterranean Sea 100% of ABFT show to be\nmature at >135 cm fork length (i.e., age 4-5 years). However, the similarity in growth rates\nof both components has raised doubts regarding the difference in age of sexual maturity,\nand novel approaches for assessing sexual maturity in ABFT suggest that maturity ogives for\nABFT originated from the Gulf of Mexico and the Mediterranean Sea are indeed similar.\nLinked comment: Supplemental Line 26: differences in growth rates between western and\neastern populations. What is the citation for this? Stewart 2022 stated that they: “found that\nthere was no significant difference in growth parameters between individuals assigned to\ngenetically distinct spawning stocks.”\nResponse: There have been multiple growth studies for Atlantic bluefin.. Stewart 2022 found\nno differences between genetically distinct individuals, however in ICCAT a Von Bertalanfly\ngrowth function (Cort et al 1991) is used for the east, and a Richards growth function (Ailloud\net al 2017) is used for the west. Similarity (or otherwise) in growth rates between the western\nand eastern spawning populations is not, however, directly pertinent to the inferences made\nin the study, and we have therefore removed this section to reduce potential confusion.\nFigure 2: The color scale on this figure makes it difficult to resolve some of the more subtle\ntemperature patterns. In particular, a lot of the text is dealing with temperatures above 20 C,\nbut the scale goes all the way to 0 C, thus obscuring the patterns. I am particularly curious\nwhere the line is for >28 C waters.\nResponse: We thank the reviewer for this suggestion and have now provided a new figure\nwhere we hope that temperature patterns are more easily interpreted and the 28 contour is more\neasily followed , however we have compressed the temperature scale at low temperatures to\nemphasise the focus in this work on finer-scale differences at the warm end of the thermal\nrange.\nLine 218: Seasonal averaged water temperature. In reading this through it is not clear what\nthis term refers to. Average between which days of the year? Does a value >28C or >30C\neven make sense based on what we know about the distribution of individuals at different life\nstages.\nResponse: The otolith temperature refers to the temperature averaged over the duration of\ngrowth of the otolith (either 1 year or 3 months). We further note that growth is fastest\n(and otolith apposition greatest) in early portion of the first year of life and thus that\naveraged temperatures will be biased to the first half of the first year of life. As noted in the\ntext, few individuals record temperatures >>28C. Water temperatures close to and\nexceeding 28C are seen in the Gulf of Mexico and Florida current in summer months. As\nnoted above development of partial regional endothermy may also raise otolith\ntemperatures above ambient water.\nReviewer #2 (Remarks to the Author):\nTrueman and colleagues provide an interesting example of how isotopic analyses of fish\notoliths (ear bones) can be used to reconstruct temperature histories as well as aspects of\nphysiological growth constraints of different life stages of Atlantic bluefin tuna. Fisheries\necologists are starting to use these innovative measurements to reveal a lot about the\nenvironments experienced by highly migratory species of fish. The spatial scale of the present\nstudy (Gulf of Mexico, Atlantic Ocean and Mediterranean Sea) is impressive. The difference\nin environmental (temperature) characteristics of the two main spawning areas (GoM and\nMS) provide interesting contrasts for future climate-driven changes in habitat suitability. The\nprojections have clear fisheries management of an important, transboundary fishery.\nI have provided a number of suggested edits and comments directly onto the manuscript\n(word doc). Please be sure to find this attachment.\nWe thank the reviewer for further constructive comments on the manuscript and provide\nresponses below:\nThree points.\n1) it is important to recognize and visualize the uncertainty in the Tpref and Cresp\nmeasurements. The dome-shaped curves suggest no error in these measurements.\nResponse: The 95% confidence intervals around individual Temperature and C estimates\nresp\n(determined from Monte Carlo resampling) are now provided in the materials and methods,\nand the Monte Carlo estimated standard deviations around the derived population\ntemperature variables (T , T T ) are now added to Table 1.\npref lim Cresp IQR\n2) Related to point 1, the ensemble CMIP6 projections were bias corrected but no statistical\ndownscaling was attempted. The CMIP6 projections may not need to be downscaled given\nthe relatively coarse (basin-scale) resolution of the presentation. It would be interesting for\nthe authors to comment on this.\n(also linked comment copied from the annotated manuscript):\nYou are taking the ensemble average from CMIP6 which is good. However, can you justify not\nusing statistical downscaling for your statements about thermal constraints in spawning\nareas? At quite coarse scales (e.g. seasonally averaged) this is likely okay. For previous work\nin GoM, they weighted model members by agreement to measured temperatures – some\nensemble members performed quite poorly…\nResponse: We are interested in showing how the surface temperature across the whole\nAtlantic, including the GoM and Mediterranean, evolves in future projections. While\nstatistical downscaling may somewhat refine individual regions of interest (like the GoM) it\nwould not be simply applied across the larger regions of the current study, and applying it\nseparately for each region may introduce biases that are difficult to correct for, based on the\ndata availability and downscaling process for each region. As the reviewer notes, for the\nrelatively large regions we are assessing, and fairly coarse temporal resolution, we feel that\nthe resolution provided by the CMIP GCMs is adequate.\nRegarding the inter model differences, it is true models might have different skills when\ncompared with present day observations, or the observational record. While there are many\ndifferent approaches to ensemble averaging, we again felt that a simple multi model mean\nwould introduce the least regional bias when considering the wider GoM, Mediterranean and\nAtlantic domain we are working with. SST biases are a known issue in many models (most\nnotably in the Southern Ocean, but also other global regions) and are often related to incident\nshort wave radiation and cloud parameterisations (e.g. Hyder et al.,\nhttps://doi.org/10.1038/s41467-018-05634-2). However, as we are mainly examining the\nchange in SST, rather than absolute values, this is less of an issue. To arrive at the absolute\nvalues in our analysis a simple bias correction was undertaken; extracting the relative changes\nwith respect to each model’s initial state and adding it to the observed initial state.\nWe did undertake minor pruning of the ensemble to remove extremely obvious outliers but\noverall, the ensemble mean is generally consistent with individual model trends, and the\nensemble standard deviation is more robust through the inclusion of a large ensemble. The\nshaded region in the time series represent inter-model standard deviation.\n3) one of the main figures (projections of change in year when an average summer\ntemperature of 18 deg C is surpassed) is confusing. It almost appears as though the color\nscale was reversed. It is difficult to see the spawning area in the Mediterranean - perhaps\nwhite boxes / lines can be used instead of black.\nResponse: We apologise for lack of clarity in this image. In most models the summer\ntemperature threshold is already exceeded at the start of the model run (2016) in the south-\nwestern sector of the map, and so the red area dominates. White regions (NaNs) are areas\nwhere the temperature does not reach the threshold before 2100. The blue region advances\nfurther into this region of NaNs in the stronger warming scenarios (eg extending east of 30W\nin ssp585), indicating the threshold being exceeded over a wider area. At any fixed\ngeographic point, for instance 40N, 60W, (easily located by the grid lines), you see that ssp126\nnever exceeds the threshold, while for successive scenarios it becomes blue and then\nprogressively lighter, indicating it crossing the threshold earlier as the scenarios become more\nintense. This will not be universal at every point, due to some variation between models in\neach ensemble between scenarios, natural variability and the ocean circulation pattern, but\nthe general trend toward the threshold being exceed earlier in most locations for stronger\nscenarios holds. We have amended the figure caption slightly below for clarity.\nFigure 4. CMIP6 model consensus projections. Left hand plots: projections of the year when\nthe summer (July, August, September) seasonal average sea surface temperature crosses\nthe 28°C limiting threshold (T ) for metabolic performance for ABFT juveniles under shared\nlim\nsocioeconomic pathway scenarios. White space implies that water will not exceed 28°C\nwithin the timeframe of the projection (year 2100). Faster warming sees less ‘white’ space\nas a greater proportion of the total area exceeds 28°C, particularly in later years of the\nsimulation (blue colours). Right hand plots: associated spatially averaged surface\ntemperature change trajectories. The shaded regions represent inter-model standard\ndeviation. We have also modified Fig 4 to reflect the RCP nomenclature: (e.g. 1-2.6).\nBuilding mechanistic models (based on physiology) is important when making projections of\nclimate change impacts, particularly under no-analog futures. This work on Atlantic bluefin\ntuna is a good example of such a study.\nMyron A. Peck\nReviewer 2 made further helpful comments annotated on the text document – we have\naddressed all - for clarity we summarise our responses here:\nAbstract – Thank-you for helpful comments to clarify language in the abstract, we have\nmodified text to address each of the comments made.\nIntroduction - we have clarified where text refers to species or populations, and removed\nthe term ‘fitness’.\nWe have clarified our description realised vs fundamental niche.\nWe have noted that phenological shifts may be a response to warming\nResults –\nWe have refined text describing C values in the first 3 months of life to improve clarity\nresp\nDepth integrated? I can’t recall how you treated the depth layers. In any case, it won’t\nchange the signal in otolith, only the way you interpret geographical presence / absence if\nthermoclines exist, etc.\nThe sea surface temperature variable (surface_temperature, “ts”) from the CMIP6\nensemble is used. We have not used any vertical profiles, although in a climate model this\nwill typically be equal to the ocean temperature of the top ocean grid cell – of the order 1 m\nthick. This will be substantially similar over the ocean mixed layer.\nDiscussion – we have added caveats noting the broad spatial and temporal scale of our\nprojections, and our inability to project importance of smaller scale features such as frontal\nsystems, or prey availability.\nMaterials and methods –\nSampling the inner core of otoliths - we cannot be certain that we are sampling exactly 3\nmonths of life – throughout we refer to approximately first 3 months of life. The important\npoint here is that the 3 month samples are treated differently to the 1 year average\nsamples. Our interpretation points out that the 3 month samples record relatively high C\nresp\nvalues for the temperature experienced, compared to 1 year averaged samples, consistent\nwith sampling early life stages.\nReviewer #3 (Remarks to the Author):\nTrueman et al review\nThis interesting study used tuna otolith stable isotopes to estimate field metabolic rates\n(carbon) and thermal preferences (oxygen) of several life stages of Atlantic bluefin. They\nanalyzed a large dataset of samples across many years and modeled the experienced\ntemperatures and field metabolic rates. Monte Carlo resampling was used to assess the\nvariability of model estimates and model parameters. They also used climate models to\nassess how thermal habitats might change overtime and how that relates to the valuable\ntuna fishery. Overall, they found bluefin tuna prefer lower temperatures than those\npredicted by metabolic theory. Gulf of Mexico habitats may become too warm for optimal\ngrowth and survival, but habitats in the Mediterranean may increase. The interesting\nconclusions are supported by the data presented, but some of the supplemental material is\nmissing from the manuscript and I suggest some more methodical details are expanded upon.\nOverall, this is a very interesting and creative paper and I would support publication with some\nminor revisions.\nBelow, I offer some thoughts to consider as I reviewed the paper.\nAbstract\nLine 52: ‘ectothermic species…’ bluefin may be considered endothermic due to the regional\ngeneration of heat.\nResponse: please see the response to the first point made by reviewer 1\nLine 58: ’thermal limiting temperatures’ – clarify warmer or increased temperatures\nResponse: Text modified to ‘avoiding temperatures warm enough to limit metabolic\nperformance’.\nLine 60: ‘..next 50 years…’ expand here the expectations for next 50 years that temps will\nincrease in some regions. Also, the ability to limit global warming to below 2C is very\nunlikely so I suggest avoiding this statement or rewording\nResponse: While limiting warming below 2 C seems increasingly unlikely, we include as a\ntarget benchmark. Text refined slightly to …”limiting global warming to below 2°C\nwould preserve habitat conditions…” this remains consistent with our findings even if\nambitious / optimistic\nRegarding ‘improving’ habitat conditions the idea here was that current temperatures in\nmuch of the Mediterranean are lower than Tpref or Tlim - so that warming is expected to\nincreased thermal habitat suitability (albeit temporarily) - but it is true that warming alone is\nunlikely to accurately predict improvements in overall habitat conditions\nLine 62: ‘based on field observations. AND numerous biological assumptions\nResponse: Arguably all predictions of animal performance are based on numerous biological\nassumptions… We have revised text to emphasise that our predictions are not constrained\nby laboratory conditions, and therefore address biological assumptions associated with\nextrapolation from laboratory to field settings.\nIntro\nLine 94: wild individuals do experience fluctuating temperatures, but also seek out thermal\npreferences behaviorally\nResponse: within ecological constraints yes - but clearly temperature is a major factor\ndefining species’ distribution - so there are limits to the ability to behaviourally\nthermoregulate - and these limits likely vary ontogenetically (e.g. critical periods of limited\nLine 104-105: environmental warming will affect performance if confined/limited to space,\nbut mobile fishes will seek out and find thermal preferences\nResponse: as above, yes, within limits.\nLine 107: thermal histories will also rely on the precision and accuracy of the method used to\nassess experienced temperature, and what integrated time scale it represents\nResponse: absolutely agree, and one benefit of the otolith isotope method is that we\nrecover time individual experienced temperature and expressed metabolic rate averaged\nover relatively long and matched time periods\nLine 126: ‘… isotopically distinct… maybe provide some more detail here and define how in\nterms of decreased or increased 13C/12C ratios.. maybe average or median values of sea\nwater (DIC) and respiratory carbon\nResponse: Text revised to state: In marine waters the two carbon sources are isotopically\ndistinct, as d13C values of DIC typically range between -1 and 2‰, whereas d13C values of\nanimals within marine food webs rarely exceed -10‰\nLine 156: …infer preferred field temperatures…this is very much dependent on the\nconsistency of the amount of otolith aragonite samples (e.g. months to years). More detail on\nthe consistency of the various micromill raster sizes and drill bit areas and sample masses\nwould be more convincing\nResponse: - see below - yes inferring preferred temperature from the relative frequency of\nobserved inferred temperatures across individuals does require an assumption that the\ntimeframe over which temperatures are sampled is equivalent among individuals - see\nbelow\nLine 157: .. first year of life thermally limited. Tuna grow rapidly within the first year of life,\nand the otolith morphology changes significantly. The diameter and dimensions of a tuna\notolith would change dramatically within 6 to 12 to 18 months. Thus, micromilling the\naragonite with difference drill paths would result in the aggregation of different timescales.\nThis can be resolved with more detail on the dimensions of drilled otoliths cores used for SIA.\nIt is plausible that the first year of life temperature experience (and otolith growth) is\nvariable and complex.\nResponse: there is a consistent sampling methodology for the majority of otoliths considered\nhere. The milling protocol (cited in Rooker et al papers) samples the entire otolith material\ngrown in the first year along a common plane of section. There is some variation in precise\ntime sampled due both to variable growth rates during the first year of life and imprecision in\nmilling across a complex 3D structure, but the broad averaging of all otolith material formed\nin the first year of life, and the relatively large dataset mitigates against systematic variation\naccording to otolith milling path. The individuals sampled at c.3 months total age are\nsampled with a different methodology, and we consider data from these fish separately to\naccount for potential systematic effects associated with otolith sampling.\nLine 177-178: how does regional endothermy (warmer temps) affect blood and endolymph\ndynamics related to otolith biomineralization (i.e. protein and enzyme function, crystal\nformation)? The intro cites ectothermic fish species often, yet this study focuses on\nendothermic bluefin tuna\nResponse: please see response to the same point also raised by reviewer 1\nLine 213 Figure 2A: Temperature map from 2021 – what is the time span and temperature\ntrend of the 4,776 samples used in study? Figure 2B of the sectioned otolith shows that the\nmicro milling path was very different, encompassing the full first year or only the first three\nmonths of life. These are very different time scales and that should be clarified. One way to\ntest if the micromill path size had any influence on isotope values would be to compare the 1-\nyear data to the 3-month data for C and O with a simple boxplots or t-tests. That could be\npresented in the supplemental material.\nResponse: The breakdown of individuals sampled to reflect one year or 3 month time\nintervals is provided in the materials and methods. We have treated data from the 3 month\nand 1 year milling strategies separately - and we expect the time averaged experienced\ntemperature and metabolic response to that temperature 3 to be different based on the\ndifferences in time / body size averaging\nLine 287: the climate projections seem very ‘hand-wavy’ in my opinion. This is not my\nexpertise so I am not sure how valid the climate projection models are\nResponse: These projections are the most robust estimate of the possible evolution of sea\nsurface temperature based on our current understanding of the climate system. The CMIP\nensemble is the premier global climate modelling effort, and is the underpinning basis for the\nIPCC climate projections and features the most advanced models of each participating\nmodelling centre, representing a truly vast number of person hours of development. The\nexperimental choices, model setup and output requirements are strictly defined (Eyring et al.,\nhttps://doi.org/10.5194/gmd-9-1937-2016) and their output subject to considerable scrutiny in\nall aspects by the climate science community. This does not mean they are flawless, and each\nprojections and indeed the ensemble mean does has its uncertainty, as we don’t yet understand\nand every aspect of climate or resolve all processes within these models . However, the models\ndo tend to agree on bigger climate signals (such as large scale SST change) and large scale\nimpacts of excess radiative forcing on climate (and are reported as such, IPCCAR6 for e.g/).\nHence a multi model mean is fair estimation of the most probable future scenario, and a\nmultimodel standard deviation provides a robust uncertainty estimate based on the wide space\nof available choices made in parameterisations, resolution etc across the participating climate\nmodelling centres.\nLine 274: The supplemental figure Fig S2 was missing in the materials?\nResponse: Apologies, this was left from an earlier draft – the effect of temperature on\ninterquartile ranges of C values is visualised in figure 3E and shown (with uncertainties) in\nresp\nTable 1\nLine 316: the temperature experience by a fish can be mediated daily. Diving to deep depths\nand cooler waters to slow stomach digestion after feeding at surface, would be an example.\nThe behavioral depth distribution of fish important to consider in broad otolith signatures\nthat integrate monthly experiences. This is considered later on line 335\nResponse: The reviewer is correct that behavioural thermoregulation may influence the\ntemperature experienced by individual fish This is a major benefit of the otolith isotope\napproach as we quantify the time integrated experienced temperature including any\nbehavioural thermoregulation. It is true that our projections of potential future habitats reflect\nsurface temperature and some mitigation may be possible via behavioral thermoregulation -\nhowever we note that this is likely an energy-demanding strategy and therefore may result in\nreduced resources available for growth.\nLine 324: mortality – is there a lethal temperature where bluefin would be unable to sustain\ncellular processes?\nResponse: There is of course a lethal temperature (or rather a range of lethal temperatures\nwhich likely vary with life stage and ecological / environmental context) where blulefin are\nunable to sustain cellular processes, and the natural range of ABFT is constrained to waters\nsubstantially lower than lethal limits . In this study, however, we draw inferences around\nwhole organism metabolic responses to conditions experienced by fishes in natural settings,\nwhich may differ substantially from absolute physiological limits under experimental\nsettings. As we draw inferences from wild (surviving) individuals, we are unable to identify\nlethal (field) temperatures.\nLine 419: citation 52 repeated twice. Also, was the same raster path size, area and depth\nused for all otoliths?\nResponse: Thanks, reference corrected. Yes, a standardised raster path protocol was\nfollowed throughout, except for the individuals sampled at 3 months. We analyse fish\nsampled for different ages (3 month old, yearling, adults 3 month sampled and adult year\nsampled) separately to reduce effects of sampling different portions of the otolith.\nLine 440: did not see the appendix in the supplemental?\nResponse: Full data will be provided at acceptance, and are submitted via the journal\nassociated Figshare\nLine 467: water 18O – was the decided value a median or mean? Please clarify how that was\ndecided\nResponse: The 18O values were estimated from cited sources – these are not means or\nw\nmedians as the cited sources are not specific values for the regions concerned. Rather we\ndrew on measured data to estimate the distribution of values to incorporate into Monte\nCarlo re-sampling. Text has been modified to clarify this.\nLine 474: diet 13C – are the assumed diet values based on juvenile or adult fish? Would you\nexpect there to be a difference in 13C between juveniles and adult and perhaps between the\nMed and Gulf? Was a fractionation factor applied to estimate 13C diet? Providing a little\nmore detail here would be helpful, perhaps in the supplement\nResponse: Values are based on literature including juvenile (age 0 and 1 fish). No\nfractionation factor is applied – while some fractionation between diet and respiratory CO2\nis expected, it cannot be large as the fractionation between diet and muscle tissue is\ncorrespondingly minor (c. 1‰) – but there are no published estimates of isotopic\nfractionation in C between diet and respiratory CO2 in fishes. Given that any fractionation\nfactor would be uniformly applied, and minor compared to the c. 18‰ difference in 13C\nvalues between respiratory CO2 and DIC, we do not add a fractionation term. Text has been\nadded to the material and methods to clarify this.\nLine 512: The font size and style seem different in Table 2. Very nice to see the Monte Carlo\nresampling to assess the effect of variation in model parameters. Well done!\nResponse: Thank-you! Table 1 format has been changed and is now similar to Table 2.\nLine 536: Did not see supplemental Figure 4? In fact, there was only 1 supplemental figure\npresent so that need to be corrected.\nResponse: Apologies, the distribution estimates are now included in the main results Table 1.\nThere is only 1 figure in the supplementary - the figure number in the original text was\nmistakenly left from previous draft versions."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The revised manuscript addressed many of the concerns I raised in my original review.\nBelow are a few comments on issues and wording that I feel still need to be addressed.\nLine 60: For precision add a word or two to “for which otolith data are available.” This\nobviously does not mean age data, but what type of data is needed.\nLine 124, 126. 130: The terms metabolic carbon and respiratory carbon are used\ninterchangeably. I think sticking to one would be useful as it be confusing to have two types\nof carbon, one of which has two names.\nLine 238: The statement is the proportion assigned to the warmer western population in the\neastern Atlantic has remained stable. In my look at the figure I would say that it has varied\nover time, but maybe without a long term trend. Nonetheless the convergence in 2010 of\nthe lines is pretty remarkable.\nLine 282/Figure 3: Do all of the adult fish have a population assigned to them in the\nanalyses? If so it would be worth color-coding the adult fish as well. The split in the panel D\nis also a prominent feature. I may have missed it in this read, but I do not recall this being\nexplained.\nLine 394: The hypothesis that seems to be stated here is that the failure to return to the\nhigher recruitment of western Bluefin tuna that was experienced in earlier decades is due to\nthe Gulf of Mexico exceeding 28C in the summer. Was there a time period when that was\nnot the case. Stating this another way. When recruitment in the west was high did the Gulf of\nMexico remain under 28C?\nLine 399: Topt- This is the only spot that this appears when I search it. Is this the same as\nTpref. IIt would be worth putting in the value in parentheses. Is Topt 25C? If so most of the\nwestern Slope Sea where sampling has occurred and larvae have been found is >25 in the\nJuly-Sept.", "reviewer_2": "I have read the revised manuscript by Trueman and colleagues. They have addressed my\nmain concerns (uncertainty in estimates, model resolution / coverage, some suggested\nedits). Note, my main concerns were fairly minor compared to the other two reviewers. In\nshort, I am satisfied with their responses and support publication of this paper in Nature\nCommunications.\nMyron Peck", "reviewer_3": "The authors have sufficiently addressed reviewer comments and the revised manuscript is\nmuch improved."}, "author_response": "Point-by-point reposne REVIEWERS' COMMENTS\nReviewer #1 (Remarks to the Author):\nThe revised manuscript addressed many of the concerns I raised in my original review. Below\nare a few comments on issues and wording that I feel still need to be addressed.\nLine 60: For precision add a word or two to “for which otolith data are available.” This obviously\ndoes not mean age data, but what type of data is needed.\nThank-you – it would be more precise to state that the approach is valid for any case where\notoliths are available - as there are relatively few cases where large volumes of stable isotope\ndata are available, but there are many large otolith archives gloablly, and otoliths are\ncommonly collected for ageing – we have rephrased to “for which otoliths are available” -\nLine 124, 126. 130: The terms metabolic carbon and respiratory carbon are used\ninterchangeably. I think sticking to one would be useful as it be confusing to have two types of\ncarbon, one of which has two names.\nThank-you – we have removed the term ‘metabolic carbon’\nLine 238: The statement is the proportion assigned to the warmer western population in the\neastern Atlantic has remained stable. In my look at the figure I would say that it has varied over\ntime, but maybe without a long term trend. Nonetheless the convergence in 2010 of the lines is\npretty remarkable.\nThank-you for this comment, we have slightly revised the text to read:\nOver the fime period of the sample, the proporfion of adult tuna with an assigned origin to the\nwarmer western populafion has fallen consistently for adult tuna caught in the western and\ncentral North Atlanfic, but has fluctuated with no overall trend for fish caught in the eastern North\nAtlanfic. By 2010, fewer than 25% of fish from any of the capture locafions are assigned to a\nwestern origin (Supp. Fig. S1).\nLine 282/Figure 3: Do all of the adult fish have a population assigned to them in the analyses? If\nso it would be worth color-coding the adult fish as well. The split in the panel D is also a\nprominent feature. I may have missed it in this read, but I do not recall this being explained.\nThe adult fish are mostly assigned to origin - the assignment is primarily based on the oxygen\nisotope value (western origin fish experiencing warmer waters) so that assignment to origin\ndivides by temperature. The colour coding in panels A and B in Figure 3 was originally by\ncapture origin (which is the same as population of origin for these yearling fish). We have now\nrevised the figure to colour by assigned (or known) population origin and applied this to all\npanels A-D.\nIn adult fish where isotope sampling averages across the entire first year of life (panel D), there\nis essentially no overlap in thermal conditions experienced - whereas in fish sampled in the first\nyear of life (panel B and C) the experienced temperatures overlap, presumably because of more\naccurate milling of otolith aragonite. The split in datapoints (relatively few data points recording\nwater temperatures of c27 degrees reflects differences in inferred water 18O values between\nthe Mediterranean and Gulf of Mexico. It is likely that true 18O water values vary and the\nMonteCarlo resampling is designed to address this uncertainty. This is explained in the\n‘limitations to data’ section in the supplementary materials.\nLine 394: The hypothesis that seems to be stated here is that the failure to return to the\nhigher recruitment of western Bluefin tuna that was experienced in earlier decades is due to\nthe Gulf of Mexico exceeding 28C in the summer. Was there a time period when that was not the\ncase. Stating this another way. When recruitment in the west was high did the Gulf of Mexico\nremain under 28C?\nThanks for this point – we have expanded the text slightly to emphasise that during periods of\nhigh recruitment prior to the 1980s, the spatial and temporal extent of water lower than 28\ndegrees in the Gulf of Mexico was considerably higher.\nCurrently,in the Gulf of Mexico, monthly average surface water temperature exceeds 28°C,\nreaching 29-30 degrees in July-October82-84. Since the period of high recruitment of western\norigin ABFT prior to the 1980s85, summer water temperature in the northern Gulf of Mexico has\nrisen by approximately c.0.2 degrees per decade, and the spafial extent of water less than 28°C,\nand the temporal durafion of sub-28°C conditions are now considerably smaller83-84. Therefore\nperiods of high recruitment were characterised by a greater spafial extent and temporal durafion\nof sub-28°C water in the northern Gulf of Mexico, and recent low recruitment may be a\nconsequence of water temperatures in the Gulf of Mexico and southern Gulf Stream exceeding\n28°C.\nLine 399: Topt- This is the only spot that this appears when I search it. Is this the same as Tpref. IIt would\nbe worth pufting in the value in parentheses. Is Topt 25C? If so most of the western Slope Sea where\nsampling has occurred and larvae have been found is >25 in the July-Sept.\nApologies, yes this should be T rather than T , as this is the most commonly experienced\npref opt\ntemperature. This has been changed.\nIt is interesting that the Slope Sea is records temperatures higher than Tpref in July-Sept. Our\ndata for western fish all average the temperature experienced over the first year, and Tpref\ntherefore represents a yearly average temperature. It would be very interesting indeed to\nanalyse otolith margins of fish caught in the Slope Sea in September, determine Tpref for\nshorter timeframes and compare across regions -but that is beyond the scope of this work.\nReviewer #2 (Remarks to the Author):\nI have read the revised manuscript by Trueman and colleagues. They have addressed my main\nconcerns (uncertainty in estimates, model resolution / coverage, some suggested edits). Note,\nmy main concerns were fairly minor compared to the other two reviewers. In short, I am\nsatisfied with their responses and support publication of this paper in Nature Communications.\nMyron Peck\nReviewer #3 (Remarks to the Author):\nThe authors have sufficiently addressed reviewer comments and the revised manuscript is\nmuch improved."}]

Decision letter