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Abstract The maximum intrinsic rate of population increase (r_max) represents a population's maximum capacity to replace itself and is central to fisheries management and conservation. Species with lowerr_maxtypically have slower life histories compared to species with faster life histories and higherr_max. Here, we posit that metabolic rate is related to the fast–slow life history continuum and the connection may be stronger for maximum metabolic rate and aerobic scope compared to resting metabolic rate. Specifically, we ask whether variation inr_maxor any of its component life‐history traits – age‐at‐maturity, maximum age, and annual reproductive output – explain variation in resting and maximum metabolic rates and aerobic scope across 84 shark and teleost species, while accounting for the effects of measurement temperature, measurement body mass, ecological lifestyle, and evolutionary history. Overall, we find a strong connection between metabolic rate and the fast‐slow life history continuum, such that species with faster population growth (higherr_max) generally have higher maximum metabolic rates and broader aerobic scopes. Specifically,r_maxis more important in explaining variation in maximum metabolic rate and aerobic scope compared to resting metabolic rate, which is best explained by age‐at‐maturity (out of the life history traits examined). In conclusion, teleosts and sharks share a common fast–slow physiology/life history continuum, with teleosts generally at the faster end and sharks at the slower end, yet with considerable overlap. Our work improves our understanding of the diversity of fish life histories and may ultimately improve our understanding of intrinsic sensitivity to overfishing. 

Abstract Warming temperatures elicit shifts in habitat use and geographic distributions of fishes, with uneven effects across life stages. Spawners and embryos often have narrower thermal tolerances than other life stages, and are thus particularly sensitive to warming. Here, we examine the spatiotemporal variability of thermal spawning habitat for Pacific cod in the eastern Bering Sea. Specifically, we use bottom temperatures from downscaled global climate models coupled with an experimentally-derived hatch success and temperature relationship to predict how the spatial extent, mean latitude, and consistency of thermal spawning habitat has varied over time. Predictions are validated with observations of spawning adults and early larvae. We find that habitat availability has not increased in the past but is predicted to increase and shift northward in the future, particularly if no climate change mitigation occurs. Habitat hotspots are consistent across shorter time periods but do shift across the shelf by the end of the century such that highly suitable areas in the past and present are not predicted to be suitable in the future. This work highlights the importance of coupling experimental data with climate models to identify the complex and mechanistic dynamics among temperature, life histories, and ecology, particularly under climate change. 

ABSTRACT The gill surface area of aquatic ectotherms is thought to be closely linked to the ontogenetic scaling of metabolic rate, a relationship that is often used to explain and predict ecological patterns across species. However, there are surprisingly few within-species tests of whether metabolic rate and gill area scale similarly. We examined the relationship between oxygen supply (gill area) and demand (metabolic rate) by making paired estimates of gill area with resting and maximum metabolic rates across ontogeny in the relatively inactive California horn shark, Heterodontus francisci. We found that the allometric slope of resting metabolic rate was 0.966±0.058 (±95% CI), whereas that of maximum metabolic rate was somewhat steeper (1.073±0.040). We also discovered that the scaling of gill area shifted with ontogeny: the allometric slope of gill area was shallower in individuals <0.203 kg in body mass (0.564±0.261), but increased to 1.012±0.113 later in life. This appears to reflect changes in demand for gill-oxygen uptake during egg case development and immediately post hatch, whereas for most of ontogeny, gill area scales in between that of resting and maximum metabolic rate. These relationships differ from predictions of the gill oxygen limitation theory, which argues that the allometric scaling of gill area constrains metabolic processes. Thus, for the California horn shark, metabolic rate does not appear limited by theoretical surface-area-to-volume ratio constraints of gill area. These results highlight the importance of data from paired and size-matched individuals when comparing physiological scaling relationships. 

Abstract Life history theory suggests that maximum size and growth evolve to maximize fitness. In contrast, the Gill Oxygen Limitation Theory (GOLT) suggests that growth and maximum size in fishes and other aquatic, water‐breathing organisms is constrained by the body mass‐scaling of gill surface area. Here, we use new data and a novel phylogenetic Bayesian multilevel modelling framework to test this idea by asking the three questions posed by the GOLT regarding maximum size, growth and gills. Across fishes, we ask whether the body mass‐scaling of gill surface area explains (1) variation in the von Bertalanffy growth coefficient (k) above and beyond that explained by asymptomatic size (W_∞), (2) variation in growth performance (a trait that integrates the tradeoff betweenkandW_∞) and (3) more variation in growth performance compared to activity (as approximated by caudal fin aspect ratio). Overall, we find that there is only a weak relationship among maximum size, growth and gill surface area across species. Indeed, the body mass‐scaling of gill surface area does not explain much variation ink(especially for those species that reach the sameW_∞) or growth performance. Activity explained three to five times more variation in growth performance compared to gill surface area. Our results suggest that in fishes, gill surface area is not the only factor that explains variation in maximum size and growth, and that other covariates (e.g. activity) are likely important in understanding how growth, maximum size and other life history traits vary across species. 

Abstract Traits underlie organismal responses to their environment and are essential to predict community responses to environmental conditions under global change. Species differ in life‐history traits, morphometrics, diet type, reproductive characteristics and habitat utilization.Trait associations are widely analysed using phylogenetic comparative methods (PCM) to account for correlations among related species. Similarly, traits are measured for some but not all species, and missing continuous traits (e.g. growth rate) can be imputed using ‘phylogenetic trait imputation’ (PTI), based on evolutionary relatedness and trait covariance. However, PTI has not been available for categorical traits, and estimating covariance among traits without ecological constraints risks inferring implausible evolutionary mechanisms.Here, we extend previous PCM and PTI methods by (1) specifying covariance among traits as a structural equation model (SEM), and (2) incorporating associations among both continuous and categorical traits. Fitting a SEM replaces the covariance among traits with a set of linear path coefficients specifying potential evolutionary mechanisms. Estimated parameters then represent regression slopes (i.e. the average change in trait Y given an exogenous change in trait X) that can be used to calculate both direct effects (X impacts Y) and indirect effects (X impacts Z and Z impacts Y).We demonstrate phylogenetic structural‐equation mixed‐trait imputation using 33 variables representing life history, reproductive, morphological, and behavioural traits for all >32,000 described fishes worldwide. SEM coefficients suggest that one degree Celsius increase in habitat is associated with an average 3.5% increase in natural mortality (including a 1.4% indirect impact that acts via temperature effects on the growth coefficient), and an average 3.0% decrease in fecundity (via indirect impacts on maximum age and length). Cross‐validation indicates that the model explains 54%–89% of variance for withheld measurements of continuous traits and has an area under the receiver‐operator‐characteristics curve of 0.86–0.99 for categorical traits.We use imputed traits to classify all fishes into life‐history types, and confirm a phylogenetic signal in three dominant life‐history strategies in fishes. PTI using phylogenetic SEMs ensures that estimated parameters are interpretable as regression slopes, such that the inferred evolutionary relationships can be compared with long‐term evolutionary and rearing experiments. 

Metabolic morphology—the morphological features related to metabolic rate—offers broad comparative insights into the physiological performance and ecological function of species. However, some metabolic morphological traits, such as gill surface area, require costly and lethal sampling. Measurements of gill slit height from anatomically accurate drawings, such as those in field guides, offer the opportunity to understand physiological and ecological function without the need for lethal sampling. Here, we examine the relationship between gill slit height and each of the three traits that comprise ecological lifestyle: activity, maximum body size, and depth across nearly all sharks (n= 455). We find that gill slit heights are positively related to activity (measured by the aspect ratio of the caudal fin) and maximum size but negatively related to depth. Overall, gill slit height is best explained by the suite of ecological lifestyle traits rather than any single trait. These results suggest that more active, larger and shallower species (and endothermic species) have higher metabolic throughput as indexed by gill slit height (oxygen uptake) and ecological lifestyle (oxygen expenditure). We show that meaningful ecophysiological relationships can be revealed through measurable metabolic morphological traits from anatomically accurate drawings, which offers the opportunity to estimate class-wide traits for analyses of life history theory and the relationship between biodiversity and ecological function.