Biology subjects

Bigman, J. S.

Publications and source records attributed to Bigman, J. S..

8 recordsLinked to original sources

bioRxiv2026

Dynamic structural equation models for ecosystem-based fisheries management: case studies and a practical guide

Once central challenge in adopting ecosystem-based fisheries management (EBFM) is understanding and predicting the interconnected processes, feedbacks, and temporal dependencies that characterize ecosystem dynamics. Structural equation models and structural causal models (SEM and SCM) quantify interconnected relationships and evaluate causality from observational data but cannot readily accommodate the incomplete and irregularly sampled data typical of complex systems. Dynamic structural equation models (DSEM) estimate SEMs but accommodate lagged effects, missing data, and non-linear and non-stationary effects. However, there is little guidance regarding how DSEM can be used to support EBFM, particularly within governance and decision-making contexts. Here, we present three case studies that highlight distinct inferential goals for understanding ecosystem processes in the context of EBFM. First, we quantify ecosystem-level indicators to support monitoring of climate-driven ecosystem changes. Second, we examine whether hypothesized direct and indirect ecosystem linkages improve predictions of recruitment. Finally, we compare support for hypotheses of causal drivers of fish productivity. To provide practical advice, we synthesize lessons learned into a workflow to for others navigating DSEM. We suggest that the first step is identifying the inferential objective, which establishes the foundation for the remainder of the workflow, guiding the development of graphical models, model specification, and the selection of statistical and scientific validation steps (e.g., testing conditional independencies) needed to evaluate hypothesized causal relationships. By integrating observational data, expert knowledge, and mechanistic hypotheses within a unified framework, DSEM is a powerful tool for advancing EBFM, and more broadly, understanding the processes that govern complex ecosystems.

ecology↗

bioRxiv2026

Bias correction for integrated climate projection modeling

Projections of future conditions from Earth systems models (ESMs) are necessary to understand and predict effects of changing environmental conditions on biological systems. Such projections suffer from biases, or mismatches between model output and observations. While adjusting or bias-correcting model output is common, many methods exist with little understanding of their effects on forecasts of biological change. Here, we explore the bias-correction process and its effects on downstream predictive biological models. As an example, we use the Bering 10K, a downscaled ESM for a productive and economically important subarctic ecosystem. We first characterize existing biases for three categories of variables exhibiting different scales and challenges: bottom temperature, sea ice, and net primary production. We then apply eight bias-correction approaches to six indices generated from the three categories and quantify sources of uncertainty in the trajectories of these ecosystem variables. Finally, we demonstrate how different bias-correction approaches affect downstream biological models using three case studies: 1) fish thermal spawning habitat suitability, (2) predicted zooplankton abundance, and (3) match-mismatch of phytoplankton and zooplankton bloom timing. We find that biases manifest in absolute values over time and in the timing of seasonal events. Time series of all six indices differed depending on bias-correction method, differences that were propagated to downstream biological models. For a given year and simulation, depending on method, thermal spawning habitat suitability and zooplankton abundance differed up to 149% and 151%, and match-mismatch increased or did not change. Our work highlights that bias correction reduces mismatches between observations and model output but choosing an approach requires careful consideration as to not amplify and propagate bias in downstream biological models. To that end, we identify best practices for bias correcting global or regional ESMs, including a decision tree to help improve forecasts of the effects of climate change on biological systems.

ecology↗

bioRxiv2025

Changes in body size with age do not follow the temperature-size rule

The temperature size-rule is often described as a reduction in ectothermic body size with warming. This coincides with the expectation that faster growth under warming would lead to larger sizes early in life but smaller sizes later in life. Here, we use > 99,000 observations of weight-at-age of four commercially-important fishes over 25 years to ask whether changes in size and growth can be explained by temperature. We also examine whether oxygen, a key part of a proposed mechanism behind the temperature size-rule, explains patterns of weight-at-age better than temperature. Changes in weight-at-age over time were more related to temperature than oxygen but the effect of temperature on weight was small and did not vary by age, counter to the temperature size-rule. Importantly, these results were sensitive to how the relationship between weight-at-age and temperature was modeled. While the functional form (linear or polynomial) mattered little, how space was included in the model led to different conclusions regarding how temperature affects size and growth. Assuming that spatial and spatiotemporal random effects - those that account for the higher degree of similarity between observations collected closer in space and time - are shared across ages led to different results compared to allowing these effects to vary by age. Models with shared effects suggested weight for younger ages had positive relationships with temperature and negative relationships for older ages. However, these models provided spurious support for the temperature size-rule as they had less statistical support than models that allowed spatial effects to vary by age. Overall, our work highlights that relationships among size, growth, temperature, and oxygen may not be as straightforward as theory suggests and illustrates that modeling decisions can have a large effect on tests of ecological theory, and more broadly, our ability to understand biological responses to climate change.

ecology↗

bioRxiv2024

Ecological lifestyle and gill slit height across sharks

Morphology that is linked to metabolic rate - metabolic morphology - provides 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 from anatomically-accurate drawings, such as those in field guides, offer the opportunity to understand physiological and ecological relationships without the need for physical, lethal sampling. Here, we assess the relationship between the metabolic physiology and ecology of nearly all extant sharks. Specifically, we examine the relationship between gill slit height and each of the three traits that comprise ecological lifestyle: activity, maximum size, and depth. 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. We also show that 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 have higher metabolic demands and that these greater metabolic demands can be estimated from external morphological and ecological traits. Our work demonstrates that meaningful ecophysiological relationships can be revealed through measurable metabolic morphological traits from anatomically-accurate drawings.

ecology↗

bioRxiv2024

Offspring size resolves a latitudinal population growth rate paradox in rays and skates

The maximum intrinsic population growth rate, rmax, is a key determinant of the limits for sustainable fishing and is increasingly used in risk assessments. Metabolic theory suggests that rmax scales with adult body size, temperature (and hence depth) such that smaller-bodied species and those in warmer, shallower waters have greater rmax and, therefore, will be less sensitive to overexploitation. However, warm shallow-water tropical rays have lower rmax than cold deep-water temperate skates contra to the metabolic expectation. To resolve this paradox, we build from recent advances that suggest that offspring size may be key to understanding rmax. Specifically, we examine how rmax is related to adult size, offspring size, temperature, and depth across 85 ray and skate species. Our results show that offspring size mediates relationships between rmax, adult body size, temperature, and depth. Indeed, tropical rays had, on average, larger offspring and lower rmax compared to the temperate skates, despite living in warmer, shallower waters. Thus, despite the expectation from theory that tropical species should have faster life histories compared to temperate species, our result explains why tropical rays are actually less resilient. It remains unclear as to why tropical rays have such large offspring but we speculate that this is due to greater predation risk in shallow tropical waters driving the additional maternal investment in offspring size via the evolution of viviparity and matrotrophy. Our work highlights the complex relationships among life histories and the environment and may help explain global biogeographic patterns of intrinsic sensitivity to overexploitation.

ecology↗

bioRxiv2022

Predicting Pacific cod spawning habitat in a changing climate

Warming temperatures elicit shifts in habitat use and geographic distributions of fishes, with uneven effects across life stages. Spawners and embryos are particularly sensitive to environmental conditions, with direct impacts of temperature on spawning habitat, as well as indirect connections between their population dynamics and fisheries effort, productivity, and management. Here, we ask how changing environmental conditions and thermal sensitivities of developing embryos confer spatiotemporal variability of thermally-suitable spawning habitat for Pacific cod in the eastern Bering Sea. Specifically, we use bottom temperature values from regionally downscaled global climate models coupled with an experimentally-derived relationship between hatch success and temperature to predict how the extent, mean latitude, and consistency of suitable spawning habitat has changed in the past and may change into the future. We then validate our predictions of suitable spawning habitat with distributions of adults and larvae and examine whether thermal habitat availability relates to recruitment success into the adult cod into the population. We find that the extent and mean latitude of suitable spawning habitat increase over time, particularly if no climate change mitigation occurs in the future. Hotspots of suitable spawning habitat are consistent across shorter time periods but do shift across the Bering Sea shelf by the end of the century. Finally, we find no correlation between the availability of suitable spawning habitat and annual estimates of recruitment. Collectively, our results suggest that as temperatures warm, the availability of suitable spawning habitat will increase and expand spatially and, thus, is not likely to limit recruitment. 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, and offers a pathway for examining life stage-specific changes in habitat use and distribution with continued climate change.

ecology↗

bioRxiv2022

Gills, growth, and activity across fishes

Life history theory argues that an organisms maximum size and its corresponding growth rate have evolved to maximize lifetime reproductive output. The Gill Oxygen Limitation Theory suggests that in aquatic organisms, maximum size is instead constrained by the surface area of the gills, the primary site of gas exchange with the environment. A central prediction of this theory is a tight relationship among maximum size, growth, and gill surface area. Yet since this idea was first tested in the early 1980s, data availability has increased and analytical methods have advanced considerably. Here, we revisit this relationship with new data and a novel phylogenetic Bayesian multilevel modeling framework that allows us to understand how individual variation in gill surface area confers relationships of maximum size, growth, and gills across species. Specifically, we bring gill surface area into an allometric context and examine whether the gill surface area for a given body size (intercept) and the rate at which gill surface changes with size (slope), for a given species, explains growth performance -- an index integrating the life history tradeoff between growth and maximum size -- across fish species. Additionally, we assess whether variation in von Bertalanffy growth coefficients across species can be explained by gill surface area. Finally, we explore whether additional factors - here, activity and evolutionary history -- explain variation in maximum size and growth across species. Overall, we find that although a positive relationship exists among maximum size, growth, and gill surface area across fishes, it is weak. Additionally, gill surface area does not explain much variation in growth coefficients across species, especially for those that reach the same maximum size. However, we find that the activity level of a fish explains more variation in maximum size and growth across species compared to gill surface area. Our results support the idea that in fishes, growth and maximum size are not simply related to gill surface area, and that other covariates--both tractable (e.g., activity, metabolic rate, temperature) and less tractable (e.g., predation risk, resource availability, and variation)--appear to explain more variation in life history traits across species.

ecology↗

bioRxiv2020

The metabolic pace of life histories across fishes

All life acquires energy through metabolic processes and that energy is subsequently allocated to life-sustaining functions such as survival, growth, and reproduction. Thus, it has long been assumed that metabolic rate is related to the life history of an organism. Indeed, metabolic rate is commonly believed to set the pace of life by determining where an organism is situated along a fast-slow life history continuum. However, empirical evidence of a relationship between metabolic rate and life histories is lacking, especially for ectothermic organisms. Here, we ask whether three life history traits - maximum body mass, generation length, and growth performance - explain variation in resting metabolic rate (RMR) across fishes. We found that growth performance, which accounts for the trade-off between growth rate and maximum body size, explained variation in RMR, yet maximum body mass and generation length did not. Our results suggest that measures of life history that encompass trade-offs between life history traits, rather than traits in isolation, explain variation in RMR across fishes. Ultimately, understanding the relationship between metabolic rate and life history is crucial to metabolic ecology and has the potential to improve prediction of the ecological risk of data-poor species.

ecology↗