Top‐Down and Bottom‐Up Control of Life‐History Strategies in Coho Salmon (Oncorhynchus kisutch)

An assessment of terminology for intraspecific diversity in fishes, with a focus on "ecotypes" and "life histories"

Understanding and preserving intraspecific diversity (ISD) is important for species conservation. However, ISD units do not have taxonomic standards and are not universally recognized. The terminology used to describe ISD is varied and often used ambiguously. We compared definitions of terms used to describe ISD with use in recent studies of three fish taxa: sticklebacks (Gasterosteidae), Pacific salmon and trout (Oncorhynchus spp., "PST"), and lampreys (Petromyzontiformes). Life history describes the phenotypic responses of organisms to environments and includes biological parameters that affect population growth or decline. Life-history pathway(s) are the result of different organismal routes of development that can result in different life histories. These terms can be used to describe recognizable life-history traits. Life history is generally used in organismal- and ecology-based journals. The terms paired species/species pairs have been used to describe two different phenotypes, whereas in some species and situations a continuum of phenotypes may be expressed. Our review revealed overlapping definitions for race and subspecies, and subspecies and ecotypes. Ecotypes are genotypic adaptations to particular environments, and this term is often used in genetic- and evolution-based journals. "Satellite species" is used for situations in which a parasitic lamprey yields two or more derived, nonparasitic lamprey species. Designatable Units, Evolutionary Significant Units (ESUs), and Distinct Population Segments (DPS) are used by some governments to classify ISD of vertebrate species within distinct and evolutionary significant criteria. In situations where the genetic or life-history components of ISD are not well understood, a conservative approach would be to call them phenotypes.

Trade-offs between accuracy and interpretability in von Bertalanffy random-effects models of growth

Better understanding of variation in growth will always be an important problem in ecology. Individual variation in growth can arise from a variety of processes; for example, individuals within a population vary in their intrinsic metabolic rates and behavioral traits, which may influence their foraging dynamics and access to resources. However, when adopting a growth model, we face trade-offs between model complexity, biological interpretability of parameters, and goodness of fit. We explore how different formulations of the von Bertalanffy growth function (vBGF) with individual random effects and environmental predictors affect these trade-offs. In the vBGF, the growth of an organism results from a dynamic balance between anabolic and catabolic processes. We start from a formulation of the vBGF that models the anabolic coefficient (q) as a function of the catabolic coefficient (k), a coefficient related to the properties of the environment (γ) and a parameter that determines the relative importance of behavior and environment in determining growth (ψ). We treat the vBGF parameters as a function of individual random effects and environmental variables. We use simulations to show how different functional forms and individual or group variability in the growth function's parameters provide a very flexible description of growth trajectories. We then consider a case study of two fish populations of Salmo marmoratus and Salmo trutta to test the goodness of fit and predictive power of the models, along with the biological interpretability of vBGF's parameters when using different model formulations. The best models, according to AIC, included individual variability in both k and γ and cohort as predictor of growth trajectories, and are consistent with the hypothesis that habitat selection is more important than behavioral and metabolic traits in determining lifetime growth trajectories of the two fish species. Model predictions of individual growth trajectories were largely more accurate than predictions based on mean size-at-age of fish. Our method shares information across individuals, and thus, for both fish populations investigated, allows using a single measurement early in the life of individual fish or cohort to obtain accurate predictions of lifetime individual or cohort size-at-age.

Separating intrinsic and environmental contributions to growth and their population consequences

Among-individual heterogeneity in growth is a commonly observed phenomenon that has clear consequences for population and community dynamics yet has proved difficult to quantify in practice. In particular, observed among-individual variation in growth can be difficult to link to any given mechanism. Here, we develop a Bayesian state-space framework for modeling growth that bridges the complexity of bioenergetic models and the statistical simplicity of phenomenological growth models. The model allows for intrinsic individual variation in traits, a shared environment, process stochasticity, and measurement error. We apply the model to two populations of steelhead trout (Oncorhynchus mykiss) grown under common but temporally varying food conditions. Models allowing for individual variation match available data better than models that assume a single shared trait for all individuals. Estimated individual variation translated into a roughly twofold range in realized growth rates within populations. Comparisons between populations showed strong differences in trait means, trait variability, and responses to a shared environment. Together, individual- and population-level variation have substantial implications for variation in size and growth rates among and within populations. State-dependent life-history models predict that this variation can lead to differences in individual life-history expression, lifetime reproductive output, and population life-history diversity.

Estimating von Bertalanffy parameters with individual and environmental variations in growth

Variation among individuals is an ubiquitous feature of natural populations. However, the relative roles of intrinsic individual differences and stochastic processes in generating variation remain poorly understood. For somatic growth, identifying the contribution of individual and stochastic processes to observed variation in size has important implications both for basic and applied biology. Here we propose and develop methods for estimating individual variation in growth using size-at-age data. We modify the von Bertalanffy growth model to explicitly incorporate individual, environmental, and stochastic variation and provide analytic expressions for the mean and variance of length-at-age in populations. We use a Bayesian statistical model to estimate individual variation from length-at-age data and apply the model to simulated data to test its efficacy. Although a first step towards understanding individual variation, we demonstrate that estimating individual variation from observational samples is possible and provide a platform for future analytical and statistical developments.

Control of puberty in farmed fish

Puberty comprises the transition from an immature juvenile to a mature adult state of the reproductive system, i.e. the individual becomes capable of reproducing sexually for the first time, which implies functional competence of the brain-pituitary-gonad (BPG) axis. Early puberty is a major problem in many farmed fish species due to negative effects on growth performance, flesh composition, external appearance, behaviour, health, welfare and survival, as well as possible genetic impact on wild populations. Late puberty can also be a problem for broodstock management in some species, while some species completely fail to enter puberty under farming conditions. Age and size at puberty varies between and within species and strains, and are modulated by genetic and environmental factors. Puberty onset is controlled by activation of the BPG axis, and a range of internal and external factors are hypothesised to stimulate and/or modulate this activation such as growth, adiposity, feed intake, photoperiod, temperature and social factors. For example, there is a positive correlation between rapid growth and early puberty in fish. Age at puberty can be controlled by selective breeding or control of photoperiod, feeding or temperature. Monosex stocks can exploit sex dimorphic growth patterns and sterility can be achieved by triploidisation. However, all these techniques have limitations under commercial farming conditions. Further knowledge is needed on both basic and applied aspects of puberty control to refine existing methods and to develop new methods that are efficient in terms of production and acceptable in terms of fish welfare and sustainability.