Harvested populations are more variable only in more variable environments

Plasticity is a locally adapted trait with consequences for ecological dynamics in novel environments

Phenotypic plasticity is predicted to evolve in more variable environments, conferring an advantage on individual lifetime fitness. It is less clear what the potential consequences of that plasticity will have on ecological population dynamics. Here, we use an invertebrate model system to examine the effects of environmental variation (resource availability) on the evolution of phenotypic plasticity in two life history traits-age and size at maturation-in long-running, experimental density-dependent environments. Specifically, we then explore the feedback from evolution of life history plasticity to subsequent ecological dynamics in novel conditions. Plasticity in both traits initially declined in all microcosm environments, but then evolved increased plasticity for age-at-maturation, significantly so in more environmentally variable environments. We also demonstrate how plasticity affects ecological dynamics by creating founder populations of different plastic phenotypes into new microcosms that had either familiar or novel environments. Populations originating from periodically variable environments that had evolved greatest plasticity had lowest variability in population size when introduced to novel environments than those from constant or random environments. This suggests that while plasticity may be costly it can confer benefits by reducing the likelihood that offspring will experience low survival through competitive bottlenecks in variable environments. In this study, we demonstrate how plasticity evolves in response to environmental variation and can alter population dynamics-demonstrating an eco-evolutionary feedback loop in a complex animal moderated by plasticity in growth.

Harvest is associated with the disruption of social and fine-scale genetic structure among matrilines of a solitary large carnivore

Harvest can disrupt wildlife populations by removing adults with naturally high survival. This can reshape sociospatial structure, genetic composition, fitness, and potentially affect evolution. Genetic tools can detect changes in local, fine-scale genetic structure (FGS) and assess the interplay between harvest-caused social and FGS in populations. We used data on 1614 brown bears, Ursus arctos, genotyped with 16 microsatellites, to investigate whether harvest intensity (mean low: 0.13 from 1990 to 2005, mean high: 0.28 from 2006 to 2011) caused changes in FGS among matrilines (8 matrilines; 109 females ≥4 years of age), sex-specific survival and putative dispersal distances, female spatial genetic autocorrelation, matriline persistence, and male mating patterns. Increased harvest decreased FGS of matrilines. Female dispersal distances decreased, and male reproductive success was redistributed more evenly. Adult males had lower survival during high harvest, suggesting that higher male turnover caused this redistribution and helped explain decreased structure among matrilines, despite shorter female dispersal distances. Adult female survival and survival probability of both mother and daughter were lower during high harvest, indicating that matriline persistence was also lower. Our findings indicate a crucial role of regulated harvest in shaping populations, decreasing differences among "groups," even for solitary-living species, and potentially altering the evolutionary trajectory of wild populations.

A functional trait approach to identifying life history patterns in stochastic environments

Temporal variation in demographic processes can greatly impact population dynamics. Perturbations of statistical coefficients that describe demographic rates within matrix models have, for example, revealed that stochastic population growth rates (log(λ s)) of fast life histories are more sensitive to temporal autocorrelation of environmental conditions than those of slow life histories. Yet, we know little about the mechanisms that drive such patterns. Here, we used a mechanistic, functional trait approach to examine the functional pathways by which a typical fast life history species, the macrodetrivore Orchestia gammarellus, and a typical slow life history species, the reef manta ray Manta alfredi, differ in their sensitivity to environmental autocorrelation if (a) growth and reproduction are described mechanistically by functional traits that adhere to the principle of energy conservation, and if (b) demographic variation is determined by temporal autocorrelation in food conditions. Opposite to previous findings, we found that O. gammarellus log(λ s) was most sensitive to the frequency of good food conditions, likely because reproduction traits, which directly impact population growth, were most influential to log(λ s). Manta alfredi log(λs ) was instead most sensitive to temporal autocorrelation, likely because growth parameters, which impact population growth indirectly, were most influential to log(λ s). This differential sensitivity to functional traits likely also explains why we found that O. gammarellus mean body size decreased (due to increased reproduction) but M. alfredi mean body size increased (due to increased individual growth) as food conditions became more favorable. Increasing demographic stochasticity under constant food conditions decreased O. gammarellus mean body size and increased log(λ s) due to increased reproduction, whereas M. alfredi mean body and log(λ s) decreased, likely due to decreased individual growth. Our findings signify the importance of integrating functional traits into demographic models as this provides mechanistic understanding of how environmental and demographic stochasticity affects population dynamics in stochastic environments.

Trait-based predictions and responses from laboratory mite populations to harvesting in stochastic environments

Predictions on population responses to perturbations are often derived from trait-based approaches like integral projection models (IPMs), but are rarely tested. IPMs are constructed from functions that describe survival, growth and reproduction in relation to the traits of individuals and their environment. Although these functions comprise biologically non-informative statistical coefficients within standard IPMs, model parameters of the recently developed dynamic energy budget IPM (DEB-IPM) are life-history traits like "length at maturation" and "maximum reproduction rate". Testing predictions from mechanistic IPMs against empirical observations can therefore provide functional insights into the links between individual life history, the environment and population dynamics. Here, we compared the population dynamics of the bulb mite (Rhizoglyphus robini) predicted by a DEB-IPM with those observed in an experiment where populations experienced daily food rations that were either positively correlated over time (red noise), negatively (blue noise) or uncorrelated (white noise). We also selectively harvested large adults in half of these populations. The model failed to generate detailed predictions of population structure as juvenile numbers were overestimated; likely because juvenile-adult interference competition was underestimated. The model performed well at the population level as, for both harvested and unharvested populations, simulations matched the observed, long-term stochastic growth rate λ_s . We next generalised the model to investigate how stochastic change affects mite λ_s , which correlated well with the frequency f of experiencing periods of good environment, but, due to the relationship between f and noise colour ρ, did not correlate well with shifts in ρ. The sensitivity of λ_s to perturbations in life-history parameters depended on the type of stochastic change, as well as population growth. Our findings show that responses to differential mortality depend on individual life-history traits, environmental characteristics and population growth. As long-term climate change causes ever greater environmental fluctuations, trait-based approaches will be increasingly important in predicting population responses to change. We therefore conclude by illustrating what questions can be examined with mechanistic trait-based models like the DEB-IPM, the answers to which will advance our knowledge of the functional links between individual traits, the environment and population dynamics.

Old-Growth Fishes Become Scarce under Fishing

Researchers have long recognized the importance of ecological differences at the species level in structuring natural communities yet until recently have often overlooked the influence of intraspecific trait variation, which can profoundly alter community dynamics [1]. Human extraction of living resources can reduce intraspecific trait variation by, for example, causing truncation of age and size structure of populations, where numbers of older individuals decline far more with exploitation than younger individuals. Age truncation can negatively affect population and community stability, increasing variability in population and community biomass [2-6], reducing productivity [7-10] and life-history diversity in traits such as the spatial and temporal pattern of reproduction and migration [4, 11-16]. Here, we quantified the extent of age truncation in 63 fished populations across five ocean regions, as measured by how much the proportions of fish in the oldest age groups declined over time. The proportion of individuals in the oldest age classes decreased significantly in 79% to 97% of populations (compared to historical or unfished values, respectively), and the magnitude of decline was greater than 90% in 32% to 41% of populations. The pervasiveness and intensity of age truncation indicates that fishing is likely reducing the stability of many marine communities. Our findings suggest that more emphasis should be given to management measures that reduce the impact of fishing on age truncation, including no-take areas, slot limits that prohibit fishing on all except a narrow range of fish sizes, and rotational harvesting.