Size- and stage-dependence in cause-specific mortality of migratory brown trout

Evidence‐based management of natural populations under strong human influence frequently requires not only estimates of survival but also knowledge about how much mortality is due to anthropogenic vs. natural causes. This is the case particularly when individuals vary in their vulnerability to different causes of mortality due to traits, life history stages, or locations. Here, we estimated harvest and background (other cause) mortality of landlocked migratory salmonids over half a century. In doing so, we quantified among‐individual variation in vulnerability to cause‐specific mortality resulting from differences in body size and spawning location relative to a hydropower dam. We constructed a multistate mark–recapture model to estimate harvest and background mortality hazard rates as functions of a discrete state (spawning location) and an individual time‐varying covariate (body size). We further accounted for among‐year variation in mortality and migratory behaviour and fit the model to a unique 50‐year time series of mark–recapture–recovery data on brown trout (Salmo trutta ) in Norway. Harvest mortality was highest for intermediate‐sized trout, and outweighed background mortality for most of the observed size range. Background mortality decreased with body size for trout spawning above the dam and increased for those spawning below. All vital rates varied substantially over time, but a trend was evident only in estimates of fishers' reporting rate, which decreased from over 50% to less than 10% throughout the study period. We highlight the importance of body size for cause‐specific mortality and demonstrate how this can be estimated using a novel hazard rate parameterization for mark–recapture models. Our approach allows estimating effects of individual traits and environment on cause‐specific mortality without confounding, and provides an intuitive way to estimate temporal patterns within and correlation among different mortality sources

The Langevin diffusion as a continuous-time model of animal movement and habitat selection

TM was supported by the Centre for Advanced Biological Modelling at the University of Sheffield, funded by the Leverhulme Trust, award number DS-2014-081.1. The utilisation distribution of an animal describes the relative probability of space use. It is natural to think of it as the long-term consequence of the animal's short-term movement decisions: it is the accumulation of small displacements which, over time, gives rise to global patterns of space use. However, many estimation methods for the utilisation distribution either assume the independence of observed locations and ignore the underlying movement (e.g. kernel density estimation), or are based on simple Brownian motion movement rules (e.g. Brownian bridges). 2. We introduce a new continuous-time model of animal movement, based on the Langevin diffusion. This stochastic process has an explicit stationary distribution, conceptually analogous to the idea of the utilisation distribution, and thus provides an intuitive framework to integrate movement and space use. We model the stationary (utilisation) distribution with a resource selection function to link the movement to spatial covariates, and allow inference about habitat preferences of animals. 3. Standard approximation techniques can be used to derive the pseudo-likelihood of the Langevin diffusion movement model, and to estimate habitat preference and movement parameters from tracking data. We investigate the performance of the method on simulated data, and discuss its sensitivity to the time scale of the sampling. We present an example of its application to tracking data of Steller sea lions (Eumetopias jubatus). 4. Due to its continuous-time formulation, this method can be applied to irregular telemetry data. The movement model is specified using a habitat-dependent utilisation distribution, and it provides a rigorous framework to estimate long-term habitat selection from correlated movement data. The Langevin movement model can be approximated by linear model, which allows for very fast inference. Standard tools such as residuals can be used for model checking.PostprintPeer reviewe

Challenging claims in the study of migratory birds and climate change

Recent shifts in phenology in response to climate change are well established but often poorly understood. Many animals integrate climate change across a spatially and temporally dispersed annual life cycle, and effects are modulated by ecological interactions, evolutionary change and endogenous control mechanisms. Here we assess and discuss key statements emerging from the rapidly developing study of changing spring phenology in migratory birds. These well-studied organisms have been instrumental for understanding climate-change effects, but research is developing rapidly and there is a need to attack the big issues rather than risking affirmative science. Although we agree poorly on the support for most claims, agreement regarding the knowledge basis enables consensus regarding broad patterns and likely causes. Empirical data needed for disentangling mechanisms are still scarce, and consequences at a population level and on community composition remain unclear. With increasing knowledge, the overall support (‘consensus view’) for a claim increased and between-researcher variability in support (‘expert opinions') decreased, indicating the importance of assessing and communicating the knowledge basis. A proper integration across biological disciplines seems essential for the field's transition from affirming patterns to understanding mechanisms and making robust predictions regarding future consequences of shifting phenologies

When three traits make a line: evolution of phenotypic plasticity and genetic assimilation through linear reaction norms in stochastic environments

Genetic assimilation emerges from selection on phenotypic plasticity. Yet, commonly used quantitative genetics models of linear reaction norms considering intercept and slope as traits do not mimic the full process of genetic assimilation. We argue that intercept–slope reaction norm models are insufficient representations of genetic effects on linear reaction norms and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead, we suggest a model with three traits representing genetic effects that, respectively, (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually becomes equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs of maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population

Delayed density-dependent onset of spring reproduction in a fluctuating population of field voles

Delayed density-dependent demographic processes are thought to be the basis for multi-annual cyclic fluctuations in small rodent populations, but evidence for delayed density dependence of a particular demographic trait is rare. Here, using capture–recapture data from 22 sites collected over nine years, we demonstrate a strong effect of population density with a one-year lag on the timing of the onset of spring reproduction in a cyclically fluctuating population of field voles Microtus agrestis in northern England. The mean date for the onset of spring reproduction was delayed by about 24 days for every additional 100 voles ha-1 in the previous spring. This delayed density dependence is sufficient to generate the type of cyclic population dynamics described in the study system. Copyright 2011 The Authors. Oikos Copyright 2011 Nordic Society Oiko

Predicting changes in abundance and juvenile proportions of earthworms in the field using glmmADMB in R

The study aimed at investigating effects of three differently acting biocides; the insecticide esfenvalerate, the fungicide picoxystrobin and the bactericide triclosan, applied individually and as a mixture, on an earthworm community in the field. A concentration-response design was chosen and results were analyzed using univariate and multivariate approaches. Effects on juvenile proportions were less pronounced and more variable than effects on abundance, but effects in general were species- and chemical-specific, and temporal variations distinct. Esfenvalerate and picoxystrobin appeared to elicit stronger effects than triclosan at laboratory-based ECx values, which is in accordance with our previous laboratory study on Eisenia fetida. The mixture affected abundance and juvenile proportions, but the latter only at high mixture concentrations. Esfenvalerate and picoxystrobin appeared to be the main drivers for the mixture's toxicity. Species-specific toxicity patterns question the reliability of mixture toxicity predictions derived on E. fetida for field earthworms. Biocide concentrations equaling EC50s (reproduction) for E. fetida provoked effects on the field earthworms mainly exceeding 50%, indicating effect intensification from the laboratory to field as well as the influence of indirect effects produced by species interactions. The differing results of the present field study and the previous laboratory study imply that lower- and higher-tier studies may not be mutually exclusive, but to be used in complementary

Quantitative genetics state-space modeling of phenotypic plasticity and evolution

Living organisms adapt to changes in environment by phenotypic plasticity and evolution by natural selection (or they migrate). At detailed genetic levels these phenomena are complicated, and quantitative genetics attempts to capture essential processes at a higher abstraction level. Phenotypic plasticity is then commonly modeled by reaction norms, which describe how individual traits in a population are expressed in response to changes in environmental variables. The mean reaction norms are evolvable, and here I present a general quantitative genetics state-space model for evolutionary reaction norm dynamics. Reaction norms make use of a reference environment, which is traditionally set to zero. This is problematic when the reference environment is the environment a population is adapted to, for the reason that this environment is a population property, which in itself may be evolvable. With reference to Ergon (2018), I describe models that take such evolvability into account. The resulting models are fundamentally different from most engineering system models, where given reference values are constant, and therefore without consequences can be set to zero. For simplicity I assume only temporal variations in environment, although there obviously are a lot of spatial variations in nature, and I assume that no mutations are involved. Fundamentals from quantitative evolutionary theory are given in appendices

Data from: Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial-capture-recapture data

1. Capture-recapture (CR) techniques are commonly used to gain information about population dynamics, demography and life-history traits of populations. However, traditional CR models cannot separate mortality from emigration. Recently developed spatial-capture-recapture (SCR) models explicitly incorporate spatial information into traditional CR models, thus allowing for individuals’ movements to be modelled explicitly. 2. In this paper, we extend SCR models using robust-design data to allow for both processes in which individuals can disappear from the population, mortality and dispersal, to be estimated separately. We formulate a general robust-design spatial capture-recapture (RD-SCR) model, explore the properties of the model in a simulation study, and compare the results to a Cormack-Jolly-Seber model and a non-spatial robust-design model with temporary emigration. In the case study, we fit several versions of the general model to data on field voles (Microtus agrestis) and compare the results with those from the non-spatial models fitted to the same data. We also evaluate assumptions of the fitted models with a series of simulation-based posterior predictive goodness-of-fit checks that are applicable to SCR models in general and the RD-SCR model in particular. 3. The simulation results show that the model preforms well under a wide range of dispersal distances. Our model outperforms the traditional CR models in terms of both accuracy and precision for survival. The case study showed that adult females have an approximately 3.5 times higher mortality rate than adult males. Males have larger home-ranges and disperse longer distances than females, but both males and females mostly move their activity centres within their previous home-range between trapping sessions at three week intervals. 4. Our RD-SCR model has several advantages compared to other approaches to estimate “true” survival instead of only “apparent” survival. Additionally, the model extracts information about space use and dispersal distributions that are relevant for behavioural studies as well as studies of life-history variation, population dynamics and management. The model can be widely applied due to the flexible framework, and other variations of the model could easily be implemented

Case study data on field voles

This file is an ASCII text representation of an R list object created by the ‘dput’ function in R. It can be read into R by the ‘dget’ function. Please see the README.txt file for a description of the list elements. See Appendix S2 of the paper for detailed information about the data. The data have the same structure as the data that can be simulated and fit to the RD-SCR model provided in Appendix S3 of the paper

Data from: Thermal plasticity in postembryonic life history traits of a widely distributed Collembola: Effects of macroclimate and microhabitat on genotypic differences

Life history traits in many ectotherms show complex patterns of variation among conspecific populations sampled along wide latitudinal or climatic gradients. However, few studies have assessed whether these patterns can be explained better by thermal reaction norms of multiple life history traits, covering major aspects of the life cycle. In this study, we compared five populations of a Holarctic, numerically dominant soil microarthropod species, Folsomia quadrioculata, sampled from a wide latitudinal gradient (56–81°N), for growth, development, fecundity, and survival across four temperatures (10, 15, 20, and 25°C) in common garden experiments. We evaluated the extent to which macroclimate could explain differences in thermal adaptation and life history strategies among populations. The common garden experiments revealed large genotypic differences among populations in all the traits, which were little explained by latitude and macroclimate. In addition, the life history strategies (traits combined) hardly revealed any systematic difference related to latitude and macroclimate. The overall performance of the northernmost population from the most stochastic microclimate and the southernmost population, which remains active throughout the year, was least sensitive to the temperature treatments. In contrast, performance of the population from the most predictable microclimate peaked within a narrow temperature range (around 15°C). Our findings revealed limited support for macroclimate-based predictions, and indicated that local soil habitat conditions related to predictability and seasonality might have considerable influence on the evolution of life history strategies of F. quadrioculata. This study highlights the need to combine knowledge on microhabitat characteristics, and demography, with findings from common garden experiments, for identifying the key drivers of life history evolution across large spatial scales, and wide climate gradients. We believe that similar approaches may substantially improve the understanding of adaptation in many terrestrial ectotherms with low dispersal ability