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This study provides a regional picture of long‐term changes in Atlantic salmon growth at the southern edge of their distribution, using a multi‐population approach spanning 49 years and five populations. We provide empirical evidence of salmon life history being influenced by a combination of common signals in the marine environment and population‐specific signals. We identified an abrupt decline in growth from 1976 and a more recent decline after 2005. As these declines have also been recorded in northern European populations, our study significantly expands a pattern of declining marine growth to include southern European populations, thereby revealing a large‐scale synchrony in marine growth patterns for almost five decades. Growth increments during their sea sojourn were characterized by distinct temporal dynamics. At a coarse temporal resolution, growth during the first winter at sea seemed to gradually improve over the study period. However, the analysis of finer seasonal growth patterns revealed ecological bottlenecks of salmon life histories at sea in time and space. Our study reinforces existing evidence of an impact of early marine growth on maturation decision, with small‐sized individuals at the end of the first summer at sea being more likely to delay maturation. However, each population was characterized by a specific probabilistic maturation reaction norm, and a local component of growth at sea in which some populations have better growth in some years might further amplify differences in maturation rate. Differences between populations were smaller than those between sexes, suggesting that the sex‐specific growth threshold for maturation is a well‐conserved evolutionary phenomenon in salmon. Finally, our results illustrate that although most of the gain in length occurs during the first summer at sea, the temporal variability in body length at return is buffered against the decrease in post‐smolt growth conditions. The intricate combination of growth over successive seasons, and its interplay with the maturation decision, could be regulating body length by maintaining diversity in early growth trajectories, life histories, and the composition of salmon populations. [ABSTRACT FROM AUTHOR]

Mass mortality events are ubiquitous in nature and can be caused by, for example, diseases, extreme weather and human perturbations such as contamination. Despite being prevalent and rising globally, how mass mortality in early life causes population‐level effects such as reduced total population biomass, is not fully explored. In particular for fish, mass mortality affecting early life may be dampened by compensatory density‐dependent processes. However, due to large variations in year‐class strength, potentially caused by density‐independent variability in survival, the impact at the population level may be high in certain years. We quantify population‐level impacts at two levels of mass mortality (50% and 99% additional mortality) during early life across 40 fish species using age‐structured population dynamics models. The findings from these species‐specific models are further supported by an analysis of detailed stock‐specific models for three of the species. We find that population impacts are highly variable between years and species. Short‐lived species that exhibit a low degree of compensatory density dependence and high interannual variation in survival experience the strongest impacts at the population level. These quantitative and general relationships allow predicting the range of potential impacts of mass mortality events on species based on their life history. This is critical considering that the frequency and severity of mass mortality events are increasing worldwide. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Taxa Methods Results Main Conclusions Ecologically similar species living in sympatry are expected to segregate to reduce the effects of competition where resources are limiting. Segregation from heterospecifics commonly occurs in space, but it is often unknown whether such segregation has underlying environmental causes. Indeed, species could segregate because of different fundamental environmental requirements (i.e., ‘niche divergence’), because competitive exclusion at sympatric sites can force species to either change the habitat use they would have at allopatric sites (i.e., ‘niche displacement’) or to avoid certain areas, independently of habitat (i.e., ‘spatial avoidance’). Testing these hypotheses requires the comparison between sympatric and allopatric sites. Understanding the competitive mechanisms that underlie patterns of spatial segregation could improve predictions of species responses to environmental change, as competition might exacerbate the effects of environmental change.North Atlantic and Arctic.Common guillemots Uria aalge and Brünnich's guillemots Uria lomvia.Here, we examine support for these explanations for spatial segregation in two closely‐related seabird species, common guillemots (Uria aalge) and Brünnich's guillemots (U. lomvia). For this, we collated a pan‐Atlantic data set of breeding season foraging tracks from 1046 individuals, collected from 20 colonies (8 sympatric and 12 allopatric). These were analysed with habitat models in a spatially transferable framework to compare habitat preferences between species at sympatric and allopatric sites.We found no effect of the distribution of heterospecifics on local habitat preferences of the focal species. We found differences in habitat preferences between species, but these were not sufficient to explain the observed levels of spatial segregation at sympatric sites.Assuming we did not omit any relevant environmental variables, these results suggest a mix of niche divergence and spatial avoidance produces the observed patterns of spatial segregation. [ABSTRACT FROM AUTHOR]

Recent advances in biologging open promising perspectives in the study of animal movements at numerous scales. It is now possible to record time series of animal locations and ancillary data (e.g. activity level derived from on‐board accelerometers) over extended areas and long durations with a high spatial and temporal resolution. Such time series are often piecewise stationary, as the animal may alternate between different stationary phases (i.e. characterized by a specific mean and variance of some key parameter for limited periods). Identifying when these phases start and end is a critical first step to understand the dynamics of the underlying movement processes.We introduce a new segmentation‐clustering method we called segclust2d (available as a r package at cran.r-project.org/package=segclust2d). It can segment bivariate (or more generally multivariate) time series and possibly cluster the various segments obtained, corresponding to different phases assumed to be stationary. This method is easy to use, as it only requires specifying a minimum segment length (to prevent over‐segmentation), based on biological rather than statistical considerations.This method can be applied to bivariate piecewise time series of any nature. We focus here on two types of time series related to animal movement, corresponding to (a) at large scale, series of bivariate coordinates of relocations, to highlight temporary home ranges, and (b) at smaller scale, bivariate series derived from relocations data, such as speed and turning angle, to highlight different behavioural modes such as transit, feeding and resting.Using computer simulations, we show that segclust2d can rival and even outperform previous, more complex methods, which were specifically developed to highlight changes of movement modes or home range shifts (based on hidden Markov and Ornstein–Uhlenbeck modelling), which, contrary to our method, usually require the user to provide relevant initial guesses to be efficient. Furthermore, we demonstrate it on actual examples involving a zebra's small‐scale movements and an elephant's large‐scale movements, to illustrate how various movement modes and home range shifts, respectively, can be identified. [ABSTRACT FROM AUTHOR]

Although inter‐individual heterogeneity in many aspects of dispersal behaviour is widely reported, this key life‐history trait is predominantly modelled as a dichotomous state of philopatry versus dispersal. The increasing body of evidence for dispersal syndromes (i.e. a suite of correlated morphological, behavioural and life‐history traits associated with dispersal) implies substantial but, to date, undocumented individual heterogeneity in behavioural tactics during dispersal. Using a large sample (n = 154) of GPS monitored juvenile roe deer Capreolus capreolus, we evaluated among‐individual behavioural heterogeneity in dispersal tactics, and the individual and environmental drivers of these alternative tactics. We developed a sequential three‐stage decision tree based on space use stability, exploration events and the directionality of movement. We identified six discrete alternative behavioural tactics during the dispersal period which were characterised by different timing, amplitude and duration in movement: slightly less than half of the deer were sedentary, either 'strictly philopatric' or 'explorers', which subsequently settled on their natal range; around 40% dispersed ('classic dispersal'), of which, one in six subsequently aborted, moving back to their natal range ('aborted dispersal'); finally, around 15% expressed either a 'progressive dispersal' tactic, gradually moving away from their natal area to settle elsewhere, or a 'multi‐range' tactic. The propensity to express an alternative dispersal tactic was strongly influenced by an individual's local environment. In particular, when landscape heterogeneity, resource quality and human‐related disturbance in the natal range were low, individuals were 1) more likely to adopt the alternative tactics of either progressive dispersal or multi‐ranging, but 2) also more likely to abort their dispersal attempt. Our work indicates that natal dispersal is likely not a single uniform behaviour, but that individuals may adopt a variety of alternative movement tactics which are likely governed by different selection pressures, with potentially important impacts for population dynamics and functioning. [ABSTRACT FROM AUTHOR]