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Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research.This study focuses on a particular strand of research in this area, based around step selection analysis (SSA). SSA is a popular way of inferring drivers of movement decisions, but, perhaps less well appreciated, it also parametrises a model of animal movement. Of key interest is that this model can be propagated forwards in time to predict the space use patterns over broader spatial and temporal scales than those that pertain to the proximate movement decisions of animals.Here, we provide a guide for understanding and using the various existing techniques for scaling up step selection models to predict broad‐scale space use patterns. We give practical guidance on when to use which technique, as well as specific examples together with code in R and Python.By pulling together various disparate techniques into one place, and providing code and instructions in simple examples, we hope to highlight the importance of these techniques and make them accessible to a wider range of ecologists, ultimately helping expand the usefulness of SSA. [ABSTRACT FROM AUTHOR]

Research Highlight: Bond, M. L., Lee, D. E., Ozgul, A., Farine, D. R., & König, B. (2021). Leaving by staying: Social dispersal in giraffes. Journal of Animal Ecology, https://doi. org/10.1111/1365-2656.13582. Dispersal is a key ecological and evolutionary process, which shows marked variability between and within species. The social and kinship structure of species fundamentally affects the patterns and types of dispersal, but information on how animals with fission-fusion group dynamics disperse is missing. Bond et al. provide novel data on natal dispersal of giraffe calves in relation to their dynamic multilayered social system, showing that individuals from both sexes can disperse socially, by switching association with different social groups, without leaving their natal area. The results highlight that traditional spatial-only measures of dispersal, such as dispersal distance, may be inadequate for social species with overlapping social units. [ABSTRACT FROM AUTHOR]

Keywords: accelerometer; animal movement; behaviour; biologging; GPS; modelling; sensor technology; tracking Technological solutions to record the movements, behaviour and physiology of animals, and associated methodological advancements for analysing the data collected, have revolutionized research in animal ecology and beyond (Brisson-Curadeau, Patterson, Whelan, Lazarus, & Elliott, [18]; Kenward, [56]; Ropert-Coudert, Beaulieu, Hanuise, & Kato, [91]; Ropert-Coudert & Wilson, [92]; Weimerskirch, [107]). The general term for this technological approach to study animals is called Biologging - 'the use of miniaturized animal-attached tags for logging and/or relaying data about an animal's movements, behaviour, physiology, and/or environment' (Rutz & Hays, [94]). Thanks to ever smaller loggers which can record an animal's behaviour for ever longer periods of time, biologging is now allowing researchers to study with unprecedented detail how behaviours develop in slow-maturing animals. While an increasing body of research has shown the impact of consistent individual differences in behavioural phenotypes, called animal personalities or behavioural syndromes (Réale et al., [89]; Sih, Bell, Johnson, & Ziemba, [96]), on foraging behaviour, exploratory movements and other spatial behaviours (Bijleveld et al., [12]; Boon, Réale, & Boutin, [15]; Minderman et al., [75]; van Overveld & Matthysen, [103]; Villegas-Ríos, Réale, Freitas, Moland, & Olsen, [105]; Wilson & McLaughlin, [112]), the important relationship between animal personality and foraging site fidelity has not been studied yet. [Extracted from the article]

It is fundamentally important for many animal ecologists to quantify the costs of animal activities, although it is not straightforward to do so. The recording of triaxial acceleration by animal‐attached devices has been proposed as a way forward for this, with the specific suggestion that dynamic body acceleration (DBA) be used as a proxy for movement‐based power.Dynamic body acceleration has now been validated frequently, both in the laboratory and in the field, although the literature still shows that some aspects of DBA theory and practice are misunderstood. Here, we examine the theory behind DBA and employ modelling approaches to assess factors that affect the link between DBA and energy expenditure, from the deployment of the tag, through to the calibration of DBA with energy use in laboratory and field settings.Using data from a range of species and movement modes, we illustrate that vectorial and additive DBA metrics are proportional to each other. Either can be used as a proxy for energy and summed to estimate total energy expended over a given period, or divided by time to give a proxy for movement‐related metabolic power. Nonetheless, we highlight how the ability of DBA to predict metabolic rate declines as the contribution of non‐movement‐related factors, such as heat production, increases.Overall, DBA seems to be a substantive proxy for movement‐based power but consideration of other movement‐related metrics, such as the static body acceleration and the rate of change of body pitch and roll, may enable researchers to refine movement‐based metabolic costs, particularly in animals where movement is not characterized by marked changes in body acceleration. [ABSTRACT FROM AUTHOR]

Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high‐resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data. Most existing methods were designed with smaller data sets in mind and can thus be prohibitively slow. Here, we introduce a method for segmenting high‐resolution movement trajectories into sites of interest and transitions between these sites. This builds on a previous algorithm of Benhamou and Riotte‐Lambert (2012). Adapting it for use with high‐resolution data. The data's resolution removed the need to interpolate between successive locations, allowing us to increase the algorithm's speed by approximately two orders of magnitude with essentially no drop in accuracy. Furthermore, we incorporate a color scheme for testing the level of confidence in the algorithm's inference (high = green, medium = amber, low = red). We demonstrate the speed and accuracy of our algorithm with application to both simulated and real data (Alpine cattle at 1 Hz resolution). On simulated data, our algorithm correctly identified the sites of interest for 99% of "high confidence" paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e.g., food). Our algorithm gives an efficient method for turning a long, high‐resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point‐to‐point analysis techniques such as optimal foraging theory. It is encoded into an R package called SitesInterest, so should serve as a valuable tool for making sense of these increasingly large data streams. We have constructed a new method for identifying sites of interest, tailored specifically for use with high resolution data. This allows for a complicated movement trajectory to be simplified into a "Markov chain‐like" description of behavioural choices, highlighting the animal's broadscale decisions. [ABSTRACT FROM AUTHOR]

Abstract: Demographic senescence is increasingly recognised as an important force shaping the dynamics of wild vertebrate populations. However, our understanding of the processes that underpin these declines in survival and fertility in old age remains limited. Evidence for age‐related changes in foraging behaviour and habitat use is emerging from wild vertebrate studies, but the extent to which these are driven by within‐individual changes, and the consequences for fitness, remain unclear. Using longitudinal census observations collected over four decades from two long‐term individual‐based studies of unmanaged ungulates, we demonstrate consistent within‐individual declines in home range area with age in adult females. In both systems, we found that within‐individual decreases in home range area were associated with increased risk of mortality the following year. Our results provide the first evidence from the wild that age‐related changes in space use are predictive of adult mortality. [ABSTRACT FROM AUTHOR]

Aim: Historically, climate has been a dominant driver of global vegetation patterns. Recently, ecological understanding has been updated to acknowledge the influence of human land use (the dominant driver of biodiversity change) in shaping global vegetation patterns. We test whether Raunkiær's life form, a plant classification system designed to reflect climatic drivers, affects how plants respond to both land use and climate. Location: Forty‐one countries across six continents. Time period: 1990 to 2013. Major taxa studied: Terrestrial plants. Methods: Combining data from the biodiversity and land use database PREDICTS, and plant trait databases TRY and BIEN, we use generalized linear mixed models with weighted effects coding to test whether Raunkiær's life form affects plant response to land use and climate in over 4800 species at over 300 sites globally. Results: We provide evidence that human land use is comparable to climate in influencing life form occurrence and that land use produces divergent outcomes across life forms. Main conclusions: Combined with climatic suitability, land use acts as a filter contracting the realized niche of trees and expanding the realized niche of disturbance‐tolerant species. Our results highlight the fundamental role of human activity in shaping species' distribution. [ABSTRACT FROM AUTHOR]

Home range sizes of territorial animals are often observed to vary periodically in response to seasonal changes in foraging opportunities. Here we develop the first mechanistic model focused on the temporal dynamics of home range expansion and contraction in territorial animals. We demonstrate how simple movement principles can lead to a rich suite of range size dynamics, by balancing foraging activity with defensive requirements and incorporating optimal behavioral rules into mechanistic home range analysis. Our heuristic model predicts three general temporal patterns that have been observed in empirical studies across multiple taxa. First, a positive correlation between age and territory quality promotes shrinking home ranges over an individual’s lifetime, with maximal range size variability shortly before the adult stage. Second, poor sensory information, low population density, and large resource heterogeneity may all independently facilitate range size instability. Finally, aggregation behavior toward forage-rich areas helps produce divergent home range responses between individuals from different age classes. This model has broad applications for addressing important unknowns in animal space use, with potential applications also in conservation and health management strategies. [ABSTRACT FROM AUTHOR]

Wind is an important climatic factor for flying animals as by affecting their locomotion, it can deeply impact their life-history characteristics., In the context of globally changing wind patterns, we investigated the mechanisms underlying recently reported increase in body mass of a population of wandering albatrosses ( Diomedea exulans) with increasing wind speed over time., We built a foraging model detailing the effects of wind on movement statistics and ultimately on mass gained by the forager and mass lost by the incubating partner. We then simulated the body mass of incubating pairs under varying wind scenarios. We tracked the frequency at which critical mass leading to nest abandonment was reached to assess incubation success., We found that wandering albatrosses behave as time minimizers during incubation as mass gain was independent of any movement statistics but decreased with increasing mass at departure. Individuals forage until their energy requirements, which are determined by their body conditions, are fulfilled. This can come at the cost of their partner's condition as mass loss of the incubating partner depended on trip duration. This behaviour is consistent with strategies of long-lived species which favoured their own survival over their current reproductive attempt. In addition, wind speed increased ground speed which in turn reduced trip duration and males foraged further away than females at high ground speed., Contrasted against an independent data set, the simulation performed satisfactorily for males but less so for females under current wind conditions. The simulation predicted an increase in male body mass growth rate with increasing wind speed, whereas females' rate decreased. This trend may provide an explanation for the observed increase in mass of males but not of females. Conversely, the simulation predicted very few nest abandonments, which is in line with the high breeding success of this species and is contrary to the hypothesis that wind patterns impact incubation success by altering foraging movement. [ABSTRACT FROM AUTHOR]

An introduction is presented which discusses various topics within the issue including the effects of individual movements on ecological processes, use of habitat selection to predict species abundances in heterogeneous environments and concept of the movement ecology framework.

Understanding how intraspecific trait variability ( ITV) responds to both abiotic and biotic constraints is crucial to predict how individuals are assembled in plant communities, and how they will be impacted by ongoing global environmental change., Three key functional traits [plant height, leaf area ( LA) and specific leaf area ( SLA)] were assessed to quantify the range of ITV of four dominant plant species along a rainfall gradient in semi-arid Mediterranean shrublands. Variance partitioning and confirmatory multilevel path analyses were used to assess the direct and indirect effects of rainfall, space limitation (crowding) and neighbouring plant traits on ITV., The direct effect of the local neighbourhood on the trait values of subordinate individuals was as strong as the effect of rainfall. The indirect effect of rainfall, however, mediated by the effect of the local neighbourhood on the trait values of subordinate individuals, was weak. Rainfall decreased the height and SLA of subordinate individuals, but increased their LA. Neighbouring plant traits were just as strong predictors as crowding in explaining changes in ITV., Synthesis. Our study provides a framework to disentangle the direct effects of abiotic factors and their indirect effects on ITV mediated by the local neighbourhood. Our results highlight that abiotic and biotic constraints are both substantial sources of trait variations at the individual level, and can blur processes underlying changes in ITV. Considering and disentangling combined sources with an individual perspective would help to refine our predictions for community assembly and functional ecology. [ABSTRACT FROM AUTHOR]

Human-related food resources such as garbage dumps and feeding sites have been shown to significantly influence space use, breeding success and population dynamics in a variety of animal species. In contrast, relatively little is known on the effects of unpredictable sources of food, such as carcasses discarded by hunters, on carnivore species. We evaluated the effect of elephant carcasses, mainly deriving from trophy hunting, on the ranging and feeding behavior of spotted hyenas (Crocuta crocuta) in the Okavango Delta, Botswana. Using data from hyenas monitored before and during carcass availability via GPS radio-collars and camera traps, we investigated changes in ranging and feeding behavior over time. Carcass availability influenced hyenas’ ranging behavior for an average of 10–12 days, after which their movements returned to patterns observed before carcass availability. In particular, we observed an increased spatial clustering of locations and reduced speeds (up to 15% less) between successive locations with carcass availability. Consistent feeding at carcasses during the first two weeks was typical, and some individuals fed from elephant carcasses for as long as 50 days. The impact and conservation value of hunting are often assessed based solely on the effects on the hunted species. Our results show that hunting remains can influence other species and suggest that such extra food could have important effects on critical life history processes and ultimately population dynamics. We recommend conservationists and wildlife managers evaluate management strategies and hunting practices regarding carcass disposal in order to incorporate the potential collateral impacts of hunting on non-hunted species in the same community. [ABSTRACT FROM AUTHOR]

Although observed functional differences between alien and native plant species support the idea that invasions are favoured by niche differentiation ( ND), when considering invasions along large ecological gradients, habitat filtering ( HF) has been proposed to constrain alien species such that they exhibit similar trait values to natives., To reconcile these contrasting observations, we used a multiscale approach using plant functional traits to evaluate how biotic interactions with native species and grazing might determine the functional structure of highly invaded grasslands along an elevation gradient in New Zealand., At a regional scale, functional differences between alien and native plant species translated into nonrandom community assembly and high ND. Alien and native species showed contrasting responses to elevation and the degree of ND between them decreased as elevation increased, suggesting a role for HF. At the plant-neighbourhood scale, species with contrasting traits were generally spatially segregated, highlighting the impact of biotic interactions in structuring local plant communities. A confirmatory multilevel path analysis showed that the effect of elevation and grazing was moderated by the presence of native species, which in turn influenced the local abundance of alien species., Our study showed that functional differences between aliens and natives are fundamental to understand the interplay between multiple mechanisms driving alien species success and their coexistence with natives. In particular, the success of alien species is driven by the presence of native species which can have a negative (biotic resistance) or a positive (facilitation) effect depending on the functional identity of alien species. [ABSTRACT FROM AUTHOR]

• Probabilistic framework for interpreting uncertainty- the probability profile. • Probability profiles describe behavioral variation predicted from machine learning. • Variation inherent in behavior measured with accelerometers incorporated into model. • Show creation of profiles with a random forest and clustered self-organizing map. • Used a matrix-based validation (L1-norm) to evaluate how well the models predict. Many studies of animal distributions use habitat and climactic variables to explain patterns of observed space use. However, without behavioral information, we can only speculate as to why and how these characteristics are important to species persistence. Animal-borne accelerometer and magnetometer data loggers can be used to detect behaviors and when coupled with telemetry improve our understanding of animal space use and habitat requirements. However, these loggers collect tremendous quantities of data requiring automated machine learning techniques to identify patterns in the data. Supervised machine learning requires a set of training signals with known behaviors to train the model to identify the unique signal characteristics associated with each behavior. In contrast, unsupervised approaches aggregate unlabeled signals into groups based purely on signal similarity but, without additional information, do not identify specific behaviors. In this paper, we propose a probabilistic framework for interpreting uncertainty in machine learning techniques—the probability profile—and demonstrate how to post hoc identify behaviors within signal groups. We assess model performance using a matrix-based measure of dissimilarity. We used a Random Forest (RF) and a clustered self-organizing map (CSOM) for comparison and demonstrate the use of a behavioral profile for each using a data set of high-frequency accelerometer and magnetometer data collected from 7 captive wild pigs (Sus scrofa) moving in a 1 ha outdoor enclosure. We found that the RF had more discrimination than the CSOM which had fewer clusters associated with high probabilities of a single behavior (>50%). The leave- p -out cross validation statistic of the probability matrix ( L 1 ¯) indicated that there was an average maximum dissimilarity of 20% and 65% between the training and test data sets for the RF and CSOM methods, respectively. Using a probability profile to describe groups predicted from machine learning allows the variation and error inherent in behavioral prediction to be incorporated directly into the model to better reflect the nuances of behavior derived from accelerometer and/or magnetometer signals. We discuss the data requirements of this framework, demonstrate its application to field data, highlight critical assumptions and caveats, and examine how it may be used to generate new ecological inference. [ABSTRACT FROM AUTHOR]

Habitat filtering ( HF, trait convergence) and niche differentiation ( ND, trait divergence) are known to impact upon plant community structure. Both processes integrate individual responses to the abiotic environment and biotic interactions. Thus, it is difficult to clearly identify the underlying abiotic and biotic factors that ultimately impact community structure by looking at community-level patterns of trait divergence or convergence alone., We used a functional trait-based and multiscale approach to assess how biotic interactions and aridity determine the functional structure of semi-arid shrublands sampled along a large aridity gradient in Spain. At the regional scale, we investigated functional differences among species (axes of specialization) to identify important traits for community assembly. At the community scale, we evaluated the relative impact of HF and ND on community structure using a null model approach. Finally, at the plant neighbourhood scale, we evaluated the impact of biotic interactions on community structure by investigating the spatial patterns of trait aggregation., The shrub species surveyed can be separated along four axes of specialization based on their above-ground architecture and leaf morphology. Our community scale analysis suggested that the functional structure of semi-arid communities was clearly non-random, HF and ND acting independently on different traits to determine community structure along the aridity gradient. At the plant neighbourhood scale, the spatial distribution of species was also clearly not random, suggesting that competition and facilitation impacted on the observed changes in the functional diversity of shrubland communities along the aridity gradient., Synthesis: Our results demonstrated that HF and ND acted simultaneously on independent traits to jointly determine community structure. Most importantly, our multiscale approach suggested that competition and facilitation interplayed with aridity to determine this structure. Competition appeared to be constant along the aridity gradient and explained the high functional diversity observed in semi-arid shrublands. Facilitation affected subordinate and rare species and, thus, may act to enhance the biodiversity of these ecosystems. Finally, the framework employed in our study allows moving forward from the examination of patterns to the development of mechanistic trait-based approaches to study plant community assembly. [ABSTRACT FROM AUTHOR]

Statisticians frequently voice concern that their interactions with applied researchers start only after data have been collected. The same can be said for our experience with home-range studies. Too often, conversations about home range begin with questions concerning estimation methods, smoothing parameters, or the nature of autocorrelation. More productive efforts start by asking good (and interesting) research questions; once these questions are defined, it becomes possible to ask how various design and analysis strategies influence one's ability to answer these questions. With this process in mind, we address key sample-design and data-analysis issues related to the topic of home range. The impact of choosing a particular home-range estimator (e.g., minimum convex polygon, kernel density estimator, or local convex hull) will be question dependent, and for some problems other movement or use-based metrics (e.g., mean step lengths or time spent in particular areas) may be worthy of consideration. Thus, we argue the need for more question-driven and focused research and for clearly distinguishing the biological concept of an animal's home range from the statistical quantities one uses to investigate this concept. For comparative studies, it is important to standardize sampling regimes and estimation methods as much as possible, and to pay close attention to missing data issues. More attention should also be given to temporally changing space-use patterns, with biologically meaningful time periods (e.g., life-history stages) used to define sampling periods. Last, we argue the need for closer connections between theoretical and empirical researchers. Advances in ecological theory, and its application to natural resources management, will require carefully designed research studies to test theoretical predictions from more mechanistic modeling approaches. [ABSTRACT FROM AUTHOR]

Animal migration has long intrigued scientists and wildlife managers alike, yet migratory species face increasing challenges because of habitat fragmentation, climate change and over-exploitation. Central to the understanding migratory species is the objective discrimination between migratory and nonmigratory individuals in a given population, quantifying the timing, duration and distance of migration and the ability to predict migratory movements. Here, we propose a uniform statistical framework to (i) separate migration from other movement behaviours, (ii) quantify migration parameters without the need for arbitrary cut-off criteria and (iii) test predictability across individuals, time and space. We first validated our novel approach by simulating data based on established theoretical movement patterns. We then formulated the expected shapes of squared displacement patterns as nonlinear models for a suite of movement behaviours to test the ability of our method to distinguish between migratory movement and other movement types. We then tested our approached empirically using 108 wild Global Positioning System (GPS)-collared moose Alces alces in Scandinavia as a study system because they exhibit a wide range of movement behaviours, including resident, migrating and dispersing individuals, within the same population. Applying our approach showed that 87% and 67% of our Swedish and Norwegian subpopulations, respectively, can be classified as migratory. Using nonlinear mixed effects models for all migratory individuals we showed that the distance, timing and duration of migration differed between the sexes and between years, with additional individual differences accounting for a large part of the variation in the distance of migration but not in the timing or duration. Overall, the model explained most of the variation (92%) and also had high predictive power for the same individuals over time (69%) as well as between study populations (74%). The high predictive ability of the approach suggests that it can help increase our understanding of the drivers of migration and could provide key quantitative information for understanding and managing a broad range of migratory species. [ABSTRACT FROM AUTHOR]

Home range behaviour is a common pattern of space use, having fundamental consequences for ecological processes. However, a general mechanistic explanation is still lacking. Research is split into three separate areas of inquiry – movement models based on random walks, individual-based models based on optimal foraging theory, and a statistical modelling approach – which have developed without much productive contact. Here we review recent advances in modelling home range behaviour, focusing particularly on the problem of identifying mechanisms that lead to the emergence of stable home ranges from unbounded movement paths. We discuss the issue of spatiotemporal scale, which is rarely considered in modelling studies, as well as highlighting the need to consider more closely the dynamical nature of home ranges. Recent methodological and theoretical advances may soon lead to a unified approach, however, conceptually unifying our understanding of linkages among home range behaviour and ecological or evolutionary processes. [ABSTRACT FROM AUTHOR]

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis. [ABSTRACT FROM AUTHOR]

Animal home range use is a central focus of ecological research. However, how and why home range size varies between individuals is not well studied or understood for most species. We develop a hierarchical analytical approach—using generalized linear mixed-effects modeling of time series of home range sizes—that allows variance in home range size to be decomposed into components due to variation in temporal, spatial, and individual-level processes, also facilitating intra- and interspecific comparative analyses. We applied the approach to data from a roe deer population radiotracked in central Italy. Over multiple timescales, temporal variation is explained by photoperiod and climate and spatial variation by the distribution of habitat types and spatial variance in radio-tracking error. Differences between individuals explained a substantial amount of variance in home range size, but only a relatively minor part was explained by the individual attributes of sex and age. We conclude that the choice of temporal scale at which data are collected and the definition of home range can significantly influence biological inference. We suggest that the appropriate choice of scale and definition requires a good understanding of the ecology and life history of the study species. Our findings contrast with several common assumptions about roe deer behavior. [ABSTRACT FROM AUTHOR]

We model the growth, dispersal and mutation of two phenotypes of a species using reaction–diffusion equations, focusing on the biologically realistic case of small mutation rates. Having verified that the addition of a small linear mutation term to a Lotka–Volterra system limits it to only two steady states in the case of weak competition, an unstable extinction state and a stable coexistence state, we exploit the fact that the spreading speed of the system is known to be linearly determinate to show that the spreading speed is a nonincreasing function of the mutation rate, so that greater mixing between phenotypes leads to slower propagation. We also find the ratio at which the phenotypes occur at the leading edge in the limit of vanishing mutation. [ABSTRACT FROM AUTHOR]

Wind is fundamentally related to shelter and flight performance: two factors that are critical for birds at their nest sites. Despite this, airflows have never been fully integrated into models of breeding habitat selection, even for well‐studied seabirds. Here, we use computational fluid dynamics to provide the first assessment of whether flow characteristics (including wind speed and turbulence) predict the distribution of seabird colonies, taking common guillemots Uria aalge breeding on Skomer Island as our study system. This demonstrates that occupancy is driven by the need to shelter from both wind and rain/wave action, rather than airflow characteristics alone. Models of airflows and cliff orientation both performed well in predicting high‐quality habitat in our study site, identifying 80% of colonies and 93% of avoided sites, as well as 73% of the largest colonies on a neighbouring island. This suggests generality in the mechanisms driving breeding distributions and provides an approach for identifying habitat for seabird reintroductions considering current and projected wind speeds and directions. [ABSTRACT FROM AUTHOR]

There are numerous examples of phenological shifts that are recognized both as indicators of climate change and drivers of ecosystem change. A pressing challenge is to understand the causal mechanisms by which climate affects phenology. We combined annual population census data and individual longitudinal data (1992-2018) on grey seals, Halicheorus grypus, to quantify the relationship between pupping season phenology and sea surface temperature. A temperature increase of 2°C was associated with a pupping season advance of approximately seven days at the population level. However, we found that maternal age, rather than sea temperature, accounted for changes in pupping date by individuals. Warmer years were associated with an older average age of mothers, allowing us to explain phenological observations in terms of a changing population age structure. Finally, we developed a matrix population model to test whether our observations were consistent with changes to the stable age distribution. This could not fully account for observed phenological shift, strongly suggesting transient modification of population age structure, for example owing to immigration. We demonstrate a novel mechanism for phenological shifts under climate change in long-lived, age- or stage-structured species with broad implications for dynamics and resilience, as well as population management. [ABSTRACT FROM AUTHOR]

Sleep serves vital physiological functions, yet how sleep in wild animals is influenced by environmental conditions is poorly understood. Here we use high-resolution biologgers to investigate sleep in wild animals over ecologically relevant time scales and quantify variability between individuals under changing conditions. We developed a robust classification for accelerometer data and measured multiple dimensions of sleep in the wild boar (Sus scrofa) over an annual cycle. In support of the hypothesis that environmental conditions determine thermoregulatory challenges, which regulate sleep, we show that sleep quantity, efficiency and quality are reduced on warmer days, sleep is less fragmented in longer and more humid days, while greater snow cover and rainfall promote sleep quality. Importantly, this longest and most detailed analysis of sleep in wild animals to date reveals large inter- and intra-individual variation. Specifically, short-sleepers sleep up to 46% less than long-sleepers but do not compensate for their short sleep through greater plasticity or quality, suggesting they may pay higher costs of sleep deprivation. Given the major role of sleep in health, our results suggest that global warming and the associated increase in extreme climatic events are likely to negatively impact sleep, and consequently health, in wildlife, particularly in nocturnal animals. [ABSTRACT FROM AUTHOR]

An individual's future behaviour and fitness are strongly influenced by early life experience. Within the suite of factors that underpin juvenile development, sleep plays a particularly important role, fulfilling vital physiological and cognitive functions. Sleep ontogeny is the process by which sleep time becomes shorter and more consolidated into fewer bouts from in utero development to adulthood; however, how sleep quantity, fragmentation and quality develop in neonates in the wild is unknown. We investigated this question in 19 free-ranging fallow deer fawns, Dama dama , during the first 5 weeks of life. Specifically, we examined how sleep developed, how it differed between and within individuals, and how it was affected by environmental conditions, using accelerometer-derived estimates of sleep and a Bayesian hierarchical modelling approach. We showed that sleep duration rapidly decreased and became more consolidated, quickly approaching an adult-like condition. Moreover, fawns exhibited consistent individual differences in sleep quantity, fragmentation and quality, as well as in the rate at which sleep developed. Finally, environmental conditions affecting thermoregulation mediated sleep behaviour; sleep time was reduced and was of lower quality on warmer days, and sleep quality was further compromised in more humid conditions but was higher with greater rainfall. While sleep ontogeny in free-ranging fawns is partially shaped by the environment, our study reveals previously unknown individual differences in sleep behaviour present from birth, and in the rate of sleep development. We suggest that such individual differences may represent pace-of-life syndromes and may have important consequences for individual fitness later in life. • Fallow deer fawns' sleep rapidly decreases and consolidates in their first 5 weeks. • Fawns differ in sleep patterns and the rate of development from birth. • High temperature and humidity impair fawns' sleep. • Individual differences in sleep ontogeny may be related to pace-of-life syndromes. • Minimally invasive biologging is a viable approach to studying sleep in the wild. [ABSTRACT FROM AUTHOR]

Many animals return to their home areas (i.e., ‘homing’) after translocation to sites further away. Such translocations have traditionally been used in behavioral ecology to understand the orientation and migration behavior of animals. The movement itself can then be followed by marking and recapturing animals or by tracking, for example, using GPS systems. Most detailed studies investigating this behavior have been conducted in smaller vertebrates (e.g., birds, amphibians, and mice), whereas information on larger mammals, such as red deer, is sparse. We conducted GPS-assisted translocation experiments with red deer at two sites in the Czech Republic. Individuals were translocated over a distance of approximately 11 km and their home journey was tracked. Circular statistics were used to test for significant homeward orientation at distances of 100, 500, 1000, and 5000 m from the release site. In addition, we applied Lavielle trajectory segmentation to identify the different phases of homing behavior. Thirty-one out of 35 translocations resulted in successful homing, with a median time of 4.75 days (range 1.23–100 days). Animals were significantly oriented towards home immediately after release and again when they came closer to home; however, they did not show a significant orientation at the distances in between. We were able to identify three homing phases, an initial ‘exploratory phase’, followed by a ‘homing phase’ which sometimes was again followed by an ‘arrival phase’. The ‘homing phase’ was characterized by the straightest paths and fastest movements. However, the variation between translocation events was considerable. We showed good homing abilities of red deer after translocation. Our results demonstrate the feasibility of conducting experiments with environmental manipulations (e.g., to impede the use of sensory cues) close to the release site. The homing behavior of red deer is comparable to that of other species, and might represent general homing behavior patterns in animals. Follow-up studies should further dissect and investigate the drivers of the individual variations observed and try to identify the sensory cues used during homing. [ABSTRACT FROM AUTHOR]

Conservation and population management decisions often rely on population models parameterized using census data. However, the sampling regime, precision, sample size, and methods used to collect census data are usually heterogeneous in time and space. Decisions about how to derive population‐wide estimates from this patchwork of data are complicated and may bias estimated population dynamics, with important implications for subsequent management decisions.Here, we explore the impact of site selection and data aggregation decisions on pup survival estimates, and downstream estimates derived from parameterized matrix population models (MPMs), using a long‐term dataset on grey seal (Halichoerus grypus) pup survival from southwestern Wales. The spatiotemporal and methodological heterogeneity of the data are fairly typical for ecological census data and it is, therefore, a good model to address this topic.Data were collected from 46 sampling locations (sites) over 25 years, and we explore the impact of data handling decisions by varying how years and sampling locations are combined to parameterize pup survival in population‐level MPMs. We focus on pup survival because abundant high‐quality data are available on this developmental stage.We found that survival probability was highly variable with most variation being at the site level, and poorly correlated among sampling sites. This variation could generate marked differences in predicted population dynamics depending on sampling strategy. The sample size required for a confident survival estimate also varied markedly geographically.We conclude that for populations with highly variable vital rates among sub‐populations, site selection and data aggregation methods are important. In particular, including peripheral or less frequently used areas can introduce substantial variation into population estimates. This is likely to be context‐dependent, but these choices, including the use of appropriate weights when summarizing across sampling areas, should be explored to ensure that management actions are successful. [ABSTRACT FROM AUTHOR]

Macrophytes play important functional roles in river ecosystems, providing habitat and food, as well as influencing flow, water chemistry, and sediment dynamics. They also represent an important component of river biodiversity.Artificial river barriers have the potential to disrupt macrophyte dispersal, and compromise their distribution and persistence, but little information is available compared to barrier impacts on fish and macroinvertebrates. Here, we review the mechanisms supporting dispersal of river macrophytes in rivers and evaluate the nature of barrier impacts on macrophytes.Hydrochory (dispersal of propagules by water) is the principal mechanism of downstream dispersal, while zoochory (dispersal of propagules by animals) is likely to be the most important vector of upstream dispersal and inter‐catchment transport.Most studies have focused on the impact of large structures such as dams, and the findings indicate the impact is highly context dependent. Slow‐flowing habitats upstream of dams can act as traps to drifting propagules and thereby interrupt hydrochory. However, the consequences of interrupted hydrochory for downstream populations are unclear. River regulation can result in lower macrophyte diversity, although the lentic habitats associated with reservoirs can also favour an increase in the abundance and richness of macrophyte communities.Instream barriers are unlikely to affect zoochory by birds directly, but barriers are well known to restrict fish movements, so there is considerable potential for barriers to disrupt zoochory by fish, although no empirical study has specifically examined this possibility.There is a paucity of studies examining the impacts of low‐head barriers on macrophyte dispersal. Given the influence of macrophytes on river processes, we call for further research into barrier impacts on macrophyte population dynamics in order to gain a better understanding of the consequences of river fragmentation for fluvial communities and ecosystem functioning. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems rank among the most endangered ecosystems in the world and are under increasing threat from aquatic invasive species (AIS). Understanding the range expansion of AIS is key for mitigating their impacts. Most approaches rely on Species Distribution Models (SDMs) to predict the expansion of AIS, using mainly environmental variables, yet ignore the role of human activities in favouring the introduction and range expansion of AIS. In this study, we use five SDM algorithms (independently and in ensemble) and two accuracy measures (TSS, AUC), combined with a null modelling approach, to assess the predictive performance of the models and to quantify which predictors (environmental and anthropogenic from the native and introduced regions) best explain the distribution of nine freshwater invasive species (including fish, arthropods, molluscs, amphibians and reptiles) in a large island (Great Britain), and which species characteristics affect model performance. Our results show that the distribution of invasive species is difficult to predict by SDMs, even in cases when TSS and AUC model accuracy values are high. Our study strongly advocates the use of null models for testing SDMs performance and the inclusion of information from the native area and a variety of both human-related and environmental predictors for a more accurate modelling of the range expansion of AIS. Otherwise, models that only include climatic variables, or rely only on standard accuracy measures or a single algorithm, might result in mismanagement of AIS. [ABSTRACT FROM AUTHOR]

Animal‐attached technologies can be powerful means to quantify space use and behavior; however, there are also ethical implications associated with capturing and instrumenting animals. Furthermore, tagging approaches are not necessarily well‐suited for examining the movements of multiple individuals within specific, local areas of interest. Here, we assess a method of quantifying animal space use based on a modified theodolite with an inbuilt laser rangefinder. Using a database of >4200 tracks of migrating birds, we show that detection distance increases with bird body mass (range 5 g to >10 kg). The maximum distance recorded to a bird was 5500 m and measurement error was ≤5 m for targets within this distance range: a level comparable to methods such as GPS tagging. We go on to present a case study where this method was used to assess habitat selection in seabirds operating in dynamic coastal waters close to a tidal turbine. Combining positional data with outputs from a hydrographic model revealed that great cormorants (Phalacrocorax carbo) appeared to be highly selective of current characteristics in space and time, exploiting areas where mean current speeds were <0.8 m·s−1 and diving at times when turbulent energy levels were low. These birds also oriented into tidal currents during dives. Taken together, this suggests that collision risks are low for cormorants at this site, as the 2 conditions avoided by cormorants (high mean current speeds and turbulence levels) are associated with operational tidal turbines. Overall, we suggest that this modified theodolite system is well‐suited to the quantification of movement in small areas associated with particular development strategies, including sustainable energy devices. [ABSTRACT FROM AUTHOR]

Mammals use thermoregulatory behavioural strategies to reduce the cost of physiological thermoregulation. Environmental temperatures should, therefore, impact their decisions. We investigated the effect of environmental temperature on the movement decisions of a large mammal with low capacity for physiological thermoregulation: the giant anteater, Myrmecophaga tridactyla. We GPS-tracked 14 giant anteaters in the Brazilian Pantanal wetland over 5 years. We used hidden Markov models to identify two behavioural states (encamping, as a proxy of resting, and moving, as a proxy of being active) across individuals' trajectories. Then, we estimated the effect of environmental temperature on the probability of moving across the hours of the day in open and forested habitats. We also used integrated step selection analysis to understand how environmental temperature drives giant anteater's habitat selection across the day. Giant anteaters showed three important behavioural thermoregulatory strategies in response to environmental temperature changes: they modulated activity duration, completely shifted activity period on a scale of days and selected forests as thermal shelters. With increasing environmental temperature, giant anteaters increased activity duration, nocturnality and diurnal selection for forests, increasing energy intake while avoiding heat gain by solar radiation. With decreasing environmental temperature, they decreased activity duration, increased diurnality and increased nocturnal selection for forests, thus gaining heat from solar radiation when active and taking shelter in milder microclimates when resting. Besides their high short-term behavioural plasticity regarding activity, giant anteaters also used forests to thermoregulate. These results provide insights into how other mammals could respond to climate change. In particular, we highlight the importance of forests as thermal shelters, offering milder temperatures than adjacent open areas during both hot and cold weather spells. Thermal shelters will become more and more indispensable to animal thermoregulation as the frequency and intensity of extreme weather events increase. • Anteaters use activity modulation as a behavioural strategy to thermoregulate. • Anteaters selected forests as thermal shelters. • Anteaters show the importance of forests to mammals' thermoregulation. • Deforestation should intensify climate change effects on mammals' homeostasis. [ABSTRACT FROM AUTHOR]

Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and trade‐offs, and testing the repeatability of evolutionary outcomes.Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short‐lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco‐evolutionary consequences of dispersal.We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes. [ABSTRACT FROM AUTHOR]

Agro-ecosystems constitute essential habitat for many organisms. Agricultural intensification, however, has caused a strong decline of farmland biodiversity. Organic farming (OF) is often presented as a more biodiversity-friendly practice, but the generality of the beneficial effects of OF is debated as the effects appear often species- and context-dependent, and current research has highlighted the need to quantify the relative effects of local- and landscape-scale management on farmland biodiversity. Yet very few studies have investigated the landscape-level effects of OF; that is to say, how the biodiversity of a field is affected by the presence or density of organically farmed fields in the surrounding landscape. We addressed this issue using the metacommunity framework, with weed species richness in winter wheat within an intensively farmed landscape in France as model system. Controlling for the effects of local and landscape structure, we showed that OF leads to higher local weed diversity and that the presence of OF in the landscape is associated with higher local weed biodiversity also for conventionally farmed fields, and may reach a similar biodiversity level to organic fields in field margins. Based on these results, we derive indications for improving the sustainable management of farming systems. [ABSTRACT FROM AUTHOR]

Abstract: Dispersal is a key process governing the dynamics of socially and spatially structured populations and involves three distinct stages: emigration, transience and settlement. At each stage, individuals have to make movement decisions, which are influenced by social, environmental and individual factors. Yet, a comprehensive understanding of the drivers that influence such decisions is still lacking, particularly for the transient stage during which free‐living individuals are inherently difficult to follow. Social circumstances such as the likelihood of encountering conspecifics can be expected to strongly affects decision‐making during dispersal, particularly in territorial species where encounters with resident conspecifics are antagonistic. Here, we analysed the movement trajectories of 47 dispersing coalitions of Kalahari meerkats Suricata suricatta through a landscape occupied by constantly monitored resident groups, while simultaneously taking into account environmental and individual characteristics. We used GPS locations collected on resident groups to create a georeferenced social landscape representing the likelihood of encountering resident groups. We used a step‐selection function to infer the effect of social, environmental and individual covariates on habitat selection during dispersal. Finally, we created a temporal mismatch between the social landscape and the dispersal event of interest to identify the temporal scale at which dispersers perceive the social landscape. Including information about the social landscape considerably improved our representation of the dispersal trajectory compared to analyses that only accounted for environmental variables. The latter were only marginally selected or avoided by dispersers. Before leaving their natal territory, dispersers selected areas frequently used by their natal group. In contrast, after leaving their natal territory, they selectively used areas where they were less likely to encounter unrelated groups. This pattern was particularly marked in larger dispersing coalitions and when unrelated males were part of the dispersing coalition. Our results suggest that, in socially and spatially structured species, dispersers gather and process social information during dispersal, and that reducing risk of aggression from unrelated resident groups outweighs benefits derived from conspecific attraction. Finally, our work underlines the intimate link between the social structure of a population and dispersal, which affect each other reciprocally. [ABSTRACT FROM AUTHOR]

Trait-based approaches represent a promising way to understand how trophic interactions shape animal communities. The approach relies on the identification of the traits that mediate the linkages between adjacent trophic levels, i.e. 'trait-matching'. Yet, how trait-matching explains the abundance and diversity of animal communities has been barely explored. This question may be particularly critical in the context of land-use intensification, currently threatening biodiversity and associated ecosystem services., We collected a large dataset on plant and grasshopper traits from communities living in 204 grasslands, in an intensively managed agricultural landscape. We used a multi-trait approach to quantify the relative contributions of trait-matching and land-use intensification acting at both local and landscape scales on grasshopper functional diversity. We considered two key independent functional traits: incisor strength and body size of grasshopper species. Incisor strength, a resource-acquisition trait, strongly matches grasshopper feeding niche. Body size correlates with mobility traits, and may determine grasshopper dispersal abilities., Plant functional diversity positively impacted the diversity of grasshopper resource-acquisition traits, according to the degree of trait-matching observed between plants and herbivores. However, this positive effect was significantly higher in old grasslands. In addition, the presence of specific habitats in the landscape (i.e. wood and alfalfa) strongly enhanced grasshopper resource-acquisition trait diversity in the focal grassland. Finally, grasshopper body size increased with landscape simplification, although the response was modulated by local factors such as soil depth., Trait-matching between plants and herbivores was an important driver explaining the abundance and diversity of resource-acquisition traits within grasshopper communities. However, the presence of specific habitats in the surrounding landscape had also a strong influence on herbivore functional diversity in grasslands. Our study suggests that also mass effects are a central mechanism promoting higher functional diversity within animal communities in highly disturbed anthropogenic systems., A is available for this article. [ABSTRACT FROM AUTHOR]

One of the predicted consequences of climate change is a shift in body mass distributions within animal populations. Yet body mass, an important component of the physiological state of an organism, can affect key life-history traits and consequently population dynamics. Over the past decades, the wandering albatross--a pelagic seabird providing bi-parental care with marked sexual size dimorphism--has exhibited an increase in average body mass and breeding success in parallel with experiencing increasing wind speeds. To assess the impact of these changes, we examined how body mass affects five key life-history traits at the individual level: adult survival, breeding probability, breeding success, chick mass and juvenile survival. We found that male mass impacted all traits examined except breeding probability, whereas female mass affected none. Adult male survival increased with increasing mass. Increasing adult male mass increased breeding success and mass of sons but not of daughters. Juvenile male survival increased with their chick mass. These results suggest that a higher investment in sons by fathers can increase their inclusive fitness, which is not the case for daughters. Our study highlights sex-specific differences in the effect of body mass on the life history of a monogamous species with bi-parental care. [ABSTRACT FROM AUTHOR]

Addressing ongoing biodiversity loss requires collaboration between conservation scientists and practitioners. However, such collaboration has proved challenging. Despite the potential importance of tracking animal movements for conservation, reviews of the tracking literature have identified a gap between the academic discipline of movement ecology and its application to biodiversity conservation. Through structured conversations with movement ecologists and conservation practitioners, we aimed to understand whether the identified gap is also perceived in practice, and if so, what factors hamper collaboration and how these factors can be remediated. We found that both groups are motivated and willing to collaborate. However, because their motivations differ, there is potential for misunderstandings and miscommunications. In addition, external factors such as funder requirements, academic metrics, and journal scopes may limit the applicability of scientific results in a conservation setting. Potential solutions we identified included improved communication and better presentation of results, acknowledging each other's motivations and desired outputs, and adjustment of funder priorities. Addressing gaps between science and implementation can enhance collaboration and support conservation action to address the global biodiversity crisis more effectively. [ABSTRACT FROM AUTHOR]

Understanding the role of traits in dispersal is necessary to improve our knowledge of historical biogeography, community assembly processes and predictions of species' future movements. Here we aimed to determine the relationship between three traits (coastal distribution, body size, position on the fast/slow life history continuum) and past dispersal probability on an evolutionary timescale in chameleons (Chamaeleonidae). Using species' distribution data we identified the nine most important biogeographic regions for all included chameleons (181/217 species). We compiled life history trait data and used phylogenetic factor analysis to infer independent body size and fast/slow life history trait axes. Finally, we tested whether traits and trait combinations related to biogeographic dispersal success in the past, using trait‐dependent biogeographic models. All three traits were associated with past biogeographical movements. Lineages having coastal distributions and those with large bodies had higher dispersal probabilities. Interestingly, chameleons with either a very fast or very slow life history were more successful dispersers than species with an intermediate strategy. Together, the three traits – coastal, large‐bodied and extreme life history – form a dispersal syndrome. Traits have played an important role in the biogeographic history of chameleons. While only fast traits have been linked to present‐day invasion success in reptiles, both extremes of the life history spectrum were likely advantageous for dispersal and establishment during past biogeographic movements. Fast‐living species may be less susceptible to stochastic extinction in the first phases of a colonization (due to rapid population growth), and slow‐living species may be less vulnerable to environmental stochasticity (due to low demographic variability). Our results call for broader analyses testing the general influence of life history strategy in biogeographic dispersal success, which would help explain species distribution patterns on Earth. [ABSTRACT FROM AUTHOR]

1. Impediments to animal movement are ubiquitous and vary widely in both scale and permeability. It is essential to understand how impediments alter ecological dynamics via their influence on animal behavioural strategies governing space use and, for anthropogenic features such as roads and fences, how to mitigate these effects to effectively manage species and landscapes. 2. Here, we focused primarily on barriers to movement, which we define as features that cannot be circumnavigated but may be crossed. Responses to barriers will be influenced by the movement capabilities of the animal, its proximity to the barriers, and habitat preference. We developed a mechanistic modelling framework for simultaneously quantifying the permeability and proximity effects of barriers on habitat preference and movement. 3. We used simulations based on our model to demonstrate how parameters on movement, habitat preference and barrier permeability can be estimated statistically. We then applied the model to a case study of road effects on wild mountain reindeer summer movements. 4. This framework provided unbiased and precise parameter estimates across a range of strengths of preferences and barrier permeabilities. The quality of permeability estimates, however, was correlated with the number of times the barrier is crossed and the number of locations in proximity to barriers. In the case study we found that reindeer avoided areas near roads and that roads are semi-permeable barriers to movement. There was strong avoidance of roads extending up to c. 1 km for four of five animals, and having to cross roads reduced the probability of movement by 68.6% (range 3.5-99.5%). 5. Human infrastructure has embedded within it the idea of networks: nodes connected by linear features such as roads, rail tracks, pipelines, fences and cables, many of which divide the landscape and limit animal movement. The unintended but potentially profound consequences of infrastructure on animals remain poorly understood. The rigorous framework for simultaneously quantifying movement, habitat preference and barrier permeability developed here begins to address this knowledge gap. [ABSTRACT FROM AUTHOR]

Using trait-based approaches to study trophic interactions may represent one of the most promising approaches to evaluate the impact of trophic interactions on ecosystem functioning. To achieve this goal, it is necessary to clearly identify which traits determine the impact of one trophic level on another., Using functionally contrasting grasshopper species, we tested the ability of multiple traits (morphological, chemical and biomechanical) to predict herbivore impact on the biomass of a diverse plant community. We set-up a cage experiment in an old species rich grassland field and evaluated how multiple candidate grasshopper effect traits mediated herbivore impact on plant biomass., Grasshoppers had different impact on plant community biomass (consuming up to 60% of plant community biomass). Grasshopper impact was positively correlated with their incisive strength while body size or grasshopper C:N ratio exhibited low predictive ability. Importantly, the strong relationship between the incisive strength and the impact was mediated by the grasshopper feeding niche, which was well predicted in our study by two simple plant traits (leaf dry matter content, leaf C:N ratio). Feeding niche differences between grasshoppers were explained by differences in incisive strength, highlighting the fundamental linkage between grasshopper effect traits and their niche., Our study contributes to the development of the trait-based approach in the study of trophic interactions by providing a first experimental test of the relationship between herbivore effect traits, their impact on plant community biomass, and in a larger extent on ecosystem functioning. By comparing the relative importance of multiple interacting grasshopper traits, our study showed that incisive strength was a key effect trait which determined grasshopper feeding niche and its relative impact on plant community biomass. [ABSTRACT FROM AUTHOR]

The biomedical literature has consistently highlighted that long-term elevation of glucocorticoids might impair immune functions. However, patterns are less clear in wild animals. Here, we re-explored the stress–immunity relationship considering the potential effects of behavioural profiles. Thirteen captive roe deer (Capreolus capreolus) were monitored over an eight-week period encompassing two capture events. We assessed how changes in baseline faecal cortisol metabolite (FCM) concentrations following a standardized capture protocol and an immune challenge using anti-rabies vaccination affected changes in 13 immune parameters of innate and adaptive immunity, and whether these changes in baseline FCM levels and immune parameters related to behavioural profiles. We found that individuals with increased baseline FCM levels also exhibited increased immunity and were characterized by more reactive behavioural profiles (low activity levels, docility to manipulation and neophilia). Our results suggest that the immunity of large mammals may be influenced by glucocorticoids, but also behavioural profiles, as it is predicted by the pace-of-life syndrome hypothesis. Our results highlight the need to consider covariations between behaviour, immunity and glucocorticoids in order to improve our understanding of the among-individual variability in the stress–immunity relationships observed in wildlife, as they may be underpinned by different life-history strategies. [ABSTRACT FROM AUTHOR]

The energetic gains from foraging and costs of movement are expected to be key drivers of animal decision‐making, as their balance is a large determinant of body condition and survival. This fundamental perspective is often missing from habitat selection studies, which mainly describe correlations between space use and environmental features, rather than the mechanisms behind these correlations.To address this gap, we present a novel parameterisation of step selection functions (SSFs), that we term the energy selection function (ESF). In this model, the likelihood of an animal selecting a movement step depends directly on the corresponding energetic gains and costs, and we can therefore assess how moving animals choose habitat based on energetic considerations.The ESF retains the mathematical convenience and practicality of other SSFs and can be quickly fitted using standard software. In this article, we outline a workflow, from data gathering to statistical analysis, and use a case study of polar bears Ursus maritimus to demonstrate application of the model.We explain how defining gains and costs at the scale of the movement step allows us to include information about resource distribution, landscape resistance and movement patterns. We further demonstrate this process with a case study of polar bears and show how the parameters can be interpreted in terms of selection for energetic gains and against energetic costs.The ESF is a flexible framework that combines the energetic consequences of both movement and resource selection, thus incorporating a key mechanism into habitat selection analysis. Further, because it is based on familiar habitat selection models, the ESF is widely applicable to any study system where energetic gains and costs can be derived, and has immense potential for methodological extensions. [ABSTRACT FROM AUTHOR]

Because many large mammal species have wide geographical ranges, spatially distant populations may be confronted with different sets of environmental conditions. Investigating how home range ( HR) size varies across environmental gradients should yield a better understanding of the factors affecting large mammal ecology., We evaluated how HR size of a large herbivore, the roe deer ( Capreolus capreolus), varies in relation to seasonality, latitude (climate), weather, plant productivity and landscape features across its geographical range in Western Europe. As roe deer are income breeders, expected to adjust HR size continuously to temporal variation in food resources and energetic requirements, our baseline prediction was for HR size to decrease with proxies of resource availability., We used GPS locations of roe deer collected from seven study sites ( EURODEER collaborative project) to estimate fixed-kernel HR size at weekly and monthly temporal scales. We performed an unusually comprehensive analysis of variation in HR size among and within populations over time across the geographical range of a single species using generalized additive mixed models and linear mixed models, respectively., Among populations, HR size decreased with increasing values for proxies of forage abundance, but increased with increases in seasonality, stochastic variation of temperature, latitude and snow cover. Within populations, roe deer HR size varied over time in relation to seasonality and proxies of forage abundance in a consistent way across the seven populations. Thus, our findings were broadly consistent across the distributional range of this species, demonstrating a strong and ubiquitous link between the amplitude and timing of environmental seasonality and HR size at the continental scale., Overall, the variability in average HR size of roe deer across Europe reflects the interaction among local weather, climate and seasonality, providing valuable insight into the limiting factors affecting this large herbivore under contrasting conditions. The complexity of the relationships suggests that predicting ranging behaviour of large herbivores in relation to current and future climate change will require detailed knowledge not only about predicted increases in temperature, but also how this interacts with factors such as day length and climate predictability. [ABSTRACT FROM AUTHOR]

Background: Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. Methods and results: Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. Conclusions: We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal–barrier interactions and foraging strategies. [ABSTRACT FROM AUTHOR]

Deterministic niche-based processes have been proposed to explain species relative abundance within communities but lead to different predictions: habitat filtering ( HF) predicts dominant species to exhibit similar traits while niche differentiation ( ND) requires that species have dissimilar traits to coexist., Using a multiple trait-based approach, we evaluated the relative roles of HF and ND in determining species abundances in productive grasslands. Four dimensions of the functional niche of 12 co-occurring grass species were identified using 28 plant functional traits. Using this description of the species niche, we investigated patterns of functional similarity and dissimilarity and linked them to abundance in randomly assembled six-species communities subjected to fertilization/disturbance treatments., Our results suggest that HF and ND jointly determined species abundance by acting on contrasting niche dimensions. The effect of HF decreased relative to ND with increasing disturbance and decreasing fertilization. Dominant species exhibited similar traits in communities whereas dissimilarity favored the coexistence of rare species with dominants by decreasing inter-specific competition. This stabilizing effect on diversity was suggested by a negative relationship between species over-yielding and relative abundance., We discuss the importance of considering independent dimensions of functional niche to better understand species abundance and coexistence within communities. [ABSTRACT FROM AUTHOR]

Recent theory suggests that animals should switch facultatively among canonical movement modes as a complex function of internal state, landscape characteristics, motion capacity, and navigational capacity. We tested the generality of this paradigm for free-ranging elk (Cervus elaphus) over 5 orders of magnitude in time (minutes to years) and space (meters to 100 km). At the coarsest spatiotemporal scale, elk shifted from a dispersive to a home-ranging phase over the course of 1-3 years after introduction into a novel environment. At intermediate spatiotemporal scales, elk continued to alternate between movement modes. During the dispersive phase, elk alternated between encamped and exploratory modes, possibly linked to changes in motivational goals from foraging to social bonding. During the home-ranging phase, elk movements were characterized by a complex interplay between attraction to preferred habitat types and memory of previous movements across the home-range. At the finest temporal and spatial scale, elk used area-restricted search while browsing, interspersed with less sinuous paths when not browsing. Encountering a patch of high-quality food plants triggered the switch from one mode to the next, creating biphasic movement dynamics that were reinforced by local resource heterogeneity. These patterns suggest that multiphasic structure is fundamental to the movement patterns of elk at all temporal and spatial scales tested. [ABSTRACT FROM AUTHOR]

Background: Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. Methods and results: Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. Conclusions: We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal–barrier interactions and foraging strategies. [ABSTRACT FROM AUTHOR]

Few biodiversity indicators are available that reflect the state of broad-sense biodiversity—rather than of particular taxa—at fine spatial and temporal resolution. One such indicator, the Biodiversity Intactness Index (BII), estimates how the average abundance of the native terrestrial species in a region compares with their abundances in the absence of pronounced human impacts. We produced annual maps of modelled BII at 30-arc-second resolution (roughly 1 km at the equator) across tropical and subtropical forested biomes, by combining annual data on land use, human population density and road networks, and statistical models of how these variables affect overall abundance and compositional similarity of plants, fungi, invertebrates and vertebrates. Across tropical and subtropical biomes, BII fell by an average of 1.9 percentage points between 2001 and 2012, with 81 countries seeing an average reduction and 43 an average increase; the extent of primary forest fell by 3.9% over the same period. We did not find strong relationships between changes in BII and countries' rates of economic growth over the same period; however, limitations in mapping BII in plantation forests may hinder our ability to identify these relationships. This is the first time temporal change in BII has been estimated across such a large region. [ABSTRACT FROM AUTHOR]