More than one million barriers fragment Europe's rivers.

Rivers support some of Earth's richest biodiversity1 and provide essential ecosystem services to society2, but they are often fragmented by barriers to free flow3. In Europe, attempts to quantify river connectivity have been hampered by the absence of a harmonized barrier database. Here we show that there are at least 1.2 million instream barriers in 36 European countries (with a mean density of 0.74 barriers per kilometre), 68 per cent of which are structures less than two metres in height that are often overlooked. Standardized walkover surveys along 2,715 kilometres of stream length for 147 rivers indicate that existing records underestimate barrier numbers by about 61 per cent. The highest barrier densities occur in the heavily modified rivers of central Europe and the lowest barrier densities occur in the most remote, sparsely populated alpine areas. Across Europe, the main predictors of barrier density are agricultural pressure, density of river-road crossings, extent of surface water and elevation. Relatively unfragmented rivers are still found in the Balkans, the Baltic states and parts of Scandinavia and southern Europe, but these require urgent protection from proposed dam developments. Our findings could inform the implementation of the EU Biodiversity Strategy, which aims to reconnect 25,000 kilometres of Europe's rivers by 2030, but achieving this will require a paradigm shift in river restoration that recognizes the widespread impacts caused by small barriers.

Sleep in the wild: the importance of individual effects and environmental conditions on sleep behaviour in wild boar.

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.

How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection.

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.

Experimental evolution of dispersal: Unifying theory, experiments and natural systems.

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.

Covariation between glucocorticoids, behaviour and immunity supports the pace-of-life syndrome hypothesis: an experimental approach.

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.

Interacting lethal and nonlethal human activities shape complex risk tolerance behaviors in a mountain herbivore.

Animals perceive human activities as risky and generally respond with fear-induced proactive behaviors to buffer the circadian patterns of lethal and nonlethal disturbances, such as diel migrations (DMs) between risky places during safe nighttime and safer places during risky daytime. However, such responses potentially incur costs through movement or reduced foraging time, so individuals should adjust their tolerance when human activities are harmless, through habituation. Yet this is a challenging cognitive task when lethal and nonlethal risks co-occur, forming complex landscapes of fear. The consequences of this human-induced complexity have, however, rarely been assessed. We studied the individual DM dynamics of chamois (Rupicapra rupicapra rupicapra), 89 GPS-tracked individual-years, from/to trails in the French Alps in areas with co-occurring lethal (hunting) and nonlethal (hiking and skiing) disturbances, with different intensities across seasons. We developed a conceptual framework relying on the risk-disturbance hypothesis and habituation to predict tolerance adjustments of chamois under various disturbance contexts and across contrasted seasonal periods. Based on spatial and statistical analyses combining periodograms and multinomial logistic models, we found that DM in relation to distance to a trail was a consistent response by chamois (~85% of individuals) to avoid human disturbance during daytime, especially during the hiking and hunting periods. Such behavior revealed a low tolerance of most chamois to human activities, although there was considerable interindividual heterogeneity in DM. Interestingly, there was an increased tolerance among the most disturbed diel migrants, potentially through habituation, with chamois performing shorter DMs in areas highly disturbed by hikers. Crucially, chamois that were most human-habituated during the hiking period remained more tolerant in the subsequent harvesting period, which could increase their risk of being harvested. In contrast, individuals less tolerant to hiking performed longer DMs when hunting risk increased, and compared to hiking, hunting exacerbated the threshold distance to trails triggering DMs. No carryover effect of hunting beyond the hunting period was observed. In conclusion, complex human-induced landscapes of fear with co-occurring disturbances by nature-based tourism and hunting may shape unexpected patterns of tolerance to human activities, whereby animal tolerance could become potentially deleterious for individual survival.

Energy-based step selection analysis: Modelling the energetic drivers of animal movement and habitat use.

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.

Airflow modelling predicts seabird breeding habitat across islands.

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.

Climate causes shifts in grey seal phenology by modifying age structure.

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.

Research Highlight: Social dispersal in giraffes.

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.

Global effects of land use on local terrestrial biodiversity.

Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

Optimizing the use of biologgers for movement ecology research.

The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF). We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology. We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data. Taking advantage of the biologging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high-frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location-only technology such as GPS. Equally important will be the establishment of multidisciplinary collaborations to catalyse the opportunities offered by current and future biologging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes and for building realistic predictive models.

Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal.

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.

Declining home range area predicts reduced late-life survival in two wild ungulate populations.

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.

Socially informed dispersal in a territorial cooperative breeder.

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.

Fathers matter: male body mass affects life-history traits in a size-dimorphic seabird.

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.

Dynamic Range Size Analysis of Territorial Animals: An Optimality Approach.

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.

Impact of changing wind conditions on foraging and incubation success in male and female wandering albatrosses.

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.

'You shall not pass!': quantifying barrier permeability and proximity avoidance by animals.

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. 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. 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. 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%). 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.

Organic fields sustain weed metacommunity dynamics in farmland landscapes.

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.