Abstract Infections at the animal-human or wildlife-livestock interfaces have severe health and socio-economic consequences. Combined with empirical data, mathematical models can contribute to a better understanding of the reservoirs of these infections, which is a priority for mitigating their impact by using appropriate management interventions. Taking brucellosis in the Bargy massif (French Alps) as an example of a zoonosis at the wildlife-livestock interface, we developed and calibrated a multi-host model integrating data on direct and environment-mediated cross-species contacts from field observations. Estimates of the basic reproduction number ( R 0 ) allowed to identify the population of Alpine ibex ( Capra ibex ) and its environment as an essential host in the reservoir, driving both pathogen maintenance (within-species R 0 ≥1: 1.66, 95% credible interval: 1.42-2.03) and its transmission to livestock (between-species R 0 >0: 0.035, 0.01-0.05). Our approach can be adapted to other multi-host pathogens, which will contribute to improve the understanding and management of these complex systems.

Wildlife and domestic populations frequently share diseases with a potential for cross-species transmission, posing significant threats to animal and human health, economy and biodiversity conservation. While quantifying disease transmission in natural populations is critical to understand the dynamics of infectious diseases, transmission processes remain difficult to assess as they are difficult to observe directly. Brucellosis, caused by Brucella melitensis and Brucella abortus, is one of the most important worldwide zoonotic diseases and affects both domestic and wild ruminants. Here, we investigated the transmission of B. melitensis in an Alpine ibex (Capra ibex) population, the first known wild-living reservoir for this pathogen. We aimed to quantify disease transmission within the population by disentangling the contributions of four alternative transmission routes: abortion products, infectious parturition products, venereal transmission and vertical transmission. We modelled host-disease dynamics developing a spatially explicit, sex- and age-structured individual-based model that reproduces host demography and pathogen transmission by contacts among susceptible and infectious individuals. By fitting our model on 13 years of host-population and disease monitoring, we estimated the relative importance of the four transmission routes. We quantified the proportion of transmissions attributed to each route and estimated the effective reproduction number (Reff), distinguishing age- and sex-specific contribution. We identified abortion products as the primary driver of Brucella transmission, accounting for 57%-85% of all transmissions. All other routes were of secondary importance, although the contribution of venereal transmission remained uncertain (from 4% to 25%). Females played a central role in disease maintenance, with an effective reproduction number well above one (2.1), while males' contribution was quantitatively negligible with a value below one (0.4). Our results provide key insights to implement targeted management operations. Since most transmissions occur through abortion products, targeting recently infected females could reduce the effective reproduction number below one, promoting pathogen extinction. Furthermore, because abortions are expected to peak in late spring, control measures aiming to limit transmission from ibex to other species, including livestock, should be prioritized during this high-risk period.Read the free for this article on the Journal blog.

Abstract Animal movement paths display substantial complexity and variability, promoting efforts to identify universal rules and models that best describe them. Using high‐resolution (≥10 Hz) movement from 43 vertebrate species spanning diverse taxa, body sizes, and lifestyles, we show that paths are universally composed of straight‐line steps interspersed with sharp turns, echoing patterns documented in lower taxa such as bacteria. We report how vertebrate “fundamental steps”—straight travel segments between successive detected turns (with F stepduration as the turn‐to‐turn interval and F steplength as the corresponding distance when displacement is available)—and “fundamental turn angles” ( F turnangles ; net changes in travel heading between successive steps) vary with species' mass, locomotor mode, behavior, and environment. Here, “fundamental” denotes the finest scale step/turn events resolvable under our sampling rate and turn‐detection criteria; these event‐scale steps/turns are intrinsically different from the straight‐line segments inferred from low‐resolution position data. To explain these relationships, we posit that animals inherently move in a straight line until sensory information signals a better heading, triggering a turn. Across all species examined, animals spent the vast majority of their travel time moving in straight lines (species‐level means >90%), with turns representing discrete decision points influenced by body size, locomotor mode, and ecological context. Larger animals turned less frequently, consistent with biomechanical constraints of mass and rotational inertia, while aerial species often exhibited higher turning rates driven by soaring flight demands. We further show that turns can be linked to diverse behavioral drivers, including prey pursuit, obstacle avoidance, predator evasion, and exploitation of environmental energy. By explicitly quantifying turns, we clarify how distributions of step durations and turn angles interact to shape movement patterns and why different statistical models (e.g., correlated random walks, Lévy flights) emerge when lower resolution data are analyzed. Finally, we demonstrate how fundamental steps and turns can be incorporated into an agent‐based modeling framework using penguins as a case study, enabling reconstruction of realistic tracks and prediction of movement responses to environmental change. Straight‐line travel punctuated by decision‐driven turns thus emerges as a fundamental principle of vertebrate movement, linking fine‐scale movement structure, ecological context, and emergent patterns of space use.

Anthropogenic land conversion is putting increasing pressure on wildlife populations around the world. To mitigate impacts, it is necessary to develop a detailed mechanistic understanding of how animals are affected by different types of human activity. A key challenge is to disentangle the effects of static infrastructure, like roads or buildings, and the presence of humans in the landscape. To address this question, we examined if terrestrial mammals altered their movement behaviour around buildings in response to reduced human mobility during COVID-19 lockdowns. We compiled GPS tracking data from 35 study sites across five continents, for 10 carnivore species and 13 herbivore species, totalling >1 million location records from 586 individuals. For each study, we used integrated step selection analysis to test the extent to which animals changed their avoidance of buildings as lockdown took effect, leveraging the recently released Microsoft MLBuildings dataset of global building locations. Analysis of population-level effects revealed that, in areas with high Human Footprint Index (HFI), animals tended to show a significant reduction in their avoidance of buildings during lockdown, but not in low HFI areas. No such trend was detected during equivalent periods in years other than 2020, indicating that behavioural changes were a result of reduced human mobility during lockdowns. Overall, our findings suggest that animals living alongside humans exhibit greater plasticity when people change their behaviour, likely indicating the combined effects of environmental filtering and habituation. More generally, our study provides a critical first step towards developing evidence-based tools for forecasting how wildlife movement behaviour may change in response to different land-use strategies, human activities, conservation interventions or environmental perturbations.

The ability to evaluate fatigability during locomotion is crucial in various fields, from wildlife biology to clinical medicine. In wildlife, resistance to fatigue, or endurance, can determine the success of certain predator-prey encounters and underpins the ability of animals to migrate or disperse over long distances. In clinical contexts, endurance provides a reliable marker of physiological function, which could help guide exercise prescriptions and aid clinical decision making. However, current methods do not allow for accurate, non-invasive assessment of physical capacities over extended periods in natural and clinical settings. We propose a method for modelling the intensity-duration relationship based on dynamic body acceleration (DBA) records, from which we derived critical intensity, a key metabolic threshold in exercise physiology that delimits heavy from severe intensity domains. We recorded accelerometer data from 19 free-ranging species (n=272) across a wide interspecific and intraspecific range: from rats (10-2 kg) to elephants (103 kg), including oncology patients to regular runners. The three-parameter hyperbolic DBA-duration model revealed an excellent fit on experimental DBA records (median r2=0.995). By retrieving laboratory estimates of metabolic threshold for 15 species (n=688) from the literature, we demonstrated that critical DBA is a reliable proxy of metabolic threshold assessed in the laboratory both at the interspecific (r2=0.88, P<0.001) and intraspecific (Homo sapiens) levels (r2=0.90, P=0.051). The proposed method opens up new avenues for deciphering interactions among animals and between animals and their environment, through the lens of movement and physiology, but also for individualising the assessment of physical capacity in a clinical context.

Although the widespread effects of climate change impact almost all ecosystems, we lack a detailed understanding of how wildlife that thrive in human‐dominated environments are able to adjust their life history to modifications in land use of their natural habitat. In particular, spatial variation in environmental conditions is predicted to influence body development during the crucial early life phase, with marked impacts on individual performance and population dynamics for long‐lived species. Large herbivores have increased substantially in number and distribution over the last half century across Europe. The synanthropic roe deer ( Capreolus capreolus ) has been particularly successful, gradually colonizing agricultural landscapes. However, little is known about how habitat heterogeneity in this heavily human‐impacted environment impacts demographic performance. Specifically, we predicted that fawns born in predominantly cultivated local habitats would achieve faster early development due to the food subsidies obtained from agricultural crops by their mothers. Contrary to our expectations, fawns in semi‐natural forest were around 10% heavier at birth than those born in more mixed (by 0.163 ± 0.058 kg) and open (by 0.169 ± 0.006 kg) agricultural habitats. However, the body mass of all fawns subsequently increased at a similar average rate (0.148 ± 0.058 kg/day) over the first 20 days of life, irrespective of their habitat. This habitat‐dependent variation in early life mass appeared to be driven by reproductive phenology, as (1) early‐born fawns were heavier than late‐born fawns, and (2) mothers living in forest gave birth around 10 days earlier than those living in the mixed and open sectors. Semi‐natural habitats might thus be the more suitable for fawn early development, despite the availability and abundance of energetically rich food resources for lactating mothers in open and mixed habitats.

Travel is considered to account for a substantial proportion of endothermic species energy expenditure. However, transport costs depend on speed of the animal and slope angle of the terrain. We used biologging data from six ungulate species within the French mountains, combined with mapping data, to examine how these different species reacted to slopes by varying travel speed, and chosen ascent and descent angles, in relation to vectoral dynamic body acceleration (VeDBA; as a proxy for energy expenditure). As predicted by theory and as seen in pumas, animals travelled obliquely so that the angle that any individual experienced was lower than that of the topography. Travel speed affected the VeDBA-based proxy for cost of transport (COT) even though most species moved slower on steeper inclines. Models that considered speed, COT, slope, and habitat type showed clear relationships between COT and slope with variation across habitat types and according to species. Species-specific choice of travel speeds and slope chosen by animals underpins fundamental differences in species physiology and ecology via links in heat production and time spent per altitude. Understanding these interrelations points to the complexity of factors affecting space use by mountain ungulates and is crucial for conservation efforts, especially in fast-changing environments where energy expenditure, temperature changes, and resource accessibility impact population wellbeing.

The ongoing development of recreational activities in natural areas raises concerns about their environmental impacts, particularly in mountain ecosystems. Those biodiversity hotspots are highly attractive for outdoor activities, but they are also highly sensitive to human disturbance. However, little is still known about the impacts of massive nature-based sporting events, whose number has recently exploded. We focused on the impact of two types of massive sporting event (MSE) that occurred in the Bargy massif (northern French Alps) over a period of 10 years: a trail running competition with 600-1300 participants spread over four races, and stages of three emblematic cycling races, including the Tour de France. Based on the GPS monitoring of 139 individuals, we analysed several behavioural metrics during daytime and the following night when the MSE occurred, and compared them with reference data without MSE, recorded on the same dates but in other years. We revealed that trail running events exacerbate the 'corridor of fear' in Alpine ibex, a chronic and proactive response to the infrastructure concentrating human activities, that reshaped behavioural decisions at multiple spatiotemporal scales. Ibex redistributed farther from the hiking trails used by trail runners (-9% GPS locations within 500 m, representing a 20% relative decrease, +8% in the 500-1000 m range, representing a 25% relative increase). We also found increased movements (+14%) and activity levels during daytime in individuals close to the event route the night before the MSE. By contrast, cycling events had much more limited effects on ibex distribution and behaviour. While cycling events occurred primarily during summer when most of the ibex were already far from the roads, trail running events occurred at the beginning of the birth period and crossed the seasonal range of ibex, raising questions about the consequences for reproductive outputs. These findings highlight the need to consider the timing and route of MSE to avoid areas used during critical periods in the biological cycle of species, and more generally to address the rapidly growing impacts of MSE on mountain species already challenged by climate change during the crucial spring-summer period.Read the free for this article on the Journal blog.

Recurring events like migrations are an important part of the biological cycles of species. Understanding the factors influencing the timing of such events is crucial for determining how species face the pervasive consequences of climate change in highly seasonal environments. Relying on data from 406 GPS-collared Alpine ibex Capra ibex monitored across 17 populations, we investigated the environmental and individual drivers of short-distance migrations in this mountain ungulate. We found that vegetation phenology, including spring growth and autumn senescence, along with snow dynamics-snowmelt in spring, onset of snow cover in autumn-were the main drivers of the timing of migration. In spring, ibex migration timing was synchronized with the peak of vegetation green-up, but more in males than in females. Specifically, a peak of green-up occurring 10 days later delayed migration by 6.4 days for males and 2.7 days for females. This led to increased differences in migration timing between sexes when the peak of green-up occurred early or late in the season. In addition, ibex delayed migration timing when the length of the spring season was longer and when the date of snowmelt on ibex summer ranges occurred later. Similarly, in autumn, prolonged vegetation senescence and delayed onset of snow cover led to later migration. Overall, we observed a high degree of behavioural plasticity, with individuals responding to inter-annual variations in vegetation and snow phenology, even though the extent of these adjustments in migration dates was lower than the magnitude of the interannual changes in environmental conditions. Nonetheless, females could be less plastic than males in their timing of spring migration, likely due to the parturition period following migration forcing them to trade off foraging needs with predation risk. As the identified drivers of ibex migration are known to be and will continue to be largely impacted by climate change, the capacity of ibex to respond to such rapid changes could differ between sexes.

Animal movement paths display substantial complexity and variability, leading researchers to seek underlying rules that govern these patterns and mathematical models that best describe them. Using high-resolution (≥ 10 Hz) movement from 43 vertebrate species across diverse taxa, mass, and lifestyles, we show that movement paths are universally composed of straight-line steps interspersed with sharp turns, echoing a pattern documented for lower taxa such as bacteria. We report how these vertebrate ‘fundamental step lengths’ and ‘fundamental turn angles’, which are intrinsically different from the straight-line paths detailed in studies using low resolution position data, vary with species’ mass, lifestyle, behaviour, and environmental context. To explain these, we posit that animals inherently move in a straight line until sensory information signals a perceived better heading, which instigates a turn. The constellation of fundamental step lengths and turn angles over varying time intervals affects how well different models of animal movement (such as random walk or Lévy flight) fit lower resolution data. By examining turns as decision points, we can seek drivers of animal movement patterns and thereby work to predict future paths under varying conditions.

With the ongoing rise in global average temperatures, animals are expected to increasingly dedicate their time and energy to thermoregulation. In response to high temperatures, animals typically either seek for and move into thermal refuges, or reduce their activity during the hottest hours of the day. Yet, the often lower resource availability in thermal refuges, combined with the reduction of foraging activity, may create indirect energetic costs of behavioural thermoregulation, forcing individuals to further adjust their behaviours under different spatial contexts. To elucidate such complex behavioural responses of individuals living in different landscapes, we studied how alpine chamois behaviour (Rupicapra rupicapra), a cold-adapted endotherm, varied in relation to both temperature and within-home range access to thermal refuges. We used Hidden Markov Models to analyse individual time-budgets and daily habitat use of 26 GPS-tagged females monitored during summer in the French Alps. Females showed heat stress avoidance behaviours above a threshold temperature of 17.8°C, increasing the use of forest and northern slopes by 2.8% and 2.2%, respectively, for each 1°C increase in temperature. Individuals with access to forests also increased daily time spent foraging, while individuals with access to northern slopes increased the time spent relocating at the expense of foraging. Including local landscape context and jointly analysing resource selection and behavioural activity is hence key for improved insights into nuanced changes in individual responses to climate change in different spatial contexts, providing also an improved evidence base for wildlife managers to identify and protect key thermal cover habitats.

Caring for newborn offspring hampers resource acquisition of mammalian females, curbing their ability to meet the high energy expenditure of early lactation. Newborns are particularly vulnerable, and, among the large herbivores, ungulates have evolved a continuum of neonatal antipredator tactics, ranging from immobile hider (such as roe deer fawns or impala calves) to highly mobile follower offspring (such as reindeer calves or chamois kids). How these tactics constrain female movements around parturition is unknown, particularly within the current context of increasing habitat fragmentation and earlier plant phenology caused by global warming. Here, using a comparative analysis across 54 populations of 23 species of large herbivores from 5 ungulate families (Bovidae, Cervidae, Equidae, Antilocapridae and Giraffidae), we show that mothers adjust their movements to variation in resource productivity and heterogeneity according to their offspring’s neonatal tactic. Mothers with hider offspring are unable to exploit environments where the variability of resources occurs at a broad scale, which might alter resource allocation compared with mothers with follower offspring. Our findings reveal that the overlooked neonatal tactic plays a key role for predicting how species are coping with environmental variation. Combining a large-scale dataset of 23 ungulate species (in which newborns follow contrasting tactics of predator avoidance) with continuous-time stochastic movement models, the authors reveal that there are multiple dimensions of maternal movement behaviour and space use.

Recreational activities often result in a spatial and/or temporal activity shift in wildlife. With the concurrent development of outdoor activities and increase in temperatures due to climate change, mountain species face increasing pressures in terms of managing their activity pattern to limit both risk exposure and thermal discomfort. Using more than 15 years of long-term GPS and activity sensor data, we investigated how female northern chamois, Rupicapra rupicapra rupicapra, adjust their summer circadian activity to spatiotemporal variation in both temperatures and hikers’ presence. Chamois' behaviour was more affected by high temperatures than by hikers’ presence. During the hottest days, they shifted their activity peak earlier in the morning, were more active at night and during activity peaks, less active during daytime and had longer morning and evening peaks compared to the coldest days. Yet, total daily activity was only slightly different during the hottest days compared to the coldest days. Conversely, hikers' disturbance had weak effects on activity levels and on the timing of activity peaks. This is especially true for temporal disturbance (weekdays versus weekends and public holidays), possibly because most weekdays in summer fell during school holidays. Only during the hottest conditions, the morning activity peak was shorter and the evening peak longer in females living in the most exposed areas compared to females living in the least exposed areas. One possible explanation for the overall low effect of hikers' disturbance may be that behavioural changes buffering animals from high temperatures and hikers' presence (e.g. moving away from trails) allow them to just marginally modify their activity pattern. In the context of ongoing socioenvironmental changes, it is critical to conserve habitats providing thermal refuges against summer heat and protection from disturbance to mitigate potential detrimental consequences.

ABSTRACTSeasonal migrations are central ecological processes connecting populations, species and ecosystems in time and space. Land migrations, such as those of ungulates, are particularly threatened by habitat transformations and fragmentation, climate change and other environmental changes caused by anthropogenic activities. Mountain ungulate migrations are neglected because they are relatively short, although traversing highly heterogeneous altitudinal gradients particularly exposed to anthropogenic threats. Detecting migration routes of these species and understanding their drivers is therefore of primary importance to predict connectivity and preserve ecosystem functions and services. The populations of Alpine ibexCapra ibex, an iconic species endemic to the Alps, have all been reintroduced from the last remnant source population. Because of their biology and conservation history, Alpine ibex populations are mostly disconnected. Hence, despite a general increase in abundance and overall distribution range, their conservation is strictly linked to the interplay between external threats and related behavioral responses, including space use and migration. By using 337 migratory tracks from 425 GPS-collared individuals from 15 Alpine ibex populations distributed across their entire range, we (i) identified the environmental drivers of movement corridors in both spring and autumn and (ii) compared the abilities of three modeling approaches to predict migratory movements between seasonal ranges of the 15 populations. Trade-offs between energy expenditure, food, and cover seemed to be the major driver of migration routes: steep south-facing snow-free slopes were selected while high elevation changes were avoided. This revealed the importance of favorable resources and an attempt to limit energy expenditures and perceived predation risk. Based on these findings, we provided efficient connectivity models to inform conservation of Alpine ibex and its habitats, and a framework for future research investigating connectivity in migratory species.

BackgroundNetwork theory is largely applied in real-world systems to assess landscape connectivity using empirical or theoretical networks. Empirical networks are usually built from discontinuous individual movement trajectories without knowing the effect of relocation frequency on the assessment of landscape connectivity while theoretical networks generally rely on simple movement rules. We investigated the combined effects of relocation sampling frequency and landscape fragmentation on the assessment of landscape connectivity using simulated trajectories and empirical high-resolution (1 Hz) trajectories of Alpine ibex (Capra ibex). We also quantified the capacity of commonly used theoretical networks to accurately predict landscape connectivity from multiple movement processes.MethodsWe simulated forager trajectories from continuous correlated biased random walks in simulated landscapes with three levels of landscape fragmentation. High-resolution ibex trajectories were reconstructed using GPS-enabled multi-sensor biologging data and the dead-reckoning technique. For both simulated and empirical trajectories, we generated spatial networks from regularly resampled trajectories and assessed changes in their topology and information loss depending on the resampling frequency and landscape fragmentation. We finally built commonly used theoretical networks in the same landscapes and compared their predictions to actual connectivity.ResultsWe demonstrated that an accurate assessment of landscape connectivity can be severely hampered (e.g., up to 66% of undetected visited patches and 29% of spurious links) when the relocation frequency is too coarse compared to the temporal dynamics of animal movement. However, the level of landscape fragmentation and underlying movement processes can both mitigate the effect of relocation sampling frequency. We also showed that network topologies emerging from different movement behaviours and a wide range of landscape fragmentation were complex, and that commonly used theoretical networks accurately predicted only 30-50% of landscape connectivity in such environments.ConclusionsVery high-resolution trajectories were generally necessary to accurately identify complex network topologies and avoid the generation of spurious information on landscape connectivity. New technologies providing such high-resolution datasets over long periods should thus grow in the movement ecology sphere. In addition, commonly used theoretical models should be applied with caution to the study of landscape connectivity in real-world systems as they did not perform well as predictive tools.

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

Brucellosis due to Brucella melitensis affects domestic and wild ruminants, as well as other mammals, including humans. Despite France being officially free of bovine brucellosis since 2005, two human cases of Brucella melitensis infection in the French Alps in 2012 led to the discovery of one infected cattle herd and of one infected population of wild Alpine ibex (Capra ibex). In this review, we present the results of 10 years of research on the epidemiology of brucellosis in this population of Alpine ibex. We also discuss the insights brought by research and expert assessments on the efficacy of disease management strategies used to mitigate brucellosis in the French Alps.

In variable environments, habitats that are rich in resources often carry a higher risk of predation. As a result, natural selection should favour individuals that balance allocation of time to foraging versus avoiding predation through an optimal decision-making process that maximizes fitness. The behavioural trade-off between resource acquisition and risk avoidance is expected to be particularly acute during gestation and lactation, when the energetic demands of reproduction peak. Here, we investigated how reproductive female roe deer adjust their foraging activity and habitat use during the birth period to manage this trade-off compared with non-reproductive juveniles, and how parturition date constrains individual tactics of risk-resource management. Activity of reproductive females more than doubled immediately following parturition, when energy demand is highest. Furthermore, compared with non-reproductive juveniles, they increased their exposure to risk by using open habitat more during daytime and ranging closer to roads. However, these post-partum modifications in behaviour were particularly pronounced in late-parturient females who adopted a more risk-prone tactic, presumably to compensate for the growth handicap of their late-born offspring. In income breeders, individuals that give birth late may be constrained to trade risk avoidance for foraging during peak allocation to reproduction, with probable consequences for individual fitness.