ECOLOGY. Terrestrial animal tracking as an eye on life and planet

The growing methodological toolkit for identifying and studying social learning and culture in non-human animals

There is a growing consensus that animals' socially transmitted knowledge should be recognized when planning conservation management, but demonstrating social learning or culture can present considerable challenges, especially in the wild. Fortunately, decades of research have spawned a rich methodological toolkit for exactly this purpose. Here, we review principal approaches, including: social learning experiments; analyses of natural or experimentally seeded diffusions of novel behaviours, sometimes using specialist statistical techniques; mapping of behavioural variation across neighbouring, sympatric or captive groups, or at larger scales; and assessment of aspects of cross-generational transmission, including teaching, learning during ontogenetic development and cumulative change. Some methods reviewed were developed for captive studies, but have subsequently been adapted for application in the wild, or are useful for exploring a species' general propensity to learn and transmit information socially. We highlight several emerging 'rapid assessment' approaches-including camera trapping, passive acoustic monitoring, animal-borne tags, AI-assisted data mining and computer simulations-that should prove useful in addressing particularly urgent conservation needs. We conclude by considering how best to use this growing methodological toolkit in practice, to guide further research on animal social learning and cultures, and maximize conservation and policy impact.This article is part of the theme issue 'Animal culture: conservation in a changing world'.

A call for increased integration of experimental approaches in movement ecology

Rapid developments in animal-tracking technology have enabled major advances in the field of movement ecology, which seeks to understand the drivers and consequences of movement across scales, taxa, and ecosystems. The field has made ground-breaking discoveries, yet the majority of studies in movement ecology remain reliant on observational approaches. While important, observational studies are limited compared to experimental methods that can reveal causal relationships and underlying mechanisms. As such, we advocate for a renewed focus on experimental approaches in animal movement ecology. We illustrate a way forward in experimental movement ecology across two fundamental levels of biological organisation: individuals and social groups. We then explore the application of experiments in movement ecology to study anthropogenic influences on wildlife movement, and enhance our mechanistic understanding of conservation interventions. In each of these examples, we draw upon previous research that has effectively employed experimental approaches, while highlighting outstanding questions that could be answered by further experimentation. We conclude by highlighting the ways experimental manipulations in both laboratory and natural settings provide a promising way forward to generate mechanistic understandings of the drivers, consequences, and conservation of animal movement.

A well-connected Earth: The science and conservation of organismal movement

Global biodiversity targets focus on landscape and seascape connectivity as a foundational component of biodiversity conservation, including networks of connected protected areas. Recent advances allow the measurement and prediction of organismal movements at multiple scales. We provide a definition of connectivity that links movement to persistence and ecological function. Connectivity science can guide planning for biodiversity, ecosystem services, ecological restoration, and climate adaptation. Ongoing climate change and land and sea use are closing the window of opportunity for connectivity conservation. A coordinated global effort is required to implement scientific knowledge and to monitor, map, protect, and restore areas that promote movement and maintain well-connected ecosystems for biodiversity in the long term.

Pronghorn movements and mortality during extreme weather highlight the critical importance of connectivity

Human disturbance and development are fragmenting landscapes, limiting the ability of organisms to freely move to meet their survival and reproductive needs. Simultaneously, extreme weather events-such as tropical cyclones, megafires, and heatwaves-pose a major threat to survival and may require animals to rapidly move to escape. As the dual forces of landscape fragmentation and extreme weather events continue to intensify, researchers urgently need to develop an understanding of the synergistic effects of these forces on animal mobility and survival. Here, we present a case study on pronghorn (Antilocapra americana) that undertook extraordinary long-distance movements (up to 399 km) to escape a once-in-two-decades extreme snowstorm in the Red Desert, WY, USA. Although Wyoming is a seemingly underdeveloped landscape, high fence density and two major highways in the region exposed pronghorn to novel barriers that delayed movement, restricted habitat access, and ultimately hindered their ability to escape extreme snow accumulation. The synergistic effects of movement barriers and extreme weather increased mortality rates by 3.7-fold such that over 50% of GPS-monitored pronghorn perished. These findings highlight the critical need to study escape movements and prioritize connectivity planning to curtail mass mortality events and ensure population persistence.

Remote Vital Sensing in Clinical Veterinary Medicine: A Comprehensive Review of Recent Advances, Accomplishments, Challenges, and Future Perspectives

Remote vital sensing in veterinary medicine is a relatively new area of practice, which involves the acquisition of data without invasion of the body cavities of live animals. This paper aims to review several technologies in remote vital sensing: infrared thermography, remote photoplethysmography (rPPG), radar, wearable sensors, and computer vision and machine learning. In each of these technologies, we outline its concepts, uses, strengths, and limitations in multiple animal species, and its potential to reshape health surveillance, welfare evaluation, and clinical medicine in animals. The review also provides information about the problems associated with applying these technologies, including species differences, external conditions, and the question of the reliability and classification of these technologies. Additional topics discussed in this review include future developments such as the use of artificial intelligence, combining different sensing methods, and creating monitoring solutions tailored to specific animal species. This contribution gives a clear understanding of the status and future possibilities of remote vital sensing in veterinary applications and stresses the importance of that technology for the development of the veterinary field in terms of animal health and science.

The underlying causes of differential migration: assumptions, hypotheses, and predictions

Mechanisms governing the migratory decisions of birds have long fascinated ecologists and sparked considerable debate. Identifying factors responsible for variation in migration distance, also known as differential migration, has been a popular approach to understanding the mechanisms underlying migratory behaviour more generally. However, research progress has been slowed by the continued testing of overlapping, non-mechanistic, and circular predictions among a small set of historically entrenched hypotheses. We highlight the body size hypothesis and suggest that the predictions commonly tested have impeded progress because body size relationships with migration distance are predictions made by several distinct hypotheses with contrasting mechanisms. The cost of migration itself has not been adequately accounted for in most hypotheses, and we propose two flight efficiency hypotheses with time- and energy-minimizing mechanisms that allow individuals to mitigate the risks inherent to longer migrations. We also advance two conceptual versions of the social dominance hypothesis based on two distinct underlying mechanisms related to distance minimization and food maximization that will help clarify the role of competition in driving migratory decisions. Overall, we describe and refine 12 mechanistic hypotheses proposed to explain differential migration (along with several other special-case hypotheses), seven of which have underlying mechanisms related to food limitation as past research has identified this to be an important driver of differential migration. We also thoroughly reviewed 145 publications to assess the amount of support for 10 critical assumptions underlying alternative hypotheses for differential migration in birds. Our review reveals that surprisingly few studies explicitly evaluate assumptions within a differential migration context. Generating and testing strong predictions and critical assumptions underlying mechanisms of alternative hypotheses will improve our ability to differentiate among these explanations of differential migration. Additionally, future intraspecific progress will be greatest if investigators continue to focus on mechanisms underlying variation in migration distance within rather than among demographic classes, as previous research has found differing mechanisms to be responsible for differential migration among demographic classes. Interspecifically, a thorough comparative analysis that seeks to explain variation in migration distance among species would broaden both our understanding of the mechanisms regulating current differential migration patterns and those that led to the evolution of migration more generally. Collectively, we provide a framework that, together with advances in animal-borne tracking and other technology, can be used to advance our understanding of the causes of differential migration distance, and migratory decisions more generally.

Influence of Reproductive Status on Occupancy of Salvage-Logged Boreal Forest by Moose (Alces americanus)

Wildlife-habitat relationships reflect the behavioral choices made by species in response to perceived risks and rewards. Ungulates must often choose between habitats that provide forage and those offering concealment from predators, yet natural and anthropogenic disturbances create risky landscapes where tradeoffs may be difficult to navigate. Ungulate responses to forest disturbance may vary by sex and reproductive state, given that reproductive females with calves often prioritize predator avoidance. We investigated state-dependent habitat use by reproductive and solitary moose (Alces americanus) in response to salvage logging after a widespread infestation by spruce beetle (Dendroctonus rufipennis) in the boreal forest of Yukon, Canada. We used camera traps and multistate occupancy models to examine moose occurrence in unsalvaged and salvage-logged forests at different regenerative stages (0-10 years and 11-25 years postlogging) and levels of tree retention after logging. We compared results to single-state occupancy models that did not account for reproductive status. As predicted, single-state models showed high use of stands with low canopy cover and maximum tree removal (i.e., clear-cuts). This suggested that moose capitalized on shrubby forage available in logged stands, regardless of regenerative stage. However, this result was overly simplistic. Multistate occupancy models revealed that forest age was the most important factor for female moose with calves, in contrast to solitary moose. Females with calves tended to avoid newly logged areas and preferred regenerating and unsalvaged forests with hiding cover, although estimates of effect size had low precision. Climate change is contributing to the rising frequency and severity of bark beetle outbreaks, and post-infestation salvage logging has been implicated in the decline of moose populations in western Canada. Our results support the need to maintain diverse, mixed-age forest landscapes to meet the food and cover requirements of moose in different demographic classes.

How cryptic animal vectors of fungi can influence forest health in a changing climate and how to anticipate them

Fungal spores are usually dispersed by wind, water, and animal vectors. Climate change is accelerating the spread of pathogens to new regions. While well-studied vectors like bark beetles and moths contribute to pathogen transmission, other, less-recognized animal species play a crucial role at different scales. Small-scale dispersers, such as mites, rodents, squirrels, and woodpeckers, facilitate fungal spread within trees or entire forest regions. On a larger scale, birds contribute significantly to long-distance fungal dispersal, potentially aiding the establishment of invasive species across continents. These vectors remain underexplored and are often overlooked in fungal disease studies and are therefore called cryptic vectors. Understanding the full range of dispersal mechanisms is critical as climate change drive shifts in species distributions and increases vector activity. Expanding monitoring and detection tools to include these hidden carriers will improve our ability to track the distribution of fungal pathogens. Integrating targeted research, innovative technologies, and collaborative efforts across disciplines and borders is essential for enhancing disease management and mitigating fungal disease's ecological and economic impacts. KEY POINTS: • Cryptic animal vectors play a critical role in fungal spore dispersal across forests and continents. • Climate change accelerates fungal pathogen spread by altering species distributions, increasing vector activity, and facilitating long-distance dispersal. • Innovative monitoring tools, like eDNA sampling and predictive modelling, are essential to uncover cryptic vector contributions and mitigate fungal disease impacts.

A new data-driven paradigm for the study of avian migratory navigation

Avian navigation has fascinated researchers for many years. Yet, despite a vast amount of literature on the topic it remains a mystery how birds are able to find their way across long distances while relying only on cues available locally and reacting to those cues on the fly. Navigation is multi-modal, in that birds may use different cues at different times as a response to environmental conditions they find themselves in. It also operates at different spatial and temporal scales, where different strategies may be used at different parts of the journey. This multi-modal and multi-scale nature of navigation has however been challenging to study, since it would require long-term tracking data along with contemporaneous and co-located information on environmental cues. In this paper we propose a new alternative data-driven paradigm to the study of avian navigation. That is, instead of taking a traditional theory-based approach based on posing a research question and then collecting data to study navigation, we propose a data-driven approach, where large amounts of data, not purposedly collected for a specific question, are analysed to identify as-yet-unknown patterns in behaviour. Current technological developments have led to large data collections of both animal tracking data and environmental data, which are openly available to scientists. These open data, combined with a data-driven exploratory approach using data mining, machine learning and artificial intelligence methods, can support identification of unexpected patterns during migration, and lead to a better understanding of multi-modal navigational decision-making across different spatial and temporal scales.

Long-term studies provide unique insights into evolution

From experimental evolution in the laboratory to sustained measurements of natural selection in the wild, long-term studies have revolutionized our understanding of evolution. By directly investigating evolutionary dynamics in real time, these approaches have provided unparallelled insights into the complex interplay between evolutionary process and pattern. These approaches can reveal oscillations, stochastic fluctuations and systematic trends that unfold over extended periods, expose critical time lags between environmental shifts and population responses, and illuminate how subtle effects may accumulate into significant evolutionary patterns. Long-term studies can also reveal otherwise cryptic trends that unfold over extended periods, and offer the potential for serendipity: observing rare events that spur new evolutionary hypotheses and research directions. Despite the challenges of conducting long-term research, exacerbated by modern funding landscapes favouring short-term projects, the contributions of long-term studies to evolutionary biology are indispensable. This is particularly true in our rapidly changing, human-dominated world, where such studies offer a crucial window into how environmental changes and altered species interactions shape evolutionary trajectories. In this Review article, we showcase the groundbreaking discoveries of long-term evolutionary studies, underscoring their crucial role in advancing our understanding of the complex nature of evolution across multiple systems and timescales.

An annual cycle perspective on energetics and locomotion of migratory animals

Animal migrations, or long-distance movements, on land, through water or in the air, are considered energetically costly because of the investment in persistent locomotion typical for migration. Diverse strategies exist to manage these energetic costs. Yet migration is only one stage in an annual cycle and may not be the most energetically costly. To better understand how free-ranging animals adaptively organize energy expenditure and locomotion, an annual cycle perspective is needed. Bio-logging data are collected for a range of animal species and could facilitate a life cycle approach to study energy expenditure. We provide examples from several studies across different taxa, as well as a more in-depth exploration from our own recent research on time activity budgets based on field observations and bio-logging data to estimate daily energy expenditure in a migratory seabird throughout a year. Our research has shown that daily energy expenditure is highest (1.7× average daily energy expenditure) during the spring migration of long-distance migratory gulls, whereas short-distance migrants expend the most energy (1.4× average daily energy expenditure) during the breeding season. Based on the examples provided, we show how bio-energetic models create exciting opportunities to study daily energetics and behaviour of migratory animals, although limitations also still exist. Such studies can reveal when, where and why peaks and lulls in energy expenditure arise over the annual cycle of a migrant, if long-distance movements are indeed energetically expensive and how animals can adapt to fluctuating demands in their natural environment throughout the year.

Integrating Landscapes of Fear and Energy Reveals the Behavioural Strategies That Shape Predator-Prey Interactions

Disparate bodies of literature implicate risk avoidance and energy conservation as important drivers of animal movement decisions. Theory posits that these phenomena interact in ecologically consequential ways, but rigorous empirical tests of this hypothesis have been hampered by data limitations. We fuse fluid dynamics, telemetry, and attack data to reconstruct risk and energy landscapes traversed by migrating juvenile salmon and their predators. We find that migrants primarily use midriver microhabitats that facilitate migration at night. During daylight, predators become more aggressive in the midriver, and prey reduce midriver use in favour of nearshore microhabitats, resulting in increased energy expenditure and decreased migration efficiency. Predators attack most when migrants are not prioritising threat avoidance and during ephemeral periods of low lighting. Our findings suggest that predator-prey interactions result from an interplay between landscapes of fear and energy, which can determine the degree to which predators affect prey through mortality or fear.

Robust analysis of diel activity patterns

Research Highlight: Iannarilli, F., Gerber, B. D., Erb, J., & Fieberg, J. R. (2024). A 'how-to' guide for estimating animal diel activity using hierarchical models. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.14213. Diel activity patterns are ubiquitous in living organisms and have received considerable research attention with advances in the collection of time-stamped data and the recognition that organisms may respond to global change via behaviour timing. Iannarilli et al. (2024) provide a roadmap for analysing diel activity patterns with hierarchical models, specifically trigonometric generalized linear mixed-effect models and cyclic cubic spline generalized additive models. These methods are improvements over kernel density estimators, which for nearly two decades have been the status quo for analysing activity patterns. Kernel density estimators have several drawbacks; most notably, data are typically aggregated (e.g. across locations) to achieve sufficient sample sizes, and covariates cannot be incorporated to quantify the influence of environmental variables on activity timing. Iannarilli et al. (2024) also provide a comprehensive tutorial which demonstrates how to format data, fit models, and interpret model predictions. We believe that hierarchical models will become indispensable tools for activity-timing research and envision the development of many extensions to the approaches described by Iannarilli et al. (2024).

Establishing bio-logging data collections as dynamic archives of animal life on Earth

Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption. Second, we need to develop integrated data collections on standardized data platforms that support data preservation through public archiving and strategies that ensure long-term access. We outline pathways to reach these goals, highlighting the need for resources to govern community data standards and guide data mobilization efforts. We propose the launch of a community-led coordinating body and provide recommendations for how stakeholders-including government data centres, museums and those who fund, permit and publish bio-logging work-can support these efforts.

Sexually differentiated decision-making involves faster recruitment in the early stages for the Tibetan antelopes Pantholops hodgsonii

Group living is widespread across diverse taxa, and the mechanisms underlying collective decision-making in contexts of variable role division are critical for understanding the dynamics of group stability. While studies on collective behavior in small animals such as fish and insects are well-established, similar research on large wild animals remains challenging due to the limited availability of sufficient and systematic field data. Here, we aimed to explore the collective decision-making pattern and its sexual difference for the dimorphic Tibetan antelopes Pantholops hodgsonii (chiru) in Xizang Autonomous Region, China, by analyzing individual leadership distribution, as well as the joining process, considering factors such as calving stages and joining ranks. The distinct correlations of decision participants' ratio with group size and decision duration underscore the trade-off between accuracy and speed in decision-making. Male antelopes display a more democratic decision-making pattern, while females exhibit more prompt responses after calving at an early stage. This study uncovers a partially shared decision-making strategy among Tibetan antelopes, suggesting flexible self-organization in group decision processes aligned with animal life cycle progression.

Tigers in their new territory: intraspecific interactions among the reintroduced tiger population in Panna Tiger Reserve, Central India

Intra-specific interactions among top carnivores are among the most intriguing behavioural aspects and essential components of population dynamics. Static interactions pertain to space use, while dynamic interactions involve spatio-temporal patterns influenced by social structure, distribution, mate selection, and density. Previous studies have focused on static interactions, successfully estimating spatial overlap but leading to a knowledge gap of dynamic interaction to be able to compute attraction and avoidance on similar spatio-temporal scales. We fitted VHF and GPS collars to 13 tigers to study the static and dynamic interactions among the reintroduced tiger population in Panna Tiger Reserve. To investigate spatial interactions, we used Autocorrelated Kernel Density Estimator methods. To capture dynamic interactions at different scales, we calculated Benhamou's Movement Interaction index and a Correlation Coefficient (Cr) at two critical distance thresholds (Δ500m and 100m). We documented 18 and 35 intra-sex dyads for males and females respectively, and 73 inter-sex dyads from 2009 to 2019. We observed high spatial overlap in male*female dyads. Dynamic interactions and similar movement patterns were noted in mother*cub dyads, while male movements were predominantly independent. We evaluated 23 male*female dyads and found moderate to strong dynamic interactions between individuals. Spatial interaction largely depends on home-range shape and size and does not necessarily affect dynamic interaction. Males and females moved independently to avoid intra-guild competition, exhibiting unsynchronized movement patterns. However, interaction was infrequently recorded, primarily during mating. Female siblings showed philopatry and preferred to move jointly before establishing their own territories. Initially, founder females had limited choice for mate selection with only one male, but as more males became available, females exhibited clear and consistent mate selection. This indicates that founder populations for reintroduction should include adequate mate choices.

Human Footprint and Forest Disturbance Reduce Space Use of Brown Bears (Ursus arctos) Across Europe

Three-quarters of the planet's land surface has been altered by humans, with consequences for animal ecology, movements and related ecosystem functioning. Species often occupy wide geographical ranges with contrasting human disturbance and environmental conditions, yet, limited data availability across species' ranges has constrained our understanding of how human pressure and resource availability jointly shape intraspecific variation of animal space use. Leveraging a unique dataset of 758 annual GPS movement trajectories from 375 brown bears (Ursus arctos) across the species' range in Europe, we investigated the effects of human pressure (i.e., human footprint index), resource availability and predictability, forest cover and disturbance, and area-based conservation measures on brown bear space use. We quantified space use at different spatiotemporal scales during the growing season (May-September): home range size; representing general space requirements, 10-day long-distance displacement distances, and routine 1-day displacement distances. We found large intraspecific variation in brown bear space use across all scales, which was profoundly affected by human footprint index, vegetation productivity, and recent forest disturbances creating opportunity for resource pulses. Bears occupied smaller home ranges and moved less in more anthropized landscapes and in areas with higher resource availability and predictability. Forest disturbances reduced space use while contiguous forest cover promoted longer daily movements. The amount of strictly protected and roadless areas within bear home ranges was too small to affect space use. Anthropized landscapes may hinder the expansion of small and isolated populations, such as the Apennine and Pyrenean, and obstruct population connectivity, for example between the Dinaric Pindos population and the Alpine or Carpathian population. Our findings call for actions to maintain bear movements across landscapes with high human footprint, for example by maintaining forest integrity, to support viable bear populations and their ecosystem functions.

Migration matters in conservation and management: Exploring the 10% rule for demographic independence via simulation

Delineating a threshold migration rate for demographic independence important for understanding connectivity among fragmented populations and defining management units for conservation and harvest regulation. In turn, defining management units is an essential step in sustainable management to avoid unintentional depletion of resources managed for conservation or harvest. The 10% rule of demographic connectivity is a rule of thumb that delineates the threshold of demographic independence when the behavior of two populations shifts from synchronous at >10% to independent at <10%. However, the accuracy of the 10% rule to real-world scenarios and application to natural resource management is unknown. We evaluated the 10% rule using simulation for two life history types: Pacific cod, Gadus macrocephalus, a gadid with relatively fast growth, and blackspotted rockfish, Sebastes melanostictus, a long-lived rockfish species. Results were obtained by simulating a real-world tool for evaluating demographic connectivity, positive correlation in estimated population sizes. We assessed the effect of migration on demographic connectivity on otherwise independent populations under one- and two-way migration, and with various population sizes and life history parameters. Sensitivity testing showed that positive correlation in population size does not occur in roughly a quarter of simulations, regardless of the migration rate. When positive correlation in population size does occur, mean migration rates over all simulations were between 5% and 10%: 0.089 (8.9%) for blackspotted rockfish and 0.058 (5.8%) for Pacific cod. However, the range of migration resulting in demographic connectivity was large, 0.02-0.44 for blackspotted rockfish and 0.02-0.40 for Pacific cod.

The Influence of Migration Timing and Local Conditions on Reproductive Timing in Arctic-Breeding Birds

For birds breeding in the Arctic, nest success is affected by the timing of nest initiation, which is partially determined by local conditions such as snow cover. However, conditions during the non-breeding season can carry over to affect the timing of breeding. We used tracking and breeding data from 248 individuals of 8 species and subspecies of Arctic-breeding shorebirds to estimate how the timing of nest initiation is related to local conditions like snowmelt phenology versus prior conditions, measured by the timing and speed of migration. Using path analysis, our global model showed that local and prior conditions have similar effect sizes (Standardised Path Coefficients ± SE of 0.44 ± 0.07 and 0.43 ± 0.07 for snowmelt and arrival timing, respectively), suggesting that both influence the timing of breeding and therefore potentially reproductive output. However, the importance of each variable varied across species. Individuals that arrived later to the breeding grounds did not leave the wintering grounds later, but instead took longer to migrate, potentially reflecting differences in flight speed or time spent at stopover sites. We hypothesise that this may be due to reduced habitat quality at some stopover sites or an inability to adjust their departure timing or migration speed to match the advancing spring phenology in the North. Individuals that migrated longer distances also arrived and nested later. Our results highlight the benefits and potential conservation implications of using a full annual cycle approach to assess the factors influencing reproductive timing of birds.

Maximizing biological insights from instruments attached to animals

Instruments attached to animals ('biologgers') have facilitated extensive discoveries about the patterns, causes, and consequences of animal behavior. Here, we present examples of how biologging can deepen our fundamental understanding of ecosystems and our applied understanding of global change impacts by enabling tests of ecological theory. Applying the iterative process of science to biologging has enabled a diverse set of insights, including social and experiential learning in long-distance migrants, state-dependent risk aversion in foraging predators, and resource abundance driving movement across taxa. Now, biologging is poised to tackle questions and refine ecological theories at increasing levels of complexity by integrating measurements from numerous individuals, merging datasets from multiple species and their environments, and spanning disciplines, including physiology, behavior and demography.

Tracking individual animals can reveal the mechanisms of species loss

As biodiversity loss continues, targeted conservation interventions are increasingly necessary. Stemming species loss requires mechanistic understanding of the processes governing population dynamics. However, this information is unavailable for most animals because it requires data that are difficult to collect using traditional methods. Advances in animal tracking technology have generated an avalanche of high-resolution observations for a growing list of species around the globe. To date, most research using these data has focused on questions about animal behavior, with less emphasis on population processes. Here, we argue that tracking data are uniquely poised to bring powerful new insights to the urgent, global problem of halting species extinctions by revealing when, where, how, and why populations are changing.

Seasonal Variations and Sexual Differences in Home Range Sizes and Activity Patterns of Endangered Long-Tailed Gorals in South Korea

The long-tailed goral (Naemorhedus caudatus) faces significant threats from habitat loss and fragmentation and is classified as a Class I endangered species by the Ministry of Environment in South Korea and vulnerable by the IUCN. Understanding the behavioral ecology of this species is crucial for effective conservation and protective measures. Using GPS collars, this study investigated the home range sizes and activity patterns of nine rehabilitated long-tailed gorals (four males and five females) across three regions (Yanggu, Seoraksan National Park, and Uljin) from 2014 to 2016. The 95% minimum convex polygon (MCP) home range averaged 0.64 ± 0.33 km2, while the 50% MCP home range averaged 0.15 ± 0.05 km2. The male home ranges were larger than the female home ranges. Additionally, the home ranges varied seasonally, with the smallest recorded in winter. The activity pattern of long-tailed gorals was predominantly crepuscular and diurnal, with no significant sexual differences. There were no significant differences in activity during spring, summer, and autumn; however, activity in winter differed significantly from that in the other seasons. The data provided on the home ranges and activity patterns of the species will serve as a basis for developing effective conservation and management strategies to protect this endangered species. By elucidating the spatial and temporal behaviors of long-tailed gorals, this study enhances our understanding of the ecological needs of the species and helps develop precise conservation measures.

Hidden space use behaviors of a nonbreeding migratory bird: the role of environment and social context

BACKGROUND

Movement behavior strongly mediates species and environment interactions, yet our understanding is constrained by challenges tracking space use at fine spatiotemporal resolutions.

METHODS

Using an automated telemetry array, we quantified variation in and drivers of space use for a nonbreeding population of migratory bird, the American redstart Setophaga ruticilla.

RESULTS

We identified two distinct and common behaviors - territoriality and floating,- that were governed primarily by NDVI as a proxy of resource availability. Within seasons, declines in weekly resources increased the prevalence of forays and the area of space utilized. Floaters were less likely to maintain body condition throughout the nonbreeding season, which is expected to negatively influence fitness and survival.

CONCLUSIONS

Our study demonstrates that nonbreeding migratory birds exhibit a high degree of plasticity in space use that is driven primarily by resource availability but influenced by the dominance hierarchy within an individual's environment which are expected to have important implications on migratory populations.

A benchmark for computational analysis of animal behavior, using animal-borne tags

BACKGROUND

Animal-borne sensors ('bio-loggers') can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community.

METHODS

To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers.

RESULTS

We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available.

CONCLUSIONS

In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE , to enable community use of BEBE.

Effects of temperature experienced across life stages on morphology and flight behavior of painted lady butterflies (Vanessa cardui)

BACKGROUND

With ongoing anthropogenic climate change, there is increasing interest in how organisms are affected by higher temperatures, including how animals respond behaviorally to increasing temperatures. Movement behavior is especially relevant, as the ability of a species to shift its range is implicitly dependent upon movement capacity and motivation. Temperature may influence movement behavior of ectotherms both directly, through an increase in body temperature, and indirectly, through temperature-dependent effects on physiological and morphological traits.

METHODS

We investigated the influence of ambient temperature during two life stages, larval and adult, on body size and movement behavior of the painted lady butterfly (Vanessa cardui). We reared painted ladies to emergence at either a "low" (24 °C) or "high" (28 °C) temperature. At eclosion, we assessed flight behavior in an arena test. We used a full factorial experimental design in which half of the adults that emerged from each rearing treatment were tested at either the "low" or "high" temperature. We measured adult body size, including wingspan, and determined flight speed, distance, and duration from video recordings.

RESULTS

Adult butterflies that experienced the higher temperature during development were larger. We documented an interaction of rearing x testing temperature on flight behavior: unexpectedly, the fastest butterflies were those who experienced a change in temperature, whether an increase or decrease, between rearing and testing. Individuals that experienced matching thermal environments flew more slowly, but for more time and covering more distance. We found no influence of body size per se on flight.

CONCLUSIONS

We conclude that the potential role of "matching" thermal environments across life stages has been underinvestigated with regard to how organisms may respond to warming conditions.

Navigating discreetly: Spatial ecology of urban wild boar in Bordeaux City's landscape of fear, France

An exemplary urban adapter, the wild boar (Sus scrofa) has successfully colonized urban ecological niches worldwide. Improvement of strategies for optimal management of urban wild boar need to gather more empirical evidence of their spatial ecology. This study is based on GPS tracking and capture-mark-recapture (CMR) of 10 and 59 wild boar, respectively, captured in Bordeaux Metropolis (France). It shows that wild boar have become urban dwellers, with intra-urban home ranges varying from 1.3 to 64.6 km2 (MCP 100 %) and from 0.5 to 9.6 km2 (KDE 95 %), depending on urban conditions. CMR results confirm the low propensity to move away from urban areas (with a mean distance of 2 km between capture and recapture sites), despite a relatively low one-year survival rate since capture (47.5 %), primarily attributable to removal efforts. Wild boar strongly depended on urban woods, mostly during daytime resting, and highly frequented urban meadows during night foraging. Their use of urban agricultural areas was minimal, but they were mostly monitored following corn and grape harvests. Wild boar mitigated the risk associated with close proximity to humans by: a nocturnal activity (72.2 % of active locations registered from sunset to sunrise), which could also be partially attributed to their sensitivity to heat; a strong use of covered habitats, especially during daytime resting and when close to buildings and roads; and a low mobility during night-time foraging (1974 m average daily distance travelled). Moreover, we demonstrate high inter- and intra-individual variability in the spatio-temporal behaviour of urban wild boar. Finally, we discuss the gap between these results and the narratives surrounding the spatial ecology of urban wild boar. Our results not only confirm the species' ability to adapt to urban environments, but also highlight their behavioural flexibility, underscoring the relevance of significant changes in representations and management activities to mitigate human-urban wild boar conflicts.

Influence of season, sex, and interspecific interactions on the diel activity patterns of two sympatric African small carnivores

Animal activity patterns vary seasonally and between species, facilitating species coexistence. In Africa, however, factors affecting the activity of many small carnivores remain poorly understood, especially for congeneric and sympatric species whose similar sizes may lead to interspecific competition. Here, we investigated differences and variations in the activity patterns of two sympatric Viverridae species in a seasonal African landscape. We continuously radio-tracked 15 small-spotted genets (Genetta genetta) and five Cape genets (G. tigrina) over 24-h cycles throughout the year. We analysed the effects of season, sex, and interspecific interactions on circadian rhythms using multi-cosinor regression models. Both species maintained a nocturnal activity pattern year-round, decreasing activity significantly during the cold-dry season. This pattern aligns with the thermoregulatory hypothesis-especially for species with an elongated body like genets-suggesting decreased activity under extreme cold weather conditions to conserve energy. Females in both species were less active than males, possibly due to their smaller home ranges, especially during the cold-dry season. These effects were particularly pronounced in Cape genets, which primarily inhabit riverine forests. Female Cape genets adjusted their activity onset, possibly to minimize encounters with males, mostly during the hot-wet season when caring for their offspring. Small-spotted genets shifted their activity onset and peak in riverine forests-areas of potential contact with Cape genets-compared to areas without Cape genets. Overall, our study underscores the critical role of seasonal environmental changes and interspecific interactions in shaping the activity patterns of two carnivore species within a semi-arid Albany Thicket landscape.

Spatial Ecology of a Resident Avian Predator During the Non-Breeding Period in Managed Habitats of Southeastern Europe

Describing home range and resource selection is crucial for understanding ecological needs and creating conservation programs. Still, our knowledge of spatial and behavioural ecology for most species remains limited. Here, we used satellite transmitters to investigate core and home range sizes, habitat selection, and roost characteristics in seven tawny owl males in Western Serbia during the autumn-winter period 2023. Using minimum convex polygon (MCP) and autocorrelated kernel density estimation (AKDE), we found clear variability in core area and home range sizes. Also, adult and heavier males have smaller core area and home ranges than juvenile and lightweight individuals. The Bhattacharyya coefficient showed minor home range overlap in tagged males. The final model for evaluation of habitat selection suggests that the likelihood of owl occurrence was positively correlated with the share of anthropogenic infrastructure and negatively associated with the increase in the proportion of cultivated land within the home range. However, scores of model performance metrics showed moderate predictive accuracy, implying that other unmeasured variables may dictate species presence. Our study illustrates the ecological plasticity and ability of the tawny owl to adapt to a human-modified environment while providing new information about the spatial ecology of this widespread predator in Europe.

Foxtrot migration and dynamic over-wintering range of an Arctic raptor

Advances in tracking technologies have revealed the diverse migration patterns of birds, which are critical for range mapping and population estimation. Population trends are usually estimated in breeding ranges where birds remain stationary, but for species that breed in remote areas like the Arctic, these trends are often assessed in over-wintering ranges. Assessing population trends during the wintering season is challenging due to the extensive movements of birds in these ranges, which requires a deep understanding of the movement dynamics. However, these movements remain understudied, particularly in the mid-latitudes, where many Arctic breeders overwinter, increasing uncertainty in their ranges and numbers. Here, we show that the Arctic breeding raptor Rough-legged buzzard, which overwinters in the mid-latitudes, has a specific wintering strategy. After migrating ca. 1500 km from the Arctic to mid-latitudes, the birds continue to move throughout the entire over-wintering period, traveling another 1000 km southwest and then back northeast as the snowline advances. This continuous movement makes their wintering range dynamic throughout the season. In essence, this movement represents an extension of the quick migration process, albeit at a slower pace, and we have termed this migration pattern 'foxtrot migration', drawing an analogy to the alternating fast and slow movements of the foxtrot dance. These results highlight the potential errors in range mapping from single mid-winter surveys and emphasize the importance of this migration pattern in assessing the conservation status of bird species. Understanding this migration pattern could help to correctly estimate bird populations in over-wintering ranges, which is especially important for species that nest in hard-to-reach regions such as the Arctic.

Next-Generation Remote Sensing Data at Multiple Spatial Scales Improves Understanding of Habitat Selection by a Small Mammal

Recent advances in optical remote sensing (RS) technology in combination with lightweight Global Positioning System (GPS) tracking devices now make analyzing the multi-scale habitat selection (HS) of small mammals < 2 kg possible. However, there have been relatively few multi-scale HS studies integrating fine-scale RS data with data-rich, GPS-derived movement data from small mammals. This is critical because small mammals commonly select habitat features across multiple scales. To address this gap, we investigated the HS of a small mammal, fox squirrels (Sciurus niger), which are known to cover relatively large areas and select fine-scale environmental features. We specifically asked the following questions: (1) Do next-generation RS variables improve HS models at single spatial scales? (2) Do multi-scale HS models improve upon those at single spatial scales? Using data from 45 individuals, we constructed HS models at three spatial scales: 4 ha (210 m × 210 m), 0.09 ha (30 m × 30 m), and 0.01 ha (10 m × 10 m) using traditional and next-generation RS data. The 4-ha model, using traditional and next-generation RS data, produced the best single-scale model, explaining 58% of the variations in HS. However, the multi-scale model provided the most informative model, explaining 68% of the variations in HS. Our models provide evidence for the value of next-generation RS data when quantifying HS and additional support for the idea of studying HS at multiple spatial scales.

Age, sex, and temperature shape off-territory feeder use in black-capped chickadees

Spatial ecology tends to focus on average movement patterns within animal groups; however, recent studies highlight the value of considering movement decisions both within and among individuals. We used a marked population of black-capped chickadees (Poecile atricapillus), to assess the causes and consequences of within- and among-individual differences in chickadee space use. Individuals that used feeders in addition to their most-visited "core feeder" were defined as engaging in off-territory feeder use. We found that females were more likely than males to visit off-territory feeders as ambient temperatures decrease and energetic demands increase. This may be due to sex-related differences in dominance, where males which are the dominant sex in chickadees, have priority access to feeders, while females must increase their foraging areas to meet higher energetic demand. We also found that independent of temperature, adult males were less likely than juvenile males and both juvenile and adult females to forage off-territory. We suggest that this may be due to age-specific benefits of space use in males, where un-paired juvenile males may increase feeder exploration to gain information about potential mates. Finally, we found that chickadees that had a higher propensity to visit off-territory feeders were less likely to survive to the next fall. Overall, our results suggest that dominance hierarchies and individual energetics impact within- and among-individual variation in off-territory feeder use. We provide suggestions for future studies to further investigate fitness-related consequences of within- and among-individual variation in space use.

Sick without signs. Subclinical infections reduce local movements, alter habitat selection, and cause demographic shifts

In wildlife populations, parasites often go unnoticed, as infected animals appear asymptomatic. However, these infections can subtly alter behaviour. Field evidence of how these subclinical infections induce changes in movement behaviour is scarce in free-ranging animals, yet it may be crucial for zoonotic disease surveillance. We used an ultra-high-resolution tracking system (ATLAS) to monitor the movements of 60 free-ranging swallows every 8 seconds across four breeding seasons, resulting in over 1 million localizations. About 40% of these swallows were naturally infected with haemosporidian parasites. Here, we show that infected individuals had reduced foraging ranges, foraged in lower quality habitats, and faced a lowered survival probability, with an average reduction of 7.4%, albeit with some variation between species and years. This study highlights the impact of subclinical infections on movement behaviour and survival, emphasizing the importance of considering infection status in movement ecology. Our findings provide insights into individual variations in behaviour and previously unobservable local parasite transmission dynamics.

Multiphasic movement and step-selection patterns of dispersed tigers in the central Indian landscape

Large carnivores play a crucial role in the ecosystem, though their conservation needs a landscape-level approach due to their wide range of habitats and dispersal events. The study of tigers in a human-dominated landscape matrix and their adaptation and adjustment of movement behaviours during the dispersal phase is essential for long-term conservation planning and management policy. We studied the dispersal event of five VHF/GPS collared individuals during 2009-2020. We investigated movement parameters (step length), and the effects of anthropogenic pressures (distance from village), distance from water and vegetation cover, on behavioural phase under a Hidden Markov Model framework. We also tested the effects of distance from village, vegetation cover, and habitat types on animal movement using an integrated Step Selection Function framework. The mean step length (405.44±10.63 m/hr) varied widely by different time of day. Displacement was high during the night (665.28±21.36 m/hr) compared to day (434.16±17.37 m/hr). Tigers moved fast (872.7m; 95% CI 839.1-906.3m) with longer step length and a directional turning angle in non-forested areas (i.e. the human-dominated landscape), likely to avoid conflict with humans. Individuals distinctly exhibited two behavioural states: encamping (~32% of the time) and travelling (~68% of the time). Further, they avoided the human-dominated landscape and mostly remained in and forested areas, especially during nighttime. Our study is the first attempt to understand behavioural transition of dispersal tigers and their habitat selection. Lesser anthropogenic disturbance and high vegetation cover positively influenced the tiger dispersal, while water availability did not affect their state transitional probability. Additionally, dispersers showed high affinity towards forested land during nighttime for travelling.The findings of this study show the importance of functional corridors and stepping stones (mostly encamping areas), and also provide baseline knowledge for integrated landscape management planning and policymaking for the long-term survival of tigers in metapopulation framework.

A wrap-around movement path randomization method to distinguish social and spatial drivers of animal interactions

Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses about the factors determining animal interactions often involves comparing observed interactions with reference or 'null' models. One approach to accounting for spatial drivers of social interactions in reference models is randomizing animal movement paths to decouple spatial and social phenotypes while maintaining environmental effects on movements. Here, we update a reference model that detects social attraction above the effect of spatial constraints. We explore the use of our 'wrap-around' method and compare its performance to the previous approach using agent-based simulations. The wrap-around method provides reference models that are more similar to the original tracking data, while still distinguishing between social and spatial drivers. Furthermore, the wrap-around approach results in fewer false-positives than its predecessor, especially when animals do not return to one place each night but change movement foci, either locally or directionally. Finally, we show that interactions among GPS-tracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from spatial constraints on their movements. We conclude by highlighting the biological situations in which the updated method might be most suitable for testing hypotheses about the underlying causes of social interactions. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Harnessing the gut microbiome: a potential biomarker for wild animal welfare

The welfare of wild animal populations is critically important to conservation, with profound implications for ecosystem health, biodiversity, and zoonotic disease transmission. Animal welfare is typically defined as the accumulated affective mental state of an animal over a particular time period. However, the assessment of animal welfare in the wild poses unique challenges, primarily due to the lack of universally applicable biomarkers. This perspective explores the potential role of the gut microbiome, a dynamic and non-invasive biomarker, as a novel avenue for evaluating animal welfare in wild animals. The gut microbiome, through interactions with the host's physiology, behavior, and cognition, offers a promising opportunity to gain insights into the well-being of animals. In this synthesis, we discuss the distinction between fitness and welfare, the complexities of assessing welfare in wild populations, and the linkages between the gut microbiome and aspects of animal welfare such as behavior and cognition. We lastly elucidate how the gut microbiome could serve as a valuable tool for wildlife managers, with the potential to serve as a non-invasive yet informative window into the welfare of wild animals. As this nascent field evolves, it presents unique opportunities to enhance our understanding of the well-being of wild animals and to contribute to the preservation of ecosystems, biodiversity, and human health.

Tracking Small Animals in Complex Landscapes: A Comparison of Localisation Workflows for Automated Radio Telemetry Systems

Automated radio telemetry systems (ARTS) have the potential to revolutionise our understanding of animal movement by providing a near-continuous record of individual locations in the wild. However, localisation errors in ARTS data can be very high, especially in natural landscapes with complex vegetation structure and topography. This curtails the research questions that may be addressed with this technology. We set up an ARTS grid in a valley with heterogeneous vegetation cover in the Colombian high Andes and applied an analytical pipeline to test the effectiveness of localisation methods. We performed calibration trials to simulate animal movement in high- or low-flight, or walking on the ground, and compared workflows with varying decisions related to signal cleaning, selection, smoothing, and interpretation, along with four multilateration approaches. We also quantified the influence of spatial features on the system's accuracy. Results showed large variation in localisation error, ranging between 0.4-43.4 m and 474-1929 m, depending on the localisation method used. We found that the selection of higher radio signal strengths and data smoothing based on the temporal autocorrelation are useful tools to improve accuracy. Moreover, terrain ruggedness, height of movement, vegetation type, and the location of animals inside or outside the grid area influence localisation error. In the case of our study system, thousands of location points were successfully estimated for two high-altitude hummingbird species that previously lacked movement data. Our case study on hummingbirds suggests ARTS grids can be used to estimate small animals' home ranges, associations with vegetation types, and seasonality in occurrence. We present a comparative localisation pipeline, highlighting the variety of possible decisions while processing radio signal data. Overall, this study provides guidance to improve the resolution of location estimates, broadening the application of this tracking technology in the study of the spatial ecology of wild populations.

The statistical building blocks of animal movement simulations

Animal movement plays a key role in many ecological processes and has a direct influence on an individual's fitness at several scales of analysis (i.e., next-step, subdiel, day-by-day, seasonal). This highlights the need to dissect movement behavior at different spatio-temporal scales and develop hierarchical movement tools for generating realistic tracks to supplement existing single-temporal-scale simulators. In reality, animal movement paths are a concatenation of fundamental movement elements (FuMEs: e.g., a step or wing flap), but these are not generally extractable from a relocation time-series track (e.g., sequential GPS fixes) from which step-length (SL, aka velocity) and turning-angle (TA) time series can be extracted. For short, fixed-length segments of track, we generate their SL and TA statistics (e.g., means, standard deviations, correlations) to obtain segment-specific vectors that can be cluster into different types. We use the centroids of these clusters to obtain a set of statistical movement elements (StaMEs; e.g.,directed fast movement versus random slow movement elements) that we use as a basis for analyzing and simulating movement tracks. Our novel concept is that sequences of StaMEs provide a basis for constructing and fitting step-selection kernels at the scale of fixed-length canonical activity modes: short fixed-length sequences of interpretable activity such as dithering, ambling, directed walking, or running. Beyond this, variable length pure or characteristic mixtures of CAMs can be interpreted as behavioral activity modes (BAMs), such as gathering resources (a sequence of dithering and walking StaMEs) or beelining (a sequence of fast directed-walk StaMEs interspersed with vigilance and navigation stops). Here we formulate a multi-modal, step-selection kernel simulation framework, and construct a 2-mode movement simulator (Numerus ANIMOVER_1), using Numerus RAMP technology. These RAMPs run as stand alone applications: they require no coding but only the input of selected parameter values. They can also be used in R programming environments as virtual R packages. We illustrate our methods for extracting StaMEs from both ANIMOVER_1 simulated data and empirical data from two barn owls (Tyto alba) in the Harod Valley, Israel. Overall, our new bottom-up approach to path segmentation allows us to both dissect real movement tracks and generate realistic synthetic ones, thereby providing a general tool for testing hypothesis in movement ecology and simulating animal movement in diverse contexts such as evaluating an individual's response to landscape changes, release of an individual into a novel environment, or identifying when individuals are sick or unusually stressed.

Mammals show faster recovery from capture and tagging in human-disturbed landscapes

Wildlife tagging provides critical insights into animal movement ecology, physiology, and behavior amid global ecosystem changes. However, the stress induced by capture, handling, and tagging can impact post-release locomotion and activity and, consequently, the interpretation of study results. Here, we analyze post-tagging effects on 1585 individuals of 42 terrestrial mammal species using collar-collected GPS and accelerometer data. Species-specific displacements and overall dynamic body acceleration, as a proxy for activity, were assessed over 20 days post-release to quantify disturbance intensity, recovery duration, and speed. Differences were evaluated, considering species-specific traits and the human footprint of the study region. Over 70% of the analyzed species exhibited significant behavioral changes following collaring events. Herbivores traveled farther with variable activity reactions, while omnivores and carnivores were initially less active and mobile. Recovery duration proved brief, with alterations diminishing within 4-7 tracking days for most species. Herbivores, particularly males, showed quicker displacement recovery (4 days) but slower activity recovery (7 days). Individuals in high human footprint areas displayed faster recovery, indicating adaptation to human disturbance. Our findings emphasize the necessity of extending tracking periods beyond 1 week and particular caution in remote study areas or herbivore-focused research, specifically in smaller mammals.

Combined effects of landscape fragmentation and sampling frequency of movement data on the assessment of landscape connectivity

BACKGROUND

Network 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.

METHODS

We 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.

RESULTS

We 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.

CONCLUSIONS

Very 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.

Seasonal habitat use and diel vertical migration in female spurdog in Nordic waters

BACKGROUND

Studying habitat use and vertical movement patterns of individual fish over continuous time and space is innately challenging and has therefore largely remained elusive for a wide range of species. Amongst sharks, this applies particularly to smaller-bodied and less wide-ranging species such as the spurdog (Squalus acanthias Linnaeus, 1758), which, despite its importance for fisheries, has received limited attention in biologging and biotelemetry studies, particularly in the North-East Atlantic.

METHODS

To investigate seasonal variations in fine-scale niche use and vertical movement patterns in female spurdog, we used archival data from 19 pregnant individuals that were satellite-tagged for up to 365 days in Norwegian fjords. We estimated the realised niche space with kernel densities and performed continuous wavelet analyses to identify dominant periods in vertical movement. Triaxial acceleration data were used to identify burst events and infer activity patterns.

RESULTS

Pregnant females frequently utilised shallow depths down to 300 m at temperatures between 8 and 14 °C. Oscillatory vertical moments revealed persistent diel vertical migration (DVM) patterns, with descents at dawn and ascents at dusk. This strict normal DVM behaviour dominated in winter and spring and was associated with higher levels of activity bursts, while in summer and autumn sharks predominantly selected warm waters above the thermocline with only sporadic dive and bursts events.

CONCLUSIONS

The prevalence of normal DVM behaviour in winter months linked with elevated likely foraging-related activity bursts suggests this movement behaviour to be foraging-driven. With lower number of fast starts exhibited in warm waters during the summer and autumn months, habitat use in this season might be rather driven by behavioural thermoregulation, yet other factors may also play a role. Individual and cohort-related variations indicate a complex interplay of movement behaviour and habitat use with the abiotic and biotic environment. Together with ongoing work investigating fine-scale horizontal movement as well as sex- and age-specific differences, this study provides vital information to direct the spatio-temporal distribution of a newly reopened fishery and contributes to an elevated understanding of the movement ecology of spurdog in the North-East Atlantic and beyond.

Agreements for conserving migratory shorebirds in the Asia-Pacific are better fit for addressing habitat loss than hunting

A full-life cycle approach is a tenet of migratory species conservation, yet the degree to which this is achieved remains largely unassessed. This knowledge gap can be addressed using the concept of social-ecological fit, understood as the match between governance and ecological dimensions. Here, we assess the social-ecological fit for conserving migratory shorebirds in the Asia-Pacific, focusing on habitat loss and hunting. We identify the governance architectures for addressing these two threats and then assess the coordinating capacity of each architecture, measure institutional coverage for each species across their range, and determine the degree of institutional connectivity along their migratory network. We find that social-ecological fit is higher for the governance of habitat designation than for hunting management, with implications for governance practice. Analyses of social-ecological fit thus provide critical insights on the potential effectiveness of governance and therefore are a useful first step for migratory species conservation.

Development of a multisensor biologging collar and analytical techniques to describe high-resolution spatial behavior in free-ranging terrestrial mammals

Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data. Here, we present (i) a custom-designed integrated multisensor collar (IMSC), which was field tested on 71 free-ranging wild boar (Sus scrofa) over 2 years; (ii) a machine learning behavioral classifier capable of identifying six behaviors in free-roaming boar, validated across individuals equipped with differing collar designs; and (iii) laboratory and field-based calibration and accuracy assessments of animal magnetic heading measurements derived from raw magnetometer data. The IMSC capacity and durability exceeded expectations, with a 94% collar recovery rate and a 75% cumulative data recording success rate, with a maximum logging duration of 421 days. The behavioral classifier had an overall accuracy of 85% in identifying the six behavioral classes when tested on multiple collar designs and improved to 90% when tested on data exclusively from the IMSC. Both laboratory and field tests of magnetic compass headings were in precise agreement with expectations, with overall median magnetic headings deviating from ground truth observations by 1.7° and 0°, respectively. Although multisensor equipment and sophisticated analyses are now commonplace in biologging studies, the IMSC hardware and analytical framework presented here provide a valuable tool for biologging researchers and will facilitate standardization of biologging data across studies. In addition, we highlight the potential of additional analyses available using this framework that can be adapted for use in future studies on terrestrial mammals.

Determinants of macaques' space use: A test for the ecological constraints model using GPS collars

As a central topic in Behavioral Ecology, animal space use involves dynamic responses to social and ecological factors. We collared 22 rhesus macaques (Macaca mulatta) from six groups on Neilingding Island, China, and collected 80,625 hourly fixes over a year. Using this high-resolution location data set, we quantified the macaques' space use at the individual level and tested the ecological constraints model while considering various environmental and human interfering factors. As predicted by the ecological constraints model, macaques in larger groups had longer daily path lengths (DPLs) and larger home ranges. We found an inverted U-shape relationship between mean daily temperatures and DPLs, indicating that macaques traveled farther on mild temperature days, while they decreased DPLs when temperatures were too high or too low. Anthropogenic food subsidies were positively correlated to DPLs, while the effect of rainfall was negative. Macaques decreased their DPLs and core areas when more flowers and less leaves were available, suggesting that macaques shifted their space use patterns to adapt to the seasonal differences in food resources. By applying GPS collars on a large number of individuals living on a small island, we gained valuable insights into within-group exploitation competition in wild rhesus macaques.

Overton C, A. Lorenz A, L. Matchett E, L. Mott A, A. Mackell D, T. Ackerman J, De La Cruz SEW, Patil VP, Prosser DJ, Takekawa JY, Orthmeyer DL, Pitesky ME, Díaz-Muñoz SL, Riggs BM, Gendreau J, Reed ET, Petrie MJ, Williams CK, Buler JJ, Hardy MJ, Ladman BS, Legagneux P, Bêty J, Thomas PJ, Rodrigue J, Lefebvre J, Casazza ML. Mitigating Risk: Predicting H5N1 Avian Influenza Spread with an Empirical Model of Bird Movement

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting ~600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was effective for wild waterfowl, but predictions lagged HPAIv detections in poultry facilities and among some highly impacted nonmigratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multispecies tracking to highlight potential high-risk disease spread locations and more effectively manage outbreaks.

Telemetry without collars: performance of fur- and ear-mounted satellite tags for evaluating the movement and behaviour of polar bears

The study of animal movement provides insights into underlying ecological processes and informs analyses of behaviour and resource use, which have implications for species management and conservation. The tools used to study animal movement have evolved over the past decades, allowing for data collection from a variety of species, including those living in remote environments. Satellite-linked radio and GPS collars have been used to study polar bear (Ursus maritimus) ecology and movements throughout the circumpolar Arctic for over 50 years. However, due to morphology and growth constraints, only adult female polar bears can be reliably collared. Collars have proven to be safe, but there has been opposition to their use, resulting in a deficiency in data across much of the species' range. To bolster knowledge of movement characteristics and behaviours for polar bears other than adult females, while also providing an alternative to collars, we tested the use of fur- and ear-mounted telemetry tags that can be affixed to polar bears of any sex and age. We tested three fur tag designs (SeaTrkr, tribrush and pentagon tags), which we affixed to 15 adult and 1 subadult male polar bears along the coast of Hudson Bay during August-September 2021-2022. Fur tags were compared with ear tags deployed on 42 subadult and adult male polar bears captured on the coast or the sea ice between 2016 and 2022. We used data from the tags to quantify the amount of time subadult and adult males spent resting versus traveling while on land. Our results show the three fur tag designs remained functional for shorter mean durations (SeaTrkr = 58 days; tribrush = 47 days; pentagon = 22 days) than ear tags (121 days), but positional error estimates were comparable among the Argos-equipped tags. The GPS/Iridium-equipped SeaTrkr fur tags provided higher resolution and more frequent location data. Combined, the tags provided sufficient data to model different behavioural states. Furthermore, as hypothesized, subadult and adult male polar bears spent the majority of their time resting while on land, increasing time spent traveling as temperatures cooled. Fur tags show promise as a short-term means of collecting movement data from free-ranging polar bears.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40317-024-00373-2.

Predator in proximity: how does a large carnivore respond to anthropogenic pressures at fine-scales? Implications for interface area management

Background

Driven by habitat loss and fragmentation, large carnivores are increasingly navigating human-dominated landscapes, where their activity is restricted and their behaviour altered. This movement, however, raises significant concerns and costs for people living nearby. While intricately linked, studies often isolate human and carnivore impacts, hindering effective management efforts. Hence, in this study, we brought these two into a common framework, focusing on an interface area between the critical tiger habitat and the human-dominated multiple-use buffer area of a central Indian protected area.

Methods

We employed a fine-scale camera trap survey complemented by GPS-collar movement data to understand spatio-temporal activity patterns and adjustments of tigers in response to anthropogenic pressures. We used an occupancy framework to evaluate space use, Bayesian circular GLMs to model temporal activity, and home range and step length analyses to assess the movement patterns of tigers. Further, we used predation-risk models to understand conflict patterns as a function of tiger presence and other habitat variables.

Results

Despite disturbance, a high proportion of the sampled area was occupied by 17 unique tigers (ψ = 0.76; CI [0.73-0.92]). The distance to villages (β ± SE = 0.63 ± 0.21) and the relative abundance of large-bodied wild prey (β ± SE = 0.72 ± 0.37) emerged as key predictors of tiger space use probability, indicating a preference for wild prey by tigers, while human influences constrained their habitat utilisation. Distance to villages was also identified as the most significant predictor of the tigers' temporal activity (μ ± σ = 3.03 ± 0.06 rad) that exhibited higher nocturnality near villages. A total of 11% of tiger home ranges were within village boundaries, accompanied by faster movement in these areas (displacement 40-82% higher). Livestock depredation probability by tigers increased with proximity to villages (P = 0.002) and highway (P = 0.003). Although tiger space use probability (P = 0.056) and wild prey abundance (P = 0.134) were non-significant at the 0.05 threshold, their presence in the best-fit predation-risk model suggests their contextual relevance for understanding conflict risk. The results highlight the importance of appropriately managing livestock near human infrastructures to effectively mitigate conflict.

Conclusions

Shared space of carnivores and humans requires dynamic site-specific actions grounded in evidence-based decision-making. This study emphasises the importance of concurrently addressing the intricate interactions between humans and large carnivores, particularly the latter's behavioural adaptations and role in conflict dynamics. Such an integrated approach is essential to unravel cause-effect relationships and promote effective interface management in human-dominated landscapes.

ExMove: An open-source toolkit for processing and exploring animal-tracking data in R

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.