Movement ecology-the study of how and why animals move within their environments-stands to offer transformative insights into our rapidly changing world, with benefits for both nature and people. Here, we present the first global horizon scan for movement ecology, engaging leading experts to identify innovations likely to shape the field over the next two decades. These include: engineering breakthroughs, such as long-lived miniature tags with enhanced sensing capacities, non-invasive attachment mechanisms and real-time data processing; analytical advances to predict movement trajectories and scale individual data to population-level patterns; and targeted coordination to mobilize data, scale collaborative infrastructure and expand participation in underrepresented regions. Strategic investment in these priorities would advance understanding of wildlife biology and ecosystem functions, providing mechanistic insights that could help address planetary-scale challenges from biodiversity loss to global health. To highlight these opportunities, we map alignment between identified innovations, movement ecology applications and key multilateral environmental frameworks, including the Kunming-Montreal Global Biodiversity Framework and the Sustainable Development Goals. Our analyses fill a gap at a critical juncture in the evolution of movement ecology as a discipline, offering a community-driven agenda that calls attention to the wide-reaching implications of the advancements on the horizon today.

Abstract Communication structures society, and is likewise shaped by relationships and shared tasks; yet, for most socially complex species, we know little of their full vocal repertoire and its functions. We investigated how communication structures the who, what, and when of social interactions in cooperative carrion crows – group-living birds who rely on coordinated behaviors, as in chick care. Leveraging machine learning to integrate large-scale data from crow-borne audio-loggers and nest cameras, we charted the vocal repertoire across 24 cooperative groups and mapped all discovered call types to behaviors and social context. We found that crows used a rich repertoire across three domains of joint behavior – flocking, chick care, and territorial display. Relatively quiet call types were abundant and included close-range calls that may coordinate chick care by announcing nest visits. Our study demonstrates how combining continuous-capture data and machine learning can reveal a holistic understanding of how vocalizations function across contexts.

Wildlife is increasingly forced to share space with humans, facing disturbances that operate across different spatial and temporal scales. The press-pulse framework, originally developed in the disturbance ecology literature, distinguishes between long-term sustained 'presses' and more acute 'pulses'. Because pulses occur during ongoing press conditions, their ecological effects depend on how they interact with that background, helping explain why certain disturbances result in transient, localized changes, while others lead to lasting, widespread impacts. Here, we expand this framework by applying it to regimes of human disturbances, and incorporating 'pauses' as a third category. Pulses and pauses (e.g. episodes of extreme weather, or drastic changes in human mobility) can substantially affect wildlife behaviour, yet their effects are often modulated by background 'press' conditions. We offer a conceptual framework for disentangling effects across space and time and highlight how plasticity in wildlife movement-particularly in terms of navigating risks and tracking resources-can lead to both adaptive and nonadaptive responses to human disturbances. This enables predictions about how shifts in animal movement can influence human wildlife interactions and conflict with humans under different scenarios. Applying the press-pulse-pause framework to movement ecology allows researchers to improve our understanding of how wildlife is affected by different disturbance regimes, advancing efforts to foster sustainable human-wildlife coexistence in an era of mounting pressures.

Sustainable human–wildlife coexistence requires a mechanistic understanding of the many ways that humans affect animals. However, progress is hampered by the lack of accessible data measuring the dynamic presence of people. Here, we leverage mobile-device data to disentangle how human presence and landscape modification differentially influence the use of geographic and environmental space for 37 mammal and bird species across the United States. Human presence affected more than 65% of species, with substantial variation across species. For ~60% of species that responded to human activities, the effects were interdependent—animals tended to react more strongly to human presence in less modified habitats. Our results demonstrate that human presence and landscape modification have complex combined effects on wildlife, which need to be considered for effective management.

Many research fields rely on assessing the behaviour of wild or captive animals, using observational and experimental protocols. This work is highly susceptible to sampling biases which, when unrecognized or undisclosed, can cause replication failure. Here, we illustrate how the STRANGE framework can be used to improve reporting quality and, ultimately, replicability in animal behaviour research. Using a combination of real-world and hypothetical case studies, we demonstrate how structured reporting of information about subjects and testing procedures can help contextualize mixed findings, enabling both improved assessments of research replicability and deeper biological insight. As a flexible tool for identifying, mitigating and reporting sampling biases, the STRANGE framework is already being leveraged productively by a wide range of user groups, including researchers, consortia, educators and journals. Our case study analyses have revealed several specific opportunities to support further community engagement and uptake. We recommend using the STRANGE framework to develop teaching materials on sampling biases, to support the work of many-labs consortia, to prepare robust preregistrations and registered reports and to conduct systematic retrospective analyses of seemingly unreliable findings. With its light-touch, researcher-led approach, the STRANGE framework has initiated an exciting grassroots push towards improved study designs, reporting and replicability in animal behaviour research.

Effective biodiversity conservation requires innovative spatial planning strategies for unprotected areas. A major obstacle to promoting sustainable human–wildlife coexistence is our limited understanding of how animal movement is affected by habitat fragmentation, barriers like roads, fences, settlements and infrastructure, and human disturbance. This information is essential for ensuring good functional connectivity in human-modified landscapes, yet is rarely available to spatial planners, who instead must resort to using coarse proxies or simulated data. Cutting-edge animal-tracking technology is the method of choice for filling this knowledge gap. Miniature wildlife ‘wearables’ can be used to record high-resolution movement trajectories (GPS) and estimate activity budgets (accelerometer) for wild animals, revealing the specific environmental conditions that cause species to either thrive or struggle. Now is the time to strategically deploy this proven methodology at scale, to learn how best to share space with wildlife. A new initiative by the National Geographic Society is building a global network of field teams to track a wide range of terrestrial mammals and birds across gradients of land modification worldwide. Each field team will investigate their chosen study species in a matched pair of high- and low-disturbance sites (e.g., urban/rural; unprotected/protected), yielding contrasts for aggregated downstream analyses across taxonomic groups, regions, and environmental contexts. This unprecedented collaborative effort will significantly advance our understanding of the behaviour and ecological needs of wildlife in human-modified landscapes, enabling innovative, context-appropriate and scalable approaches to spatial planning. Specifically, by integrating dynamic wildlife movement data into their decision-support systems, spatial planners will be able to determine acceptable degrees of habitat fragmentation, maximise functional connectivity, create effective wildlife corridors, bridges and refugia, reduce the barrier-function of road networks and other infrastructure, and minimise disturbance by aligning the mobility needs of humans and wildlife. This work will not only benefit wildlife, but it will also strengthen ecosystem integrity, health and resilience more generally, realising nature’s full potential to contribute to a good quality of life for people.

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.

Animal movement data have transformed our understanding of ecological systems and shaped conservation practice, but have limited influence on tracking progress towards international biodiversity goals. Existing biodiversity indicators adopted in frameworks such as the Kunming–Montréal Global Biodiversity Framework — the primary multilateral conservation agreement that aims to halt and reverse biodiversity loss by 2030 — are typically not responsive enough to detect biodiversity change in time to guide action, nor sufficiently biologically informative to explain or predict changes. In this Perspective, we provide seven reasons why movement data can help to tackle these limitations by adding biological realism, mechanistic understanding, and early-warning capacity to current and future indicators. Movement data already inform conservation efforts, from local management to global treaties for migratory species, and are increasingly helpful to uncover sources of environmental change, while enhancing monitoring capability and policy relevance. We recommend that the scientific community ground existing connectivity metrics in empirical movement data, develop new indicators that flag rapid change, and invest in modelling and attribution studies that use movement data to identify drivers of biodiversity loss and recovery. Biodiversity indicators are essential for tracking progress towards international biodiversity goals, but existing indicators have important shortcomings and are not based on animal movement data. This Perspective outlines why incorporating movement data into biodiversity indicators can help to address these shortcomings, improve monitoring and inform effective conservation actions.

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.

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. Animal-borne electronic tags, or bio-loggers, are increasingly used for research and wildlife conservation. This Perspective discusses the importance of standardization, long-term archiving and sharing of bio-logging data, and outlines a roadmap to achieve these goals.

Developing robust strategies for human-wildlife coexistence is hampered by our limited understanding of how humans impact animal space use. It is challenging to measure the relative effects of landscape modification and human mobility on wildlife, since these factors are typically confounded. The extreme change in human mobility levels that occurred during COVID-19 lockdowns provided an opportunity to disentangle these impacts. Many gull species are considered urban adapters, capable of roosting, foraging and breeding near humans in highly modified environments. We predicted that lockdown-induced changes in human mobility would affect gulls' selection for urban and beach habitats because of altered disturbance levels and food availability. We analysed GPS tracking data from 113 individual gulls over multiple years (2015-2022), across three species in western Europe (herring gull Larus argentatus, lesser black-backed gull L. fuscus and yellow-legged gull L. michahellis). We found that, during lockdowns, selection for urban areas increased in two of ten colonies and selection for beaches increased in one colony and decreased in two others. This heterogeneous pattern likely reflects differences in how gull populations respond to opportunities and challenges presented by human-modified landscapes. Understanding this context dependence is emerging as a priority for coordinated efforts to promote sustainable human-wildlife coexistence.

Historically, much research in animal communication has focused on the information content and ultimate function of vocalisations. These include defending territories, sounding the alarm, attracting mates, and advertising identity. The proximate mechanisms that shape signal production and perception—including cognitive processes and cultural transmission—have only recently started attracting attention. Corvids are a well-established study system in comparative cognition and social evolution research, yet their vocal communication remains surprisingly understudied compared to other songbirds, which have been central to advancing our understanding of how natural selection shapes communication. With their flexible, context-dependent communication and capacity for vocal learning, corvids represent a particularly promising system for addressing open questions relating to vocal communication. Their diverse ecological and social environments, combined with extensively studied cognitive abilities, make them well-suited for investigating the co-evolution of communication, sociality, and cognition. To unlock the potential of corvids as a system for studying vocal communication, several methodological opportunities and challenges must be addressed. These include the development of experimental designs suited to both wild and captive settings, and the adoption of advanced technologies for data collection in naturalistic environments. Recent advances in data processing—such as machine learning, acoustic classification, and automated tracking—open up promising new avenues for decoding corvid communication. These tools are promising to reshape the field by enabling more fine-grained, large-scale analyses of vocal behaviour. Ultimately, a deeper understanding of corvid vocal communication can significantly enhance our broader insights into the evolution of animal communication and the origins of human language. Furthermore, it holds applied value for improving animal welfare and conservation, including innovations in welfare monitoring and strategies for addressing human-wildlife conflict.

Conservation translocations are increasingly used in species' recovery. Their success often depends upon maintaining or restoring survival-relevant behaviour, which is socially learned in many animals. A lack of species- or population-appropriate learning can lead to the loss of adaptive behaviour, increasing the likelihood of negative human interactions and compromising animals' ability to migrate, exploit resources, avoid predators, integrate into wild populations, reproduce and survive. When applied well, behavioural tools can address deficiencies in socially learned behaviours and boost survival. However, their use has been uneven between species and translocation programmes, and behaviour commonly contributes to translocation failure. Critically, current international guidance (e.g. the International Union for Conservation of Nature's translocation guidelines) does not directly discuss social learning or its facilitation. We argue that linking knowledge about social learning to appropriate translocation strategies will enhance guidance and direct future research. We offer a framework for incorporating animal social learning into translocation planning, implementation, monitoring and evaluation across wild and captive settings. Our recommendations consider barriers practitioners face in contending with logistics, time constraints and intervention cost. We emphasize that stronger links between researchers, translocation practitioners and wildlife agencies would increase support for social learning research, and improve the perceived relevance and feasibility of facilitating social learning.This article is part of the theme issue 'Animal culture: conservation in a changing world'.

Predicting animal movements and spatial distributions is crucial for our comprehension of ecological processes and provides key evidence for conserving and managing populations, species and ecosystems. Notwithstanding considerable progress in movement ecology in recent decades, developing robust predictions for rapidly changing environments remains challenging. To accurately predict the effects of anthropogenic change, it is important to first identify the defining features of human-modified environments and their consequences on the drivers of animal movement. We review and discuss these features within the movement ecology framework, describing relationships between external environment, internal state, navigation and motion capacity. Developing robust predictions under novel situations requires models moving beyond purely correlative approaches to a dynamical systems perspective. This requires increased mechanistic modelling, using functional parameters derived from first principles of animal movement and decision-making. Theory and empirical observations should be better integrated by using experimental approaches. Models should be fitted to new and historic data gathered across a wide range of contrasting environmental conditions. We need therefore a targeted and supervised approach to data collection, increasing the range of studied taxa and carefully considering issues of scale and bias, and mechanistic modelling. Thus, we caution against the indiscriminate non-supervised use of citizen science data, AI and machine learning models. We highlight the challenges and opportunities of incorporating movement predictions into management actions and policy. Rewilding and translocation schemes offer exciting opportunities to collect data from novel environments, enabling tests of model predictions across varied contexts and scales. Adaptive management frameworks in particular, based on a stepwise iterative process, including predictions and refinements, provide exciting opportunities of mutual benefit to movement ecology and conservation. In conclusion, movement ecology is on the verge of transforming from a descriptive to a predictive science. This is a timely progression, given that robust predictions under rapidly changing environmental conditions are now more urgently needed than ever for evidence-based management and policy decisions. Our key aim now is not to describe the existing data as well as possible, but rather to understand the underlying mechanisms and develop models with reliable predictive ability in novel situations.

Chimpanzees were among the first animals recognized to have culture, and our understanding of the breadth of their cultural repertoire has grown significantly since the 1960s. Throughout their range, chimpanzee populations have come under increasing pressure, with their endangered status necessitating immediate and long-term conservation interventions. Recognizing the importance of diverse behavioural repertoires for chimpanzees' survival, there has been a recent focus of conservation efforts on preserving their culturally transmitted behaviours and the environments in which they are exhibited. This article evaluates the practicality of developing conservation measures focused on chimpanzee culture. We highlight innovative conservation strategies aimed at integrating chimpanzee cultural behaviours into conservation policies. We review synergistic conservation initiatives led by the International Union for Conservation of Nature, the UN Convention on the Conservation of Migratory Species of Wild Animals and other international and local groups that share the goal of preserving chimpanzee populations and their cultural diversity. We underline how successful conservation implementation requires engagement and collaboration with a diverse group of interested or affected people. Finally, we provide recommendations aimed at guiding future efforts to incorporate animal cultures into conservation strategies.This article is part of the theme issue 'Animal culture: conservation in a changing world'.

Abstract Over the past five decades, a large number of wild animals have been individually identified by various observation systems and/or temporary tracking methods, providing unparalleled insights into their lives over both time and space. However, so far there is no comprehensive record of uniquely individually identified animals nor where their data and metadata are stored, for example photos, physiological and genetic samples, disease screens, information on social relationships. Databases currently do not offer unique identifiers for living, individual wild animals, similar to the permanent ID labelling for deceased museum specimens. To address this problem, we introduce two new concepts: (1) a globally unique animal ID (UAID) available to define uniquely and individually identified animals archived in any database, including metadata archived at the time of publication; and (2) the digital ‘home’ for UAIDs, the Movebank Life History Museum (MoMu), storing and linking metadata, media, communications and other files associated with animals individually identified in the wild. MoMu will ensure that metadata are available for future generations, allowing permanent linkages to information in other databases. MoMu allows researchers to collect and store photos, behavioural records, genome data and/or resightings of UAIDed animals, encompassing information not easily included in structured datasets supported by existing databases. Metadata is uploaded through the Animal Tracker app, the MoMu website, by email from registered users or through an Application Programming Interface (API) from any database. Initially, records can be stored in a temporary folder similar to a field drawer, as naturalists routinely do. Later, researchers and specialists can curate these materials for individual animals, manage the secure sharing of sensitive information and, where appropriate, publish individual life histories with DOIs. The storage of such synthesized lifetime stories of wild animals under a UAID (unique identifier or ‘animal passport’) will support basic science, conservation efforts and public participation.

Mobile devices, and other tracking technologies, generate detailed data on the movements and behavior of billions of people worldwide. At present, these data are predominantly used to pursue corporate interests. We argue that improving access to human-mobility data is essential for addressing urgent conservation and sustainability goals. Close collaboration between industry and the research community has the potential to generate substantive environmental and societal benefits.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.