A guide to pre-processing high-throughput animal tracking data

Active European warzone impacts raptor migration

Human conflicts can have impacts on wildlife, from direct mortality and environmental damage to the displacement of people, changing institutional dynamics and altering economies.1,2,3 Extreme anthropogenic disturbances related to conflict may act as a barrier to migrating birds and increase the energetic costs of migration.4 On February 24th, 2022, the Russian Federation invaded Ukraine, with targeted attacks on Kyiv and the eastern regions.5 By March 3rd, when the first of 19 tagged Greater Spotted Eagles entered Ukraine on migration, the conflict had spread to most major cities, including parts of western Ukraine.6 We quantified how conflict impacted the migratory behavior of this species using GPS tracks and conflict data from the Armed Conflict Location and Event Data (ACLED) project7,8 in a quasi-experimental before-after control-impact design, accounting for meteorological conditions. Migrating eagles were exposed to conflict events along their migration through Ukraine and exhibited different behavior compared with previous years, using fewer stopover sites and making large route deviations. This delayed their arrival to the breeding grounds and likely increased the energetic cost of migration, with sublethal fitness effects. Our findings provide a rare window into how human conflicts affect animal behavior and highlight the potential impacts of exposure to conflict events or other extreme anthropogenic disturbances on wildlife.

Environmental factors influencing red knot (Calidris canutus islandica) departure times of relocation flights within the non-breeding period

Deciding when to depart on long-distance, sometimes global, movements can be especially important for flying species. Adverse weather conditions can affect energetic flight costs and navigational ability. While departure timings and conditions have been well-studied for migratory flights to and from the breeding range, few studies have focussed on flights within the non-breeding season. Yet in some cases, overwintering ranges can be large enough that ecological barriers, and a lack of resting sites en route, may resist movement, especially in unfavorable environmental conditions. Understanding the conditions that will enable or prohibit flights within an overwintering range is particularly relevant in light of climate change, whereby increases in extreme weather events may reduce the connectivity of sites. We tracked 495 (n = 251 in 2019; n = 244 in 2020) overwintering red knots (Calidris canutus islandica) in the Dutch Wadden Sea and investigated how many departed towards the UK (on westward relocation flights), which requires flying over the North Sea. For those that departed, we used a resource selection model to determine the effect of environmental conditions on the timing of relocation flights. Specifically, we investigated the effects of wind, rain, atmospheric pressure, cloud cover, and migratory timing relative to sunset and tidal cycle, which have all been shown to be crucial to migratory departure conditions. Approximately 37% (2019) and 36% (2020) of tagged red knots departed on westward relocation flights, indicating differences between individuals' space use within the overwintering range. Red knots selected for departures between 1 and 2.5 h after sunset, approximately 4 h before high tide, with tailwinds and little cloud cover. However, rainfall and changes in atmospheric pressure appear unimportant. Our study reveals environmental conditions that are important for relocation flights across an ecological barrier, indicating potential consequences of climate change on connectivity.

Low migratory connectivity and similar migratory strategies in a shorebird with contrasting wintering population trends in Europe and West Africa

Migratory shorebird populations are declining worldwide, showing an apparent inability to respond to the interplaying challenges emerging along their flyways. Within the East Atlantic Flyway, non-breeding populations show moderate to strong declines in Sub-Saharan Africa, contrasting with stable or increasing trends in Europe. Local factors are insufficient to explain the opposite tendencies and, therefore, investigating migratory strategies and connectivity of these populations may help identifying the drivers of their demography. We followed the migratory journeys of 20 grey plovers (Pluvialis squatarola) from their wintering grounds in Guinea-Bissau (West Africa), Portugal and France (Europe) using tracking devices. Grey plovers wintering in Africa and Europe were found to share breeding grounds at European Russia and Western Siberia, revealing low migratory connectivity in the Eastern Atlantic population. All individuals followed a "skipping" migratory strategy, flying mostly mid-distance bouts, and using an unexpected large network of stopover sites to re-fuel usually for short periods. We identified 66 different stopover sites along the West African, European and Russian/Siberian coasts. All birds stopped at the Wadden Sea in both migratory periods, highlighting the importance of this region and the risk for a potential bottleneck. Low migratory connectivity and similar migratory strategies shared by grey plovers wintering in Europe and West Africa do not support their contrasting population trends.

Prospecting during egg laying informs incubation recess movements of eastern wild turkeys

BACKGROUND

Central place foragers must acquire resources and return to a central location after foraging bouts. During the egg laying (hereafter laying) period, females are constrained to a nest location, thus they must familiarize themselves with resources available within their incubation ranges after nest site selection. Use of prospecting behaviors by individuals to obtain knowledge and identify profitable (e.g., resource rich) locations on the landscape can impact demographic outcomes. As such, prospecting has been used to evaluate nest site quality both before and during the reproductive period for a variety of species.

METHODS

Using GPS data collected from female eastern wild turkeys (Meleagris gallopavo silvestris) across the southeastern United States, we evaluated if prospecting behaviors were occurring during laying and what landcover factors influenced prospecting. Specifically, we quantified areas prospected during the laying period using a cluster analysis and the return frequency (e.g., recess movements) to clustered laying patches (150-m diameter buffer around a clustered laying period location) during the incubation period.

RESULTS

The average proportion of recess movements to prospected locations was 56.9%. Nest fate was positively influenced (μ of posterior distribution with 95% credible 0.19, 0.06-0.37, probability of direction = 99.8%) by the number of patches (90-m diameter buffer around a clustered laying period location) a female visited during incubation recesses. Females selected for areas closer to the nest site, secondary roads, hardwood forest, mixed pine-hardwood forest, water, and shrub/scrub, whereas they avoided pine forest and open-treeless areas.

CONCLUSIONS

Our findings suggest that having a diverse suite of clustered laying patches to support incubation recesses is impactful to nest fate. As such, local conditions within prospected locations during incubation may be key to successful reproductive output by wild turkeys. We suggest that prospecting could be important to other phenological periods. Furthermore, future research should evaluate how prospecting for brood-rearing locations may occur before or during the incubation period.

Home range overlap between small Indian mongooses and free roaming domestic dogs in Puerto Rico: implications for rabies management

The small Indian mongoose (Urva auropunctata) is the primary terrestrial wildlife rabies reservoir on at least four Caribbean islands, including Puerto Rico. In Puerto Rico, mongooses represent a risk to public health, based on direct human exposure and indirectly through the transmission of rabies virus to domestic animals. To date, the fundamental ecological relationships of space use among mongooses and between mongooses and domestic animals remain poorly understood. This study is the first to report mongoose home range estimates based on GPS telemetry, as well as concurrent space use among mongooses and free roaming domestic dogs (FRDD; Canis lupus familiaris). Mean (± SE) home range estimates from 19 mongooses in this study (145 ± 21 ha and 60 ± 14 ha for males and females, respectively) were greater than those reported in prior radiotelemetry studies in Puerto Rico. At the scale of their home range, mongooses preferentially used dry forest and shrubland areas, but tended to avoid brackish water vegetation, salt marshes, barren lands and developed areas. Home ranges from five FRDDs were highly variable in size (range 13-285 ha) and may be influenced by availability of reliable anthropogenic resources. Mongooses displayed high home range overlap (general overlap index, GOI = 82%). Home range overlap among mongooses and FRDDs was intermediate (GOI = 50%) and greater than home range overlap by FRDDs (GOI = 10%). Our results provide evidence that space use by both species presents opportunities for interspecific interaction and contact and suggests that human provisioning of dogs may play a role in limiting interactions between stray dogs and mongooses.

Potential for automatic detection of calving in beef cows grazing on rangelands from Global Navigate Satellite System collar data

Dystocia is one of the main causes of calf death around calving. In addition, peripartum deaths may occur due to other factors, such as weather or predators, especially in the case of grazing animals. Precision Livestock Farming (PLF) tools aimed at the automatic detection of calving may be useful for farmers, allowing cow assistance in case of dystocia or checking the condition of the cow-calf pair after calving. Such PLF systems are commercially available for dairy cows, but these tools are not suitable for rangelands, mainly due to power and connectivity constraints. Thus, since most commercial PLF tools for rangelands are based on Global Navigate Satellite System (GNSS) technology, the objective of this study was to design and evaluate several indicators built from data gathered with GNSS collars to characterise their potential for the detection of calving on rangelands. Location data from 57 cows, 42 of which calved during the study, were curated and analysed following a standardised procedure. Several indicators were calculated using two different strategies. The first approach consisted of having indicators that could be computed using the data of a single GNSS collar (cow indicators). The second strategy involved the use of data from several animals (herd indicators), which requires more animals to be monitored, but may allow the characterisation of social behaviour. Several indicators, such as the length of the daily trajectory or the sinuosity of cow path, showed significant differences between the pre- and postpartum periods, but no clear differences between calving day and previous days. Herd indicators, such as the distance to herd centroid or to the nearest peer were superior in terms of the detection of calving day, as cows showed isolation behaviour from 24 hours before calving. Relative indicators, i.e., the value of cow or herd indicators for the calving cow in relation to the average value of the same indicators for its herdmates, provided additional information on cow behaviour. For instance, according to the relative indicator for the change in daily trajectory, pregnant cows had a differential exploratory behaviour up to 14 days before calving. In conclusion, data from commercial GNSS collars proved to be useful for the computation of several indicators related to the occurrence of calving on rangelands. Some of those indicators showed changes from baseline values on the day before calving, which could serve to predict the onset of parturition.

Changes in movement, habitat use, and response to human disturbance accompany parturition events in bighorn sheep (Ovis canadensis)

Parturition and the early neonatal period are critical life history stages in ungulates with considerable implications for population growth and persistence. Understanding the changes in behaviour induced by ungulate parturition is important for supporting effective population management, but reliably identifying birth sites and dates presents a challenge for managers. Rocky Mountain bighorn sheep (Ovis canadensis canadensis) are one such highly valued and ecologically important species in montane and subalpine ecosystems of Western North America. In the face of changing patterns of anthropogenic land use, wildlife managers increasingly require site-specific knowledge of the movement and habitat selection characteristics of periparturient sheep to better inform land use planning initiatives and ensure adequate protections for lambing habitat. We used movement data from GPS collared parturient (n = 13) and non-parturient (n = 8) bighorn sheep in Banff National Park, Canada to (1) identify lambing events based on changes in key movement metrics, and (2) investigate how resource selection and responses to human use change during the periparturient period. We fit a hidden Markov model (HMM) to a multivariate characterization of sheep movement (step length, daily home range area, residence time) to predict realistic lambing dates for the animals in our study system. Leave-one-out cross validation of our model resulted in a 93% success rate for parturient females. Our model, which we parameterized using data from known parturient females, also predicted lambing events in 25% of known non-parturient ewes in a test dataset. Using a latent selection difference function and resource selection functions, we tested for postpartum changes in habitat use, as well as seasonal differences in habitat selection. Immediately following lambing, ewes preferentially selected high-elevation sites on solar aspects that were more rugged, closer to escape terrain, and further from roads. Within-home range habitat selection was similar between individuals in different reproductive states, but parturient ewes had stronger selection for low snow depth, sites closer to barren ground, and sites further from trails. We propose that movement-based approaches such as HMMs are a valuable tool for identifying critical parturition habitat in species with complex movement patterns and may have particular utility in study areas without access to extensive field observations or vaginal implant transmitters. Furthermore, our results suggest that managers should minimize human disturbance in lambing areas to avoid interfering with maternal behaviour and ensure access to a broad range of suitable habitat in the periparturient period.

Wild gibbons plan their travel pattern according to food types of breakfast

Planning for the future is a complex skill that is often considered uniquely human. This cognitive ability has never been investigated in wild gibbons (Hylobatidae). Here we evaluated the movement patterns from sleeping trees to out-of-sight breakfast trees in two groups of endangered skywalker gibbons (Hoolock tianxing). These Asian apes inhabit a cold seasonal montane forest in southwestern China. After controlling for possible confounding variables including group size, sleeping pattern (sleep alone or huddle together), rainfall and temperature, we found that food type (fruits or leaves) of the breakfast tree was the most important factor affecting gibbon movement patterns. Fruit breakfast trees were more distant from sleeping trees compared with leaf trees. Gibbons left sleeping trees and arrived at breakfast trees earlier when they fed on fruits compared with leaves. They travelled fast when breakfast trees were located further away from the sleeping trees. Our study suggests that gibbons had foraging goals in mind and plan their departure times accordingly. This ability may reflect a capacity for route-planning, which would enable them to effectively exploit highly dispersed fruit resources in high-altitude montane forests.

Fear of large carnivores amplifies human-caused mortality for mesopredators

The challenge that large carnivores face in coexisting with humans calls into question their ability to carry out critical ecosystem functions such as mesopredator suppression outside protected areas. In this study, we examined the movements and fates of mesopredators and large carnivores across rural landscapes characterized by substantial human influences. Mesopredators shifted their movements toward areas with twofold-greater human influence in regions occupied by large carnivores, indicating that they perceived humans to be less of a threat. However, rather than shielding mesopredators, human-caused mortality was more than three times higher than large carnivore-caused mortality. Mesopredator suppression by apex predators may thus be amplified, rather than dampened, outside protected areas, because fear of large carnivores drives mesopredators into areas of even greater risk from human super predators.

ATfiltR: A solution for managing and filtering detections from passive acoustic telemetry data

Acoustic telemetry is a popular and cost-efficient method for tracking the movements of animals in the aquatic ecosystem. But data acquired via acoustic telemetry often contains spurious detections that must be identified and excluded by researchers to ensure valid results. Such data management is difficult as the amount of data collected often surpasses the capabilities of simple spreadsheet applications. ATfiltR is an open-source package programmed in R that allows users to integrate all telemetry data collected into a single file, to conditionally attribute animal data and location data to detections and to filter spurious detections based on customizable rules. Such tool will likely be useful to new researchers in acoustic telemetry and enhance results reproducibility.•ATfiltR compiles telemetry files and identifies and stores all data that was collected outside of your study period (e.g. when your receivers were on land for servicing) elsewhere.•As spurious detections are unlikely to appear sequentially in the data, ATfiltR finds all detections that occurred only once (per receiver or in the whole array) within a user-designated time period and stores them elsewhere.•ATfiltR identifies detections that are impossible given the animals' swimming speeds and the receivers detection range and stores them elsewhere.

Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking

BACKGROUND

Movement is central to understanding the ecology of animals. The most robustly definable segments of an individual's lifetime track are its diel activity routines (DARs). This robustness is due to fixed start and end points set by a 24-h clock that depends on the individual's quotidian schedule. An analysis of day-to-day variation in the DARs of individuals, their comparisons among individuals, and the questions that can be asked, particularly in the context of lunar and annual cycles, depends on the relocation frequency and spatial accuracy of movement data. Here we present methods for categorizing the geometry of DARs for high frequency (seconds to minutes) movement data.

METHODS

Our method involves an initial categorization of DARs using data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four scalar "whole-path metrics" of trajectory geometry: 1. net displacement (distance between start and end points), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in north-eastern Israel. We conducted a principle components analysis (PCA) to obtain a factor, PC1, that essentially captures the scale of movement. We then used a generalized linear mixed model with PC1 as the dependent variable to assess the effects of age and sex on movement.

RESULTS

We clustered 6230 individual DARs into 7 categories representing different shapes and scale of the owls nightly routines. Five categories based on size and elongation were classified as closed (i.e. returning to the same roost), one as partially open (returning to a nearby roost) and one as fully open (leaving for another region). Our PCA revealed that the DAR scale factor, PC1, accounted for 86.5% of the existing variation. It also showed that PC2 captures the openness of the DAR and accounted for another 8.4% of the variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal quadrimester, as well as identify some idiosyncratic behavior of individuals within family groups in relation to location. Finally, we showed in two ways that DARs were significantly larger in young than adults and in males than females.

CONCLUSION

Our study offers a new method for using high-frequency movement data to classify animal diel movement routines. Insights into the types and distributions of the geometric shape and size of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis.

Spatial memory predicts home range size and predation risk in pheasants

Most animals confine their activities to a discrete home range, long assumed to reflect the fitness benefits of obtaining spatial knowledge about the landscape. However, few empirical studies have linked spatial memory to home range development or determined how selection operates on spatial memory via the latter's role in mediating space use. We assayed the cognitive ability of juvenile pheasants (Phasianus colchicus) reared under identical conditions before releasing them into the wild. Then, we used high-throughput tracking to record their movements as they developed their home ranges, and determined the location, timing and cause of mortality events. Individuals with greater spatial reference memory developed larger home ranges. Mortality risk from predators was highest at the periphery of an individual's home range in areas where they had less experience and opportunity to obtain spatial information. Predation risk was lower in individuals with greater spatial memory and larger core home ranges, suggesting selection may operate on spatial memory by increasing the ability to learn about predation risk across the landscape. Our results reveal that spatial memory, determined from abstract cognitive assays, shapes home range development and variation, and suggests predation risk selects for spatial memory via experience-dependent spatial variation in mortality.

Movement predictability of individual barn owls facilitates estimation of home range size and survival

BACKGROUND

There is growing attention to individuality in movement, its causes and consequences. Similarly to other well-established personality traits (e.g., boldness or sociability), conspecifics also differ repeatedly in their spatial behaviors, forming behavioral types ("spatial-BTs"). These spatial-BTs are typically described as the difference in the mean-level among individuals, and the intra-individual variation (IIV, i.e., predictability) is only rarely considered. Furthermore, the factors determining predictability or its ecological consequences for broader space-use patterns are largely unknown, in part because predictability was mostly tested in captivity (e.g., with repeated boldness assays). Here we test if (i) individuals differ in their movement and specifically in their predictability. We then investigate (ii) the consequences of this variation for home-range size and survival estimates, and (iii) the factors that affect individual predictability.

METHODS

We tracked 92 barn owls (Tyto alba) with an ATLAS system and monitored their survival. From these high-resolution (every few seconds) and extensive trajectories (115.2 ± 112.1 nights; X̅ ± SD) we calculated movement and space-use indices (e.g., max-displacement and home-range size, respectively). We then used double-hierarchical and generalized linear mix-models to assess spatial-BTs, individual predictability in nightly max-displacement, and its consistency across time. Finally, we explored if predictability levels were associated with home-range size and survival, as well as the seasonal, geographical, and demographic factors affecting it (e.g., age, sex, and owls' density).

RESULTS

Our dataset (with 74 individuals after filtering) revealed clear patterns of individualism in owls' movement. Individuals differed consistently both in their mean movement (e.g., max-displacement) and their IIV around it (i.e., predictability). More predictable individuals had smaller home-ranges and lower survival rates, on top and beyond the expected effects of their spatial-BT (max-displacement), sex, age and ecological environments. Juveniles were less predictable than adults, but the sexes did not differ in their predictability.

CONCLUSION

These results demonstrate that individual predictability may act as an overlooked axis of spatial-BT with potential implications for relevant ecological processes at the population level and individual fitness. Considering how individuals differ in their IIV of movement beyond the mean-effect can facilitate understanding the intraspecific diversity, predicting their responses to changing ecological conditions and their population management.

MoveApps: a serverless no-code analysis platform for animal tracking data

BACKGROUND

Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.

RESULTS

We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements.

CONCLUSIONS

The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

Movements of free-range pigs in rural communities in Zambia: an explorative study towards future ring interventions for the control of Taenia solium

Background

Taenia solium typically affects resource-poor communities where pigs are allowed to roam freely, and sanitation and hygiene levels are suboptimal. Sustainable, long-term strategies are urgently needed to control the disease. Geographically targeted interventions, i.e. screening or treatment of taeniosis among people living near infected pigs (defined as ring screening and ring treatment, respectively), have been shown to be effective control options in Peru. However, these results might not be directly generalizable to sub-Saharan African settings. Pig movements play a vital role in the transmission and, consequently, the success of ring interventions against T. solium. The aim of the present study was to explore roaming patterns of pigs in T. solium endemic communities in Zambia as a first step toward evaluating whether ring interventions should be considered as a treatment option in Zambia.

Methods

In total, 48 free-roaming pigs in two rural neighborhoods in the Eastern Province of Zambia were tracked using a Global Positioning System (GPS) receiver. Tracking took place in April (end of the rainy season) 2019 and October (end of the dry season) 2019. The number of revisitations and the time spent within rings of different radii (50, 100 and 250 m) around the coordinates of each pig owner’s household were calculated for each pig.

Results

The total tracking time for 43 pigs in the final analysis set ranged between 43 and 94 h. Pigs spent a median of 31% and 13% of the tracked time outside the 50- and 100-m radius, respectively, although large variations were observed between pigs. Overall, 25 pigs (58%) went outside the 250-m ring at least once, and individual excursions lasting up to 16 h were observed. In the dry season, 17 out of 23 pigs went outside the 250-m radius compared to only eight out of 20 pigs in the rainy season (P = 0.014).

Conclusions

In our study sites in Zambia, the majority of pigs spent most of their time within 50 or 100 m of their owner’s home, and these results are comparable with those on Peruvian pigs. Both radii could therefore be considered reasonable options in future ring interventions.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05264-0.

Mapping the "catscape" formed by a population of pet cats with outdoor access

The domestic cat (Felis catus) is among the most popular companion animals and most abundant carnivores globally. It is also a pet with an immense ecological footprint because even non-feral and food-subsidized cats can be prolific predators. Whereas knowledge about the spatial behavior of individual domestic cats is growing, we still know little about how a local population of free-ranging pet cats occupies the landscape. Using a citizen science approach, we GPS-tagged 92 pet cats with outdoor access living in a residential area in southern Norway. The resulting position data allowed us to construct both individual home range kernels and a population-level utilization distribution. Our results reveal a dense predatory blanket that outdoor cats drape over and beyond the urban landscape. It is this population-level intensity surface—the “catscape”—that potential prey have to navigate. There were few gaps in the catscape within our residential study area and therefore few terrestrial refuges from potential cat predation. However, cats spent on average 79% of their outdoor time within 50 m to their owner’s home, which suggests that the primary impact is local and most acute for wildlife in the vicinity to homes with cats. We discuss the catscape as a conceptual and quantitative tool for better understanding and mitigating the environmental impact of domestic cats.

Animal tracking moves community ecology: Opportunities and challenges

1. Individual decisions regarding how, why, and when organisms interact with one another and with their environment scale up to shape patterns and processes in communities. Recent evidence has firmly established the prevalence of intraspecific variation in nature and its relevance in community ecology, yet challenges associated with collecting data on large numbers of individual conspecifics and heterospecifics has hampered integration of individual variation into community ecology. 2. Nevertheless, recent technological and statistical advances in GPS-tracking, remote sensing, and behavioral ecology offer a toolbox for integrating intraspecific variation into community processes. More than simply describing where organisms go, movement data provide unique information about interactions and environmental associations from which a true individual-to-community framework can be built. 3. By linking the movement paths of both conspecifics and heterospecifics with environmental data, ecologists can now simultaneously quantify intra- and interspecific variation regarding the Eltonian (biotic interactions) and Grinnellian (environmental conditions) factors underpinning community assemblage and dynamics, yet substantial logistical and analytical challenges must be addressed for these approaches to realize their full potential. 4. Across communities, empirical integration of Eltonian and Grinnellian factors can support conservation applications and reveal metacommunity dynamics via tracking-based dispersal data. As the logistical and analytical challenges associated with multi-species tracking are surmounted, we envision a future where individual movements and their ecological and environmental signatures will bring resolution to many enduring issues in community ecology.

Big-data approaches lead to an increased understanding of the ecology of animal movement

Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.