Animal Movement Studies Research Articles

Evaluating Contributions of Recent Tracking-Based Animal Movement Ecology to Conservation Management

The use of animal-born sensors for location-based tracking and bio-logging in terrestrial systems has expanded dramatically in the past 10 years. This rapid expansion has generated new data on how animals interact with and respond to variation in their environment, resulting in important ecological, physiological and evolutionary insights. However, although understanding the finer details of animal locations and state also has important management relevance, applied studies are not prominent in the movement ecology literature. This is despite the long history of applied studies of animal movement and the urgent and growing need for evidence-based conservation guidance, especially in the challenging field of human-wildlife interactions. The goal of this review is to evaluate the realized contribution of tracking-based animal movement ecology to solving specific conservation problems and to identify barriers that may hinder expansion of that contribution. To do this, we (a) briefly review the history and technologies used in animal tracking and bio-logging, (b) use a series of literature searches to evaluate the frequency with which movement ecology studies are designed to solve specific conservation problems, and (c) use this information to identify challenges that limit the applied relevance of the field of movement ecology and to propose pathways to expand that applied relevance. Our literature review quantifies the limited extent to which research in the field of movement ecology is designed to solve specific conservation problems, but also the fact that such studies are slowly becoming more prevalent. We discuss how barriers that limit application of these principles are likely due to constraints imposed by the types of data used commonly in the field. For example, problems of scale mismatch, error compounding, and data paucity all create challenges that are especially pertinent in applied situations. Finding solutions to these problems will create new opportunity for movement ecologists to contribute to conservation science.

A lattice and random intermediate point sampling design for animal movement

AbstractAnimal movement studies have become ubiquitous in animal ecology for the estimation of space use and the analysis of movement behavior. In these studies, animal movement data are primarily collected at regular time intervals. We propose an irregular sampling design that could lead to greater efficiency and information gain in animal movement studies. Our novel sampling design, called lattice and random intermediate point (LARI), combines samples at regular and random time intervals. We compare the LARI sampling design to regular sampling designs in an example with common black carpenter ant location data, an example with guppy location data, and a simulation study of movement with a point of attraction. We modify a general stochastic differential equation model to allow for irregular time intervals and use this framework to compare sampling designs. When parameters are estimated reasonably well, regular sampling results in greater precision and accuracy in prediction of missing data. However, in each of the data and simulation examples explored in this paper, LARI sampling results in more accurate and precise parameter estimation and, thus, better prediction of missing data as well. This result suggests that researchers might gain greater insight into underlying animal movement processes by choosing LARI sampling over regular sampling.

Animal movement models with mechanistic selection functions

A suite of statistical methods are used to study animal movement. Most of these methods treat animal telemetry data in one of three ways: as discrete processes, as continuous processes, or as point processes. We briefly review each of these approaches and then focus in on the latter. In the context of point processes, so-called resource selection analyses are among the most common way to statistically treat animal telemetry data. However, most resource selection analyses provide inference based on approximations of point process models. The forms of these models have been limited to a few types of specifications that provide inference about relative resource use and, less commonly, probability of use. For more general spatio-temporal point process models, the most common type of analysis often proceeds with a data augmentation approach that is used to create a binary data set that can be analyzed with conditional logistic regression. We show that the conditional logistic regression likelihood can be generalized to accommodate a variety of alternative specifications related to resource selection. We then provide an example of a case where a spatio-temporal point process model coincides with that implied by a mechanistic model for movement expressed as a partial differential equation derived from first principles of movement. We demonstrate that inference from this form of point process model is intuitive (and could be useful for management and conservation) by analyzing a set of telemetry data from a mountain lion in Colorado, USA, to understand the effects of spatially explicit environmental conditions on movement behavior of this species.

Combining simulation modeling and stable isotope analyses to reconstruct the last known movements of one of Nature’s giants

The spatial ecology of rare, migratory oceanic animals is difficult to study directly. Where incremental tissues are available, their chemical composition can provide valuable indirect observations of movement and diet. Interpreting the chemical record in incremental tissues can be highly uncertain, however, as multiple mechanisms interact to produce the observed data. Simulation modeling is one approach for considering alternative hypotheses in ecology and can be used to consider the relative likelihood of obtaining an observed record under different combinations of ecological and environmental processes. Here we show how a simulation modeling approach can help to infer movement behaviour based on stable carbon isotope profiles measured in incremental baleen tissues of a blue whale (Balaenoptera musculus). The life history of this particular specimen, which stranded in 1891 in the UK, was selected as a case study due to its cultural significance as part of a permanent display at the Natural History Museum, London. We specifically tested whether measured variations in stable isotope compositions across the analysed baleen plate were more consistent with residency or latitudinal migrations. The measured isotopic record was most closely reproduced with a period of residency in sub-tropical waters for at least a full year followed by three repeated annual migrations between sub-tropical and high latitude regions. The latitudinal migration cycle was interrupted in the year prior to stranding, potentially implying pregnancy and weaning, but isotopic data alone cannot test this hypothesis. Simulation methods can help reveal movement information coded in the biochemical compositions of incremental tissues such as those archived in historic collections, and provides context and inferences that are useful for retrospective studies of animal movement, especially where other sources of individual movement data are sparse or challenging to validate.

Identifying stationary phases in multivariate time series for highlighting behavioural modes and home range settlements.

Recent advances in biologging open promising perspectives in the study of animal movements at numerous scales. It is now possible to record time series of animal locations and ancillary data (e.g. activity level derived from on-board accelerometers) over extended areas and long durations with a high spatial and temporal resolution. Such time series are often piecewise stationary, as the animal may alternate between different stationary phases (i.e. characterized by a specific mean and variance of some key parameter for limited periods). Identifying when these phases start and end is a critical first step to understand the dynamics of the underlying movement processes. We introduce a new segmentation-clustering method we called segclust2d (available as a r package at cran.r-project.org/package=segclust2d). It can segment bivariate (or more generally multivariate) time series and possibly cluster the various segments obtained, corresponding to different phases assumed to be stationary. This method is easy to use, as it only requires specifying a minimum segment length (to prevent over-segmentation), based on biological rather than statistical considerations. This method can be applied to bivariate piecewise time series of any nature. We focus here on two types of time series related to animal movement, corresponding to (a) at large scale, series of bivariate coordinates of relocations, to highlight temporary home ranges, and (b) at smaller scale, bivariate series derived from relocations data, such as speed and turning angle, to highlight different behavioural modes such as transit, feeding and resting. Using computer simulations, we show that segclust2d can rival and even outperform previous, more complex methods, which were specifically developed to highlight changes of movement modes or home range shifts (based on hidden Markov and Ornstein-Uhlenbeck modelling), which, contrary to our method, usually require the user to provide relevant initial guesses to be efficient. Furthermore, we demonstrate it on actual examples involving a zebra's small-scale movements and an elephant's large-scale movements, to illustrate how various movement modes and home range shifts, respectively, can be identified.

Rsmove—An r package to bridge remote sensing and movement ecology

Abstract Remote sensing is a valuable tool in movement ecology. However, the way it is combined with animal movement data is far from optimal as most studies overlook differences in the spatial, temporal and thematic resolutions between both data types. rsmove uses a pixel‐based approach to link animal tracking and remote sensing data that bridge the gap between these two disciplines while respecting the limitations of the latest. Additionally, if offers standardize methods to pre‐analyse the connection between animal movement and environmental change. The package guides the choice of study sites, satellite data and environmental predictors though data mining and visualization tools. rsmove offers a simple methodology to analyse animal–environment interactions that helps avoid unnecessary, time‐consuming satellite data processing through an informed decision process. The package offers a basis for a better communication between ecologists and remote sensing experts contributing to the definition of clear remote sensing data requirements. Additionally, it provides future studies on animal movement tools for a more critical approach on the selection of environmental data supporting the reproducibility of animal movement studies.

Environmental effects on flying migrants revealed by radar

Migratory animals are affected by various factors during their journeys, and the study of animal movement by radars has been instrumental in revealing key influences of the environment on flying migrants. Radars enable the simultaneous tracking of many individuals of almost all sizes within the radar range during day and night, and under low visibility conditions. We review how atmospheric conditions, geographic features and human development affect the behavior of migrating insects and birds as recorded by radars. We focus on flight initiation and termination, as well as in‐flight behavior that includes changes in animal flight direction, speed and altitude. We have identified several similarities and differences in the behavioral responses of aerial migrants including an overlooked similarity in the use of thermal updrafts by very small (e.g. aphids) and very large (e.g. vultures) migrants. We propose that many aerial migrants modulate their migratory flights in relation to the interaction between atmospheric conditions and geographic features. For example, aerial migrants that encounter crosswind may terminate their flight or continue their migration and may also drift or compensate for lateral displacement depending on their position (over land, near the coast or over sea). We propose several promising directions for future research, including the development and application of algorithms for tracking insects, bats and large aggregations of animals using weather radars. Additionally, an important contribution will be the spatial expansion of aeroecological radar studies to Africa, most of Asia and South America where no such studies have been undertaken. Quantifying the role of migrants in ecosystems and specifically estimating the number of departing birds from stopover sites using low‐elevation radar scans is important for quantifying migrant–habitat relationships. This information, together with estimates of population demographics and migrant abundance, can help resolve the long‐term dynamics of migrant populations facing large‐scale environmental changes.

Animal movements in fire‐prone landscapes

Movement is a trait of fundamental importance in ecosystems subject to frequent disturbances, such as fire-prone ecosystems. Despite this, the role of movement in facilitating responses to fire has received little attention. Herein, we consider how animal movement interacts with fire history to shape species distributions. We consider how fire affects movement between habitat patches of differing fire histories that occur across a range of spatial and temporal scales, from daily foraging bouts to infrequent dispersal events, and annual migrations. We review animal movements in response to the immediate and abrupt impacts of fire, and the longer-term successional changes that fires set in train. We discuss how the novel threats of altered fire regimes, landscape fragmentation, and invasive species result in suboptimal movements that drive populations downwards. We then outline the types of data needed to study animal movements in relation to fire and novel threats, to hasten the integration of movement ecology and fire ecology. We conclude by outlining a research agenda for the integration of movement ecology and fire ecology by identifying key research questions that emerge from our synthesis of animal movements in fire-prone ecosystems.

Estimating Wildlife Tag Location Errors from a VHF Receiver Mounted on a Drone

Recent studies have demonstrated the high potential of drones as tools to facilitate wildlife radio-tracking in rugged, difficult-to-access terrain. Without estimates of accuracy, however, data obtained from receivers attached to drones will be of limited use. We estimated transmitter location errors from a drone-borne VHF (very high frequency) receiver in a hilly and dense boreal forest in southern Québec, Canada. Transmitters and the drone-borne receiver were part of the Motus radio-tracking system, a collaborative network designed to study animal movements at local to continental scales. We placed five transmitters at fixed locations, 1–2 m above ground, and flew a quadrotor drone over them along linear segments, at distances to transmitters ranging from 20 m to 534 m. Signal strength was highest with transmitters with antennae pointing upwards, and lowest with transmitters with horizontal antennae. Based on drone positions with maximum signal strength, mean location error was 134 m (range 44–278 m, n = 17). Estimating peak signal strength against drone GPS coordinates with quadratic, least-squares regressions led to lower location error (mean = 94 m, range 15–275 m, n = 10) but with frequent loss of data due to statistical estimation problems. We conclude that accuracy in this system was insufficient for high-precision purposes such as finding nests. However, in the absence of a dense array of fixed receivers, the use of drone-borne Motus receivers may be a cost-effective way to augment the quantity and quality of data, relative to deploying personnel in difficult-to-access terrain.

Performance of GPS units for deployment on semiaquatic animals.

Global Positioning System (GPS) technology is widely used in wildlife research to study animal movement and habitat use. In order to evaluate the quality and reliability of GPS data, the factors influencing the performance of these devices must be known, especially for semiaquatic species, because terrestrial and aquatic habitat might affect GPS performance differently. We evaluated the location error and fix success rate of three GPS receiver models in stationary tests and on a semi-aquatic mammal, the Eurasian beaver (Castor fiber). The location error during stationary tests was on average 15.7 m, and increased with increasing canopy closure, slope, and horizontal dilution of precision, potentially leading to the erroneous classification of GPS positions when studying habitat use in animals. In addition, the position of the GPS antenna (flat versus 90° tilted) affected the location error, suggesting that animal behavior affects GPS performance. The fix success rate was significantly higher during stationary tests compared to when GPS units were deployed on beavers (94% versus 86%). Further, GPS receivers did not obtain any positions underwater and underground, the latter potentially allowing the estimation of activity periods in animals that use lodges or burrows as shelter. We discuss the possibilities for data screening, the use of buffer zones along the shoreline, and combination with other data loggers to avoid the erroneous classification of GPS positions when studying habitat use.

Circuit-theory applications to connectivity science and conservation.

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Resource-Area-Dependence Analysis: Inferring animal resource needs from home-range and mapping data.

An animal’s home-range can be expected to encompass the resources it requires for surviving or reproducing. Thus, animals inhabiting a heterogeneous landscape, where resource patches vary in size, shape and distribution, will naturally have home-ranges of varied sizes, so that each home-range encompasses a minimum required amount of a resource. Home-range size can be estimated from telemetry data, and often key resources, or proxies for them such as the areas of important habitat types, can be mapped. We propose a new method, Resource-Area-Dependence Analysis (RADA), which uses a sample of tracked animals and a categorical map to i) infer in which map categories important resources are accessible, ii) within which home range cores they are found, and iii) estimate the mean minimum areas of these map categories required for such resource provision. We provide three examples of applying RADA to datasets of radio-tracked animals from southern England: 15 red squirrels Sciurus vulgaris, 17 gray squirrels S. carolinensis and 114 common buzzards Buteo buteo. The analyses showed that each red squirrel required a mean (95% CL) of 0.48 ha (0.24–-0.97) of pine wood within the outermost home-range, each gray squirrel needed 0.34 ha (0.11–1.12) ha of mature deciduous woodland and 0.035–0.046 ha of wheat, also within the outermost home-range, while each buzzard required 0.54 ha (0.35–0.82) of rough ground close to the home-range center and 14 ha (11–17) of meadow within an intermediate core, with 52% of them also relying on 0.41 ha (0.29–0.59) of suburban land near the home-range center. RADA thus provides a useful tool to infer key animal resource requirements during studies of animal movement and habitat use.

Behavioral and social mechanisms behind pattern formation: an experimental study of animal movement

ContextAlthough animal movement behaviors are influenced by spatial heterogeneity, such behaviors can also generate spatial heterogeneity via interactions with the emergent spatial structure and other individuals (i.e., the social landscape).ObjectiveElucidate the behavioral and ecological mechanisms of pattern formation in a homogeneous resource landscape.MethodsWe analyzed the movement pathways and space-use patterns of the lesser grain borer (Rhyzopertha dominica) within homogeneous resource landscapes (wheat kernels). Experimental trials consisted of individual beetles foraging alone or paired with a member of the same or different sex.ResultsWe identified two sources of pattern formation: (1) beetles were attracted to areas where they or another beetle had previously fed, leading to increased patchiness via positive reinforcement; and (2) the presence of conspecifics affected whether and at what scales patchiness occurred. Solitary males had lower rates of movement and less tortuous pathways than solitary females, but both sexes generated fine-scale patchiness in the resource distribution. Patchy resource landscapes were also generated by male–female pairs, but not by same-sex pairings. Paired females in particular exhibited significantly greater daily net displacements and more random space use than solitary females.ConclusionsPattern formation is a complex process, even in a relatively simple, homogeneous resource landscape. In particular, patterns created by individuals when foraging alone versus in pairs underscores how social interactions can fundamentally alter the resultant pattern of heterogeneity that emerges in resource landscapes.

Biotelemetry marches on: A cost-effective GPS device for monitoring terrestrial wildlife.

The availability of low-cost wildlife trackers increases the capacity to collect valuable ecological data when research budgets are limited. We converted a commercially available global positioning system (GPS) product into a low-cost tracking device that sends data via the mobile phone network, and assessed its performance under varying conditions. We established a stationary test, deploying devices along a continuum from open urban areas to topographically and structurally complex forested sites. We tested three features of the device: (a) the GPS, by measuring fix success rate, fix precision and horizontal dilution of precision (HDOP), (b) remote download capacity via the mobile phone network and (c) battery drain. Measures of GPS performance demonstrated high fix success rates and precision. HDOP values were influenced by habitat type and topographical position, but generally remained very low, giving an acceptable degree of error for most applications in wildlife research. Devices experienced delayed data transmission at sites with less phone reception, and faster battery drain at sites with denser vegetation. We recorded device malfunctions in 8.2% of the 110 sampling locations, but these were not associated with habitat type or topography. Our device was effective under a wide range of conditions, and the development process we used provides guidance to other researchers aiming to develop cost-effective wildlife trackers. Reducing the financial and labour costs of acquiring high-quality movement data will improve the capacity to increase sample size in animal movement studies.

Investigating temporal variation in stable carbon and nitrogen isotope values of Florida Caribbean spiny lobster (Panulirus argus) recruits

The limited information available on the recruitment dynamics of the Caribbean spiny lobster, Panulirus argus (Latreille, 1804), has long been an issue for biologists. The long pelagic larval stage and the surface circulation in the Caribbean Sea have led many researchers to hypothesize that Caribbean lobster stocks are demographically open, implying connectivity among stocks in this region. Multiple approaches have been applied to investigate potential stock connectivity in this species, including biophysical modeling and genetic markers. Stable isotope analysis has proven to be a useful tool to study animal movement, and has been widely applied in studies of both terrestrial and aquatic species. However, this method has never been applied to Caribbean spiny lobster recruits. In the present study, we performed carbon and nitrogen stable isotope analyses on three sub-stages of the non-feeding pueruli (clear, semi-pigmented, and pigmented), as well as on the feeding, first juvenile stage that settled in the Florida Keys from August 2014 to July 2016. Results indicated that the stable isotope values differed between the feeding and non-feeding stages. The δ13C and δ15N values of the lunar monthly samples displayed notable temporal variation and oscillated during the 2-yr sampling period. Cluster analyses of the stable isotope values suggested that four clusters could have contributed to the observed Florida recruits. The results of our study reveal the possibility that the Florida spiny lobster stock receives recruits from multiple source populations outside Florida in addition to self-recruitment.

Home Range Size and Resource Use of Breeding and Non-breeding White Storks Along a Land Use Gradient

Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.

An open-source hardware GPS data logger for wildlife radio-telemetry studies: A case study using Eastern box turtles

Abstract Global Positioning System (GPS) telemetry technology has been a boon to animal spatial ecology studies. Oftentimes, the main limitation to widespread application of this technology is the cost, which can dictate the number of individuals outfitted with GPS technology, thereby limiting sample sizes. Here, we discuss the development of a low-cost, customizable, open-source hardware GPS logger for use in animal movement studies. We also present results from field tests with Eastern box turtles (Terrapene carolina) in northwestern Ohio. These GPS loggers have the potential to augment existing projects and facilitate studies that would be otherwise cost-prohibitive.

Search and foraging behaviors from movement data: A comparison of methods.

Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time–depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k‐Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.

Quantifying animal movement for caching foragers: the path identification index (PII) and cougars, Puma concolor

BackgroundMany studies of animal movement have focused on directed versus area-restricted movement, which rely on correlations between step-length and turn-angles and on stationarity through time to define behavioral states. Although these approaches might apply well to grazing in patchy landscapes, species that either feed for short periods on large, concentrated food sources or cache food exhibit movements that are difficult to model using the traditional metrics of turn-angle and step-length alone.ResultsWe used GPS telemetry collected from a prey-caching predator, the cougar (Puma concolor, Linnaeus), to test whether combining metrics of site recursion, spatiotemporal clustering, speed, and turning into an index of movement using partial sums, improves the ability to identify caching behavior. The index was used to identify changes in movement characteristics over time and segment paths into behavioral classes. The identification of behaviors from the Path Identification Index (PII) was evaluated using field investigations of cougar activities at GPS locations. We tested for statistical stationarity across behaviors for use of topographic view-sheds. Changes in the frequency and duration of PII were useful for identifying seasonal activities such as migration, gestation, and denning. The comparison of field investigations of cougar activities to behavioral PII classes resulted in an overall classification accuracy of 81%.ConclusionsChanges in behaviors were reflected in cougars’ use of topographic view-sheds, resulting in statistical nonstationarity over time, and revealed important aspects of hunting behavior. Incorporating metrics of site recursion and spatiotemporal clustering revealed the temporal structure in movements of a caching forager. The movement index PII, shows promise for identifying behaviors in species that frequently return to specific locations such as food caches, watering holes, or dens, and highlights the potential role memory and cognitive abilities play in determining animal movements.

Feedr and animalnexus.ca: A paired R package and user-friendly Web application for transforming and visualizing animal movement data from static stations.

Radio frequency identification (RFID) provides a simple and inexpensive approach for examining the movements of tagged animals, which can provide information on species behavior and ecology, such as habitat/resource use and social interactions. In addition, tracking animal movements is appealing to naturalists, citizen scientists, and the general public and thus represents a tool for public engagement in science and science education. Although a useful tool, the large amount of data collected using RFID may quickly become overwhelming. Here, we present an R package (feedr) we have developed for loading, transforming, and visualizing time‐stamped, georeferenced data, such as RFID data collected from static logger stations. Using our package, data can be transformed from raw RFID data to visits, presence (regular detections by a logger over time), movements between loggers, displacements, and activity patterns. In addition, we provide several conversion functions to allow users to format data for use in functions from other complementary R packages. Data can also be visualized through static or interactive maps or as animations over time. To increase accessibility, data can be transformed and visualized either through R directly, or through the companion site: http://animalnexus.ca, an online, user‐friendly, R‐based Shiny Web application. This system can be used by professional and citizen scientists alike to view and study animal movements. We have designed this package to be flexible and to be able to handle data collected from other stationary sources (e.g., hair traps, static very high frequency (VHF) telemetry loggers, observations of marked individuals in colonies or staging sites), and we hope this framework will become a meeting point for science, education, and community awareness of the movements of animals. We aim to inspire citizen engagement while simultaneously enabling robust scientific analysis.