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Background: Studying how the bull sharks aggregate and how they can be driven by life history traits such as reproduction, prey availability, predator avoidance and social interaction in a National Park such as Cabo Pulmo, is key to understand and protect the species. Methods: The occurrence variability of 32 bull sharks tracked with passive acoustic telemetry were investigated via a hierarchical logistic regression model, with inference conducted in a Bayesian framework, comparing sex, and their response to temperature and chlorophyll. Results: Based on the fitted model, occurrence probability varied by sex and length. Juvenile females had the highest values, whereas adult males the lowest. A strong seasonality or day of the year was recorded, where sharks were generally absent during September-November. However, some sharks did not show the common pattern, being detected just for a short period. This is one of the first studies where the Bayesian framework is used to study passive acoustic telemetry proving the potential to be used in further studies.
Subject(s)
Bayes Theorem , Seasons , Sharks , Animals , Sharks/physiology , Female , Male , California , TelemetryABSTRACT
Recent proliferation of GPS technology has transformed animal movement research. Yet, time-series data from this recent technology rarely span beyond a decade, constraining longitudinal research. Long-term field sites hold valuable historic animal location records, including hand-drawn maps and semantic descriptions. Here, we introduce a generalised workflow for converting such records into reliable location data to estimate home ranges, using 30 years of sleep-site data from 11 white-faced capuchin (Cebus imitator) groups in Costa Rica. Our findings illustrate that historic sleep locations can reliably recover home range size and geometry. We showcase the opportunity our approach presents to resolve open questions that can only be addressed with very long-term data, examining how home ranges are affected by climate cycles and demographic change. We urge researchers to translate historical records into usable movement data before this knowledge is lost; it is essential to understanding how animals are responding to our changing world.
Subject(s)
Cebus , Climate Change , Animals , Costa Rica , Cebus/physiology , Homing Behavior , Geographic Information Systems , Population Dynamics , DemographyABSTRACT
Despite being a heavily fished species, little is known about the movements of silky sharks (Carcharhinus falciformis). In this study, we report the longest (in duration and distance traveled) and most spatially extensive recorded migration for a silky shark. This shark, tagged with a fin-mount satellite transmitter at the Galapagos Islands, traveled >27,666 km over 546 days, making two westerly migrations into international waters as far as 4755 km from the tagging location. These extensive movements in an area with high international fishing effort highlights the importance of understanding silky shark migrations to inform management practices.
Subject(s)
Animal Migration , Sharks , Animals , Pacific Ocean , EcuadorABSTRACT
BACKGROUND: Long-distance migratory birds spend most of their annual cycle in non-breeding areas. During this period birds must meet their daily nutritional needs and acquire additional energy intake to deal with future events of the annual cycle. Therefore, patterns of space use and movement may emerge as an efficient strategy to maintain a trade-off between acquisition and conservation of energy during the non-breeding season. However, there is still a paucity of research addressing this issue, especially in trans-hemispheric migratory birds. METHODS: Using GPS-tracking data and a recently developed continuous-time stochastic process modeling framework, we analyzed fine-scale movements in a non-breeding population of Hudsonian godwits (Limosa haemastica), a gregarious long-distance migratory shorebird. Specifically, we evaluated if these extreme migrants exhibit restricted, shared, and periodic patterns of space use on one of their main non-breeding grounds in southern South America. Finally, via a generalized additive model, we tested if the observed patterns were consistent within a circadian cycle. RESULTS: Overall, godwits showed finely-tuned range-residence and periodic movements (each 24-72 h), being similar between day and night. Remarkably, range-resident individuals segregated spatially into three groups. In contrast, a smaller fraction of godwits displayed unpredictable and irregular movements, adding functional connectivity within the population. CONCLUSIONS: In coastal non-breeding areas where resource availability is highly predictable due to tidal cycles, range-resident strategies during both the day and night are the common pattern in a long-distance shorebird population. Alternative patterns exhibited by a fraction of non-resident godwits provide functional connectivity and suggest that the exploratory tendency may be essential for information acquisition and associated with individual traits. The methodological approach we have used contributes to elucidate how the composition of movement phases operates during the non-breeding season in migratory species and can be replicated in non-migratory species as well. Finally, our results highlight the importance of considering movement as a continuum within the annual cycle.
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Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties-including data circularity-were demonstrated. The emergent patterns helped identify 11 counties as 'disseminators' or 'facilitators' (F) and 264 counties as 'barriers' (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.
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The impact of human population movement (HPM) on the epidemiology of vector-borne diseases, such as malaria, has been described. However, there are limited data on the use of new technologies for the study of HPM in endemic areas with difficult access such as the Amazon. In this study conducted in rural Peruvian Amazon, we used self-reported travel surveys and GPS trackers coupled with a Bayesian spatial model to quantify the role of HPM on malaria risk. By using a densely sampled population cohort, this study highlighted the elevated malaria transmission in a riverine community of the Peruvian Amazon. We also found that the high connectivity between Amazon communities for reasons such as work, trading or family plausibly sustains such transmission levels. Finally, by using multiple human mobility metrics including GPS trackers, and adapted causal inference methods we identified for the first time the effect of human mobility patterns on malaria risk in rural Peruvian Amazon. This study provides evidence of the causal effect of HPM on malaria that may help to adapt current malaria control programmes in the Amazon.
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Lameness is a painful clinical condition of the bovine locomotor system that results in alterations of movement. Together with mastitis and infertility, lameness is the main welfare, health, and production problem found in intensive dairy farms worldwide. The clinical assessment of lameness results in an imprecise diagnosis and delayed intervention. Hence, the current approach to the problem is palliative rather than preventive. The five main surfaces used in free housing systems in dairy farms are two natural (grass and sand) and three artificial (rubber, asphalt, and concrete). Each surface presents a different risk potential for lameness, with grass carrying the lowest threat. The aim of the present study is to evaluate the flooring type influences on cows' movement capabilities, using all the available information relating to kinematics, kinetics, behavior, and posture in free-housed dairy cows. Inspired by a refurbished movement ecology concept, we conducted a literature review, taking into account kinematics, kinetics, behavior, and posture parameters by reference to the main surfaces used in free housing systems for dairy cows. We built an integrative analysis of functional ranges (IAFuR), which provides a combined welfare status diagram for the optimal (i.e., within the upper and lower limit) functional ranges for movement (i.e., posture, kinematics, and kinetics), navigation (i.e., behavior), and recovery capacities (i.e., metabolic cost). Our analysis confirms grass' outstanding clinical performance, as well as for all of the movement parameters measured. Grass boosts pedal joint homeostasis; provides reliable, safe, and costless locomotion; promotes longer resting times. Sand is the best natural alternative surface, but it presents an elevated metabolic cost. Rubber is an acceptable artificial alternative surface, but it is important to consider the mechanical and design properties. Asphalt and concrete surfaces are the most harmful because of the high traffic abrasiveness and loading impact. Furthermore, IAFuR can be used to consider other qualitative and quantitative parameters and to provide recommendations on material properties and the design of any surface, so as to move towards a more grass-like feel. We also suggest the implementation of a decision-making pathway to facilitate the interpretation of movement data in a more comprehensive way, in order to promote consistent, adaptable, timely, and adequate management decisions.
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Clustering is a ubiquitous task in ecological and environmental sciences and multiple methods have been developed for this purpose. Because these clustering methods typically require users to a priori specify the number of groups, the standard approach is to run the algorithm for different numbers of groups and then choose the optimal number using a criterion (e.g., AIC or BIC). The problem with this approach is that it can be computationally expensive to run these clustering algorithms multiple times (i.e., for different numbers of groups) and some of these information criteria can lead to an overestimation of the number of groups. To address these concerns, we advocate for the use of sparsity-inducing priors within a Bayesian clustering framework. In particular, we highlight how the truncated stick-breaking (TSB) prior, a prior commonly adopted in Bayesian nonparametrics, can be used to simultaneously determine the number of groups and estimate model parameters for a wide range of Bayesian clustering models without requiring the fitting of multiple models. We illustrate the ability of this prior to successfully recover the true number of groups for three clustering models (two types of mixture models, applied to GPS movement data and species occurrence data, as well as the species archetype model) using simulated data in the context of movement ecology and community ecology. We then apply these models to armadillo movement data in Brazil, plant occurrence data from Alberta (Canada), and bird occurrence data from North America. We believe that many ecological and environmental sciences applications will benefit from Bayesian clustering methods with sparsity-inducing priors given the ubiquity of clustering and the associated challenge of determining the number of groups. Two R packages, EcoCluster and bayesmove, are provided that enable the straightforward fitting of these models with the TSB prior.
Subject(s)
Algorithms , Alberta , Bayes Theorem , Brazil , Cluster AnalysisABSTRACT
Mammals can show conspicuous behavioral responses to thermal variation, including changes in movement patterns. We used an integrative approach to understand how environmental temperature can drive the movement behavior of a mammal with low capacity for physiological thermoregulation, the giant anteater (Myrmecophaga tridactyla). We tracked 52 giant anteaters in 7 areas throughout the Brazilian savannah. We estimated the distance moved, area used, use of forest areas, and mean environmental temperature for each monitoring day of each individual. We modeled these data with Mixed Structural Equations - considering the possible interactions between our variables and controlling for sex and body mass. Giant anteaters reduced displacement and increased forest use with decreasing environmental temperature, probably because of their low body heat production. It is possible that they reduce distance moved and area used by reducing the duration of activity. With decreasing temperature, forest habitats become warmer than open ones, besides buffer rain and chilly winds. Reducing displacement and using forests are important strategies to reduce body heat loss and the energetic costs of thermoregulation. However, decreasing movement can limit food access and, consequently, fitness. Therefore, we highlight the importance of forests as thermal shelters. With increasing frequency and intensity of extreme weather events, we showed the need to preserve forest patches to offer suitable conditions for tropical mammals' behavioral thermoregulation. In this context, policies favoring deforestation on Brazilian territory are especially worrisome. Finally, we emphasize the need of integrative approaches to understand the complex interactions between organisms and the environment.
Subject(s)
Ecosystem , Vermilingua , Animals , Body Temperature Regulation , Forests , Mammals , TemperatureABSTRACT
Identifying environmental correlates driving space-use strategies can be critical for predicting population dynamics; however, such information can be difficult to attain for small mobile species such as migratory songbirds. We combined radio-telemetry and high-resolution GPS tracking to examine space-use strategies under different moisture gradients for wood thrush (Hylocichla mustelina). We explored the role moisture plays in driving food abundance and, in turn, space-use strategies at a wintering site in Belize across 3 years. Individuals occupying drier habitats experienced lower food abundance and poorer body condition. Using data from our radio-tracked study population and GPS tracking from across five breeding populations, we detected low rates of overwinter site persistence across the wood thrush wintering range. Contrary to expectations, individuals in wetter habitats were more likely to engage in permanent mid-winter relocations, up to 148 km. We suggest facultative movements are instead a condition-dependent strategy that enables wintering wood thrush to locate alternative habitat as food availability declines throughout the dry season. Increased aridity is predicted across the wintering range of wood thrush, and future research should delve deeper into understanding how moisture impacts within and between season space-use dynamics and its ultimate impact on the population dynamics of this declining species.
Subject(s)
Songbirds , Animal Migration , Animals , Belize , Ecosystem , Humans , SeasonsABSTRACT
Here, we use vertebral microchemistry to investigate the habitat use patterns of the longnose stingray Hypanus guttatus in the northern and northeastern regions of Brazil, and to evaluate the existence of potential nurseries of the species. Samples were collected in Maranhão, Rio Grande do Norte and Pernambuco states between 2008 and 2019. Trace element concentrations of Ba:Ca, Mg:Ca, Mn:Ca and Sr:Ca in vertebrae were determined through laser ablation inductively coupled plasma mass spectrometry. We used one-step permutational ANOVAs to evaluate multi and single-element differences in element:Ca ratios among life stages and sexes across and within sites. Element signatures differed among all sites for both single and multi-element settings. However, there were few differences among life stages within sites, except for Mn:Ca between life stages for Maranhão state, and between sexes for Sr:Ca for both Pernambuco and Rio Grande do Norte, and Ba:Ca for Rio Grande do Norte. Furthermore, all multi and single-element analyses across locations were significant and highlight the strong differences by sites. We also performed a nonmetric multidimensional scaling analysis, which demonstrated the strong differences for samples from Rio Grande do Norte and the other two sites. By analysing the lifetime transects of each sample, we observed that there was little variation in all element:Ca ratios within sites. Therefore, we argue that the longnose stingray likely does not display extensive habitat use shifts and fulfils much of its life cycle within each area. Finally, we obtained no evidence of nurseries for any site and suggest this is likely a pattern across the species distribution. Future studies investigating habitat use with samples from larger specimens (disc width > 90 cm, >15 years) are needed to better understand the species habitat use patterns across all size ranges.
Subject(s)
Skates, Fish , Trace Elements , Animals , Ecosystem , Microchemistry , SpineABSTRACT
Sexual segregation is widely reported among sexually dimorphic species and generally attributed to intraspecific competition. Prey diversity and human activities can reinforce niche segregation by increasing resource heterogeneity. Here, we explored trophic and spatial sexual segregation in the only avian scavenger that exhibits pronounced sexual size dimorphism (up to 50% difference in body mass) and a highly despotic social system, the Andean condor (Vultur gryphus). We predicted that larger and dominant males would exclude smaller and subordinate females from high-quality resources, leading to sexual segregation particularly in human-dominated landscapes showing increased prey diversity. We compared resource use between females and males across six sites in Argentina featuring a range of prey diversity via stable isotopes analysis of molted feathers (n = 141 individuals). We then focused on two sites featuring contrasting levels of prey diversity and quantified assimilated diet via stable isotopes and space use via GPS monitoring (n = 23 and 12 tagged individuals). We found no clear differences in isotopic niche space, individual variation in isotopic signature, or assimilated diet between females and males. However, there were differences in foraging locations between sexes, with females apparently using areas of fewer food resources more frequently than males. Local conditions defined the dynamics of fine-scale sexual differences in foraging sites; yet, unpredictable and ephemeral carrion resources likely prevent segregation by sexes at the landscape scale. Our study highlights complex dynamics of sexual segregation in vultures and the relevancy of analyses under multiple spatial-temporal scales to explore segregation in social species.
Subject(s)
Falconiformes , Feeding Behavior , Animals , Argentina , Birds , Female , Fishes , Humans , MaleABSTRACT
Human movement affects malaria epidemiology at multiple geographical levels; however, few studies measure the role of human movement in the Amazon Region due to the challenging conditions and cost of movement tracking technologies. We developed an open-source low-cost 3D printable GPS-tracker and used this technology in a cohort study to characterize the role of human population movement in malaria epidemiology in a rural riverine village in the Peruvian Amazon. In this pilot study of 20 participants (mean age = 40 years old), 45,980 GPS coordinates were recorded over 1 month. Characteristic movement patterns were observed relative to the infection status and occupation of the participants. Applying two analytical animal movement ecology methods, utilization distributions (UDs) and integrated step selection functions (iSSF), we showed contrasting environmental selection and space use patterns according to infection status. These data suggested an important role of human movement in the epidemiology of malaria in the Peruvian Amazon due to high connectivity between villages of the same riverine network, suggesting limitations of current community-based control strategies. We additionally demonstrate the utility of this low-cost technology with movement ecology analysis to characterize human movement in resource-poor environments.
Subject(s)
Malaria , Rivers , Adult , Animals , Cohort Studies , Humans , Malaria/epidemiology , Peru/epidemiology , Pilot ProjectsABSTRACT
Marine animal tracking has become one of the major tools used to understand the behavior and ecology of a multitude of species in the ocean, thus there is an increasing body of knowledge about this subject worldwide, particularly for sharks. Nevertheless, little was known of the movement patterns of shark in the Mexican Pacific (MXP) and Gulf of California (GOC), except for the pioneering work carried out in the 1980s on the movements of scalloped hammerhead sharks in El Bajo Espiritu Santo and other islands in the region, as well as ongoing studies on white shark movements, migratory patterns and behavior off Isla Guadalupe. Here we present an overview of previous studies on the movements of sharks, as well as a comprehensive description of new studies currently being carried out by our research group at Pelagios Kakunjá on several species of sharks in the MXP. We show how information gleaned from these studies can be put to use to guide sustainable exploitation policies and promote effective conservation practices.
Subject(s)
Animal Migration , Conservation of Natural Resources , Sharks , Animals , Ecology , Fisheries/statistics & numerical data , Islands , MexicoABSTRACT
The study of animal movement is challenging because movement is a process modulated by many factors acting at different spatial and temporal scales. In order to describe and analyse animal movement, several models have been proposed which differ primarily in the temporal conceptualization, namely continuous and discrete time formulations. Naturally, animal movement occurs in continuous time but we tend to observe it at fixed time intervals. To account for the temporal mismatch between observations and movement decisions, we used a state-space model where movement decisions (steps and turns) are made in continuous time. That is, at any time there is a non-zero probability of making a change in movement direction. The movement process is then observed at regular time intervals. As the likelihood function of this state-space model turned out to be intractable yet simulating data is straightforward, we conduct inference using different variations of Approximate Bayesian Computation (ABC). We explore the applicability of this approach as a function of the discrepancy between the temporal scale of the observations and that of the movement process in a simulation study. Simulation results suggest that the model parameters can be recovered if the observation time scale is moderately close to the average time between changes in movement direction. Good estimates were obtained when the scale of observation was up to five times that of the scale of changes in direction. We demonstrate the application of this model to a trajectory of a sheep that was reconstructed in high resolution using information from magnetometer and GPS devices. The state-space model used here allowed us to connect the scales of the observations and movement decisions in an intuitive and easy to interpret way. Our findings underscore the idea that the time scale at which animal movement decisions are made needs to be considered when designing data collection protocols. In principle, ABC methods allow to make inferences about movement processes defined in continuous time but in terms of easily interpreted steps and turns.
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How animals explore and acquire knowledge from the environment is a key question in movement ecology. For pollinators that feed on multiple small replenishing nectar resources, the challenge is to learn efficient foraging routes while dynamically acquiring spatial information about new resource locations. Here, we use the behavioural mapping t-Stochastic Neighbouring Embedding algorithm and Shannon entropy to statistically analyse previously published sampling patterns of bumblebees feeding on artificial flowers in the field. We show that bumblebees modulate foraging excursions into distinctive behavioural strategies, characterizing the trade-off dynamics between (i) visiting and exploiting flowers close to the nest, (ii) searching for new routes and resources, and (iii) exploiting learned flower visitation sequences. Experienced bees combine these behavioural strategies even after they find an optimal route minimizing travel distances between flowers. This behavioural variability may help balancing energy costs-benefits and facilitate rapid adaptation to changing environments and the integration of more profitable resources in their routes.
Subject(s)
Bees/physiology , Feeding Behavior/physiology , Flight, Animal/physiology , Learning/physiology , Pollination/physiology , Animals , FlowersABSTRACT
Telemetry-based movement research has become central for learning about the behavior, ecology and conservation of wide-ranging species. Particularly, early telemetry studies were conducted on vultures and condors due to three main reasons: i) these birds capture the curiosity of humans, ii) their large body size allows researchers to deploy large telemetry units, and iii) they are of high conservation concern. This has resulted in a great number of scientific articles that remain scattered throughout the literature. To achieve a more cohesive view of vultures and condors movement behavior, we review all telemetry studies published up to 2017. We first present a descriptive summary of the technical and design characteristics of these studies (e.g. target species, tagging location, number of individuals tagged) and go on to discuss them under a common conceptual framework; the Movement Ecology Paradigm. The articles found (N = 97) were mainly published in the last decade and based on the tagging of individuals from 14 species (61% of the extant species) and 24 countries. Foraging was the most in-depth investigated movement phase (25 studies), with studies covering several species, using both phenomenological and mechanistic approaches and tackling the role of different drivers of movement. In contrast, commuting and natal dispersal phases were only superficially investigated (3 and 8 studies, respectively). Finally, studies dealing with the conservation and management also comprised a large portion of the reviewed articles (24 studies). Telemetry studies have revealed relevant details of vultures and condors movements, with highly accurate measurements of flight energetics and a better understanding of the morphological, physiological and context-dependent drivers that underlie the movement decisions of these birds. However, we also detected several information gaps. We expect this review helps researchers to focus their efforts and funds where more information is needed.
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Stable isotope analysis (SIA) can be a useful tool for tracking the long-distance movements of migratory taxa. However, local-scale sources of isotopic variation, such as differences in habitat use or foraging patterns, may complicate these efforts. Few studies have evaluated the implications of local-scale foraging specializations for broad-scale isotope-based tracking. Here, we use > 300 h of animal-borne video footage from green turtles (Chelonia mydas) paired with SIA of multiple tissues, as well as fine-scale Fastloc-GPS satellite tracking, to show that dietary specialization at a single foraging location (Shark Bay, Western Australia) drives a high level of among-individual δ13C variability (δ13C range = 13.2). Green turtles in Shark Bay were highly omnivorous and fed selectively, with individuals specializing on different mixtures of seagrasses, macroalgae and invertebrates. Furthermore, green turtle skin δ13C and δ15N dispersion within this feeding area (total isotopic niche area = 41.6) was comparable to that from a well-studied rookery at Tortuguero, Costa Rica, where isotopic dispersion (total isotopic niche area = 44.9) is known to result from large-scale (> 1500 km) differences in foraging site selection. Thus, we provide an important reminder that two different behavioral dynamics, operating at very different spatial scales, can produce similar levels of isotopic variability. We urge an added degree of caution when interpreting isotope data for migratory species with complex foraging strategies. For green turtles specifically, a greater appreciation of trophic complexity is needed to better understand functional roles, resilience to natural and anthropogenic disturbances, and to improve management strategies.
Subject(s)
Diet , Turtles , Animals , Carbon Isotopes , Costa Rica , Nitrogen IsotopesABSTRACT
The field of movement ecology has rapidly grown during the last decade, with important advancements in tracking devices and analytical tools that have provided unprecedented insights into where, when, and why species move across a landscape. Although there has been an increasing emphasis on making animal movement data publicly available, there has also been a conspicuous dearth in the availability of such data on large carnivores. Globally, large predators are of conservation concern. However, due to their secretive behavior and low densities, obtaining movement data on apex predators is expensive and logistically challenging. Consequently, the relatively small sample sizes typical of large carnivore movement studies may limit insights into the ecology and behavior of these elusive predators. The aim of this initiative is to make available to the conservation-scientific community a dataset of 134,690 locations of jaguars (Panthera onca) collected from 117 individuals (54 males and 63 females) tracked by GPS technology. Individual jaguars were monitored in five different range countries representing a large portion of the species' distribution. This dataset may be used to answer a variety of ecological questions including but not limited to: improved models of connectivity from local to continental scales; the use of natural or human-modified landscapes by jaguars; movement behavior of jaguars in regions not represented in this dataset; intraspecific interactions; and predator-prey interactions. In making our dataset publicly available, we hope to motivate other research groups to do the same in the near future. Specifically, we aim to help inform a better understanding of jaguar movement ecology with applications towards effective decision making and maximizing long-term conservation efforts for this ecologically important species. There are no costs, copyright, or proprietary restrictions associated with this data set. When using this data set, please cite this article to recognize the effort involved in gathering and collating the data and the willingness of the authors to make it publicly available.