Autocorrelated Kernel Density Estimation Research Articles

Livin' la vida local: philopatry results in consistent patterns of annual space use in a long‐lived lizard

AbstractFor animals exhibiting range residency, the home range is a useful framework to quantify space use. Some reptiles can live decades in the wild and experience extreme environmental variation that influences patterns of habitat use. Individuals may modify their use of space over time, reducing the utility of single‐year home range estimates. Very high frequency (VHF) telemetry data were collected for Gila monsters (Heloderma suspectum) at three Mojave Desert sites in Clark County, Nevada, and home range utilization distributions were calculated using an autocorrelated kernel density estimator. Home range size was consistent within individuals and populations, and home range size did not vary across years at any site. To measure home range fidelity (year‐to‐year reuse), we calculated Bhattacharyya's coefficient (BC) for each combination of years in which an individual was tracked and averaged estimates across individuals and populations. The average BC score was 0.86 (scale from 0 to 1; 0 = no overlap and 1 = complete overlap) and did not vary among populations. We modeled home range area accumulation to estimate the minimum sample size needed for asymptotic stability and found home range accumulation to be dynamic and variable within and across years and individuals. Analysis of the frequency of movement by individuals, average distance traveled per movement, and cumulative distance traveled per active season revealed that movement patterns vary considerably by year. Heterogeneity of space use among populations and individuals suggests that individual and local environmental variation, rather than annual variation in resource availability, may drive home range size and movement patterns of Gila monsters in southern Nevada. Annual variability in movement patterns did not translate to variability in home range size or location, and the species exhibits extremely high philopatry, using the same areas for periods of at least 3–5 years.

Spatial ecology to strengthen invasive snake management on islands

Knowledge on the spatial ecology of invasive predators positively contributes to optimizing their management, especially when involving cryptic and secretive species, such as snakes. However, this information is lacking for most invasive snakes, particularly on islands, where they are known to cause severe ecological and socio-economic impacts. This research is focused on assessing the spatial ecology of the California kingsnake (Lampropeltis californiae) on Gran Canaria to strengthen management actions. We monitored 15 radio-tagged individuals once per day on 9–11 days per month from July 2020 to June 2021 to calculate the species' home range and describe annual activity patterns in the invaded range. To account for the species' diel activity during the emergence period, we additionally monitored snakes from January to May 2021 during three consecutive days per month in four different time intervals each day. We detected movement (consecutive detections at least 6 m apart) in 31.68% of the 1146 detections during the whole monitoring period. Movements most frequently detected were shorter than 100 m (82.24%), and among them the range 0–20 m was the most recurrent (27.03%). The mean distance of movement was 62.57 ± 62.62 m in 1–2 days. Average home range was 4.27 ± 5.35 ha—calculated with the Autocorrelated Kernel Density Estimator (AKDE) at 95%—and did not significantly vary with SVL nor sex. We detected an extremely low value of motion variance (0.76 ± 2.62 σ2m) compared to other studies, with a general inactivity period from November to February, January being the less active month of the year. Diel activity was higher during central and evening hours than during early morning and night. Our results should be useful to improve control programs for this invasive snake (e.g., trap placement and visual survey guidance) on Gran Canaria. Our research highlights the importance of gathering spatial information on invasive snakes to enhance control actions, which can contribute to the management of secretive invasive snakes worldwide.

Are trapping data suited for home‐range estimation?

Modern home‐range estimation typically relies on data derived from expensive radio‐ or GPS‐tracking. Although trapping represents a low‐cost alternative to telemetry, evaluation of the performance of home‐range estimators on trap‐derived data is lacking. Using simulated data, we evaluated three variables reflecting the key trade‐offs ecologists face when designing a trapping study: 1) the number of observations obtained per individual, 2) the trap density and 3) the proportion of the home range falling inside the trapping area. We compared the performance of five home‐range estimators (MCP: Minimum Convex Polygon, LoCoH: Local Convex Hull, KDE: Kernel Density Estimation, AKDE: Autocorrelated Kernel Density Estimation, BicubIt: Bicubic Interpolation). We further explored the potential benefits of combining these estimators with asymptotic models, which leverage the saturating behavior of changes in the estimated home‐range area as the number of observations increases to improve accuracy, as well as different data‐ordering procedures. We then quantified the bias in home‐range size under the different scenarios investigated. The number of observations and the proportion of the home range within the trapping grid were the most important predictors of the accuracy and the precision of home‐range estimates. The use of asymptotic models helped to obtain accurate estimates at smaller sample sizes, while distance ordering improved the precision and asymptotic consistency of estimates. While AKDE was the best performing estimator under most conditions evaluated, bicubic interpolation was a viable alternative under common real‐world conditions of low trap density and area covered. A case study using empirical data from white‐tailed deer in Florida and another from jaguars in Belize demonstrated support for the findings of our simulation results. Although researchers with trap data often overlook home‐range estimation, our results indicate that these data have the capacity to yield accurate estimates of home‐range size. Trapping data can, therefore, lower the economic costs of home‐range analysis, potentially enlarging the span of species, researchers and questions studied in ecology and conservation.

A stable home: Autocorrelated Kernel Density Estimated home ranges of the critically endangered Elongated tortoise

Home range analysis is a standard and fundamental concept in ecology used to describe animal space use over their lifetimes. Connecting home range sizes with animal characteristics, location, and habitat can be used to inform conservation decisions. Reptiles are frequently lacking robust estimates of space use, particularly reptiles in tropical regions. Here we analyse a publicly available dataset, collected by the authors of this study, describing the movements of Critically Endangered Elongated tortoises Indotestudo elongata. The tortoise data included the locations of 17 tortoises (12 females, 5 males) collected on average once every three days for an average duration of 353.76 SE ± 33.10 days. We use these data to estimate the home range of Elongated tortoise, and explore how tortoise size and sex influences home range size. To mitigate issues resulting from low effective sample sizes and low temporal resolution of the data, we used a modern home range estimation method – Autocorrelated Kernel Density Estimators (AKDE). We found 14 of 17 individuals appear to be occupying a stable home range (using variograms to determine range residency). The average AKDE home range for all 14 individuals with range residency was 44.81 ± 10.44 ha. Bayesian Regression Models suggest comparable size estimates between male and female home ranges, despite males being physically larger than females in both mass and carapace length. These AKDE home range estimates have the added utility of being more comparable with other studies, less susceptible to errors from a suboptimal tracking regime, and are well positioned for inclusion in future meta-analyses. Keywords: testudine, autocorrelated kernel density estimator, spatial ecology, space use, Thailand, Indotestudo elongata

Spatial pattern and shelter distribution of the ocellated lizard (Timon lepidus) in two distinct Mediterranean habitats

Abstract The knowledge of a species’ spatial ecology is essential for its conservation as it helps to implement targeted protection measures to suitable habitats. In 2011 and 2013, two French populations of ocellated lizards Timon lepidus were monitored through very high frequency (VHF) radio telemetry in two distinct Mediterranean habitats: a 77 ha scrubland (n = 8) and a 1590 ha semi-arid steppe (n = 11) corresponding to a heterogeneous and homogeneous habitat respectively. The variability in spatial estimates for the seasonal habitat use of the ocellated lizard was compared within the two sites using the Autocorrelated Kernel Density Estimation (AKDE). Recursive movement patterns and spatial repartition of shelters were further assessed to study the habitat influence on the species’ space use. No significant differences between sexes or sites were identified in the computed AKDE ranges. This inter-site approach demonstrated higher shelter revisits in core-areas than in the rest of estimated home ranges for both sites. A higher shelter density was observed in the core areas of the lizards than in the rest of their home-ranges for the Mediterranean scrubland but not for the semi-arid steppe. Such findings might attest to the species’ adaptive capabilities within two distinct Mediterranean ecosystems.

Space‐use patterns of green turtles in industrial coastal foraging habitat: Challenges and opportunities for informing management with a large satellite tracking dataset

Abstract Increasing overlap between anthropogenic activities and wildlife can lead to problematic human–wildlife interactions. To manage these, an understanding of animal space‐use patterns, with sufficient temporal and spatial detail is required. Satellite telemetry can provide such detailed data; however, the cost of tracking units places a significant limitation on sample size. Satellite tracks for 72 green turtles were consolidated through collaboration with multiple entities over 8 years at seven sites within a large industrial port contributing to an ecological monitoring initiative to minimize impacts of planned developments. This study aims to determine the minimum number of satellite‐tracked green turtles required to represent spatial distribution patterns in the foraging ground and to evaluate factors underpinning differences in distribution and site fidelity metrics to inform appropriate management strategies. An autocorrelated kernel density estimator was used to construct 95% utilization distributions for individual turtles during each calendar season. Percentage overlap between pairs of seasonal utilization distributions was calculated as a measure of short‐term site fidelity. Mechanistic range shift analysis was applied to detect significant deviations from range residency behaviour. Green turtles exhibited spatially confined ranges and remained faithful to their foraging area for periods of up to 260 days. Range size was significantly different between microhabitats and study years. Only 16 individuals (22% of tracked turtles) performed significant range shifts, indicating that occupied areas represent important habitats, and most turtles are unlikely to adjust their space‐use in response to anthropogenic or natural disturbances. Although this dataset represents an atypically large sample of satellite tracked individuals, representative data were obtained at only two key sites. This study highlights the importance of evaluating clear objectives when sampling animals for satellite telemetry studies to obtain representation of sites, periods of interest, or age and sex cohorts.

Space use and site fidelity of wintering whooping cranes on the Texas Gulf Coast

AbstractThe Aransas‐Wood Buffalo population (the only non‐reintroduced, migratory population) of endangered whooping cranes (Grus americana) overwinters along the Texas Gulf Coast, USA. Understanding whooping crane space use on the wintering grounds reveals essential aspects of this species' ecology, which subsequently assists with conservation. Using global positioning system telemetry data from marked whooping cranes during 2009–2017, we fit continuous‐time stochastic process models to describe movement and home range using autocorrelated kernel density estimation (AKDE) and explored variation in home range size in relation to age, sex, reproductive status, and drought conditions. We used the Bhattacharyya coefficient of overlap and distance between home range centroids to quantify site fidelity. We examined the effects of time between winter home ranges and the sex of the crane on site fidelity using Bayesian mixed‐effects beta regression. Winter whooping crane 95% AKDE home range size averaged 30.1 ± 45.2 (SD) km2 (median = 14.3, range = 1.1–308.6). Home ranges of sub‐adult females were approximately 2 times larger than those of sub‐adult males or families. As drought worsened, home ranges typically expanded. Between consecutive years, the home ranges of an adult crane exhibited 68 ± 31% overlap (site fidelity), but fidelity to winter sites declined in subsequent winters. The overlap of adult home ranges with the nearest unrelated family averaged 33 ± 28%. As a whooping crane aged, overlap with its winter home range as a juvenile declined, regardless of sex. By 4 years of age, a whooping crane had approximately 14 ± 28% overlap with its juvenile winter home range. Limited evidence suggested male whooping cranes return to within 2 km of their juvenile home range by their fifth winter. Previous data obtained from aerial surveys led ecologists to assume that whooping crane families normally used small areas (~2 km2) and expressed persistent site fidelity. Our analyses showed <8% of families had home ranges ≤2 km2, with the average area 15 times greater, and waning site fidelity over time. Our work represents an analysis of whooping crane home ranges for this population, identifying past misconceptions of winter space use and resulting in better estimates of space requirements for future conservation efforts.

Application of GPS occurrence data to understand African white-backed vultures Gyps africanus spatial home range overlaps.

Understanding key overlap zones and habitats which are intensively shared by species in space and time is crucial as it provides vital information to inform spatial conservation with maximum benefits. The advent of high‐resolution GPS technologies associated with new analytical algorithms is revolutionizing studies underpinning species spatial and social interaction patterns within ecosystems. Here, using a robust home range estimation algorithm, the autocorrelated kernel density estimator (AKDE) equipped with an equally powerful home range overlap metric, the Bhattacharyya's coefficient (BC), we provide one of the first attempts to estimate and delineate spatial home range overlap zones for critically endangered African white‐backed vultures to inform conservation planning. Six vultures were captured in Hwange National Park using a modified cannon net system after which they were tagged and tracked with high‐resolution GPS backpacks. Overall, results suggested weaker average home range overlaps based on both the pooled data (0.38 ± 0.26), wet non‐breeding seasonal data (0.32 ± 0.23), and dry breeding season data (0.34 ± 0.28). Vultures 4, 5, and 6 consistently revealed higher home range overlaps across all the scales with values ranging between 0.60 and 0.99. Individual vultures showed consistence in space use patterns as suggested by high between‐season home range overlaps, an indication that they may be largely resident within the Hwange ecosystem. Importantly, we also demonstrate that home range overlapping geographic zones are all concentrated within the protected area of Hwange National Park. Our study provides some of the first results on African vulture home range overlaps and segregation patterns in the savanna ecosystem based on unbiased telemetry data and rigorous analytical algorithms. Such knowledge may provide vital insights for prioritizing conservation efforts of key geographic overlap zones to derive maximum conservation benefits especially when targeting wide‐ranging and critically endangered African white‐backed vultures. To this end, spatial overlap zones estimated here, although based on a small sample size, could provide a strong foundation upon which other downstream social and ecological questions can be explored further to expand our understanding on shared space use mechanisms among African vulture species.

Population‐level inference for home‐range areas

Abstract Home‐range estimates are a common product of animal tracking data, as each range represents the area needed by a given individual. Population‐level inference of home‐range areas—where multiple individual home ranges are considered to be sampled from a population—is also important to evaluate changes over time, space or covariates such as habitat quality or fragmentation, and for comparative analyses of species averages. Population‐level home‐range parameters have traditionally been estimated by first assuming that the input tracking data were sampled independently when calculating home ranges via conventional kernel density estimation (KDE) or minimal convex polygon (MCP) methods, and then assuming that those individual home ranges were measured exactly when calculating the population‐level estimates. This conventional approach does not account for the temporal autocorrelation that is inherent in modern tracking data, nor for the uncertainties of each individual home‐range estimate, which are often large and heterogeneous. Here, we introduce a statistically and computationally efficient framework for the population‐level analysis of home‐range areas, based on autocorrelated kernel density estimation (AKDE), that can account for variable temporal autocorrelation and estimation uncertainty. We apply our method to empirical examples on lowland tapir Tapirus terrestris, kinkajou Potos flavus, white‐nosed coati Nasua narica, white‐faced capuchin monkey Cebus capucinus and spider monkey Ateles geoffroyi, and quantify differences between species, environments and sexes. Our approach allows researchers to more accurately compare different populations with different movement behaviours or sampling schedules while retaining statistical precision and power when individual home‐range uncertainties vary. Finally, we emphasize the estimation of effect sizes when comparing populations, rather than mere significance tests.

Landscape characteristics influence ranging behavior of Asian elephants at the human-wildlands interface in Myanmar

ContextAsian elephant numbers are declining across much of their range driven largely by serious threats from land use change resulting in habitat loss and fragmentation. Myanmar, holding critical range for the species, is undergoing major developments due to recent sociopolitical changes. To effectively manage and conserve the remaining populations of endangered elephants in the country, it is crucial to understand their ranging behavior.ObjectivesOur objectives were to (1) estimate the sizes of dry, wet, and annual ranges of wild elephants in Myanmar; and quantify the relationship between dry season (the period when human-elephant interactions are the most likely to occur) range size and configurations of agriculture and natural vegetation within the range, and (2) evaluate how percentage of agriculture within dry core range (50% AKDE range) of elephants relates to their daily distance traveled.MethodsWe used autocorrelated kernel density estimator (AKDE) based on a continuous-time movement modeling (ctmm) framework to estimate dry season (26 ranges from 22 different individuals), wet season (12 ranges from 10 different individuals), and annual range sizes (8 individuals), and reported the 95%, 50% AKDE, and 95% Minimum Convex Polygon (MCP) range sizes. We assessed how landscape characteristics influenced range size based on a broad array of 48 landscape metrics characterizing aspects of vegetation, water, and human features and their juxtaposition in the study areas. To identify the most relevant landscape metrics and simplify our candidate set of informative metrics, we relied on exploratory factor analysis and Spearman’s rank correlation coefficient. Based on this analysis we adopted a final set of metrics into our regression analysis. In a multiple regression framework, we developed candidate models to explain the variation in AKDE dry season range sizes based on the previously identified, salient metrics of landscape composition.ResultsElephant dry season ranges were highly variable averaging 792.0 km2 and 184.2 km2 for the 95% and 50% AKDE home ranges, respectively. We found both the shape and spatial configuration of agriculture and natural vegetation patches within an individual elephant’s range play a significant role in determining the size of its range. We also found that elephants are moving more (larger energy expenditure) in ranges with higher percentages of agricultural area.ConclusionOur results provide baseline information on elephant spatial requirements and the factors affecting them in Myanmar. This information is important for advancing future land use planning that takes into account space-use requirements for elephants. Failing to do so may further endanger already declining elephant populations in Myanmar and across the species’ range.

Black bear spatial responses to the Wallow Wildfire in Arizona

AbstractThe Wallow Fire, the largest wildfire in Arizona history, encompassed 2,170 km2 and provided a rare opportunity to examine habitat selection and home ranges of American black bears (Ursus americanus) before and after a wildfire. We had fitted global positioning system (GPS) collars on 47 bears from 2005 to April 2011, and 10 of these were still collared when the fire started in May 2011. We captured and collared an additional 7 black bears within the fire perimeter post‐fire (Jul–Sep 2011 and Jun 2012). To evaluate how black bears were affected by the fire, we fit a step selection function using a conditional mixed effects Poisson regression model to estimate the relative strength of black bear habitat selection in response to burn severity. Additionally, we estimated home range sizes using an autocorrelated kernel density estimator by means of a continuous‐time movement model. We then used a generalized linear model with a negative binomial error distribution and mixed effects to estimate the effect of the burn severity on black bear home range size, while controlling for sex and drought. In spring and summer in years prior to the fire, bears selected areas that later burned in the fire. After the fire, bears used all burn severities, but their selection for high‐severity burns decreased significantly in summer 2011 and fall 2012. Home range sizes were 3.06 times larger pre‐fire than post‐fire. Our study demonstrates that black bears continued to use all burn severities after a major wildfire, and that post‐fire conditions did not result in expanded black bear home ranges.

Autocorrelation‐informed home range estimation: A review and practical guide

AbstractModern tracking devices allow for the collection of high‐volume animal tracking data at improved sampling rates over very‐high‐frequency radiotelemetry. Home range estimation is a key output from these tracking datasets, but the inherent properties of animal movement can lead traditional statistical methods to under‐ or overestimate home range areas.The autocorrelated kernel density estimation (AKDE) family of estimators was designed to be statistically efficient while explicitly dealing with the complexities of modern movement data: autocorrelation, small sample sizes and missing or irregularly sampled data. Although each of these estimators has been described in separate technical papers, here we review how these estimators work and provide a user‐friendly guide on how they may be combined to reduce multiple biases simultaneously.We describe the magnitude of the improvements offered by these estimators and their impact on home range area estimates, using both empirical case studies and simulations, contrasting their computational costs.Finally, we provide guidelines for researchers to choose among alternative estimators and anRscript to facilitate the application and interpretation of AKDE home range estimates.

Movement ecology and space-use by mountain lions in West Texas

Local knowledge regarding the movements and space-use of large carnivores can inform species’ management, conservation planning, and strategies for reducing human-wildlife conflict. However, because issues regarding large carnivores can be controversial, obtaining such information may be difficult and therefore lacking in many places. Such is the case for mountain lions ( Puma concolor ) in West Texas, where most of the land is privately owned. Therefore, we sought to better understand movements and home ranges of mountain lions in the Trans-Pecos region of Texas. We GPS collared 24 mountain lions (15 females, 9 males) between 2011 and 2017. We inspected variograms to distinguish dispersers from residents then we estimated movement metrics and home ranges using continuous-time movement models and autocorrelated kernel density estimation. Using generalized linear mixed models, we tested for seasonal differences in all movement and home range metrics. Of three subadults that dispersed, one had data appropriate for speed estimation; she exhibited faster speeds while dispersing than while exhibiting philopatric movements. Compared to adult resident males, adult resident females moved with slower average speeds (females: 11.82 ± 0.43 km/day; males: 20.36 ± 2.86 km/day), exhibited similar directional persistence in movement (females: 0.95 ± 0.14 h; males: 1.12 ± 0.21 h), crossed their home ranges in similar times (females: 5.76 ± 0.98 days; males: 7.07 ± 1.34 days), and used smaller home ranges than males (females: 283.83 ± 37.50 km 2 : males: 1077.95 ± 219.30 km 2 ). Adults moved with slowest speeds in the cold-dry season; there were no seasonal effects on other estimates. Each individual’s successive seasonal home ranges were highly overlapped (0.95 ± 0.01). The mountain lions did not expand, contract, or shift their home ranges seasonally, which may be due to ample prey-availability and limited seasonal-shifts in prey distribution. Mountain lions used areas larger than most local ranches and tended to move across the landscape quickly. Together, our results indicate that mountain lions do not typically stay on one property for long which may have implications for conservation planning and species management.

Structure and Home Range Size of Mixed-Species Bird Flocks in a Bamboo Forest in Southwestern Amazonia

Mixed-species flocks of birds are cohesive groups of two or more different species that are kept in formation by systematic behavioral interactions among the members of the flocks. Typically, mixed-species flocks form themselves around a nuclear species, which presents a specific pattern of movement during foraging, and a song that is recognized by the other species. In the understory of Neotropical forests, representatives of the family Thamnophilidae, in particular species of the genus Thamnomanes, have become adapted for the role of nuclear species in mixed-species flocks. In the present study, we describe the mixed-species flocks led by individuals of Bluish-slate Antshrike Thamnomanes schistogynus in a forest dominated by bamboo Guadua sp. in southwestern Brazilian Amazonia. We collected data within a 600 × 600 m grid subdivided into 36 1-ha plots, with a total area of 36 ha. Within this grid, we delimited the home ranges and core areas of the resident mixed-species flocks. We also identified the composition of each flocks, frequency, fidelity of its members and determined the relationship between mixed-species flocks and vegetation structure within the grid. We delimited the home ranges of eight mixed-species flocks. The mean home range, estimated using the Minimum Convex Polygon method, was 3.45 ± 0.17 ha, and estimated using the autocorrelated kernel density estimation method was 3.65 ± 0.15 ha, and the mean core area, 1.14 ± 0.03 ha. The home ranges of the mixed-species flocks led by T. schistogynus in southwestern Amazonia are among the smallest recorded in species of the genus Thamnomanes. We identified 71 different bird species in the mixed-species flocks with a mean of 41.1 ± 2.1. While the geographic distribution of the lead species T. schistogynus coincides almost exactly with that of the bamboo forests of southwestern Amazonia, our results did not indicate any systematic relationship or fidelity between the mixed-species flocks led by this species and the bamboo forest.

Post-release Movement Behaviour and Survival of Kulan Reintroduced to the Steppes and Deserts of Central Kazakhstan

Asiatic wild ass, or kulan (Equus hemionus kulan) were once a key species of the Eurasian steppes and deserts. In Kazakhstan they went extinct by the 1930s. Early reintroductions have reestablished the species in two protected areas, but the species has reclaimed <1% of their former range and remained absent from central Kazakhstan. To initiate restoration in this vast region, we captured and transported a first group of nine wild kulan to a large pre-release enclosure in the Torgai region in 2017, and two more in 2019. We used direct observations and post-release movement data of four kulan equipped with GPS-Iridium collars to document their adaptation process in a vast novel habitat without conspecifics. For comparison with movements in the source populations, we additionally equipped two kulan in Altyn Emel National Park and six in Barsa Kelmes State Nature Reserve. The nine transported kulan formed a cohesive group with very high movement correlation in the enclosure. After release, the group initially stayed tightly together but started to break up by mid-May and all kulan travelled independently by mid-August. With 48,680–136,953 km2, the 95% Autocorrelated Kernel Density Estimation ranges of the reintroduced kulan were huge and about 10–100 times larger than those in the source populations. The reintroduced mares never reconnected, there was no evidence of successful reproduction, and two of the four collared mares were killed by poachers and one died of natural causes. At least one stallion survived in the wild, but the fate of the other uncollared animals remains unclear. We speculate that the fission-fusion dynamics and low movement correlation of kulan societies and the need for migratory movements harbours the risk that animals released into a novel environment loose contact with each other. This risk is likely enhanced in steppe habitats where movement constraining factors are absent. Further kulan reintroductions to the steppes and deserts of central Kazakhstan should aim to release larger groups and build up the free-ranging population quickly to reach a critical mass, increasing the chance of kulan encountering conspecifics to successfully breed and increase their chances of survival.

Large area used by squirrel gliders in an urban area, uncovered using GPS telemetry.

The squirrel glider (Petaurus norfolcensis) is a threatened, gliding marsupial that persists in fragmented landscapes despite its restricted capacity to cross large gaps. As measures to maintain and/or restore suitable habitat depend on knowledge about the species' ecological requirements, we investigated the area used by squirrel gliders in an urban area near Newcastle, Australia. Using GPS telemetry data and the autocorrelated kernel density estimator, we estimated area used to average 10.8 ha and varied from 4.6 to 15 ha, which is equal to or greater than found in previous studies that spanned longer time periods. This has implications when identifying the minimum patch size necessary for ensuring the long‐term conservation of a squirrel glider population.

Movement, space-use and resource preferences of European golden jackals in human-dominated landscapes: insights from a telemetry study

During the last half-century, the distribution of golden jackals (Canis aureus) has rapidly increased throughout Europe. Today, golden jackals are thriving in human-dominated landscapes across Southeastern and Central Europe. Most studies on golden jackals have focused on large-scale distribution patterns; to date, little is known about the species’ fine-scale spatial ecology. In this study, we analyzed the movement behavior, space-use and resource selection of six golden jackals fitted with GPS-GSM collars in two study areas in Hungary and Serbia. Two of the jackals were a breeding pair. We found that home range size averaged 11.2 km2 (90% autocorrelated kernel density estimation), and was characterized by significant individual-level variability (range 1.3–32.5 km2). Golden jackal movements and resource selection were strongly influenced by circadian patterns: during the day, jackals travelled an average of 300 m every 6 h, and all monitored individuals selected for vegetation cover, often near edges. At night, golden jackals travelled significantly further (1 km 6 h−1), and were more likely to venture outside of cover into agricultural areas. Movement analysis of the breeding pair revealed that the male and female tended to remain in close proximity during the day, but ranged more independently at night. Altogether, our findings suggest that golden jackals’ ability to thrive in human-dominated landscapes rely on a fine spatio-temporal avoidance of humans.

Ctmmweb: A Graphical User Interface for Autocorrelation‐Informed Home Range Estimation

ABSTRACTEstimating animal home ranges is a primary purpose of collecting tracking data. Many widely used home range estimators, including conventional kernel density estimators, assume independently‐sampled data. In stark contrast, modern animal tracking datasets are almost always strongly autocorrelated. The incongruence between estimator assumptions and empirical reality often leads to systematically underestimated home ranges. Autocorrelated kernel density estimation (AKDE) directly models the observed autocorrelation structure of tracking data during home range estimation, and has been shown to perform accurately across a broad range of tracking datasets. However, compared to conventional estimators, AKDE requires additional modeling steps and has heretofore only been accessible via the command‐line ctmm R package. Here, we introduce ctmmweb, which provides a point‐and‐click graphical interface to ctmm and streamlines AKDE, its prerequisite autocorrelation modeling steps, and a number of additional movement analyses. We demonstrate ctmmweb's capabilities, including AKDE home range estimation and subsequent home range overlap analysis, on a dataset of four jaguars from the Brazilian Pantanal tracked between 2013 and 2015. We intend ctmmweb to open AKDE and related autocorrelation‐explicit analyses to a wider audience of wildlife and conservation professionals. © 2021 The Authors. Wildlife Society Bulletin published by Wiley Periodicals LLC on behalf of The Wildlife Society.

Sex‐, landscape‐ and climate‐dependent patterns of home‐range size – a macroscale study on an avian generalist predator

Animal home‐ranges are expressions of the biology and ecology of a species, and their size is often considered to be a proxy for habitat quality. Understanding the factors affecting variation in home‐range size may aid prediction of the impact of local or global environmental change on studied populations. To this end, we established an international collaborative programme to gather GPS telemetry data on the Lesser Spotted Eagle Clanga pomarina across a large part of its range. The breeding season home‐ranges of 58 individuals from Estonia, Lithuania, Poland, Hungary and Romania were estimated using autocorrelated kernel density estimation. Differences in home‐range size were analysed using linear mixed‐effects models incorporating global (latitude, longitude, climate) and local (habitat heterogeneity, land cover, topography, human disturbance) variables. Home‐range was significantly affected by habitat heterogeneity, vegetation cover and human disturbance, and also by climate, increasing with greater temperature seasonality. A quadratic relationship between home‐range and Shannon diversity index, found in males, suggests that Eagles use less space in the least and most diverse habitats. Home‐ranges were also smaller close to human settlements, but range size was positively correlated with human population density. The first result reflects the positive influence of agricultural management on prey availability, whereas the second reflects negative impacts of disturbance and loss of foraging space. Home‐ranges of male Eagles were relatively consistent in size and were more linked to environmental conditions compared with those of females. Female home‐ranges were significantly more variable in size and showed less distinctive patterns of relationship with the tested predictors. Sex‐dependent variation in home‐range may result from the different roles of males and females in breeding activities and territoriality limitations of males. The latter factor both limited and increased the home‐range size in different individuals.

Spatial patterns of the first groups of collared peccaries (Pecari tajacu) reintroduced in South America

The collared peccary (Pecari tajacu) is distributed from southwestern USA to northern Argentina; however, in some Argentinean localities it went extinct over 50 years ago. As part of a rewilding project, two peccary groups (one captive-bred family group and one mixed group formed by not genetically related individuals) were reintroduced to the Ibera National Park. Following the release, we monitored the movements of 16 individuals to obtain GPS locations every 100 min, for 6 months. We evaluated the individual’s spatial patterns by assessing site fidelity, home range changes, and habitat selection. Most members of the family group survived and established a home range whereas almost all members of the mixed group dispersed and did not survive. Using the Autocorrelated Kernel Density Estimator, the groups’ home range was 8.9 ± 1.7 km2 for the entire study period. In addition, individuals showed high fidelity to release site and a stable home range a few months after release. At larger scales (second order of selection), peccaries selected forested habitat and proximity to release site while at a smaller scale (third order of selection), they avoided grasslands. We highlight the importance of familiarity of individuals prior to release and provide recommendations for future reintroductions. Three years later, by September 2019, nine groups were established in the Ibera National Park and the abundance was over 45 individuals. This is the first post-release assessment of the movement patterns of collared peccaries in South America.