Clarifying space use concepts in ecology: Range vs. occurrence distributions.

AimA central question in ecology has been that of why animal home ranges scale more steeply with body size than do metabolic rates. Yet, the generality of this notion has scarcely been tested in non‐model species like ectotherms, which have lower metabolic requirements than endotherms and which may, therefore, have different home range area requirements. Our aim was to examine how home range area scales with body size in snakes and to shed light on how other factors may shape home range area requirements in an understudied group of ectotherms.LocationGlobal.Time period1984–2018.Major taxon studiedSerpents.MethodsWe compiled and analysed a dataset of snake home ranges from the literature to evaluate how body size, sex, climate, foraging ecology, and biogeographic factors shape home range area requirements.ResultsHome range area scaled more gradually with body size in snakes (log‐linear slope of simple linear regression 0.72 with 95% confidence interval 0.48–0.96) than has been reported for mammals and birds, and instead more closely followed the scaling of metabolic rates with body size. Male snakes had larger home ranges than females and this difference increased as temperature increased at a study site, possibly from mate‐searching behaviour of males and greater ease reaching optimal body temperatures in warmer areas. Finally, home range area scaled more steeply for snakes that forage actively than for those that rely on sit‐and‐wait ambush foraging, a reflection of their foraging ecology.Main conclusionsOur results question the general notion that animal home range areas scale more steeply with body size than does metabolism. Key distinctions in the energy demands of endotherms and ectotherms and their responses to those demands give rise to differing home range area requirements. More attention to non‐model species is needed when creating and evaluating ecological theory.

We introduce a new technique for delineating animal home ranges that is relatively simple and intuitive: the potential path area (PPA) home range. PPA home ranges are based on existing theory from time geography, where an animal's movement is constrained by known locations in space–time (i.e.,ntelemetry points) and a measure of mobility (e.g., maximum velocity). Using the formulation we provide, PPA home ranges can be easily implemented in a Geographic Information System (GIS). The advantage of the PPA home range is the explicit consideration of temporal limitations on animal movement. In discussion, we identify the PPA home range as a stand‐alone measure of animal home range or as a way to augment existing home range techniques. Future developments are highlighted in the context of the usefulness of time geography for wildlife movement analysis. To facilitate the adoption of this technique we provide a tool for implementing this method. © 2011 The Wildlife Society.

The concept of an animal's home range has evolved over time, as have methods for estimating home-range size and shape. Recently, home-range estimation methods have focused on estimating an animal's utilization distribution (UD; i.e., the probability distribution defining the animal's use of space). We illustrate the importance of the utilization distribution in characterizing the degree of overlap between home ranges (e.g., when assessing site fidelity or space-use sharing among individuals). We compare several different statistics for their ability to accurately rank paired examples in terms of their degree of overlap. These examples illustrate limitations of indices commonly used to quantify home-range overlap and suggest that new overlap indices that are a function of the UD are likely to be more informative. We suggest 2 new statistics for measuring home-range overlap: (1) for a measure of space-use sharing, we suggest a generalization of Hurlbert's (1978) E/Euniform statistic, which we term the utilization distribution overlap index (UDOI), and (2) for a general measure of similarity between UD estimates, we suggest Bhattacharyya's affinity (BA; Bhattacharyya 1943). Using a short simulation study, we found that overlap indices can accurately rank pairs of UDs in terms of the extent of overlap, but estimates of overlap indices are likely to be biased. The extent of the bias depended on sample size and the degree of overlap (UDs with a high degree of overlap resulted in statistics that were more biased [low]), suggesting that comparisons across studies may be problematic. We illustrate the use of overlap indices to quantify the degree of similarity among UD estimates obtained using 2 different data collection methods (Global Positioning Systems [GPS] and very high frequency [VHF] radiotelemetry) for an adult female northern white-tailed deer (Odocoileus virginianus) in north-central Minnesota.

Analyzing wildlife tracking data frequently involves the estimation of home ranges. However, home range studies frequently lack important analytical steps, or only insufficiently report results. This makes it difficult for other researchers to evaluate, compare, and reproduce results from published home‐range studies. To facilitate more thorough home‐range analyses and reporting of analytical details, we developed a package for the statistical software package R that offers a user‐friendly platform for comprehensive home‐range analyses. Importantly, the package automatically generates a summary report that contains all analytical parameters used during analyses, and lists the main findings. To improve usability of the package, we also provide a graphical user interface that can be called from R without any programming skills. We currently implemented the calculation of site fidelity, time to statistical independence, minimum convex polygon, kernel density estimation, Brownian Bridge Movement Model, Jennrich–Turner Ellipses, local convex hull, estimation of home range asymptote, and area‐independent core‐area estimation. © 2015 The Wildlife Society.

Secondary exposure of wildlife to pesticides has been well documented, yet exposure is typically associated with agricultural or wildland‐urban interface areas. Wildlife in undeveloped areas is generally presumed free from risk. In 2009, a male fisher was found dead in the Sierra National Forest and subsequent necropsy revealed that the animal died of acute rodenticide poisoning. Follow‐up testing revealed that 85% of fisher carcasses recovered by two research projects in the previous three years tested positive for rodenticides. Concern arose that exposure could predispose an animal to mortality from other causes, and that the underlying role of toxicants would escape notice. Further investigation indicated that the most likely source was the numerous illegal marijuana cultivation sites currently found on public lands throughout the western United States. To determine whether the presence of cultivation sites predisposed fishers to mortality from other sources, we related survival rates to the presence and number of cultivation sites found within that animal's home range over the past 10 years. Likelihood of exposure was related to the presence of cultivation sites, and female fisher survival was influenced by the number of cultivation sites within its home range. We discuss the conservation implications of this unexpected relationship.

Movement ecology is an emerging discipline within ecology. Researchers addressing ba- sic and applied questions within the movement ecology framework often rely on animal biotelemetry data. Biotelemetry sensors can collect different types of data (from track- ing an animal’s position to measuring its heart rate). Rapid technological advances in satellite based navigation and tracking devices enable researchers to track animals with smaller devices, leading to steadily increasing sampling rates. To characterize space requirements of tracked animals, the concept of a home range is often used. This thesis starts with a general introduction (chapter 1), that connects the following chapters to the wider conceptual and analytical picture. The main parts of this thesis focus on the analysis of animal tracking data using home range analyses (chapters 2 through 5) and how to statistically test for the influence of (environmental) covariates on animal movement (chapter 6). Starting at the level of data management, chapter 2 highlights the need for a data model when working with tracking data. Next, a new package for program R is introduced that implements the previously discussed data model and provides functionality for the analysis of animal tracking data (chapter 3). Within the rhr (reproducible home ranges) package, the most commonly used estimators for home-range analyses are implemented. Further, functionalities for the automatic reporting of results and a graphical user interface are provided. After these technical aspects of tracking data, different methods for the estimation of home-range core areas (chapter 4) and home ranges as such (chapter 5) are discussed. Moving beyond home ranges, chapter 6 introduces a method to test which tests whether an animal’s movement track is influenced by environmental covariates. Finally, this thesis concludes that: (i) amounts of data (tracking data and auxiliary environmental data) will continue to increase in the future; (ii) tools to handle, manage, and analyze them are of great importance (chapter 2 and 3); (iii) researchers should not get lost in methods and lose sight of the wider biological picture, rather, they should use established as well as new methods to answer interesting biological questions (chapter 4 through 6).

Breeding home range movements of pre-fledged brolga chicks, Antigone rubicunda (Gruidae) in Victoria, Australia – Implications for wind farm planning and conservation

Home ranges provide a conceptual and quantitative representation of animal-habitat associations over time. Methods to estimate home ranges have swiftly progressed by dynamically accounting for various sources of bias. Across that period of growth, one potentially influential source of bias has yet to be robustly scrutinized. Animals inhabiting the terrestrial spatial domain make movement decisions in environments with variable landscape complexity. Despite that reality, home range estimation methods tend to be informed by two-dimensional (2D) data (i.e., x and y coordinates), which analytically presume that these landscapes are flat. This analytical tendency potentially misrepresents the configuration and size of animal home range estimates. To examine the prevalence of this bias, we reviewed literature of terrestrial animal home range estimation published between 2000 and 2019. We recorded the proportion of studies that (1) recognized and (2) incorporated landscape complexity. Over 22.0% (n = 271) of the 1,203 studies recognized the importance of landscape complexity for animal movement. Interestingly, just 0.7% (n = 8) incorporated landscape complexity into the home range estimation. We infer then that landscape complexity represents an important source of bias resulting in the underestimation of terrestrial animal home range size. Given the influence of landscape complexity on terrestrial animal decision making, energetics, and fitness, our analysis highlights an important gap in current home range methodologies. We discuss the implications of our analysis for biased understandings of terrestrial animal spatial ecology with subsequent impacts on management and conservation practices built upon these estimates.

Home range estimators are a critical component for understanding animal spatial ecology. The choice of home range estimator in spatial ecology studies can significantly influence management and conservation actions, as different methods lead to vastly different interpretations of movement patterns, habitat selection, as well as home range requirements. Reptile studies in particular have struggled to reach a consensus on the appropriate home range estimators to use, and species with cryptic behavior make home range assessment difficult. We applied dynamic Brownian Bridge Movement Models (dBBMMs) to radio-telemetry data from Ophiophagus hannah, a wide-ranging snake species. We used two focal individuals at different life stages (one juvenile male and one adult male) and sought to identify whether the method would accurately represent both their home range and movement patterns. To assess the suitability of dBBMMs, we compared this novel method with traditional home range estimation methods: minimum convex polygons (MCP) and Kernel density estimators (KDE). Both KDE and MCP incorporated higher levels of Type I and Type II errors, which would lead to biases in our understanding of this species space-use and habitat selection. Although these methods identified some general spatial-temporal patterns, dBBMMs were more efficient at detecting movement corridors and accurately representing long-term shelters sites, showing an improvement over methods traditionally favored in reptile studies. The additional flexibility of the dBBMM approach in providing insight into movement patterns can help further improve conservation and management actions. Additionally, our results suggest that dBBMMs may be more widely applicable in studies that rely on VHF telemetry and not limited to studies employing GPS tags.

By studying animal movements, researchers can gain insight into many of the ecological characteristics and processes important for understanding population-level dynamics. We developed a Brownian bridge movement model (BBMM) for estimating the expected movement path of an animal, using discrete location data obtained at relatively short time intervals. The BBMM is based on the properties of a conditional random walk between successive pairs of locations, dependent on the time between locations, the distance between locations, and the Brownian motion variance that is related to the animal's mobility. We describe two critical developments that enable widespread use of the BBMM, including a derivation of the model when location data are measured with error and a maximum likelihood approach for estimating the Brownian motion variance. After the BBMM is fitted to location data, an estimate of the animal's probability of occurrence can be generated for an area during the time of observation. To illustrate potential applications, we provide three examples: estimating animal home ranges, estimating animal migration routes, and evaluating the influence of fine-scale resource selection on animal movement patterns.

Large carnivores are amongst the most susceptible species to human activities, and human-modified environments pose a threat to carnivore conservation. Wolves (Canis lupus Linnaeus, 1758) in the central Apennines, Italy, have coexisted with humans since historic times and represent a good case study to assess their spatiotemporal response to anthropogenic factors. From 2008 to 2010, we investigated the spatial behavior of wolves (seven wolves in five packs and six floaters) in the Abruzzo Lazio and Molise National Park. Orographically corrected annual home ranges of resident wolf packs, estimated through the Brownian bridge movement model, averaged 104 ± 24 km2 (mean ± SD), whereas floaters used two- to fourfold larger areas (293.8–408.7 km2). We did not detect any seasonal effect on home range size, but home ranges were larger during the night and in areas of greater road density, especially during summer. By estimating core areas through an individual-based approach, we also revealed a habitat-mediated response to human presence and activity, as resident wolves preferentially established core areas at greater elevation and in the more forested and inaccessible portions of the home range.

Summer habitat use and movements of late juvenile European flounder (Platichthys flesus) in tidal freshwaters: Results from an acoustic telemetry study

Knowing the influence of intrinsic and environmental traits on animals’ movement is a central interest of ecology and can aid to enhance management decisions. The giant anteater (Myrmecophaga tridactyla) is a vulnerable mammal that presents low capacity for physiological thermoregulation and uses forests as thermal shelters. Here, we aim to provide reliable estimates of giant anteaters’ movement patterns and home range size, as well as untangle the role of intrinsic and environmental drivers on their movement. We GPS-tracked 19 giant anteaters in Brazilian savannah. We used a continuous-time movement model to estimate their movement patterns (described by home range crossing time, daily distance moved and directionality), and provide an autocorrelated kernel density estimate of home range size. Then, we used mixed structural equations to integratively model the effects of sex, body mass and proportion of forest cover on movement patterns and home range size, considering the complex net of interactions between these variables. Male giant anteaters presented more intensive space use and larger home range than females with similar body mass, as it is expected in polygynous social mating systems. Males and females increased home range size with increasing body mass, but the allometric scaling of intensity of space use was negative for males and positive for females, indicating different strategies in search for resources. With decreasing proportion of forest cover inside their home ranges, and, consequently, decreasing thermal quality of their habitat, giant anteaters increased home range size, possibly to maximize the chances of accessing thermal shelters. As frequency and intensity of extreme weather events and deforestation are increasing, effective management efforts need to consider the role of forests as an important thermal resource driving spatial requirements of this species. We highlight that both intrinsic and environmental drivers of animal movement should be integrated to better guide management strategies.

Avian functional traits are widely studied in ecology and evolutionary biology, and these traits are often quantified from museum study skins. Across such studies, the sex ratio of specimens is highly variable or often unreported, despite knowledge that many species are sexually dimorphic in size and shape and that museum collections are sex-biased toward male specimens. Our study explicitly quantified whether sex-biased specimen sampling influences the answers to primary research questions about avian functional trait diversity and evolution. We focused on the songbird clade Emberizoidea, using an existing phylogenetic tree for this clade and a large male-specific dataset for 10 functional traits. After inter-measurer calibration, we collected a matching female-specific dataset for 408 species to assess the degree of size and shape dimorphism across the clade. We found that emberizoids are significantly dimorphic in both size and shape. We then quantified 3 metrics of functional trait diversity and found that estimated diversity differed significantly between male, female, and pooled datasets for all metrics. We found that all traits have strong significant phylogenetic signal that was of comparable magnitude despite differing significantly between sex-biased samples. We also modeled branch-specific rates of trait evolution and found these inferences to be more nuanced. Estimated rate shifts were largely congruent between sex-biased datasets, but branch-specific rates of size evolution were strongly impacted by both the sex ratio of the dataset and the choice of tool that quantified them. Thus, we found that sex-biased sampling can influence the answers to primary research questions in ecology and evolutionary biology. These issues may be avoided by sampling sex ratios consistently across taxa in these studies. Further, we recommend that these ratios should be clearly reported, and that researchers sample specimens in a way that makes sense given their questions and the biology of the organisms being studied.

Space use and movement are fundamental aspects of organisms' ecology, mirroring individual fitness, behavior, and life‐history strategies. These mechanisms are shaped by environmental heterogeneity, which often makes it difficult to understand these dynamics. Subterranean habitats are simplified and understudied environments, potentially ideal for evaluating the fine‐scale spatial ecology of organisms. Spatial capture–recapture (SCR) methods allow us to investigate animal space use and movement, including spatially explicit observation data on individuals, to assess the relationship between population dynamics and landscape ecology. In this context, we assessed individual interactions, movement ecology, and activity patterns of a subterranean population of the cave salamander Speleomantes strinatii , applying SCR modeling to a photographic capture–recapture dataset of 104 identified individuals (43 males, 35 females and 26 subadults). Analysis of overlap indices showed that the proportion of males' home range (HR) was more covered by females' HR than vice versa ( U = 25, p = 0.038). During the monitoring, females traveled longer distances in less time than males (0.60 vs. 0.22 m/day). Finally, salamanders tended to be more active during summer periods, showing a preference for the inner sectors of the cave and rougher cave walls. Combining the analysis of spatially explicit capture history (overlap and movement estimates) and SCR (activity pattern, sex‐specific density and space use), we enlightened new features and confirmed previous knowledge of the spatial ecology of S. strinatii . Our study demonstrates how structured capture–recapture data can be used to infer individual interactions and movement in low‐complexity habitats and is open to the application of SCR methods in more complex environments for revealing finer‐scale ecological variation with important conservation implications.