Effects of Point Pattern Shape on Home-Range Estimates

Abstract: Home-range estimators are commonly tested with simulated animal locational data in the laboratory before the estimators are used in practice. Although kernel density estimation (KDE) has performed well as a home-range estimator for simulated data, several recent studies have reported its poor performance when used with data collected in the field. This difference may be because KDE and other home-range estimators are generally tested with simulated point locations that follow known statistical distributions, such as bivariate normal mixtures, which may not represent well the space-use patterns of all wildlife species. We used simulated animal locational data of 5 point pattern shapes that represent a range of wildlife utilization distributions to test 4 methods of home-range estimation: 1) KDE with reference bandwidths, 2) KDE with least-squares cross-validation, 3) KDE with plug-in bandwidths, and 4) minimum convex polygon (MCP). For the point patterns we simulated, MCP tended to produce more accurate area estimates than KDE methods. However, MCP estimates were markedly unstable, with bias varying widely with both sample size and point pattern shape. The KDE methods performed best for concave distributions, which are similar to bivariate normal mixtures, but still overestimated home ranges by about 40–50% even in the best cases. For convex, linear, perforated, and disjoint point patterns, KDE methods overestimated home-range sizes by 50–300%, depending on sample size and method of bandwidth selection. These results indicate that KDE does not produce home-range estimates that are as accurate as the literature suggests, and we recommend exploring other techniques of home-range estimation.     

A scaled line-based kernel density estimator for the retrieval of utilization distributions and home ranges from GPS movement tracks

Utilization distributions (UDs) can be used to describe the intensity with which an animal or human has used a certain geographical location. Within the domain of wildlife ecology, a density distribution model represents one way to describe an animals' home range. Several methods have been developed to derive UDs, and subsequently home ranges. Most of these methods, e.g. kernel density estimation (KDE), and local convex hull methods, have been developed with point-based datasets in mind, and do not utilize additional information that comes with GPS-based tracking data (e.g., temporal information). To employ such additional information we extend the point-based KDE approach to work with sequential GPS-point tracks, the outcome of which is a line-based KDE. We first describe the design criteria for the line-KDE algorithm. Then we introduce the basic modeling approach and its refinement through the introduction of a scaling function. This scaling function modifies the utilization distribution so that a bone-like probability distribution for a single GPS track segment is obtained. Finally we compare the estimated utilization distributions and home ranges for two datasets derived using our line-KDE approach with those obtained using the point-KDE and Brownian Bridge (BB) approaches. Advantages of the line-based KDE by design are (i) a better representation of utilization density near GPS points when compared against the BB approach, and (ii) the ability to model and retain movement corridors when compared against point-KDE.     

Home-range size and movement patterns of Hooded Vultures Necrosyrtes monachus in southern Africa

Hooded Vulture Necrosyrtes monachus populations have declined dramatically in recent years, but we know little about their ecology. We radio-tagged four vultures in northern Botswana to gather data on animal movement and home-range patterns. Hooded Vultures were primarily sedentary at night. Hooded Vultures moved similar distances and speeds during the wet and dry season, and travelled over similar home ranges as measured using minimum convex polygons (MCP), but used much smaller core areas during the dry (breeding) season. We found significant differences in mean distances and speeds moved among different birds, and when comparing day to night, but not between the wet (non-breeding) and dry (breeding) season or by year. All of the variables we tested, including individual vulture differences, season, year and number of fixes, significantly influenced 95% MCP and kernel density estimate (KDE) home-range sizes. Hooded Vultures used significantly smaller KDE home-range sizes during the dry (breeding season) than in the wet (non-breeding) season. Hooded Vultures travelled smaller daily distances over smaller home ranges than most other vulture species for which data exist.     

A local nearest-neighbor convex-hull construction of home ranges and utilization distributions

We describe a new method for estimating the area of home ranges and constructing utilization distributions (UDs) from spatial data. We compare our method with bivariate kernel and α-hull methods, using both randomly distributed and highly aggregated data to test the accuracy of area estimates and UD isopleth construction. The data variously contain holes, corners, and corridors linking high use areas. Our method is based on taking the union of the minimum convex polygons (MCP) associated with the k−1 nearest neighbors of each point in the data and, as such, has one free parameter k. We propose a "minimum spurious hole covering" (MSHC) rule for selecting k and interpret its application in terms of type I and type II statistical errors. Our MSHC rule provides estimates within 12% of true area values for all 5 data sets, while kernel methods are worse in all cases: in one case overestimating area by a factor of 10 and in another case underestimating area by a factor of 50. Our method also constructs much better estimates for the density isopleths of the UDs than kernel methods. The α-hull method does not lead directly to the construction of isopleths and also does not always include all points in the constructed home range. Finally we demonstrate that kernel methods, unlike our method and the α-hull method, does not converges to the true area represented by the data as the number of data points increase.     

Incorporating Movement Behavior and Barriers to Improve Kernel Home Range Space Use Estimates

Abstract: Kernel-based utilization distribution (UD) estimates are powerful tools to investigate home range space use and resource selection in many vertebrate species. By ignoring local movement information provided by the serial correlation between successive locations and the constraints to movement imposed by obvious boundaries, the classical kernel method results in loosely estimated UDs that tend to overflow into never-visited areas and eventually in possibly biased estimates of space use and habitat selection. We improved biological relevance of kernel home range space use estimates by incorporating both movement (and activity) information and boundary constraints.     

An empirically based estimate of home range

The minimum-convex-polygon method for estimating home-range area, in which the outermost points are connected in a particular way, is extremely sensitive to sample size. Existing methods for estimating home-range area that correct for sample size fail to encompass all the important kinds of biological variation in the home-range utilization. (The home-range utilization describes the relative degree to which different units of space are frequented by an animal.) Although previous methods have assumed specific unimodal distributions, such as the bivariate normal, home-range utilizations may resemble funnels or pies as well as hills. A regression method is introduced that uses data from well-sampled individuals whose true home ranges are assumed approximately known to predict home-range areas for less well-sampled individuals. Appendix 5 summarizes this method. Sizes of home ranges estimated by the regression method are half or less than sizes estimated by previous methods in which utilization distributions are assumed to be all of a particular statistical type.     

Evaluation of Root-n Bandwidth Selectors for Kernel Density Estimation

ABSTRACT The kernel density estimator is used commonly for estimating animal utilization distributions from location data. This technique requires estimation of a bandwidth, for which ecologists often use least-squares cross-validation (LSCV). However, LSCV has large variance and a tendency to under-smooth data, and it fails to generate a bandwidth estimate in some situations. We compared performance of 2 new bandwidth estimators (root-n) versus that of LSCV using simulated data and location data from sharp-shinned hawks (Accipter striatus) and red wolves (Canis rufus). With simulated data containing no repeat locations, LSCV often produced a better fit between estimated and true utilization distributions than did root-n estimators on a case-by-case basis. On average, LSCV also provided lower positive relative error in home-range areas with small sample sizes of simulated data. However, root-n estimators tended to produce a better fit than LSCV on average because of extremely poor estimates generated on occasion by LSCV. Furthermore, the relative performance of LSCV decreased substantially as the number of repeat locations in the data increased. Root-n estimators also generally provided a better fit between utilization distributions generated from subsamples of hawk data and the local densities of locations from the full data sets. Least-squares cross-validation generated more unrealistically disjointed estimates of home ranges using real location data from red wolf packs. Most importantly, LSCV failed to generate home-range estimates for >20% of red wolf packs due to presence of repeat locations. We conclude that root-n estimators are superior to LSCV for larger data sets with repeat locations or other extreme clumping of data. In contrast, LSCV may be superior where the primary interest is in generating animal home ranges (rather than the utilization distribution) and data sets are small with limited clumping of locations.     

Evaluating home range techniques: use of Global Positioning System (GPS) collar data from chacma baboons

Global Positioning System (GPS) collars have revolutionized the field of spatial ecology, but to date, few primate studies have used them. We fitted a free-ranging, semi-habituated, juvenile male chacma baboon (Papio hamadryas ursinus) with an automatic self-releasing GPS collar and tracked his movements for 359?days. The collar captured 4254 fixes out of 5719 programmed opportunities, a 74.4?% acquisition rate, suggesting that the collar effectively tracked this baboon in a variety of habitat types. Of the data points captured, 73.7?% were three-dimensional fixes, and of these fixes, 66.9?% were highly accurate, having a dilution of precision of less than four. We calculated home range using three protocols with three estimation methods: minimum convex polygon, fixed kernel-density estimation (KDE), and fixed r local convex hull. Using all data points and the 95?% contour, these methods created home range estimations ranging from 10.8 to 23.1?km(2) for this baboon troop. Our results indicate that the KDE output using all data locations most accurately represented our data set, as it created a continuous home range boundary that excluded unused areas and outlying, potentially exploratory data points while including all seven sleeping sites and a movement corridor. However, home range estimations generated from KDE varied from 15.4 to 18.8?km(2) depending on the smoothing parameter used. Our results demonstrated that the ad hoc smoothing parameter selection technique was a better method for our data set than either the least squares cross-validation or biased cross-validation techniques. Our results demonstrate the need for primatologists to develop a standardized reporting method which documents the tool, screening protocol, and smoothing parameter used in the creation of home range estimations in order to make comparisons that are meaningful.     

Effects of sampling regime on the mean and variance of home range size estimates

1. Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.     

Comparing Global Positioning System and Very High Frequency Telemetry Home Ranges of White-Tailed Deer

ABSTRACT Use of Global Positioning System (GPS) collars on free-ranging ungulates overcomes many limitations of conventional very high frequency (VHF) telemetry and offers a practical means of studying space use and home range estimation. To better understand winter home ranges of white-tailed deer (Odocoileus virginianus), we evaluated GPS collar performance, and we compared GPS- and VHF-derived diurnal home ranges (for the same animals) and GPS-derived home range estimates for diurnal and nocturnal locations. Overall, the mean fix success rate of our GPS collars was 85% (range = 14–99%). Kernel density estimates of home range (using the 95% probability contour) derived from GPS and VHF locations were generally similar, as were GPS-derived diurnal and nocturnal home ranges. Overlap indices between GPS and VHF utilization distributions (UDs) ranged from 0.49 to 0.78 for the volume of intersection (VI) index and from 0.67 to 0.94 for Bhattacharyya's affinity (BA); overlap indices for GPS-diurnal and nocturnal UDs ranged from 0.29 to 0.81 for VI and from 0.56 to 0.94 for BA. Despite similarities of home ranges estimated from GPS versus VHF locations and GPS-diurnal versus nocturnal locations, our data also indicate that differences may have important implications for studies focused on deer use of space, habitat, and resources at a finer scale.     

Home range size estimates of red deer in Germany: environmental,individual and methodological correlates

Home range size (HRS) is the fundamental measure of space use by animals. Despite the importance of the home range concept, there is no consensus on how to estimate the HRS of animals. Assessments of the performance of commonly applied HRS estimators have largely been based on simulated data or on location data of few sample individuals occupying one study area. To empirically evaluate the impact of supplementary feeding, habitat composition, red deer sex, and estimation method (minimum convex polygon (MCP), kernel density estimator (KDE) and α-local convex hull (α-LoCoH)) on HRS, we analysed the data of 183 annual red deer home ranges using a mixed modelling approach. Red deer HRSs were smallest in areas with substantial supplementary feeding, intermediate in areas with closed forest cover but no supplementary feeding, and largest in fragmented landscapes where supplementary feeding rarely occurs. Consistently, male HRSs were larger than female HRSs. While MCP- and KDE-HRS estimates were roughly similar, estimates from the α-LoCoH method were substantially smaller than those of MCP and KDE. Analyses of 342 seasonal HRS largely reflected patterns of annual HRS. However, seasonal HRS differed between seasons and red deer sex. In areas with no or little feeding, red deer adjusted HRS seasonally, whereas red deer supplied with supplementary food during winter did not alter their HRS seasonally. Our study suggests that supplementary feeding and habitat configuration strongly affect the spatial ecology of red deer; this might have considerable sanitary and ecological implications. We suggest that sex differences in annual space use extent are proportional along a resource gradient but are mediated by seasons. Finally, method-related variation in space use studies of animals needs to be considered more cautiously.     

Home-range use by coyotes in Idaho

Radio-collared coyotes (Canis latrans) were relocated every 15 min during continuous 24-h sampling periods. The data were used to estimate patterns of home-range use by coyotes. Utilization of the the home range was found to vary spatially and behaviourally. Spatial use was determined by relative amounts of time coyotes spent and amounts of distance they travelled within each are of their home ranges. Behavioural use was based on identification of three types of movement patterns that werew postulated to represent three general kinds of behaviour: (1) resting behaviour, (2) hunting or investigative behavour, and (3) ranging or traveling behaviour. Spatial and behavioural uses of the home range area were found to be interrelated; core areas in which animals spent most of their time were also used primarily for resting or hunting. In areas in which animals spent little time, coyotes exhibited primarily ranging behaviour. Use patterns were postulated to be the result of coyotes' selection of areas due to unique vegetal, faunal, or physiogfaphic characteristics. Temporal variatrions in home-range use were found and were postulated to result from seasonal and diel changes in coyote behaviour due to the annual reproductive cycle, the seasonal and diel cycle of temperature, possible cycles in prey behaviour.     

Evaluating distributional shifts in home range estimates

A variety of methods are commonly used to quantify animal home ranges using location data acquired with telemetry. High‐volume location data from global positioning system (GPS) technology provide researchers the opportunity to identify various intensities of use within home ranges, typically quantified through utilization distributions (UDs). However, the wide range of variability evident within UDs constructed with modern home range estimators is often overlooked or ignored during home range comparisons, and challenges may arise when summarizing distributional shifts among multiple UDs. We describe an approach to gain additional insight into home range changes by comparing UDs across isopleths and summarizing comparisons into meaningful results. To demonstrate the efficacy of this approach, we used GPS location data from 16 bighorn sheep (Ovis canadensis) to identify distributional changes before and after habitat alterations, and we discuss advantages in its application when comparing home range size, overlap, and joint‐space use. We found a consistent increase in bighorn sheep home range size when measured across home range levels, but that home range overlap and similarity values decreased when examined at increasing core levels. Our results highlight the benefit of conducting multiscale assessments when comparing distributions, and we encourage researchers to expand comparative home range analyses to gain a more comprehensive evaluation of distributional changes and to evaluate comparisons across home range levels.     

Memory keeps you at home: a mechanistic model for home range emergence

Despite its central place in animal ecology no general mechanistic movement model with an emergent home-range pattern has yet been proposed. Random walk models, which are commonly used to model animal movement, show diffusion instead of a bounded home range and therefore require special modifications. Current approaches for mechanistic modeling of home ranges apply only to a limited set of taxa, namely territorial animals and/or central place foragers. In this paper we present a more general mechanistic movement model based on a biased correlated random walk, which shows the potential for home-range behavior. The model is based on an animal tracking a dynamic resource landscape, using a biologically plausible two-part memory system, i.e. a reference- and a working-memory. Our results show that by adding these memory processes the random walker produces home-range behavior as it gains experience, which also leads to more efficient resource use. Interestingly, home-range patterns, which we assessed based on home-range overlap and increase in area covered with time, require the combined action of both memory components to emerge. Our model has the potential to predict home-range size and can be used for comparative analysis of the mechanisms shaping home-range patterns.     

Home‐range size of an Andean bird: Assessing the role of physical condition

Because space‐use patterns are a key aspect of the ecology and distribution of species, identifying factors associated with variation in size of territories and home ranges has been central to studies on population ecology. Space use might vary in response to extrinsic factors like habitat quality and to intrinsic factors like physical condition and individual aggressiveness. However, the role of these factors has been poorly documented in the tropics, particularly in high‐elevation bird species. We report the home‐range size of a Neotropical Andean bird, the gray‐browed brush finch (Arremon assimilis), and evaluate the role of physical condition in explaining variation in home‐range size among individuals. We performed spot mapping to estimate the home ranges of 14 territorial males in Bogotá, Colombia, using minimum convex polygons (MCP) and 95% kernel density estimators (KDE). The mean home‐range size estimated for the 100% MCP was 0.522 ± 0.305 ha (range = 0.15–1.18 ha), whereas the 95% KDE estimation was 0.504 ± 0.471 ha (range = 0.13–1.88). We calculated the real mass index of each bird as a proxy of physical condition to assess whether individuals in better physical condition had larger home ranges. Because we found no relation between our estimations of physical condition and home‐range size, we conclude that space use in this species might depend more on ecological factors such as habitat quality or neighbor density than on individual traits. Abstract in French is available with online material.     

Use of space and home range characteristics of Lepilemur mittermeieri,an endangered sportive lemur endemic to the Ampasindava peninsula,north‐west Madagascar

Lepilemur mittermeieri, a little‐studied sportive lemur of north‐west Madagascar, endemic to the Ampasindava Peninsula, faces habitat loss through forest degradation and rapid fragmentation. Understanding its habitat requirement is the first step toward preservation of this threatened forest‐dependent species. In this study, we gathered data on the use of space and home range characteristics of L. mittermeieri. We studied individuals from early March to the end of June 2015 and 2016, in three sites of the Ampasindava peninsula. We radio‐tracked 15 individuals to obtain detailed information on the size and location of home ranges (around 450 hr of tracking). Direct observation and morphometric measurements provided additional data sets. Both kernel density estimation (KDE) and minimum convex polygon (MCP) methods yielded similar home range sizes (an average of 2.01 ha with KDE method and 1.96 ha with MCP method). We did not find differences in home range size between males and females, with respect to forest type or proximity to the forest edge. Home ranges overlapped and individuals showed low levels of territoriality. We highlighted a sexually‐dimorphic trait: males have longer upper canine than females. Our results constitute the first set of ecological information on Lepilemur mittermeieri and could be the basis for a conservation strategy for this endangered species with a very small distribution area.     

DISPERSAL BY YEARLING MALE WHITE-TAILED DEER AND IMPLICATIONS FOR MANAGEMENT

Abstract: The scale at which populations use the landscape influences ecological processes and management decisions. Dispersal and home-range size define the scale of landscape use for many large-mammal species. We measured dispersal and home-range size of yearling male white-tailed deer (Odocoileus virginianus) in southern Texas, and compared our results to values from the literature to understand the implications of dispersal in management of deer populations. We used radiotelemetry to monitor 22 yearling deer on 1 study site from October 1998 to October 1999, and 27 yearling deer on a second study site from October 1999 to October 2000. On the 2 study sites, 68% and 44% of yearling deer established new areas of use 4.4 ± 1.0 km and 8.2 ± 4.3 km, respectively, from the center of their autumn home range. Yearling males with spike antlers (2 points) were less likely to disperse than yearlings with fork antlers (>2 points) on 1 study site. Computer simulation showed that the scale at which deer use the landscape is large compared to property sizes in southern Texas and probably in other areas of the white-tailed deer's range. Differences in scale between land ownership patterns and landscape use by deer may result in a failure to meet management objectives and conflict among managers. High harvest rates for male deer occur in part because deer movements are large relative to property size, creating a “tragedy of the commons.” Cooperative management groups are beneficial if all landowners in an area agree on management objectives. Otherwise, deer-proof fences often are erected to reduce conflicts among property owners.     

HomeRange: A global database of mammalian home ranges

Motivation

Home range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home-range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange, a global database with 75,611 home-range values across 960 different species of mammals, including terrestrial, aquatic and aerial species.

Main types of variables contained

The dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home-range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit.

Spatial location and grain

The collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°.

Time period and grain

The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported.

Major taxa and level of measurement

Mammalian species from 24 of the 27 different taxonomic orders. Home-range estimates range from individual-level values to population-level averages.

Software format

Data are supplied as a comma-delimited text file (.csv) and can be loaded directly into R using the “HomeRange” R package ( https://github.com/SHoeks/HomeRange ).     

蜂桶寨自然保护区小熊猫巢域初步研究

2002年5~11月,在蜂桶寨自然保护区利用无线电遥测技术对6只小熊猫的巢域利用进行了初步研究。结果表明,6只戴颈圈个体M1、M2、M3、F1、F2、F3的巢域面积分别为330·26hm~2、135·18hm~2、190·67hm~2、98·23hm~2、141·60hm~2、204·80hm~2;雄性个体平均巢域面积为218·70hm~2,雌性个体为148·21hm~2。小熊猫个体间巢域重叠普遍,平均重叠率达25·33%,其中雄性个体之间为26·00%,雌性个体之间为23·67%,两性个体之间为25·67%。可能受人为干扰的影响,M1在6只监测个体中巢域面积、日均移动距离均为最大。     

Use of space and habitat selection by roe deer Capreolus capreolus in a Mediterranean coastal area: how does woods landscape affect home range?

The home-range dynamics and habitat selection of nine roe deer were studied from March 1994 to August 1994 in the Maremma Natural Park along the Tyrrhenian coast of Italy. The habitat was highly fragmented, with open agricultural fields prevailing in the study area (57%); the climate was Mediterranean. Data on spatial behaviour were collected by radio-tracking techniques. Habitat selection and structure were investigated by compositional and landscape analysis, both within the study area and within the home ranges. Animals of our sample showed spatial-use patterns varying from stationary to roaming. Stationary individuals used small home ranges while roaming ones moved, especially during the reproductive period in July and August. The percentage and structure of woodlands influenced the size of home ranges and the behaviour of males: stationary males used large amounts of woodlands within their home ranges and showed a territorial behaviour whereas males that used a high percentage of fields showed wider home ranges even during the territorial period. Females seemed to be less influenced by the presence and patch-structure of woodland within their home range. Landscape structure and habitat composition seemed to be important factors influencing the spatial behaviour of this roe deer population.