SYSTEMATIC NOTES (Part I)

Declines in populations of Palearctic migrants wintering in the Sahel of Africa have been linked to the impacts of climate change and habitat degradation in the region. Despite this, there is an almost complete lack of data on the density and distribution of Palearctic migrants wintering in the Sahel and whether they have the same habitat requirements as similar, resident Afrotropical species. We measured the density of five species of Palearctic warblers (Sylviidae) and 10 species of Afrotropical gleaning passerines (Sylviidae, Nectariniidae, Malaconotidae and Ploceidae) at 16 sites in the Sahel of northern Nigeria between October and April during two winters. Two species of Afrotropical gleaner (Hippolais pallida and Ploceus luteolus) showed seasonal variation in abundance, but this variation was unlikely to have decreased Afrotropical densities sufficiently to change the degree of competition experienced by Palearctic migrants. This observation, combined with a positive correlation between abundances of Afrotropical and Palearctic species, suggests that these two groups occur together and have similar spatial and temporal habitat requirements, and therefore possibly similar responses to habitat degradation. Sylvia communis appears to be the principal species utilising the region during spring migration, presumably for fattening prior to the trans-Saharan crossing, and is thus perhaps the most vulnerable species to habitat loss in the region.     

Site fidelity and seasonal changes in activity centre size of female pike Esox lucius in a small lake

The object of this study was to test site fidelity of female pike Esox lucius and to contrast the activity centre size in summer and winter in a 25 ha lake in north-eastern Germany using radio telemetry. Weekly 24 h tracking and two 96 h tracking exercises were conducted by boat from June to December 2005 and by walking on surface ice from January to February 2006. Positions of 12 E. lucius [total length ( L _T) = 450–733 mm] were recorded every 3 h within a 24 h tracking cycle. Site fidelity to individual summer activity centres was tested by translocating eight E. lucius away from their activity centre. All translocated E. lucius returned to their summer activity centre within 6 days, which provided evidence of site fidelity of E. lucius . There was no relation between E. lucius L _T or the translocation distance and return time to the activity centre after translocation. In winter, the activity centre size of E. lucius was significantly larger than in summer, but there was considerable overlap between the sites chosen in winter and those in summer. The seasonal variation in activity centre size possibly reflected changes in habitat structure ( e.g . collapse of structured vegetated habitats in winter) or prey fish distribution.     

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.     

固定核空间法和最小凸多边形法估计藏狐家域的比较

最小凸多边形法(MCP)和固定核空间法(FKE)是目前最常用的家域计算方法,但受空间自相关性、偏远位点等问题的影响,两种方法均存在明显的局限性。本文根据2006 年和2007 年在四川省石渠县和青海省都兰县的7 只藏狐352 个活动位点数据,分析MCP 和FKE 家域估计的效果和存在的问题。结果显示:(1)利用概率百分比≤95% 时,MCP 计算结果和FKE 没有显著差异;(2)极端点对高百分比(85% ～ 100% ) 下MCP影响显著,而FKE 对极端点影响控制较好;(3)FKE 家域外形复杂,计算结果受平滑度系数设置影响显著。因此,研究领域行为时,应同时使用FKE 和95% MCP 两种方法。当数据分布较理想时,FKE 能够给出更为准确的面积估计,而MCP 则因其通用性,使得研究数据与其他研究的结果更具可比性。
     

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.     

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 ).     

Effects of Telemetry Location Error on Space-Use Estimates Using a Fixed-Kernel Density Estimator

ABSTRACT Fixed-kernel density estimates using radiotelemetry locations are frequently used to quantify home ranges of animals, interactions, and resource selection. However, all telemetry data have location error and no studies have reported the effects of error on utilization distribution and area estimates using fixed-kernel density estimators. We simulated different home range sizes and shapes by mixing bivariate-normal distributions and then drawing random samples of various sizes from these distributions. We compared fixed-kernel density estimates with and without error to the true underlying distributions. The effects of telemetry error on fixed-kernel density estimates were related to sample size, distribution complexity, and ratio of median Circular Error Probable to home range size. We suggest a metric to assess the adequacy of the telemetry system being used to estimate an animal's space use before a study is undertaken. Telemetry location error is unlikely to significantly affect fixed-kernel density estimates for most wildlife telemetry studies with adequate sample sizes.     

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.     

An evaluation of behavior inferences from Bayesian state‐space models: A case study with the Pacific walrus

State‐space models offer researchers an objective approach to modeling complex animal location data sets, and state‐space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state‐space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two‐state discrete‐time continuous‐space Bayesian state‐space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state‐space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two‐state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state‐space models, and reconcile these parameters with the study species and its expected behaviors.     

Home range size of adult Indo‐Pacific bottlenose dolphins (Tursiops aduncus) in a coastal and estuarine system is habitat and sex‐specific

This study examined sex‐specific differences in home range size of adult Indo‐Pacific bottlenose dolphins off Bunbury, Western Australia. We applied a new kernel density estimation approach that accounted for physical barriers to movements. A Bayesian mixture model was developed to estimate a sex effect in home range size with latent group partitioning constrained by association data. A post hoc analysis investigated group partitioning relating to the proportion of time spent in open vs. sheltered waters. From 2007 to 2013, photographic‐identification data were collected along boat‐based systematic transect lines (n = 586). Analyses focused on adult dolphins of known sex (sighted ≥ 30 times; n = 22 males and 34 females). The 95% utilization distributions of males varied between 27 and 187 km² (; 94.8 ± 48.15) and for females between 20 and 133 km² (65.6 ± 30.9). The mixture model indicated a 99% probability that males had larger home ranges than females. Dolphins mostly sighted in open waters had larger home ranges than those in sheltered waters. Home ranges of dolphins sighted in sheltered waters overlapped with areas of highest human activity. We suggest that sex differences in home ranges are driven by male mating strategies, and home range size differences between habitats may be influenced by prey availability and predation risk.     

Negative effects of density on space use of small mammals differ with the phase of the masting‐induced population cycle

Home range size generally decreases with increasing population density, but testing how this relationship is influenced by other factors (e.g., food availability, kin structure) is a difficult task. We used spatially explicit capture–recapture models to examine how home range size varies with population density in the yellow‐necked mouse (Apodemus flavicollis). The relationship between population density and home range size was studied at two distinct phases of population fluctuations induced by beech (Fagus sylvatica) masting: post‐mast peak in abundance (first summer after mast, n = 2) and subsequent crash (second summer after mast, n = 2). We live‐trapped mice from June to September to avoid the confounding effects of autumn seedfall on home range size. In accordance with general predictions, we found that home range size was negatively associated with population density. However, after controlling for the effect of density, home ranges of mice were larger in post‐mast years than during the crash phase. This indicates a higher spatial overlap among neighbors in post‐mast years. We suggest that the increased spatial overlap is caused by negative density‐dependent dispersal that leads to high relatedness of individuals within population in the peak phase of the cycle.