Mechanistic home range models capture spatial patterns and dynamics of coyote territories in Yellowstone

Patterns of space-use by individuals are fundamental to the ecology of animal populations influencing their social organization, mating systems, demography and the spatial distribution of prey and competitors. To date, the principal method used to analyse the underlying determinants of animal home range patterns has been resource selection analysis (RSA), a spatially implicit approach that examines the relative frequencies of animal relocations in relation to landscape attributes. In this analysis, we adopt an alternative approach, using a series of mechanistic home range models to analyse observed patterns of territorial space-use by coyote packs in the heterogeneous landscape of Yellowstone National Park. Unlike RSAs, mechanistic home range models are derived from underlying correlated random walk models of individual movement behaviour, and yield spatially explicit predictions for patterns of space-use by individuals. As we show here, mechanistic home range models can be used to determine the underlying determinants of animal home range patterns, incorporating both movement responses to underlying landscape heterogeneities and the effects of behavioural interactions between individuals. Our analysis indicates that the spatial arrangement of coyote territories in Yellowstone is determined by the spatial distribution of prey resources and an avoidance response to the presence of neighbouring packs. We then show how the fitted mechanistic home range model can be used to correctly predict observed shifts in the patterns of coyote space-use in response to perturbation.     

Estimating utilization distributions with kernel versus local convex hull methods

Estimates of utilization distributions (UDs) are used in analyses of home-range area, habitat and resource selection, and social interactions. We simulated data from 12 parent UDs, representing 3 series of increasingly intense space-use patterns (clustering of points around a home site, restriction of locations to a network of nodes and corridors, and dominance of a central hole in the UD) and compared the ability of kernel density estimation (KDE) and local convex hull (LCH) construction to reconstruct known UDs from samples of 10, 50, 250, and 1,000 location points. For KDE, we considered 4 bandwidth selectors: the reference bandwidth, least-squares cross-validation (LSCV), direct plug-in (DPI), and solve-the-equation (STE). For the sample sizes and UD patterns tested here, KDE achieved significantly higher volume-of-intersection (VI) scores with known parent UDs than did LCH; KDE also provided less biased home-range area estimates under many conditions. However, LCH minimized the UD volume that occurred outside the true home range boundary (V_out). Among the KDE bandwidth estimators, relative performance depended on the type and intensity of space use patterns, sample size, and the metric used to evaluate performance. Biologists should use KDE for UD and home range estimation within a probabilistic context, unless their objective is to exclude potentially unused areas by defining the area delimited by data. © 2011 The Wildlife Society.     

Correlation and studies of habitat selection: problem,red herring or opportunity?

With the advent of new technologies, animal locations are being collected at ever finer spatio-temporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, ‘two-stage’ approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use–availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use fine-scale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use–availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data.     

Invasive rat space use on tropical islands: Implications for bait broadcast

Invasive rats on oceanic islands impact a large number of native species. Control programmes, and in many cases complete eradication, are used to alleviate these impacts. Basic data on rodent biology facilitate the design of control or eradication programmes, and is particularly required for programmes on tropical islands where such data are missing. Here we test for interactive effects of habitat and season that may alter black rat (Rattus rattus) space use dynamics and inform rodent management on two tropical islands. Five years of summer and winter trapping data were analysed using spatially explicit capture–recapture to calculate rat space-use and overlap, coupled with spool and line experiments ground-truthing microhabitat use. Variation in individual rat space use is primarily driven by sex and bottom-up trophic effects of seasonal rainfall on food resources, but is altered by island-specific contexts. In the absence of other introduced mammals, rats tend to have stable range overlap throughout the year but home range sizes fluctuate seasonally with rat density. The presence of other introduced mammals causes predictable greater seasonal fluctuations in rat space-use, putatively a behavioural adjustment to feral cats (Felis catus) diet-switching to rats from seasonal influxes of their alternative seabird prey. We identify winter as the recommended treatment period on both islands and discuss bait broadcast strategies.     

Assessing the Status of Wild Felids in a Highly-Disturbed Commercial Forest Reserve in Borneo and the Implications for Camera Trap Survey Design

The proliferation of camera-trapping studies has led to a spate of extensions in the known distributions of many wild cat species, not least in Borneo. However, we still do not have a clear picture of the spatial patterns of felid abundance in Southeast Asia, particularly with respect to the large areas of highly-disturbed habitat. An important obstacle to increasing the usefulness of camera trap data is the widespread practice of setting cameras at non-random locations. Non-random deployment interacts with non-random space-use by animals, causing biases in our inferences about relative abundance from detection frequencies alone. This may be a particular problem if surveys do not adequately sample the full range of habitat features present in a study region. Using camera-trapping records and incidental sightings from the Kalabakan Forest Reserve, Sabah, Malaysian Borneo, we aimed to assess the relative abundance of felid species in highly-disturbed forest, as well as investigate felid space-use and the potential for biases resulting from non-random sampling. Although the area has been intensively logged over three decades, it was found to still retain the full complement of Bornean felids, including the bay cat Pardofelis badia, a poorly known Bornean endemic. Camera-trapping using strictly random locations detected four of the five Bornean felid species and revealed inter- and intra-specific differences in space-use. We compare our results with an extensive dataset of >1,200 felid records from previous camera-trapping studies and show that the relative abundance of the bay cat, in particular, may have previously been underestimated due to the use of non-random survey locations. Further surveys for this species using random locations will be crucial in determining its conservation status. We advocate the more wide-spread use of random survey locations in future camera-trapping surveys in order to increase the robustness and generality of inferences that can be made.     

Spatial patterning in nocturnal prosimians: a review of methods and relevance to studies of sociality

Patterns of home range overlap between individuals are key parameters used in discussions of sociality in nocturnal prosimians. Despite the importance of space use variables in defining social structure in nocturnal prosimians, researchers have yet to reach a consensus concerning the most reliable techniques for measuring patterns of home range use. In this paper, we review the methods used in 27 studies of nocturnal prosimian ranging behavior published since 1977. We discuss the usefulness and limitations of the various methods of data collection (radio tracking, trap mark, and identification of sleeping site locations) and data analysis (minimum convex polygon method, minimum concave polygon method, and quadrat analysis) used in these studies. We conclude that the most effective method for gathering data on individual movements and social interactions is direct observation of individual radio tagged animals during all-night follows. In those cases where radio tracking and/or all-night follows are not possible, trap mark techniques can be used, although they tend to greatly underestimate home range size. We recommend that data collected on nocturnal prosimian ranging behavior be analyzed using the minimum convex polygon method, quadrat analysis, and, perhaps, one other of the more mathematically sophisticated techniques popular in studies of non-primate mammals. Finally, we urge researchers to employ standardized methods of data collection and data analysis in future studies of range use in nocturnal prosimians. Without standardization of methods, quantitative comparisons of the findings from different studies are biologically meaningless and prevent cross-species comparisons of space use and its relation to sociality.     

Short-Term Space-Use Patterns of Translocated Mojave Desert Tortoise in Southern California

Increasingly, renewable energy comprises a larger share of global energy production. Across the western United States, public lands are being developed to support renewable energy production. Where there are conflicts with threatened or endangered species, translocation can be used in an attempt to mitigate negative effects. For the threatened Mojave desert tortoise (Gopherus agassizii), we sought to compare habitat- and space-use patterns between short-distance translocated, resident, and control groups. We tested for differences in home range size based on utilization distributions and used linear mixed-effects models to compare space-use intensity, while controlling for demographic and environmental variables. In addition, we examined mean movement distances as well as home range overlap between years and for male and female tortoises in each study group. During the first active season post-translocation, home range size was greater and space-use intensity was lower for translocated tortoises than resident and control groups. These patterns were not present in the second season. In both years, there was no difference in home range size or space-use intensity between control and resident groups. Translocation typically resulted in one active season of questing followed by a second active season characterized by space-use patterns that were indistinguishable from control tortoises. Across both years, the number of times a tortoise was found in a burrow was positively related to greater space-use intensity. Minimizing the time required for translocated tortoises to exhibit patterns similar to non-translocated individuals may have strong implications for conservation by reducing exposure to adverse environmental conditions and predation. With ongoing development, our results can be used to guide future efforts aimed at understanding how translocation strategies influence patterns of animal space use.     

The analysis of space use patterns.

In this paper we describe and test a new method for characterizing the space use patterns of individual animals on the basis of successive locations of marked individuals. Existing methods either do not describe space use in probabilistic terms, e.g. the maximum distance between locations or the area of the convex hull of all locations, or they assume a priori knowledge of the probabilistic shape of each individual's use pattern, e.g. bivariate or circular normal distributions. We develop a method for calculating a probability of location distribution for an average individual member of a population that requires no assumptions about the shape of the distribution (we call this distribution the population utilization distribution or PUD). Using nine different sets of location data, we demonstrate that these distributions accurately characterize the space use patterns of the populations from which they were derived. The assumption of normality is found to result in a consistent and significant overestimate of the area of use. We then describe a function which relates probability of location to area (termed the MAP index) which has a number of advantages over existing size indices. Finally, we show how any quantities such as the MAP index derived from our average distributions can be subjected to standard statistical tests of significance.     

Field test of an automated radio‐telemetry system: tracking local space use of aerial insectivores

Documenting local space use of birds that move rapidly, but are too small to carry GPS tags, such as swallows and swifts, can be challenging. For these species, tracking methods such as manual radio‐telemetry and visual observation are either inadequate or labor‐ and time‐intensive. Another option is use of an automated telemetry system, but equipment for such systems can be costly when many receivers are used. Our objective, therefore, was to determine if an automated radio‐telemetry system, consisting of just two receivers, could provide an alternative to manual tracking for gathering data on local space use of six individuals of three species of aerial insectivores, including one Cliff Swallow (Petrochelidon pyrrhonota), one Eastern Phoebe (Sayornis phoebe), and four Barn Swallows (Hirundo rustica). We established automated radio‐telemetry systems at three sites near the city of Peterborough in eastern Ontario, Canada, from May to August 2015. We evaluated the location error of our two‐receiver system using data from moving and stationary test transmitters at known locations, and used telemetry data from the aerial insectivores as a test of the system's ability to track rapidly moving birds under field conditions. Median location error was ~250 m for automated telemetry test locations after filtering. More than 90% of estimated locations had large location errors and were removed from analysis, including all locations > 1 km from receiver stations. Our automated telemetry receivers recorded 17,634 detections of the six radio‐tagged birds. However, filtering removed an average of 89% of bird location estimates, leaving only the Cliff Swallow with enough locations for analysis of space use. Our results demonstrate that a minimal automated radio‐telemetry system can be used to assess local space use by small, highly mobile birds, but the resolution of the data collected using only two receiver stations was coarse and had a limited range. To improve both location accuracy and increase the percentage of usable location estimates collected, we suggest that, in future studies, investigators use receivers that simultaneously record signals detected by all antennas, and use of a minimum of three receiver stations with more antennas at each station.     

Quantifying personal exposure to air pollution from smartphone‐based location data

Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4‐month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location‐aware smartphone application.     

What spatial data do we need to develop global mammal conservation strategies?

Spatial data on species distributions are available in two main forms, point locations and distribution maps (polygon ranges and grids). The first are often temporally and spatially biased, and too discontinuous, to be useful (untransformed) in spatial analyses. A variety of modelling approaches are used to transform point locations into maps. We discuss the attributes that point location data and distribution maps must satisfy in order to be useful in conservation planning. We recommend that before point location data are used to produce and/or evaluate distribution models, the dataset should be assessed under a set of criteria, including sample size, age of data, environmental/geographical coverage, independence, accuracy, time relevance and (often forgotten) representation of areas of permanent and natural presence of the species. Distribution maps must satisfy additional attributes if used for conservation analyses and strategies, including minimizing commission and omission errors, credibility of the source/assessors and availability for public screening. We review currently available databases for mammals globally and show that they are highly variable in complying with these attributes. The heterogeneity and weakness of spatial data seriously constrain their utility to global and also sub-global scale conservation analyses.     

Nested clade analyses of phylogeographic data: testing hypotheses about gene flow and population history

Since the 1920s, population geneticists have had measures that describe how genetic variation is distributed spatially within a species' geographical range. Modern genetic survey techniques frequently yield information on the evolutionary relationships among the alleles or haplotypes as well as information on allele frequencies and their spatial distributions. This evolutionary information is often expressed in the form of an estimated haplotype or allele tree. Traditional statistics of population structure, such as F statistics, do not make use of evolutionary genealogical information, so it is necessary to develop new statistical estimators and tests that explicitly incorporate information from the haplotype tree. One such technique is to use the haplotype tree to define a nested series of branches (clades), thereby allowing an evolutionary nested analysis of the spatial distribution of genetic variation. Such a nested analysis can be performed regarding the geographical sampling locations either as categorical or continuous variables (i.e. some measure of spatial distance). It is shown that such nested phylogeographical analyses have more power to detect geographical associations than traditional, nonhistorical analyses and, as a consequence, allow a broader range of gene-flow parameters to be estimated in a precise fashion. More importantly, such nested analyses can discriminate between phylogeographical associations due to recurrent but restricted gene flow vs. historical events operating at the population level (e.g. past fragmentation, colonization, or range expansion events). Restricted gene flow and historical events can be intertwined, and the cladistic analyses can reconstruct their temporal juxtapositions, thereby yielding great insight into both the evolutionary history and population structure of the species. Examples are given that illustrate these properties, concentrating on the detection of range expansion events.     

How good are Bayesian belief networks for environmental management? A test with data from an agricultural river catchment

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The combined use of acoustic tracking and echosounding to investigate the movement and distribution of common bream (Abramis brama) in the River Trent,England

Spatial behaviour and distribution of fishes along a 7.6-km lowland reach of the River Trent, England, were examined using two complementary telemetry techniques: acoustic tracking to assess the movement and activity of common bream Abramis brama (L.) and quantitative echosounding for measuring the density and distribution of fish shoals. Nine adult bream (39.3–53.2 cm) were tracked by means of intraperitoneally implanted acoustic transmitters from 19 July to 12 September 2000. Home range size varied between 0.35 and 5.40 km of river length over this period. Bream were relatively inactive during daylight hours, began moving near dusk, and tended to move throughout the night. A distinct daytime residence area was occupied by most tagged fish on most occasions, while river use at night was more variable between individuals. Mobile echosounding surveys, with the transducer beaming horizontally across the river, conducted at night between July and September 2000, showed a highly contagious fish distribution within the study reach. For 200-m sections of river, there was a negative correlation between the relative frequency of acoustic tracking fixes at night and mean fish densities, as measured by echosounding for targets larger than –50 dB (c. 5-cm long). However, there was a highly significant positive rank correlation between the relative frequency of acoustic tracking fixes and acoustic targets larger than –30 dB (c. 22-cm long), most of which in this river are bream. This suggests that telemetry and echosounding can, in this part of the River Trent, be combined to provide valuable spatial information at individual and population scales for bream.     

The home-range concept: are traditional estimators still relevant with modern telemetry technology?

Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.     

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.     

Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modelling

Regional conservation planning can often make more effective use of sparse biological data by linking these data to remotely mapped environmental variables through statistical modelling. While modelling distributions of individual species is the best known and most widely used approach to such modelling, there are many situations in which more information can be extracted from available data by supplementing, or replacing, species-level modelling with modelling of communities or assemblages. This paper provides an overview of approaches to community-level modelling employed in a series of major land-use planning processes in the northeast New South Wales region of Australia, and evaluates how well communities and assemblages derived using these techniques function as surrogates in regional conservation planning. We also outline three new directions that may enhance the effectiveness of community-level modelling by: (1) more closely integrating modelling with traditional ecological mapping (e.g. vegetation mapping); (2) more tightly linking numerical classification and spatial modelling through application of canonical classification techniques; and (3) enhancing the applicability of modelling to data-poor regions through employment of a new technique for modelling spatial pattern in compositional dissimilarity.     

Space use by Great Lakes Piping Plovers during the breeding season

ABSTRACT.   Identifying and protecting breeding habitat for imperiled species requires an understanding of the spatial and temporal movements of breeding individuals. During the 2003 and 2004 breeding seasons, we examined space use by Piping Plovers ( Charadrius melodus ) in the federally endangered Great Lakes population. We used coordinate geometry to estimate home range sizes of individual birds and examined relationships between home range size and breeding stage (incubation versus chick rearing), year, sex, number of locations, minimum plover age, distance to the nearest nest, and human beach use (high, medium, or low). The mean size of home ranges of Piping Plovers that fledged at least one chick was 2.9 ± 0.5 (SE) ha (range = 0.4–11.2 ha), and the mean linear beach distance traversed was 475 ± 53 m (range = 130–1435 m). Individuals used 3 times more beach area and 1.5 times more shoreline distance in 2003 than in 2004. Females used smaller areas than males overall and during chick rearing. Home ranges were smallest on beaches with low public use, suggesting that human disturbance may cause greater movement by individual plovers and that larger protected areas may be warranted on beaches frequented by the public to minimize disturbance to breeding birds. Our results demonstrate that nesting Great Lakes Piping Plovers occupy relatively small ranges and, therefore, that even relatively small areas of suitable habitat can have a high conservation value for this endangered population. However, the total area of habitat used varied substantially among individuals, and this should be considered when protecting habitat for the species.     

Space use and social association in a gregarious ungulate: Testing the conspecific attraction and resource dispersion hypotheses

Animals use a variety of proximate cues to assess habitat quality when resources vary spatiotemporally. Two nonmutually exclusive strategies to assess habitat quality involve either direct assessment of landscape features or observation of social cues from conspecifics as a form of information transfer about forage resources. The conspecific attraction hypothesis proposes that individual space use is dependent on the distribution of conspecifics rather than the location of resource patches, whereas the resource dispersion hypothesis proposes that individual space use and social association are driven by the abundance and distribution of resources. We tested the conspecific attraction and the resource dispersion hypotheses as two nonmutually exclusive hypotheses explaining social association and of adult female caribou (Rangifer tarandus). We used location data from GPS collars to estimate interannual site fidelity and networks representing home range overlap and social associations among individual caribou. We found that home range overlap and social associations were correlated with resource distribution in summer and conspecific attraction in winter. In summer, when resources were distributed relatively homogeneously, interannual site fidelity was high and home range overlap and social associations were low. Conversely, in winter when resources were distributed relatively heterogeneously, interannual site fidelity was low and home range overlap and social associations were high. As access to resources changes across seasons, caribou appear to alter social behavior and space use. In summer, caribou may use cues associated with the distribution of forage, and in winter caribou may use cues from conspecifics to access forage. Our results have broad implications for our understanding of caribou socioecology, suggesting that caribou use season‐specific strategies to locate forage. Caribou populations continue to decline globally, and our finding that conspecific attraction is likely related to access to forage suggests that further fragmentation of caribou habitat could limit social association among caribou, particularly in winter when access to resources may be limited.     

Non-stationarity and local approaches to modelling the distributions of wildlife

Despite a growing interest in species distribution modelling, relatively little attention has been paid to spatial autocorrelation and non-stationarity. Both spatial autocorrelation (the tendency for adjacent locations to be more similar than distant ones) and non-stationarity (the variation in modelled relationships over space) are likely to be common properties of ecological systems. This paper focuses on non-stationarity and uses two local techniques, geographically weighted regression (GWR) and varying coefficient modelling (VCM), to assess its impact on model predictions. We extend two published studies, one on the presence–absence of calandra larks in Spain and the other on bird species richness in Britain, to compare GWR and VCM with the more usual global generalized linear modelling (GLM) and generalized additive modelling (GAM). For the calandra lark data, GWR and VCM produced better-fitting models than GLM or GAM. VCM in particular gave significantly reduced spatial autocorrelation in the model residuals. GWR showed that individual predictors became stationary at different spatial scales, indicating that distributions are influenced by ecological processes operating over multiple scales. VCM was able to predict occurrence accurately on independent data from the same geographical area as the training data but not beyond, whereas the GAM produced good results on all areas. Individual predictions from the local methods often differed substantially from the global models. For the species richness data, VCM and GWR produced far better predictions than ordinary regression. Our analyses suggest that modellers interpolating data to produce maps for practical actions (e.g. conservation) should consider local methods, whereas they should not be used for extrapolation to new areas. We argue that local methods are complementary to global methods, revealing details of habitat associations and data properties which global methods average out and miss.