Relative Probability Of Use Research Articles

Are all data types and connectivity models created equal? Validating common connectivity approaches with dispersal data

AbstractAimThere is enormous interest in applying connectivity modelling to resistance surfaces for identifying corridors for conservation action. However, the multiple analytical approaches used to estimate resistance surfaces and predict connectivity across resistance surfaces have not been rigorously compared, and it is unclear what methods provide the best inferences about population connectivity. Using a large empirical data set on puma (Puma concolor), we are the first to compare several of the most common approaches for estimating resistance and modelling connectivity and validate them with dispersal data.LocationSouthern California, USA.MethodsWe estimate resistance using presence‐only data, GPS telemetry data from puma home ranges and genetic data using a variety of analytical methods. We model connectivity with cost distance and circuit theory algorithms. We then measure the ability of each data type and connectivity algorithm to capture GPS telemetry points of dispersing pumas.ResultsWe found that resource selection functions based on GPS telemetry points and paths outperformed species distribution models when applied using cost distance connectivity algorithms. Point and path selection functions were not statistically different in their performance, but point selection functions were more sensitive to the transformation used to convert relative probability of use to resistance. Point and path selection functions and landscape genetics outperformed other methods when applied with cost distance; no methods outperformed one another with circuit theory.Main conclusionsWe conclude that path or point selection functions, or landscape genetic models, should be used to estimate landscape resistance for wildlife. In cases where resource limitations prohibit the collection of GPS collar or genetic data, our results suggest that species distribution models, while weaker, may still be sufficient for resistance estimation. We recommend the use of cost distance‐based approaches, such as least‐cost corridors and resistant kernels, for estimating connectivity and identifying functional corridors for terrestrial wildlife.

African Wild Dog Habitat Use Modelling Using Telemetry Data and Citizen Scientist Sightings: Are the Results Comparable?

Quantifying landscape characteristics that wildlife select is essential for conservation and management action. Models that map wildlife resource selection tend to be informed by telemetry technology which is costly to acquire/maintain and potentially risky to deploy. Therefore, there is value in pursuing alternative data collection protocols, such as citizen scientist approaches to ascertain whether they can reveal results comparable to those derived from telemetry studies. The conservation of African wild dogs (Lycaon pictus) presents an interesting case study to examine this topic. The species is rare and wideranging, hence data collection is both challenging and costly. They are, however, a groupliving species with unique and conspicuous coat markings, making them potentially well-suited to citizen science data collection strategies. Here, we fitted resource selection functions (RSFs) built from Global Position System (GPS) telemetry data, and from citizen scientist data, collected in and around Hwange National Park, Zimbabwe. We assessed comparability of these RSFs by evaluating the relative importance of parameters, parameter coefficients (direction and magnitude of effect), and the spatial predictions of relative probability of use by African wild dogs. The most important predictors in both models were proportion of woodland and bushland, the number of habitat types, and distance to waterhole. Furthermore, spatial predictions from both models displayed a high degree of overlap (r = 0.74), indicating similarities in selected and avoided habitat patches. Our analysis demonstrates that sufficient citizen science data can be a valuable alternative to telemetry data for African wild dogs. We thus encourage the collection and use of citizen science data for similar analyses, particularly when funding is limited. Our work also highlights areas in and around Hwange National Park with the highest probability of being used by African wild dogs, which is where conservation efforts should be intensified.

Barred owl habitat selection in west coast forests

ABSTRACTThe invasion of the Pacific Northwest, USA by northern barred owls (Strix varia) is a conservation conundrum because it contributes to lingering declines in populations of northern spotted owls (Strix occidentalis caurina). We evaluated factors influencing nocturnal (i.e., foraging) habitat selection by northern barred owls using a repeated‐studies design and information‐theoretic methods across 3 Pacific Northwest study areas, each containing a broad range of forest and environmental conditions. We constructed discrete‐choice resource selection functions (RSF) based upon telemetry points linked to forest inventory plots and map‐based physical environmental metrics within home ranges of radio‐tagged barred owls at Chehalis, Washington (n = 16), Springfield, Oregon (n = 22), and Arcata, California (n = 15). A general RSF based upon pooling data across study areas suggested barred owls selectively hunted for prey in lower‐slope positions on southerly aspects often near streams at low elevations, and often within red alder (Alnus rubra) dominated stands or in moderately dense patches of medium‐ and large‐diameter coniferous trees close to patches containing nests. The relative probability of use decreased with increasing densities of small‐diameter trees, suggesting barred owls avoided clearcuts and young plantations. These general patterns were modified by study‐area variation in tree species composition and density. Study‐area‐specific factors that were associated positively with barred owl habitat selection included increasing basal area of western redcedar (Thuja plicata) and red alder at Chehalis and increasing densities of western redcedar and basal area of bigleaf maple (Acer macrophyllum) and western hemlock (Tsuga heterophylla) at Springfield. At Arcata, high densities of Douglas‐fir (Pseudotsuga menziesii) trees and increasing basal area of tanoak (Notholithocarpus densiflorus) were negatively associated with barred owl habitat selection. Seasonal patterns of habitat selection did not differ dramatically although model coefficients suggested selection for specific tree species was weaker in the non‐breeding season and barred owls did not seek topographic situations that provided thermo‐regulatory benefits. The information may help inform conservation strategies for reducing competition between barred owls and northern spotted owls or perhaps in predicting colonization of new areas by barred owls. © 2017 The Wildlife Society.

Nest-site selection by Interior Least Terns and Piping Plovers at managed, off-channel sites along the Central Platte River in Nebraska, USA

Given the high productivity of Interior Least Terns (Sternula antillarum athalassos) and Piping Plovers (Charadrius melodus) on constructed off-channel nesting sites along the central Platte River in Nebraska, USA, and the possibility of creating similar habitats at other locations in their breeding range, understanding how these species use off-channel nesting habitats is important. We used data collected along the central Platte River in Nebraska, USA, over a 15-year period (2001–2015), and a discrete-choice modeling framework to assess the effects of physical site attributes and inter- and intraspecific associations on off-channel nest-site selection by Interior Least Terns and Piping Plovers. We found that Piping Plovers avoided nesting near each other, whereas colonial Interior Least Terns selected nest sites near those of conspecifics. In addition, the relative probability of use for both species was maximized when distance to the nearest predator perch was ≥ 150 m and elevation above the waterline was ≥ 3 m. Probability of use for nesting by Interior Least Terns increased as distance to water increased, whereas the probability of use by Piping Plovers was maximized when distance to water was ~50 m. Our results suggest that important features of constructed, off-channel nesting sites for both species should include no potential predator perches within 150 m of nesting habitat and nesting areas at least 3 m above the waterline. Efficient site designs for Interior Least Terns would be circular, maximizing the area of nesting habitat away from the shoreline, whereas an effective site design for Piping Plovers would be more linear, maximizing the area of nesting habitat near the waterline. An efficient site design for both species would be lobate, incorporating centralized nesting habitat for Interior Least Terns and increased access to foraging areas for nesting and brood-rearing Piping Plovers.

Habitat use and movements of common eiders wintering in southern New England

ABSTRACTLittle is known about the habitat use patterns and movement ecology of American common eiders (Somateria mollissima dresseri) despite potential negative impacts on habitat and eider populations from anthropogenic sources (e.g., oil spills, hunting, offshore wind energy facilities). We used satellite telemetry to quantify migratory phenology, home range size, winter site fidelity, and resource selection of adult female eiders (n = 24) from December 2011 to July 2013 that were captured during winter in southern New England, USA. Eiders spent 39% of their annual cycle in southern New England. In spring, eiders took an average of 16 days (range = 2–47) in 2012 and 20 days (range = 1–61) in 2013 to migrate from wintering grounds to summer areas, whereas the duration of fall migration averaged 47 days (range = 7–115). Eiders exhibited high site fidelity to wintering areas, with 83% of birds with active transmitters (n = 23) returning to the study area the following winter (2012–2013). Mean individual core use home ranges on wintering grounds averaged 38.5 km2 and 95% utilization distributions were 199.3 km2. Based on habitat selection models, eiders preferred shallow, nearshore waters that had relatively fine sediments and a high probability of hard bottom. We estimated that only 3% of our 6,212‐km2 study area had a high relative probability of use by eiders. Future development (e.g., offshore wind energy developments) should avoid shallow, nearshore waters with hard bottoms preferred by eiders to minimize potential impacts. © 2017 The Wildlife Society.

Variation In Early-Successional Habitat Use Among Independent Juvenile Forest Breeding Birds

ABSTRACT Adults and juveniles of some forest breeding birds shift habitat use during the post breeding season from late to early successional forest. Juveniles of smaller passerine species are difficult to radio-track, and there is limited information on their habitat preferences, especially once they become older and independent. We determined if independent hatch-year birds captured in early-successional habitat remained there for extended periods, or if these habitats were only occupied infrequently during foraging activities. We determined habitat use for Ovenbirds (Seiurus aurocapilla), Worm-eating Warblers (Helmitheros vermivorum) and Red-eyed Vireos (Vireo olivaceus) during the independent post-fledging period in the Missouri Ozarks. We placed radio transmitters on 29 hatch-year birds captured in clearcuts and attempted to relocate them for 24 days in the summer of 2012. All three species had a greater relative probability of use of clearcut forest stands with small trees than older forests. Ovenbi...

Sandhill crane roost selection, human disturbance, and forage resources

ABSTRACTSites used for roosting represent a key habitat requirement for many species of birds because availability and quality of roost sites can influence individual fitness. Birds select roost sites based on numerous factors, requirements, and motivations, and selection of roosts can be dynamic in time and space because of various ecological and environmental influences. For sandhill cranes (Antigone canadensis) at their main spring‐staging area along the Platte River in south‐central Nebraska, USA, past investigations of roosting cranes focused on physical channel characteristics related to perceived security as motivating roost distribution. We used 6,310 roost sites selected by 313 sandhill cranes over 5 spring migration seasons (2003–2007) to quantify resource selection functions of roost sites on the central Platte River using a discrete choice analysis. Sandhill cranes generally showed stronger selection for wider channels with shorter bank vegetation situated farther from potential human disturbance features such as roads, bridges, and dwellings. Furthermore, selection for roost sites with preferable physical characteristics (wide channels with short bank vegetation) was more resilient to nearby disturbance features than more narrow channels with taller bank vegetation. The amount of cornfields surrounding sandhill crane roost sites positively influenced relative probability of use but only for more narrow channels <100 m and those with shorter bank vegetation. We confirmed key resource features that sandhill cranes selected at river channels along the Platte River, and after incorporating spatial variation due to human disturbance, our understanding of roost site selection was more robust, providing insights on how disturbance may interact with physical habitat features. Managers can use information on roost‐site selection when developing plans to increase probability of crane use at existing roost sites and to identify new areas for potential use if existing sites become limited. © 2016 The Wildlife Society.

The influence of mitigation on sage-grouse habitat selection within an energy development field.

Growing global energy demands ensure the continued growth of energy development. Energy development in wildlife areas can significantly impact wildlife populations. Efforts to mitigate development impacts to wildlife are on-going, but the effectiveness of such efforts is seldom monitored or assessed. Greater sage-grouse (Centrocercus urophasianus) are sensitive to energy development and likely serve as an effective umbrella species for other sagebrush-steppe obligate wildlife. We assessed the response of birds within an energy development area before and after the implementation of mitigation action. Additionally, we quantified changes in habitat distribution and abundance in pre- and post-mitigation landscapes. Sage-grouse avoidance of energy development at large spatial scales is well documented. We limited our research to directly within an energy development field in order to assess the influence of mitigation in close proximity to energy infrastructure. We used nest-location data (n = 488) within an energy development field to develop habitat selection models using logistic regression on data from 4 years of research prior to mitigation and for 4 years following the implementation of extensive mitigation efforts (e.g., decreased activity, buried powerlines). The post-mitigation habitat selection models indicated less avoidance of wells (well density β = 0.18 ± 0.08) than the pre-mitigation models (well density β = -0.09 ± 0.11). However, birds still avoided areas of high well density and nests were not found in areas with greater than 4 wells per km2 and the majority of nests (63%) were located in areas with ≤ 1 well per km2. Several other model coefficients differed between the two time periods and indicated stronger selection for sagebrush (pre-mitigation β = 0.30 ± 0.09; post-mitigation β = 0.82 ± 0.08) and less avoidance of rugged terrain (pre-mitigation β = -0.35 ± 0.12; post-mitigation β = -0.05 ± 0.09). Mitigation efforts implemented may be responsible for the measurable improvement in sage-grouse nesting habitats within the development area. However, we cannot reject alternative hypotheses concerning the influence of population density and intraspecific competition. Additionally, we were unable to assess the actual fitness consequences of mitigation or the source-sink dynamics of the habitats. We compared the pre-mitigation and post-mitigation models predicted as maps with habitats ranked from low to high relative probability of use (equal-area bins: 1 – 5). We found more improvement in habitat rank between the two time periods around mitigated wells compared to non-mitigated wells. Informed mitigation within energy development fields could help improve habitats within the field. We recommend that any mitigation effort include well-informed plans to monitor the effectiveness of the implemented mitigation actions that assess both habitat use and relevant fitness parameters.

Resource configuration and abundance affect space use of a cooperatively breeding resident bird

ABSTRACT Movement and space use of birds is driven by activities associated with acquiring and maintaining access to critical resources. Thus, the spatial configuration of resources within home ranges should influence bird movements, and resource values should be relative to their locations. We radio-tracked 22 Brown-headed Nuthatches (Sitta pusilla) and related their space use and home range sizes to available resources while taking nest site locations into account. We developed utilization distributions (UDs) from nuthatch locations, and treated the area of each 95% isopleth as home range size and the height of the UD as relative probability of use. We fit models relating home range size to mean resource measures within home ranges, and used lognormal regression to relate intensity of use to resource metrics at random points by ranking linear mixed models. Nuthatch home ranges typically had two centers of activity. Areas of high use were associated with the density of recently killed snags (likely a for...

Multiscale habitat selection by a forest-dwelling shorebird, the American woodcock: Implications for forest management in southern New England, USA

Declines of young forest and associated populations of wildlife are major conservation concerns in the Northeast, USA. Active forest management is required to conserve declining populations of young forest wildlife and investigating habitat selection by target species can help inform management decision-making. The American woodcock (Scolopax minor) is a key indicator species of young forest whose populations have declined significantly since 1968. We investigated multiscale habitat selection by woodcock in Rhode Island, USA in order to characterize daytime habitat, and to predict state-wide relative probability of use by woodcock of forested land. We used radio-telemetry to monitor the daytime locations of woodcock at three state wildlife management areas from 23 May–25 August 2011 and 2012. Compared to random sites, woodcock selected younger forest where the biomass of preferred food (i.e., earthworms [Haplotaxida]) was 46–67% greater and the density of shrub and sapling stems was about two times greater. Most woodcock home ranges were <50ha and usually comprised wetland forests and deciduous or mixed upland forests on flatter slopes that were closer to streams, agricultural openings, upland young forests, and moist soils. Using resource selection functions, we found that the majority of forested land in Rhode Island was in the low-moderate classes of relative use, but 92% of older second-growth upland forest in the state is located where woodcock habitat management would be beneficial for increasing relative use. We illustrate how land managers can use resource selection functions to compare expected responses of woodcock to alternative forest management scenarios and so maximize conservation benefits.

Incorporating mortality into habitat selection to identify secure and risky habitats for savannah elephants

Empirical models of habitat selection are increasingly used to guide and inform habitat-based management plans for wildlife species. However, habitat selection does not necessarily equate to habitat quality particularly if selection is maladaptive, so incorporating measures of fitness into estimations of occurrence is necessary to increase model robustness. Here, we incorporated spatially explicit mortality events with the habitat selection of elephants to predict secure and risky habitats in northern Botswana. Following a two-step approach, we first predict the relative probability of use and the relative probability of mortality based on landscape features using logistic regression models. Combining these two indices, we then identified low mortality and high use (primary habitat) and areas of high mortality and high use (primary risk). We found that mortalities of adult elephants were closely associated with anthropogenic features, with 80% of mortalities occurring within 25km of people. Conversely, elephant habitat selection was highest at distances of 30–50km from people. Primary habitat for elephants occurred in the central portion of the study area and within the Okavango Delta; whereas risky areas occurred along the periphery near humans. The protected designation of an area had less influence on the proportion of prime habitat therein than did the locations of the area in relation to human development. Elephant management in southern Africa is moving towards a more self-sustaining, habitat-based approach, and information on selection and mortality could serve as a baseline to help identify demographic sources and sinks to stabilize elephant demography.

A re‐evaluation of a case–control model with contaminated controls for resource selection studies

1. A common sampling design in resource selection studies involves measuring resource attributes at sample units used by an animal and at sample units considered available for use. Few models can estimate the absolute probability of using a sample unit from such data, but such approaches are generally preferred over statistical methods that estimate a relative probability of use. 2. The case-control model that allows for contaminated controls, proposed by Lancaster & Imbens (1996) and Lele (2009), can estimate the absolute probability of using a sample unit from use-availability data. However, numerous misconceptions have likely prevented the widespread application of this model to resource selection studies. We address common misconceptions regarding the case-control model with contaminated controls and demonstrate its ability to estimate the absolute probability of use, prevalence and parameters associated with categorical covariates from use-availability data. 3. We fit the case-control model with contaminated controls to simulated data with varying prevalence (defined as the average probability of use across all sample units) and sample sizes (n1 = 500 used and na = 500 available samples; n1 = 1000 used and na = 1000 available samples). We then applied this model to estimate the probability Ozark hellbenders (Cryptobranchus alleganiensis bishopi) would use a location within a stream as a function of covariates. 4. The case-control model with contaminated controls provided unbiased estimates of all parameters at N = 2000 sample size simulation scenarios, particularly at low prevalence. However, this model produced increasingly variable maximum likelihood estimates of parameters as prevalence increased, particularly at N = 1000 sample size scenarios. We thus recommend at least 500-1000 used samples when fitting the case-control model with contaminated controls to use-availability data. Our application to hellbender data revealed selection for locations with coarse substrate that are close to potential sources of cover. 5. This study unites a disparate literature, addresses and clarifies many commonly held misconceptions and demonstrates that the case-control model with contaminated controls is a viable alternative for estimating the absolute probability of use from use-availability data.

Using a resource selection approach to predict the suitability of alpine habitats for a common herbivore

Climate change models predict that Australia's alpine areas will experience major declines in snow cover, which, in turn, may provide suitable habitat for species presently restricted to lower altitudes. As a result, there are concerns among land managers that many species will invade alpine areas and have a detrimental impact on fragile alpine ecosystems. However, species survival in such areas, irrespective of snow cover, is greatly dependent on the availability of suitable resources. This study investigated the selection of resources by common wombats Vombatus ursinus, which are currently restricted to, but widespread throughout, the subalpine zone of the Snowy Mountains. Our objectives were to identify habitat choices, and build a model of habitat suitability over the broader landscape, to investigate the likelihood of this common herbivore inhabiting the alpine zone. Global positioning system data were obtained from collared wombats, which were tracked for up to a year, to examine resource selection. Resource selection within the home range of individual wombats revealed that topographic position, vegetation cover, drainage, past fire disturbance, and roads were important predictors of locations. A global model showed that wombats selected locations with mid-elevations, moderate slopes, closer to water courses and roads, and with a lower proportion of grassland, which are discussed in relation to foraging and burrowing requirements. Mapping of the global model illustrated that alpine areas had a low relative probability of use by this species. Consequently, wombats are unlikely to inhabit alpine areas under given climate change scenarios of less snow cover, because the area (presently) does not contain suitable resources necessary for a wombat to maintain a home range. Researchers and managers need to be mindful of how the spatial distribution of resources, in addition to species climatic tolerances, will influence potential range shifts.

Using Pellet Groups To Assess Response Of Elk and Deer to Roads and Energy Development

Development and extraction of resources such as oil and gas has directly and indirectly reduced available habitat to wildlife through changes in behavior and resource use. To assess how elk (Cervus elaphus) and deer (Odocoileus spp.) were spatially distributed relative to roads and coal-bed natural gas well pads, we collected pellet group data during 2 summers in south-central Colorado. We used generalized linear mixed models to assess the relative probability of use of elk and deer in relation to roads and well pads. We found relative probability of use was positively associated with distance from roads, indicating greater use of areas farther away from roads. Relative probability of use was negatively associated with distance to well pads, potentially as a result of plant phenology and reseeding in disturbed areas around well pads. Other factors such as elevation, slope and vegetative security cover also influenced elk and deer spatial distributions. Based on these data, it appears resource use may be driven by forage and security cover more than disturbance features. Pellet group surveys appear to be an appropriate technique for evaluating resource use of populations across large spatial extents when logistical and financial constraints limit the use of more advanced technology such as very high frequency and global positioning system collars.

Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

BackgroundConserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled.Methodology/Principal FindingsWe present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72–88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy.Conclusions/SignificanceBy directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action.

A Comparison of Two Modeling Approaches for Evaluating Wildlife‐Habitat Relationships

ABSTRACT Studies of resource selection form the basis for much of our understanding of wildlife habitat requirements, and resource selection functions (RSFs), which predict relative probability of use, have been proposed as a unifying concept for analysis and interpretation of wildlife habitat data. Logistic regression that contrasts used and available or unused resource units is one of the most common analyses for developing RSFs. Recently, resource utilization functions (RUFs) have been developed, which also predict probability of use. Unlike RSFs, however, RUFs are based on a continuous metric of space use summarized by a utilization distribution. Although both RSFs and RUFs predict space use, a direct comparison of these 2 modeling approaches is lacking. We compared performance of RSFs and RUFs by applying both approaches to location data for 75 Rocky Mountain elk (Cervus elaphus) and 39 mule deer (Odocoileus hemionus) collected at the Starkey Experimental Forest and Range in northeastern Oregon, USA. We evaluated differences in maps of predicted probability of use, relative ranking of habitat variables, and predictive power between the 2 models. For elk, 3 habitat variables were statistically significant (P &lt; 0.05) in the RSF, whereas 7 variables were significant in the RUF. Maps of predicted probability of use differed substantially between the 2 models for elk, as did the relative ranking of habitat variables. For mule deer, 4 variables were significant in the RSF, whereas 6 were significant in the RUF, and maps of predicted probability of use were similar between models. In addition, distance to water was the top‐ranked variable in both models for mule deer. Although space use by both species was predicted most accurately by the RSF based on cross‐validation, differences in predictive power between models were more substantial for elk than mule deer. To maximize accuracy and utility of predictive wildlife‐habitat models, managers must be aware of the relative strengths and weaknesses of different modeling techniques. We conclude that although RUFs represent a substantial advance in resource selection theory, techniques available for generating RUFs remain underdeveloped and, as a result, RUFs sometimes predict less accurately than models derived using more conventional techniques.

Using Subpopulation Structure for Barren-Ground Grizzly Bear Management

Abstract The subpopulation is an intermediate level of organization that is ecologically meaningful for research and management. We used location data (n = 1,235) from 54 barren-ground grizzly bears (Ursus arctos) monitored from 1974–78 (n = 12) using VHF (very high frequency) telemetry and from 2001–06 (n = 42) using GPS (global positioning system) telemetry to delineate subpopulation structure in the Mackenzie Delta region of the Northwest Territories, Canada. We used Ward's cluster analysis to group bears into 4 subpopulations using their geographical position in 4 seasons. We used the fixed-kernel method to bound subpopulation areas and to estimate the relative probability of use by each subpopulation for each geographic information system (GIS) grid cell. The Delta is the starting point for the proposed Mackenzie Valley Pipeline. To demonstrate how subpopulation structure can be used to partition potential anthropogenic disturbance across the population, we estimated the mean probability of use of...

Components of Grizzly Bear Habitat Selection: Density, Habitats, Roads, and Mortality Risk

Abstract: We used resource selection functions (RSF) to estimate the relative probability of use for grizzly bears (Ursus arctos) adjacent to the Parsnip River, British Columbia, Canada, 1998‐2003. We collected data from 30 radiocollared bears on a rolling plateau where a large portion of the landscape had been modified by human activities, primarily forestry. We also monitored 24 radiocollared bears in mountain areas largely inaccessible to humans. Bears that lived on the plateau existed at less than one‐quarter the density of bears in the mountains. Plateau bears ate more high‐quality food items, such as meat and berries, leading us to conclude that food limitation was not responsible for the differences in densities. We hypothesized that plateau bears were limited by human‐caused mortality associated with roads constructed for forestry activities. Independent estimates of bear population size from DNA‐based mark‐recapture techniques allowed us to link populations to habitats using RSF models to scale habitat use patterns to population density. To evaluate whether differences in land‐cover type, roads, or mortality risk could account for the disparity in density we used the mountain RSF model to predict habitat use and number of bears on the plateau and vice versa. We predicted increases ranging from 34 bears to 96 bears on the plateau when switching model coefficients, excluding land‐cover types; when exchanging land‐cover coefficients, the model predicted that the plateau population would be 9 bears lower than was observed. Large reductions in the numbers of mountain bears were predicted by habitat‐selection models of bears using the plateau landscape. Although RSF models estimated in mountain and plateau landscapes could not predict bear use and abundance in the other areas, contrasts in models between areas provided a useful tool for examining the effects of human activities on grizzly bears.

LINKING OCCURRENCE AND FITNESS TO PERSISTENCE: HABITAT-BASED APPROACH FOR ENDANGERED GREATER SAGE-GROUSE

Detailed empirical models predicting both species occurrence and fitness across a landscape are necessary to understand processes related to population persistence. Failure to consider both occurrence and fitness may result in incorrect assessments of habitat importance leading to inappropriate management strategies. We took a two-stage approach to identifying critical nesting and brood-rearing habitat for the endangered Greater Sage-Grouse (Centrocercus urophasianus) in Alberta at a landscape scale. First, we used logistic regression to develop spatial models predicting the relative probability of use (occurrence) for Sage-Grouse nests and broods. Secondly, we used Cox proportional hazards survival models to identify the most risky habitats across the landscape. We combined these two approaches to identify Sage-Grouse habitats that pose minimal risk of failure (source habitats) and attractive sink habitats that pose increased risk (ecological traps). Our models showed that Sage-Grouse select for heterogeneous patches of moderate sagebrush cover (quadratic relationship) and avoid anthropogenic edge habitat for nesting. Nests were more successful in heterogeneous habitats, but nest success was independent of anthropogenic features. Similarly, broods selected heterogeneous high-productivity habitats with sagebrush while avoiding human developments, cultivated cropland, and high densities of oil wells. Chick mortalities tended to occur in proximity to oil and gas developments and along riparian habitats. For nests and broods, respectively, approximately 10% and 5% of the study area was considered source habitat, whereas 19% and 15% of habitat was attractive sink habitat. Limited source habitats appear to be the main reason for poor nest success (39%) and low chick survival (12%). Our habitat models identify areas of protection priority and areas that require immediate management attention to enhance recruitment to secure the viability of this population. This novel approach to habitat-based population viability modeling has merit for many species of concern.

USE AND INTERPRETATION OF LOGISTIC REGRESSION IN HABITAT-SELECTION STUDIES

Abstract Logistic regression is an important tool for wildlife habitat-selection studies, but the method frequently has been misapplied due to an inadequate understanding of the logistic model, its interpretation, and the influence of sampling design. To promote better use of this method, we review its application and interpretation under 3 sampling designs: random, case–control, and use–availability. Logistic regression is appropriate for habitat use–nonuse studies employing random sampling and can be used to directly model the conditional probability of use in such cases. Logistic regression also is appropriate for studies employing case–control sampling designs, but careful attention is required to interpret results correctly. Unless bias can be estimated or probability of use is small for all habitats, results of case–control studies should be interpreted as odds ratios, rather than probability of use or relative probability of use. When data are gathered under a use–availability design, logistic regr...