Displacement of Mountain Caribou From Winter Habitat by Snowmobiles

Abstract: Mountain caribou are an ecotype of woodland caribou (Rangifer tarandus caribou) that live in subalpine forests in southeastern British Columbia, Canada, extending into northern Idaho and Washington, USA. These caribou are listed as Threatened in Canada, Endangered in the United States, and are the subject of recovery planning efforts in both countries. Many areas of mountain caribou winter habitat experience intensive use by recreational snowmobilers. During 4 surveys, we recorded caribou on all 4 census blocks with little or no snowmobile activity (x̄ density = 0.41 caribou/km²), but during 3 of 4 years, we observed no caribou on the census block with intensive snowmobile activity. The year we observed caribou on the snowmobile block, most were using areas inaccessible to snowmobiles. We used a Resource Selection Function (RSF) based on radiotelemetry data for the area to compare habitat quality among the different census blocks. The absence of caribou from the intensive snowmobile area during most years could not be explained by differences in habitat quality. The RSF predicted that the intensive snowmobile area could support 53-96 caribou (95% CI). We conclude that intensive snowmobiling has displaced caribou from an area of suitable habitat. We recommend that snowmobile activity be restricted from all or most high-quality mountain caribou habitat as part of the recovery planning process.     

Female Moose Prioritize Forage Over Mortality Risk in Harvested Landscapes

Since 2010, several moose (Alces alces) populations have declined across North America. These declines are believed to be broadly related to climate and landscape change. At the western reaches of moose continental range, in the interior of British Columbia, Canada, wildlife managers have reported widespread declines of moose populations. Disturbances to forests from a mountain pine beetle (Dendroctonum ponderosae) outbreak and associated salvage logging infrastructure in British Columbia are suspected as a mechanism manifested in moose behavior and habitat selection. We examined seasonal differences in moose habitat selection in response to landscape change from mountain pine beetle salvage logging infrastructure: dense road networks and large intensive forest harvest cutblocks. We used 157,447 global positioning system locations from 83 adult female moose from 2012 to 2016 on the Bonaparte Plateau at the southern edge of the Interior Plateau of central British Columbia to test whether increased forage availability, landscape features associated with increased mortality risk, or the cumulative effects of salvage logging best explain female moose distribution using resource selection functions in an information-theoretic framework. We tested these hypotheses across biological seasons, defined using a cluster analysis framework. The cumulative effects of forage availability and risk best predicted resource selection of female moose in all seasons; however, the covariates included in the cumulative models varied between seasons. The top forage availability model better explained moose habitat use than the top risk model in all seasons, except for the calving and fall seasons where the top risk model (distance to road) better predicted moose space use. Selection of habitat that provides forage in winter, spring, and summer suggests that moose seasonally trade predation risk for the benefits of foraging in early seral vegetation communities in highly disturbed landscapes. Our results identified the need for intensive landscape-scale management to stem moose population declines. Additional research is needed on predator densities, space use, and calf survival in relation to salvage logging infrastructure. © 2020 The Wildlife Society.     

Approaches to delineate greater sage-grouse winter concentration areas

The usefulness of protected areas as regulatory mechanisms to conserve wildlife populations relies on their ability to contain all seasonal habitats necessary for species persistence. Efficient conservation practices require understanding behavior and habitat needs of individual species and populations rather than simply relying on reserves of approximate size and configuration. Priority Areas of Conservation (PACs) have been delineated as protected areas based on known breeding habitat for greater sage-grouse (Centrocercus urophasianus; sage-grouse) throughout their range. These PACs include Core Areas designated in the Wyoming Sage-grouse Executive Order; however, this order also indicated the need to identify winter concentration areas (WCAs; flocks ≥50 individuals) based on habitat features using validated resource selection functions (RSFs). We used aerial infrared videography to identify locations of wintering sage-grouse in south-central and southwest Wyoming, USA, to evaluate winter sage-grouse habitat selection with individual-based RSFs, RSFs based on WCAs, and relative flock size. We located 4,859 individuals comprising 132 flocks across our study area. Flocks occurred in Core Areas more than expected, but a biologically meaningful number of sage-grouse flocks were located outside of Core Areas. Individual-based RSFs contained useful predictors that were consistent with previous sage-grouse winter habitat selection studies. Flock size and WCA models produced similar predictions to individual-based RSF models. Individual-based and WCA-based RSF model predictions had a high degree of similarity, suggesting that identifying important winter habitats with individual-based RSF modeling is useful for locating potential WCAs when information on flock sizes is not available. Our results and survey technique provide a potential framework for identifying sage-grouse WCAs with implications for improving PAC protection of all seasonal habitats for sage-grouse conservation. © 2019 The Wildlife Society.     

Evaluating performance of aerial survey data in elephant habitat modelling

Aerial survey data are widely used to model distribution of wildlife. However, their performance in habitat modelling remains largely untested. We used aerial survey and satellite‐linked Global Positioning System (GPS) collar data for elephants, to test (i) whether there is an optimal spatial resolution of predictor variables at which habitat models based on aerial survey data that are uncorrected for locational error can accurately predict elephant habitat and (ii) whether habitat models based on these data sets can accurately predict the presence of elephants in closed woodland habitats. We applied maximum entropy modelling (Maxent) to these data sets and used the Normalised Difference Vegetation Index (NDVI) as well as distance from water points as the habitat predictors to answer these questions. Our results demonstrate better ability of aerial survey data to predict elephant presence at the coarser spatial resolution of 1000 m of both predictor variables. Habitat models derived from aerial survey data underpredicted elephant presence in more closed woodland habitats than those derived from GPS collar data. This result implies that elephants located under dense tree canopies are likely missed during an aerial survey. Our study is one of the first to empirically test and report results on the poor performance of aerial survey data in habitat modelling especially in dense woodlands.     

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.     

Increases in residential and energy development are associated with reductions in recruitment for a large ungulate

Land‐use change due to anthropogenic development is pervasive across the globe and commonly associated with negative consequences for biodiversity. While land‐use change has been linked to shifts in the behavior and habitat‐use patterns of wildlife species, little is known about its influence on animal population dynamics, despite the relevance of such information for conservation. We conducted the first broad‐scale investigation correlating temporal patterns of land‐use change with the demographic rates of mule deer, an iconic species in the western United States experiencing wide‐scale population declines. We employed a unique combination of long‐term (1980–2010) data on residential and energy development across western Colorado, in conjunction with congruent data on deer recruitment, to quantify annual changes in land‐use and correlate those changes with annual indices of demographic performance. We also examined annual variation in weather conditions, which are well recognized to influence ungulate productivity, and provided a basis for comparing the relative strength of different covariates in their association with deer recruitment. Using linear mixed models, we found that increasing residential and energy development within deer habitat were correlated with declining recruitment rates, particularly within seasonal winter ranges. Residential housing had two times the magnitude of effect of any other factor we investigated, and energy development had an effect size similar to key weather variables known to be important to ungulate dynamics. This analysis is the first to correlate a demographic response in mule deer with residential and energy development at large spatial extents relevant to population performance, suggesting that further increases in these development types on deer ranges are not compatible with the goal of maintaining highly productive deer populations. Our results underscore the significance of expanding residential development on mule deer populations, a factor that has received little research attention in recent years, despite its rapidly increasing footprint across the landscape.     

Multiscale Habitat Use by Wolverines in British Columbia,Canada

ABSTRACT Wolverine (Gulo gulo) distribution in British Columbia, Canada, includes multiple-use lands where human use and resource extraction may influence habitat selection. We evaluated seasonal habitat use by resident adult wolverines using radiotelemetry locations from 2 multiple-use landscapes in British Columbia. Food, predation risk, and human disturbance hypotheses were considered in logistic regression analyses of used and random landscapes. Male wolverine habitat associations were most supported by the food hypothesis in both summer and winter. Moose (Alces alces) winter ranges, valley bottom forests, and avalanche terrain were positively associated with winter male wolverine use. Habitat use by male wolverines in winter was also negatively associated with helicopter skiing areas in the Columbia Mountains. Habitat associations of females were more complex; combinations of variables supporting food, predation risk, or human disturbance hypotheses were included in most supported models from both summer and winter in both study areas. Females were associated with alpine and avalanche environments where hoary marmot (Marmota caligata) and Columbia ground squirrel (Spermophilus columbianus) prey are found in summer. Roaded and recently logged areas were negatively associated with female wolverines in summer. In the Columbia Mountains, where winter recreation was widespread, females were negatively associated with helicopter and backcountry skiing. Moose winter ranges within rugged landscapes were positively associated with females during winter. Our analysis suggests wolverines were negatively responding to human disturbance within occupied habitat. The population consequences of these functional habitat relationships will require additional focused research. Our spatially explicit models can be used to support conservation planning for resource extraction and tourism industries operating in landscapes occupied by wolverines.     

Estimating mountain goat abundance using DNA from fecal pellets

Non-invasive collection of tissue samples to obtain DNA for microsatellite genotyping required to estimate population size has been used for many wildlife species but rarely for ungulates. We estimated mountain goat (Oreamnos americanus) population size on a mountain complex in southwestern British Columbia by identification of individuals using DNA obtained from fecal pellet and hair samples collected during 3 sampling sessions. We identified 55 individuals from 170 samples that were successfully genotyped, and estimated a population of 77 mountain goats (SE = 7.4). Mean capture probability was 0.38 (SE = 0.037) per session. Our technique provides one of the first statistically rigorous estimates of abundance of an ungulate species using DNA derived primarily from fecal pellets. Our technique enables managers to obtain minimum counts or population estimates of ungulates in areas of low sightability that can be used for conservation and management. © 2011 The Wildlife Society.     

A Sightability Model for Mountain Goats

ABSTRACT Unbiased estimates of mountain goat (Oreamnos americanus) populations are key to meeting diverse harvest management and conservation objectives. We developed logistic regression models of factors influencing sightability of mountain goat groups during helicopter surveys throughout the Cascades and Olympic Ranges in western Washington during summers, 2004–2007. We conducted 205 trials of the ability of aerial survey crews to detect groups of mountain goats whose presence was known based on simultaneous direct observation from the ground (n = 84), Global Positioning System (GPS) telemetry (n = 115), or both (n = 6). Aerial survey crews detected 77% and 79% of all groups known to be present based on ground observers and GPS collars, respectively. The best models indicated that sightability of mountain goat groups was a function of the number of mountain goats in a group, presence of terrain obstruction, and extent of overstory vegetation. Aerial counts of mountain goats within groups did not differ greatly from known group sizes, indicating that under-counting bias within detected groups of mountain goats was small. We applied Horvitz-Thompson-like sightability adjustments to 1,139 groups of mountain goats observed in the Cascade and Olympic ranges, Washington, USA, from 2004 to 2007. Estimated mean sightability of individual animals was 85% but ranged 0.75–0.91 in areas with low and high sightability, respectively. Simulations of mountain goat surveys indicated that precision of population estimates adjusted for sightability biases increased with population size and number of replicate surveys, providing general guidance for the design of future surveys. Because survey conditions, group sizes, and habitat occupied by goats vary among surveys, we recommend using sightability correction methods to decrease bias in population estimates from aerial surveys of mountain goats.     

Breach of the northern Rocky Mountain geoclimatic barrier: initiation of range expansion by the mountain pine beetle

Aim Our aim is to examine the historical breach of the geoclimatic barrier of the Rocky Mountains by the mountain pine beetle (Dendroctonus ponderosae Hopkins). This recent range expansion from west of the North American continental divide into the eastern boreal forest threatens to provide a conduit to naïve pine hosts in eastern North America. We examine the initial expansion events and determine potential mechanism(s) of spread by comparing spread patterns in consecutive years to various dispersal hypotheses such as: (1) meso‐scale atmospheric dispersal of insects from source populations south‐west of the Rocky Mountains in British Columbia (i.e. their historical range), (2) anthropogenic transport of infested plant material, and (3) spread of insect populations across adjacent stands via corridors of suitable habitat. Location British Columbia, Canada. Methods We explore potential mechanism(s) of invasion of the mountain pine beetle using spatial point process models for the initial 3 years of landscape‐level data collection, 2004–2006. Specifically, we examine observed patterns of infestation relative to covariates reflecting various dispersal hypotheses. We select the most parsimonious models for each of the initial 3 years of invasion using information criteria statistics. Results The initial range expansion and invasion of the beetle was characterized by aerial deposition along a strong north‐west to south‐east gradient, with additional aerial deposition and localized dispersal from persisting populations in following years. Main conclusions Following deposition of a wave front of mountain pine beetles parallel to the Rocky Mountains via meso‐scale atmospheric dispersal, the areas of highest intensity of infestations advanced up to 25 km north‐east towards jack pine (Pinus banksiana) habitat in a single year. There appeared to be no association between putative anthropogenic movement of infested materials and initial range expansion of the mountain pine beetle across the continental divide.     

A piecewise linear modeling approach for testing competing theories of habitat selection: an example with mule deer in northern winter ranges

Habitat selection fundamentally drives the distribution of organisms across landscapes; density-dependent habitat selection (DDHS) is considered a central component of ecological theories explaining habitat use and population regulation. A preponderance of DDHS theories is based on ideal distributions, such that organisms select habitat according to either the ideal free, despotic, or pre-emptive distributions. Models that can be used to simultaneously test competing DDHS theories are desirable to help improve our understanding of habitat selection. We developed hierarchical, piecewise linear models that allow for simultaneous testing of DDHS theories and accommodate densities from multiple habitats and regional populations, environmental covariates, and random effects. We demonstrate the use of these models with data on mule deer (Odocoileus hemionus) abundance and net energy costs in different snow depths within winter ranges of five regional populations in western Idaho, USA. Regional population density explained 40 % of the variation in population growth, and we found that deer were ideal free in winter ranges. Deer occupied habitats with lowest net energy costs at higher densities and at a higher rate than compared to habitats with intermediate and high energy costs. The proportion of a regional population in low energy cost habitat the previous year accounted for a significant amount of variation in population growth (17 %), demonstrating the importance of winter habitat selection in regulating deer populations. These linear models are most appropriate for empirical data collected from centralized habitat patches within the local range of a species where individuals are either year-round residents or migratory (but have already arrived from migration).     

Are latrine sites an accurate predictor of seasonal habitat selection by river otters (<Emphasis Type="Italic">Lontra canadensis</Emphasis>) in freshwater systems?

Temporal variation in the availability of food resources is a likely driving factor influencing the distribution and habitat use of river otters (Lontra canadensis). Although latrine sites are commonly used to determine habitat selection, it is unclear if latrine sites are an accurate predictor or even a useful indicator of the seasonal habitat use and distribution of river otters. We apply resource selection functions (RSF) to both latrine and telemetry locations to investigate whether latrine sites identified along lake shorelines during the ice-free season are appropriate predictors of otter habitat selection along shorelines during the ice-free and ice-cover seasons in central British Columbia, Canada. We found that the top models describing otter latrine sites and telemetry locations during the ice-free season were similar. The top RSF models and associated coefficients for the ice-cover season differed, however, with otter presence being positively influenced by shallower water depths. For the spatial extrapolation of averaged RSF coefficients, we found that 21.4 and 69.3 % of predicted latrine habitat along lake shorelines overlapped with ice-cover and ice-free habitat generated from telemetry locations, respectively. The location and activity at latrine sites appear to be a useful method for monitoring otter distribution and habitat use during the ice-free, but not during the ice-cover season. The results of our RSF analyses as well as home range measurements of otters in our study area suggest that cold temperatures and ice cover may be a limiting factor for the distribution of otter populations at northern latitudes.     

基于核密度估计的动物生境适宜度制图方法

生境适宜度制图能提供动物适宜生境的空间分布信息,对野生动物种群管理、保护地规划等非常重要。生境适宜度制图的关键是构建生境适宜度模型(habitat suitability model, HSM),只基于动物出现位置数据构建HSM的方法在实践中得到了非常广泛的应用。然而现有的只基于动物出现位置数据构建HSM的方法还不能很好地直接表达动物生境适宜度和环境因子之间具有生态学意义的数量关系,因此也就不能很好地体现环境因子对动物生境利用的生态学作用。 本文提出了一种基于核密度估计构建HSM的方法,在地理信息系统技术支持下,通过运用核密度估计从代表性的动物出现位置数据中估计出动物出现对各个环境因子的概率密度函数来直接表达生境适宜度与各个环境因子之间的数量关系,以体现环境因子对动物生境利用的生态学作用,在此基础上对生境适宜度与各个环境因子之间的数量关系进行综合构建了具有明确生态学意义的HSM用于动物生境适宜度制图。以美国Voyageures国家公园的白尾鹿(Odocoileus virginianus)生境适宜度制图为例,基于365个出现位置点位数据并结合积雪深度、地表覆被类型、森林边界长度和坡度等环境因子数据,开展了该方法的案例研究。通过交叉验证计算连续Boyce指数对制图结果进行评价,结果表明：基于核密度估计方法构建的HSM预测能力强,所得出的生境适宜度图经10次交叉验证,连续Boyce指数平均值为0.75,标准差为0.11,达到了较高精度。此外,由于基于核密度估计的方法能以“生境适宜度和环境因子之间具有生态学意义的数量关系”的形式来直接体现环境因子对动物生境利用的生态学作用,就模型的可解释性而言,该方法要优于现有的其他构建HSM的方法。     

An open spatial capture–recapture model for estimating density,movement, and population dynamics from line‐transect surveys

The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line‐transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture–recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture–recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture–recapture model that can be applied to line‐transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line‐transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line‐transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.     

Scale for resource selection functions

Resource selection functions (RSFs) are statistical models defined to be proportional to the probability of use of a resource unit. My objective with this review is to identify how RSFs can be used to unravel the influence of scale in habitat selection. In wildlife habitat studies, including radiotelemetry, RSFs can be estimated using a variety of statistical methods, all of which can be used to explore the role of scale. All RSFs are bounded by the resolution of data and the spatial extent of the study area, but also allow predictor covariates to be measured at a variety of scales. Conditional logistic regression permits designs (e.g. matched case) that relate the process of habitat selection to a limited domain of resource units that might better characterize what is truly ‘available’ to the animal. Scale influences the process of habitat selection, e.g. food resources are often selected at fine spatial scales, whereas landscape patterns at much larger scales typically influence the location of home ranges. Scale also influences appropriate sampling in many ways: (1) heterogeneity might be obliterated (transmutation) if resolution or grain size is too large, (2) variance of habitat characteristics might be undersampled if extent or domain is too small, (3) timing and duration of observations can influence RSF models, and (d) both spatial and temporal autocorrelations can vary directly with the intensity of sampling. Using RSFs, researchers can examine habitat selection at multiple scales, and predictive models that bridge scales can be estimated. Using Geographical Information Systems, predictor covariates in RSF models can be measured at different scales easily so that the predictive ability of models at alternative spatial and temporal domains can be explored by the investigator. Identification of the scale that best explains the data can be evaluated by comparing alternative models using information‐theoretic metrics such as Akaike Information Criteria, and predictive capability of the models can be assessed using k‐fold cross validation.     

Factors influencing the reaction of mountain goats towards all-terrain vehicles

The increasing popularity of recreational activities in the wild has led to concerns about their potential impacts on wildlife. All-terrain vehicles (ATVs) often bring people into wildlife habitats, where they may disturb animal populations. We assessed the influence of ATVs on the behavior of mountain goats (Oreamnos americanus) in a long-term study population at Caw Ridge, Alberta, Canada. We used multinomial models containing environment-, disturbance-, and group-related factors, to evaluate the response of mountain goats to the approach of ATVs. Goats were moderately to strongly disturbed by ATVs 44% of the time, and disturbance levels were mainly influenced by the direction and speed of the approaching vehicles. Environment- or group-related factors (e.g., time of year, distance to escape terrain, group size or type) did not affect mountain goat responses to ATVs. Because goat reactions were influenced by disturbance-level factors, we propose mitigating measures regarding the use of ATVs in the wild to minimize the disturbance to mountain goats, and potentially other alpine ungulates. © 2012 The Wildlife Society.     

Heading for the hills? Evaluating spatial distribution of woodland caribou in response to a growing anthropogenic disturbance footprint

Anthropogenic landscape change (i.e., disturbance) is recognized as an important factor in the decline and extirpation of wildlife populations. Understanding and monitoring the relationship between wildlife distribution and disturbance is necessary for effective conservation planning. Many studies consider disturbance as a covariate explaining wildlife behavior. However, we propose that there are several advantages to considering the spatial relationship between disturbance and wildlife directly using utilization distributions (UDs), including objective assessment of the spatially explicit overlap between wildlife and disturbance, and the ability to track trends in this relationship over time. Here, we examined how central mountain woodland caribou (Rangifer tarandus caribou) distribution changed over time in relation to (i) anthropogenic disturbance, baseline range (defined using telemetry data from 1998 to 2005), and alpine habitat; and (ii) interannual climate variation (North Pacific Index; NPI). We developed seasonal UDs for caribou in west‐central Alberta and east‐central British Columbia, Canada, monitored with GPS collars between 1998 and 2013. We mapped the cumulative annual density of disturbance features within caribou range and used indices of overlap to determine the spatial relationship and trend between caribou UDs, anthropogenic disturbance, baseline range, alpine habitat, and the NPI. Anthropogenic disturbance increased over time, but the overlap between caribou UDs and disturbance did not. Caribou use of alpine habitat during spring, fall, and late winter increased over time, concurrent with a decrease in use of baseline range. Overlap between caribou UDs and disturbance increased during spring and fall following relatively cold, snowy winters (high NPI), but overall, climate did not explain changes in caribou distribution over time. We provide evidence supporting the hypothesis that caribou populations adjust their spatial distribution in relation to anthropogenic landscape change. Our findings could have implications for population persistence if distributional shifts result in greater use of alpine habitat during winter. Monitoring long‐term changes in the distribution of populations is a valuable component of conservation planning for species at risk in disturbed landscapes.     

Hyperspectral Analysis of Columbia Spotted Frog Habitat

Abstract: Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96% (44 wetlands) correctly classified with the 2002 data and 89% (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74% (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72% (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats.     

SCALE-DEPENDENT SUMMER RESOURCE SELECTION BY REINTRODUCED ELK IN WISCONSIN,USA

Abstract: Identifying how habitat use is influenced by environmental heterogeneity at different scales is central to understanding ungulate population dynamics on complex landscapes. We used resource selection functions (RSF) to study summer habitat use in a reintroduced and expanding elk (Cervus elaphus nelsoni) population in the Chequamegon National Forest, Wisconsin, USA. Factors were examined that influenced where elk established home ranges and that influenced habitat use within established home ranges. We also determined grain sizes over which elk responded to environmental heterogeneity and the number of categories of habitat selection from low to high that the elk distinguished. At a large spatial extent, elk home-range establishment was largely explained by the spatial distribution of wolf (Canis lupus) territories. Forage abundance was also influential but was relatively more important at a small spatial extent when elk moved within established home ranges. Areas near roads were avoided when establishing a home-range, but areas near roads were selected for use within the established home range. Elk distinguished among 4 different categories of habitat selection when establishing and moving within home ranges. Spatial and temporal cross validation demonstrated that to improve the predictive strength of habitat models in areas of low inter-annual variability in the environment, it is better to follow more individuals across diverse environmental conditions than to follow the same individuals over a longer time period. Last, our results show that the effects of environmental variables on habitat use were scale-dependent and reemphasize the necessity of analyzing habitat use at multiple scales that are fit to address specific research questions.     

Influence of interspecific competition on mule deer birthing and rearing site selection

Ungulates often alter behavior and space use in response to interspecific competition. Despite observable changes in behavior caused by competitive interactions, research describing the effects of competition on survival or growth is lacking. We used spatial modeling to determine if habitat use by female mule deer (Odocoileus hemionus) was affected by other ungulate species prior to, during, and after parturition. We conducted our study in the Book Cliffs region of eastern Utah, USA, during 2019 and 2020. We used resource selection function (RSF) analysis to model space use of 4 ungulate species that potentially competed with mule deer: bison (Bos bison), cattle, elk (Cervus canadensis), and feral horses. We incorporated RSF models for competing species into a random forest analysis to determine if space use by mule deer was influenced by these other ungulate species. We used survival and growth data from neonate mule deer to directly assess potential negative effects of other ungulates. Habitat use by elk was an important variable in predicting use locations of mule deer during birthing and rearing. The relationship was positive, suggesting interference competition was not occurring. Survival of neonate mule deer increased as the probability of use by elk increased (hazard ratio = 0.185 ± 0.497 [SE]). Further, probability of use by elk in rearing habitat had no influence on growth of neonate mule deer from birth to 6 months of age, suggesting that exploitative competition was not occurring.