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Narrow endemism presents challenges to species occurrence modeling particularly when the distribution of key local habitat features changes across space and time as a function of processes operating at larger scales. One need facing conservation in such settings is a better understanding of the biogeographic dynamics of the larger features that govern occurrence of critical local habitat. The Mescalero–Monahans shinnery sands region of western North America is a dynamic landscape where sand shinnery oak interacts with wind-driven sand to establish dune habitat. This ecosystem supports several narrowly endemic dune-dwelling species including the dunes sagebrush lizard. Using near-anniversary satellite and aerial imagery from 1986, 1998, and 2011, we integrated object-based image classification and statistical analysis to develop and validate a spatially explicit estimate of the sand shinnery oak ecosystem, including dynamics associated with its attrition and emergence, at high resolution throughout an 89,849-km2 study area encompassing the range of the dunes sagebrush lizard. The spatial estimate of the distribution and extent of the sand shinnery oak soil-vegetation association validated reasonably well (overall accuracy = 0.79; sensitivity = 0.49; specificity = 0.91) and showed that the association declined 10.3 % in extent during the 25-year assessment window. The presence of sand shinnery oak, patch size, and patch isolation were dynamic across space and time; a regression model showed that smaller, isolated patches on the periphery of the system were more likely to be lost over time whereas larger, less isolated, and centrally distributed patches were more likely to persist or expand. This study details broadly applicable methods to accurately delineate landforms throughout large extents, and offers mapping tools specific to issues surrounding Mescalero–Monahans shinnery sands endemics that are readily amenable to testing, refinement, and application in efforts to focus sustainable landscape management including conservation of endemic species.

Prioritizing habitat for animal conservation in heterogeneous landscapes requires an understanding of where animal occurrence coincides with human influences on demographic performance. We related broad-scale patterns of occurrence with risk of mortality among female Rocky Mountain elk (Cervus elaphus) in a human-modified landscape to develop a spatially-explicit framework for animal conservation at the landscape level. Variability in the spatial pattern of elk occurrence was driven by preference for specific habitat types as well as responses to human activity. In contrast, risk of mortality was a function of human modification of the landscape with little variation explained by habitat. Proximity to industrial development was associated with increased risk of mortality whereas proximity to residences and agricultural structures was associated with decreased risk. Individual-level results revealed added complexity, whereby risk of mortality was associated with a consistent pattern of occurrence relative to industrial development, yet the association between risk and occurrence relative to structures was highly variable and likely a function of disparate land-use priorities. Approaches to managing human-mediated risk at the landscape level are most effective when they decompose human activity into constituent parts influencing risk, and when individual variation relative to the population response is investigated. Conservation interventions need to target factors that have a consistent influence across the population rather than risk uncertainty that would arise from targeting factors that influence individuals in variable or situation-specific ways. The spatial tools developed herein provide guidance for sustainable landscape planning in the study area, while the concept of linking occurrence and demographic performance within a hierarchical modeling framework has general application for animal conservation in landscapes subject to change, human-caused or otherwise.

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.

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.

Animal populations are becoming increasingly exposed to human activity as human populations expand and demand for energy resources (e.g., coal, oil and natural gas) increases. We initiated this study to document survival and cause-specific mortality patterns of female Rocky Mountain elk (Cervus elaphus) exposed to increasing levels of human activity. We fitted 184 females with VHF or GPS collars over 4 years and used the Kaplan–Meier survival estimator to calculate annual survival rates. We used multinomial logistic regression to assess differences in cause-specific mortality and generalized linear mixed models to determine how probability of survival was structured during hunting season; both analyses examined a suite of 5 covariates (i.e., age, year, extent of space use, cover, and human footprint) as potentially influencing cause-specific mortality and survival probability. Annual probability of survival averaged 0.8 (±0.02 SE) over 4 years but averaged 0.91 (±0.03 SE) when harvest mortality was excluded, which was the most significant source of mortality in most years (\( \bar{x} = 0.13 \pm 0.02\,{\text{SE}} \)). We found no difference between cause-specific mortality sources relative to elk that survived during the hunting season (χ102 = 5.79, P = 0.832). The probability of a female surviving during hunting season was negatively influenced by age, year, extent of space use, cover, and human footprint. We found evidence that human activity may have influenced annual rates of natural survival (i.e., exclusive of hunting mortality) and probability of survival during the hunting season. We note that this study occurred largely on privately owned and managed residential and ranch land and focused on female elk; we acknowledge that survival rate and cause-specific patterns of mortality may vary as a function of land ownership (private vs. public), demographic status, and management and harvest practices. While temporal and spatial scales of 1 week may be sufficient to describe patterns of direct mortality during hunting season, broad temporal or spatial scale analyses may be needed to address natural mortality during other seasons.