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Species distribution models (SDMs) that rely on regional‐scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local‐scale anthropogenic variables, including wildfire history, land‐use change, invasive species, and ecological restoration practices can override regional‐scale variables to drive patterns of species distribution. Incorporating these human‐induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human‐induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field‐sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI: −6.9%, 0.6%) when one fire occurs and cover decreases by 44.7% (95% CI: −47.9%, −41.3%) if at least one fire occurred over the 36 year period of record. Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land‐use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species.

Carnivore and humans live in proximity due to carnivore recovery efforts and ongoing human encroachment into carnivore habitats globally. The American West is a region that uniquely exemplifies these human-carnivore dynamics, however, it is unclear how the research community here integrates social and ecological factors to examine human-carnivore relations. Therefore, strategies promoting human-carnivore coexistence are urgently needed. We conducted a systematic review on human-carnivore relations in the American West covering studies between 2000 and 2018.We first characterized human-carnivore relations across states of the American West. Second, we analyzed similarities and dissimilarities across states in terms of coexistence, tolerance, number of ecosystem services and conflicts mentioned in literature. Third, we used Bayesian modeling to quantify the effect of social and ecological factors influencing the scientific interest on coexistence, tolerance, ecosystem services and conflicts. Results revealed some underlying biases in humancarnivore relations research. Colorado and Montana were the states where the highest proportion of studies were conducted with bears and wolves the most studied species. Non-lethal management was the most common strategy to mitigate conflicts. Overall, conflicts with carnivores were much more frequently mentioned than benefits. We found similarities among Arizona, California, Utah, and New Mexico according to how coexistence, tolerance, services and conflicts are addressed in literature. We identified percentage of federal/private land, carnivore family, social actors, and management actions, as factors explaining how coexistence, tolerance, conflicts and services are addressed in literature. We provide a roadmap to foster tolerance towards carnivores and successful coexistence strategies in the American West based on four main domains, (1) the dual role of carnivores as providers of both

In migratory birds, among-and within-species heterogeneity in response to climate change may be attributed to differences in migration distance and environmental cues that affect timing of arrival at breeding grounds. We used eBird observations and a within-species comparative approach to examine whether migration distance (with latitude as a proxy) and weather predictors can explain spring arrival dates at the breeding site in a raptor species with a widespread distribution and diverse migration strategies, the American Kestrel Falco sparverius. We found an interactive effect between latitude and spring minimum temperatures on arrival dates, whereby at lower latitudes (short-distance migrants) American Kestrels arrived earlier in warmer springs and later in colder springs, but American Kestrels at higher latitudes (long-distance migrants) showed no association between arrival time and spring temperatures. Increased snow cover delayed arrival at all latitudes. Our results support the hypothesis that short-distance migrants are better able to respond to conditions on the breeding ground than are long-distance migrants, suggesting that long-distance migrants may be more vulnerable to shifts in spring conditions that could lead to phenological mismatch between peak resources and nesting.

The degree of coupling between the social and ecological components of social-ecological systems is seen as fundamental to understanding their functioning, interactions and trajectories. Yet, there is limited work about how to empirically understand the degree of coupling between social and ecological systems, nor the processes by which the degree of coupling could change over time. Here, we introduce a conceptual framework for characterizing trajectories over time of coupling and de-coupling in social-ecological river systems. We analyze two conceptual scenarios describing coupling and de-coupling trajectories in a social-ecological system and define a series of key concepts for understanding social-ecological system trajectories. We tested these coupling and de-coupling trajectories theory by linking these concepts to empirical case examples of two river social-ecological systems in the western United States. Finally, we propose a quantitative approach with the potential for evaluating the level of social-ecological coupling and de-coupling trajectories in other SES contexts. This paper represents an advancing on the identification of specific actions that explain current SES trajectories and immediate actions to reinforce or shift the trajectory.

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

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