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Carnivore predation on livestock is a complex management and policy challenge, yet it is also intrinsically an ecological interaction between predators and prey. Human-wildlife interactions occur in socioecological systems in which human and environmental processes are closely linked. However, underlying human-wildlife conflict and key to unpacking its complexity are concrete and identifiable ecological mechanisms that lead to predation events. To better understand how ecological theory accords with interactions between wild predators and domestic prey, we developed a framework to describe ecological drivers of predation on livestock. We based this framework on foundational ecological theory and current research on interactions between predators and domestic prey. We used this framework to examine ecological mechanisms (e.g., density-mediated effects, behaviorally mediated effects, and optimal foraging theory) through which specific management interventions operate, and we analyzed the ecological determinants of failure and success of management interventions in 3 case studies: snow leopards (Panthera uncia), wolves (Canis lupus), and cougars (Puma concolor). The varied, context-dependent successes and failures of the management interventions in these case studies demonstrated the utility of using an ecological framework to ground research and management of carnivore-livestock conflict. Mitigation of human-wildlife conflict appears to require an understanding of how fundamental ecological theories work within domestic predator-prey systems.

The rapid expansion of cannabis agriculture in the Western United States provides a rare opportunity to study how an abrupt change in land‐use policy affects local biodiversity. There is broad speculation that cannabis production on private land is expanding and having negative effects on aquatic and terrestrial ecosystems, yet there exist little empirical data to evaluate this concern. In this study, we mapped and characterized outdoor cannabis production during the first season of legal recreational production (2016) in a large legacy cannabis‐producing region of Southern Oregon, Josephine County. We descriptively compared cannabis farms to all available private parcels based on proximity to rivers/streams and undeveloped land and their overlap with carnivore richness. Using publicly available satellite imagery, we found approximately 1.34 km2 (331 acres) of cannabis cultivation within Josephine County during the first season of legal recreational production. Most cannabis production areas were small (median size 414 m2), spatially clustered at all observed scales, and recently established (67% were not visible in 2013–2014 pre‐legalization). When compared with all available private parcels, cannabis was preferentially located in forested areas, undeveloped land and slightly closer to rivers. Within riparian areas, farms were slightly closer to rivers with predicted occurrence of coho salmon (Oncorhynchus kisutch). While projected carnivore richness was similar between cannabis and all private parcels, projected fisher (Pekania pennanti) occupancy was more than five times higher on cannabis farms, with a median occupancy of 0.69 (interquartile range: 0.24–0.87). Our results establish a baseline for cannabis land cover at the time of early recreational legalization and rapid expansion and can be used to predict future patterns or ecological consequences of cannabis development in other production areas. Understanding the potential ecological impact of cannabis is increasingly important as legalization expands and may also offer insights into other rural land‐use change frontiers. [ABSTRACT FROM AUTHOR]

Over 20 years ago, ecologists were introduced to the site occupancy model (SOM) for estimating occupancy rates from detection‐nondetection data. In the ensuing decades, the SOM and its hierarchical modeling extensions have become mainstays of quantitative ecology, and estimating occupancy rates has become one of the most common applications of ecological field data. Here, we review 364 peer‐reviewed articles published between 2019–2021 that estimated occupancy. We first document broad patterns in study design and statistical methods to provide educators, developers of methodology and software, and ecologists with a clear picture of the landscape of methodologies used to estimate animal occupancy. Second, we conduct a focused review of a subset of 98 papers that applied the hierarchical SOM, drawing from methodological literature to identify discrepancies between SOM applications and methodological best practices. We discuss limits to statistical power, issues with model checking and model selection procedures, potential problems arising from unmodeled non‐independence, and reproducibility. We highlight areas of rapid advancement in interpreting animal occupancy related to animal movement, imperfect detection, and the occupancy–density relationship. We aim to help readers understand the landscape of methods available, motivate shifts toward robust and reproducible science, and inspire new software and methodological research. [ABSTRACT FROM AUTHOR]

An abstract of the study "Maximum Weight Capacity of Leaves Used by Tent-Roosting Bats: Implications for Social Structure," by Phoebe Parker-Shames and Bernal Rodriguez-Herrera, is presented.