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Abstract Background Movement plays a key role in allowing animal species to adapt to sudden environmental shifts. Anthropogenic climate and land use change have accelerated the frequency of some of these extreme disturbances, including megafire. These megafires dramatically alter ecosystems and challenge the capacity of several species to adjust to a rapidly changing landscape. Ungulates and their movement behaviors play a central role in the ecosystem functions of fire-prone ecosystems around the world. Previous work has shown behavioral plasticity is an important mechanism underlying whether large ungulates are able to adjust to recent changes in their environments effectively. Ungulates may respond to the immediate effects of megafire by adjusting their movement and behavior, but how these responses persist or change over time following disturbance is poorly understood. Methods We examined how an ecologically dominant ungulate with strong site fidelity, Columbian black-tailed deer (Odocoileus hemionus columbianus), adjusted its movement and behavior in response to an altered landscape following a megafire. To do so, we collected GPS data from 21 individual female deer over the course of a year to compare changes in home range size over time and used resource selection functions (RSFs) and hidden Markov movement models (HMMs) to assess changes in behavior and habitat selection. Results We found compelling evidence of adaptive capacity across individual deer in response to megafire. Deer avoided exposed and severely burned areas that lack forage and could be riskier for predation immediately following megafire, but they later altered these behaviors to select areas that burned at higher severities, potentially to take advantage of enhanced forage. Conclusions These results suggest that despite their high site fidelity, deer can navigate altered landscapes to track rapid shifts in encounter risk with predators and resource availability. This successful adjustment of movement and behavior following extreme disturbance could help facilitate resilience at broader ecological scales.

Abstract Many wildlife species vary habitat selection across space, time, and behavior to maximize rewards and minimize risk. Multi‐scale research approaches that identify variation in wildlife habitat selection can highlight not only habitat preferences and risk tolerance but also movement strategies that afford coexistence or cause conflict with humans. Here, we examined how anthropogenic and natural features influenced coyote (Canis latrans) habitat selection in a mixed‐use, agricultural landscape in Mendocino County, California, USA. We used resource selection functions and hidden Markov models to test whether coyote selection for anthropogenic and natural features varied by time of day or by behavioral state (resting, foraging, and traveling). We found that coyotes avoided development, but, contrary to our expectations, coyotes selected for roads, agriculture, and areas with risk of human encounter and rifle use regardless of diel period or behavioral state. While traveling, coyotes increased selection for roads and avoided ruggedness, indicating that unpaved roads may enhance connectivity for coyotes in mixed‐use landscapes. Finally, we found that coyotes selected for mountain lion habitat when resting and at night, signifying that risk from natural predators was not a factor in habitat selection at coarse scales. Coyote habitat selection for places and times associated with human activity, without variation across scales, signals a potential for conflict if coyotes are perceived by people as a nuisance.

Abstract Background As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems. Yet compared to non-human predators, little is known about the movement ecology of human hunters, including how hunting behavior interacts with the environment. Methods We characterized the hunting modes, habitat selection, and harvest success of 483 rifle hunters in California using high-resolution GPS data. We used Hidden Markov Models to characterize fine-scale movement behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Finally, we used Resource Selection Functions to quantify patterns of habitat selection for successful and unsuccessful hunters of each hunting mode. Results Hunters exhibited three distinct and successful hunting modes (“coursing”, “stalking”, and “sit-and-wait”), with coursings as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with differences in habitat use of successful and unsuccessful hunters across modes. Conclusions Our study indicates that hunters can successfully employ a diversity of harvest strategies, and that hunting success is mediated by the interacting effects of hunting mode and landscape features. Such results highlight the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.

Abstract Human–wildlife interactions are increasing in severity due to climate change and proliferating urbanization. Regions where human infrastructure and activity are rapidly densifying or newly appearing constitute novel environments in which wildlife must learn to coexist with people, thereby serving as ideal case studies with which to infer future human–wildlife interactions in shared landscapes. As a widely reviled and behaviorally plastic apex predator, the spotted hyena (Crocuta crocuta) is a model species for understanding how large carnivores navigate these human‐caused ‘landscapes of fear’ in a changing world. Using high‐resolution GPS collar data, we applied resource selection functions and step selection functions to assess spotted hyena landscape navigation and fine‐scale movement decisions in relation to social–ecological features in a rapidly developing region comprising two protected areas: Lake Nakuru National Park and Soysambu Conservancy, Kenya. We then used camera trap imagery and Barrier Behavior Analysis (BaBA) to further examine hyena interactions with barriers. Our results show that environmental factors, linear infrastructure, human–carnivore conflict hotspots, and human tolerance were all important predictors for landscape‐scale resource selection by hyenas, while human experience elements were less important for fine‐scale hyena movement decisions. Hyena selection for these characteristics also changed seasonally and across land management types. Camera traps documented an exceptionally high number of individual spotted hyenas (234) approaching the national park fence at 16 sites during the study period, and BaBA results suggested that hyenas perceive protected area boundaries' semi‐permeable electric fences as risky but may cross them out of necessity. Our findings highlight that the ability of carnivores to flexibly respond within human‐caused landscapes of fear may be expressed differently depending on context, scale, and climatic factors. These results also point to the need to incorporate societal factors into multiscale analyses of wildlife movement to effectively plan for human–wildlife coexistence.

Abstract Increasingly frequent megafires are dramatically altering landscapes and critical habitats around the world. Across the western United States, megafires have become an almost annual occurrence, but the implication of these fires for the conservation of native wildlife remains relatively unknown. Woodland savannas are among the world's most biodiverse ecosystems and provide important food and structural resources to a variety of wildlife, but they are threatened by megafires. Despite this, the great majority of fire impact studies have only been conducted in coniferous forests. Understanding the resistance and resilience of wildlife assemblages following these extreme perturbations can help inform future management interventions that limit biodiversity loss due to megafire. We assessed the resistance of a woodland savanna mammal community to the short‐term impacts of megafire using camera trap data collected before, during, and after the fire. Specifically, we utilized a 5‐year camera trap data set (2016–2020) from the Hopland Research and Extension Center to examine the impacts of the 2018 Mendocino Complex Fire, California's largest recorded wildfire at the time, on the distributions of eight observed mammal species. We used a multispecies occupancy model to quantify the effects of megafire on species' space use, to assess the impact on species size and diet groups, and to create robust estimates of fire's impacts on species diversity across space and time. Megafire had a negative effect on the detection of certain mammal species, but overall, most species showed high resistance to the disturbance and returned to detection and site use levels comparable to unburned sites by the end of the study period. Following megafire, species richness was higher in burned areas that retained higher canopy cover relative to unburned and burned sites with low canopy cover. Fire management that prevents large‐scale canopy loss is critical to providing refugia for vulnerable species immediately following fire in oak woodlands, and likely other mixed‐forest landscapes.

Abstract Coincident with international movements to protect 30% of land and sea over the next decade (“30×30”), the United States has committed to more than doubling its current protected land area by 2030. While publicly owned and managed protected areas have been the cornerstone of area‐based conservation over the past century, such lands are costly to establish and have limited capacity to protect areas of the highest value for biodiversity conservation and climate change mitigation. Here we examine the current and potential contributions of private land for reaching 30×30 conservation targets at both federal and state scales in the United States. We find that compared to publicly owned and managed protected lands, protected private lands (conservation easements) are more often in areas designated as high conservation priority, hold significantly higher mean species richness, and sequester more vulnerable land‐based carbon per unit area. These and related findings highlight the necessity of mechanisms that engage private landholders in enduring conservation partnerships.

Abstract 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.