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Non-charismatic species are often understudied, despite having unique ecological roles that are important to understand and value for ecosystem integrity, function, and health. Striped skunks (Mephitis mephitis) are one such species, as they are stigmatized and feared due to their noxious smell and potential for spreading rabies. Yet this species often co-occurs with humans, occupying a distinct but poorly understood ecological niche. To better understand this understudied species and its unique niche, we used a Bayesian N-mixture model to estimate factors driving the local abundance of striped skunks at a continent-wide scale using data from the Snapshot USA programs in 2019 and 2020. In our modelling approach, we included factors that we a-priori hypothesized would affect striped skunk local abundance, including habitat, agriculture, primary productivity, and anthropogenic factors. We found that skunks were most abundant in more productive and anthropogenically affected areas. The factors driving abundance (in order of effect) were primary productivity, impervious surface, cultivated land, and cultivated-wetland edge cover. While our results underscore striped skunks’ role as a synanthropic species that co-occurs with humans, they are more of a synanthropic misanthrope, as their close relationship with people often causes them to suffer persecution and death. But their relationship with highly productive areas also highlights how striped skunks are habitat generalists that exploit resources in many different types of habitats. Our analysis highlights the importance of programs like Snapshot USA that collect standardized data across large geographic areas and allow broad-scale studies for evaluating the local abundance of understudied species. Using these data, we were able to provide foundational information on the relative importance of the major factors affecting the local abundance of striped skunks, with implications for the management and conservation of this unique and understudied mesocarnivore across its range.

Wildlife are under continuous pressure to adapt to new environments as more land area is converted for human use and human populations continue to concentrate in suburban and exurban areas. This is especially the case for terrestrial mammals, which are forced to navigate these habitat matrices on foot. One way in which mammals may occupy urbanized landscapes is by altering their temporal activity behavior. Typically, studies have found that mammals increase their nocturnal activity within urbanized environments to avoid overlap with humans. However, to date, the majority of studies on this topic have focused on single species, and studying whether this trend holds across an entire community has important ecological implications. Specifically, understanding how differences in species temporal activity response alters predator-prey dynamics and sympatric interspecies competition can provide insight into urban wildlife community assembly and provide a mechanistic understanding of species co-occurrence within these systems. In this study, we used data from a community science camera trapping project in northern Utah to elucidate how human influence alters the temporal activity behavior of five medium- to large-sized mammals and how differences in species response affect predator-prey, human, and sympatric competitor temporal niche overlap. We found community-wide changes in activity across study sites, with increases in late night and midday activity and decreases in crepuscular activity within the more-urbanized site. However, species-specific behavioral changes varied, and these changes resulted in reduced overlap, especially between coyotes (Canis latrans) and their potential prey species. These results provide information on how human influence may alter community assembly and species-species interactions within a wildland-urban interface.

Abstract Human development and roads threaten wildlife through distinct mechanisms and understanding the influence of these elements can better inform mitigation and conservation strategies. We used camera traps to quantify the effects of major roads, environmental factors, and human development on the mammalian community composition between sites north and south of a major interstate highway in northern Utah, USA. We found no significant differences in species richness nor community similarity across the north–south divide of the highway. Through Bayesian hierarchical modeling, we compared the effects of the distance to the highway, housing and human population density, normalized difference vegetation index (NDVI), and the human footprint index to changes in mammalian community composition and species‐specific habitat usage. Community occupancy response, similarity, and species richness were negatively affected by increased housing and human population densities and positively affected by increased NDVI and decreased human footprint, whereas their response to the highway was more inconclusive. We conclude that mammalian community composition in our study area is influenced by both environmental conditions and human development while the effect of the highway was more nuanced, possibly due to the presence of a newly constructed wildlife overpass. Taken together, the lack of differences in species richness or community composition across the highway suggests that it may not currently exacerbate the effects of other anthropogenic sources of habitat fragmentation and highlights the need for additional research into human–wildlife conflict mitigation strategies.

Camera traps have become an important research tool for both conservation biologists and wildlife managers. Recent advances in spatially explicit capture-recapture (SECR) methods have increasingly put camera traps at the forefront of population monitoring programs. These methods allow for benchmark analysis of species density without the need for invasive fieldwork techniques. We conducted a review of SECR studies using camera traps to summarize the current focus of these investigations, as well as provide recommendations for future studies and identify areas in need of future investigation. Our analysis shows a strong bias in species preference, with a large proportion of studies focusing on large felids, many of which provide the only baseline estimates of population density for these species. Furthermore, we found that a majority of studies produced density estimates that may not be precise enough for long-term population monitoring. We recommend simulation and power analysis be conducted before initiating any particular study design and provide examples using readily available software. Furthermore, we show that precision can be increased by including a larger study area that will subsequently increase the number of individuals photo-captured. As many current studies lack the resources or manpower to accomplish such an increase in effort, we recommend that researchers incorporate new technologies such as machine-learning, web-based data entry, and online deployment management into their study design. We also cautiously recommend the potential of citizen science to help address these study design concerns. In addition, modifications in SECR model development to include species that have only a subset of individuals available for individual identification (often called mark-resight models), can extend the process of explicit density estimation through camera trapping to species not individually identifiable.