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Site occupancy models (SOMs) are a common tool for studying the spatial ecology of wildlife. When observational data are collected using passive monitoring field methods, including camera traps or autonomous recorders, detections of animals may be temporally autocorrelated, leading to biased estimates and incorrectly quantified uncertainty. We presently lack clear guidance for understanding and mitigating the consequences of temporal autocorrelation when estimating occupancy models with camera trap data.We use simulations to explore when and how autocorrelation gives rise to biased or overconfident estimates of occupancy. We explore the impact of sampling design and biological conditions on model performance in the presence of autocorrelation, investigate the usefulness of several techniques for identifying and mitigating bias and compare performance of the SOM to a model that explicitly estimates autocorrelation. We also conduct a case study using detections of 22 North American mammals.We show that a join count goodness‐of‐fit test previously proposed for identifying clustered detections is effective for detecting autocorrelation across a range of conditions. We find that strong bias occurs in the estimated occupancy intercept when survey durations are short and detection rates are low. We provide a reference table for assessing the degree of bias to be expected under all conditions. We further find that discretizing data with larger windows decreases the magnitude of bias introduced by autocorrelation. In our case study, we find that detections of most species are autocorrelated and demonstrate how larger detection windows might mitigate the resulting bias.Our findings suggest that autocorrelation is likely widespread in camera trap data and that many previous studies of occupancy based on camera trap data may have systematically underestimated occupancy probabilities. Moving forward, we recommend that ecologists estimating occupancy from camera trap data use the join count goodness‐of‐fit test to determine whether autocorrelation is present in their data. If it is, SOMs should use large detection windows to mitigate bias and more accurately quantify uncertainty in occupancy model parameters. Ecologists should not use gaps between detection periods, which are ineffective at mitigating temporal structure in data and discard useful data. [ABSTRACT FROM AUTHOR]

Weasels (genus Mustela and Neogale) are of management concern as declining native species in some regions and invasive species in others. Regardless of the need to conserve or remove weasels, there is increasingly a need to use non‐invasive monitoring methods to assess population trends.We conducted a literature review and held the first ever International Weasel Monitoring Symposium to synthesise information on historical and current non‐invasive monitoring techniques for weasels. We also explored current limitations, opportunities, and areas of development to guide future research and long‐term monitoring.Our literature search revealed that in the past 20 years, camera traps were the most commonly used non‐invasive monitoring method (62% of studies), followed by track plates or scent stations designed to collect footprints (23%) and walking transects for tracks in snow or soil (8.7%).Experts agreed that the most promising non‐invasive monitoring techniques available include use of citizen scientist reporting, detection dogs, detecting tracks, non‐invasive genetic surveys, and enclosed or unenclosed camera trap systems. Because each technique has benefits and limitations, using a multi‐method approach is likely required.There is a need for strong commitment to dedicated monitoring that is replicated over space and time such that trend data can be ascertained to better inform future management action. The diversity of non‐invasive monitoring methods now available makes such monitoring possible with relatively minor commitments of funding and effort. [ABSTRACT FROM AUTHOR]

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Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'. [ABSTRACT FROM AUTHOR]

While museum voucher specimens continue to be the standard for species identifications, biodiversity data are increasingly represented by photographic records from camera traps and amateur naturalists. Some species are easily recognized in these pictures, others are impossible to distinguish. Here we quantify the extent to which 335 terrestrial nonvolant North American mammals can be identified in typical photographs, with and without considering species range maps. We evaluated all pairwise comparisons of species and judged, based on professional opinion, whether they are visually distinguishable in typical pictures from camera traps or the iNaturalist crowdsourced platform on a 4-point scale: (1) always, (2) usually, (3) rarely, or (4) never. Most (96.5%) of the 55,944 pairwise comparisons were ranked as always or usually distinguishable in a photograph, leaving exactly 2,000 pairs of species that can rarely or never be distinguished from typical pictures, primarily within clades such as shrews and small-bodied rodents. Accounting for a species geographic range eliminates many problematic comparisons, such that the average number of difficult or impossible-to-distinguish species pairs from any location was 7.3 when considering all species, or 0.37 when considering only those typically surveyed with camera traps. The greatest diversity of difficult-to-distinguish species was in Arizona and New Mexico, with 57 difficult pairs of species, suggesting the problem scales with overall species diversity. Our results show which species are most readily differentiated by photographic data and which taxa should be identified only to higher taxonomic levels (e.g., genus). Our results are relevant to ecologists, as well as those using artificial intelligence to identify species in photographs, but also serve as a reminder that continued study of mammals through museum vouchers is critical since it is the only way to accurately identify many smaller species, provides a wealth of data unattainable from photographs, and constrains photographic records via accurate range maps. Ongoing specimen voucher collection, in addition to photographs, will become even more important as species ranges change, and photographic evidence alone will not be sufficient to document these dynamics for many species. [ABSTRACT FROM AUTHOR]

The establishment of protected areas (PAs) is a central strategy for global biodiversity conservation. While the role of PAs in protecting habitat has been highlighted, their effectiveness at protecting mammal communities remains unclear. We analyzed a global dataset from over 8671 camera traps in 23 countries on four continents that detected 321 medium‐ to large‐bodied mammal species. We found a strong positive correlation between mammal taxonomic diversity and the proportion of a surveyed area covered by PAs at a global scale (β = 0.39, 95% confidence interval [CI] = 0.19–0.60) and in Indomalaya (β = 0.69, 95% CI = 0.19–1.2), as well as between functional diversity and PA coverage in the Nearctic (β = 0.47, 95% CI = 0.09–0.85), after controlling for human disturbances and environmental variation. Functional diversity was only weakly (and insignificantly) correlated with PA coverage at the global scale (β = 0.22, 95% CI = −0.02–0.46), pointing to a need to better understand the functional response of mammal communities to protection. Our study provides important evidence of the global effectiveness of PAs in conserving terrestrial mammals and emphasizes the critical role of area‐based conservation in a post‐2020 biodiversity framework. [ABSTRACT FROM AUTHOR]

Managed public wild areas have dual mandates to protect biodiversity and provide recreational opportunities for people. These goals could be at odds if recreation, ranging from hiking to legal hunting, disrupts wildlife enough to alter their space use or community structure., We evaluated the effect of managed hunting and recreation on 12 terrestrial wildlife species by employing a large citizen science camera trapping survey at 1947 sites stratified across different levels of human activities in 32 protected forests in the eastern USA., Habitat covariates, especially the amount of large continuous forest and local housing density, were more important than recreation for affecting the distribution of most species. The four most hunted species (white-tailed deer, raccoons, eastern grey and fox squirrels) were commonly detected throughout the region, but relatively less so at hunted sites. Recreation was most important for affecting the distribution of coyotes, which used hunted areas more compared with unhunted control areas, and did not avoid areas used by hikers., Most species did not avoid human-made trails, and many predators positively selected them. Bears and bobcats were more likely to avoid people in hunted areas than unhunted preserves, suggesting that they perceive the risk of humans differently depending on local hunting regulations. However, this effect was not found for the most heavily hunted species, suggesting that human hunters are not broadly creating 'fear' effects to the wildlife community as would be expected for apex predators., Synthesis and applications. Although we found that hiking and managed hunting have measureable effects on the distribution of some species, these were relatively minor in comparison with the importance of habitat covariates associated with land use and habitat fragmentation. These patterns of wildlife distribution suggest that the present practices for regulating recreation in the region are sustainable and in balance with the goal of protecting wildlife populations and may be facilitated by decades of animal habituation to humans. The citizen science monitoring approach we developed could offer a long-term monitoring protocol for protected areas, which would help managers to detect where and when the balance between recreation and wildlife has tipped. [ABSTRACT FROM AUTHOR]

Camera trap surveys are useful to understand animal species population trends, distribution, habitat preference, behavior, community dynamics, periods of activity, and species associations with environmental conditions. This information is ecologically important, because many species play important roles in local ecosystems as predators, herbivores, seed dispersers, and disease vectors. Additionally, many of the larger wildlife species detected by camera traps are economically important through hunting, trapping, or ecotourism. Here we present a data set of camera‐trap surveys from 6,043 locations across all 100 counties of North Carolina, USA from 2009 to 2019. These data come from 26 survey initiatives and contain 215,108 records of 36 mammal species and three species of terrestrial birds. This large data set increases the geographical distribution data for these 39 mammal and bird species by >500% over what is available for North Carolina in the Global Biodiversity Information Facility (GBIF). These data can be used to conduct inquiries about species, populations, communities, or ecosystems, and to produce useful information on wildlife behavior, distribution, and interactions. There are no copyright restrictions. Please cite this paper when using the data for publication. [ABSTRACT FROM AUTHOR]

Trail networks are common infrastructure in protected areas for visitors to exercise, connect with nature, and learn about natural and cultural resources. However, there are concerns that the presence and construction of trails affect the quality of wildlife habitats, extending human disturbance into secluded areas. In this study, we developed a before-after control-impact experimental design to investigate the impacts of new trail construction on six terrestrial vertebrate species in an Appalachian protected area in the U.S. Using camera traps, we monitored animal use of the study area before, during, and after construction, on the trail, near the trail, and at a control site. Our results indicate statistically significant impacts of trail building and presence on four common species. During trail construction, white-tailed deer (Odocoileus virginianus) and coyotes (Canis latrans) decreased their activity on and/or near the trail, while raccoons (Procyon lotor) increased activity on the trail. These three species returned to the area at pre-building levels once trail construction was complete. After trail building, eastern gray squirrel (Sciurus carolinensis) showed decreased use of the trail area. We also observed altered timing of daily activity patterns for squirrels and deer, both diurnal species. Deer activity became more spread throughout the day within the near-trail zone during construction. After the trail was complete, squirrels shifted activity to earlier in the day, after sunrise and prior to the peak of recreational activity. We conclude that while trail building may alter habitat quality for some species, this mostly occurred during the construction phase, and was fairly minor for our study species. To minimize impacts, we suggest that trail building be restricted to a short time period during a season when species of concern are least sensitive. Our use of control sites allowed us to distinguish experimental effects from natural population fluctuations, and should serve as a foundation for future work investigating the effects of trails and other linear human disturbances on wildlife communities, especially in sensitive habitats and ecosystems. [ABSTRACT FROM AUTHOR]

Citizen science initiatives have shown promise to provide informal education about nature and conservation and simultaneously gather scientific data at large scales. eMammal is a platform for citizen science projects that recruits volunteers to place camera traps that collect data in the form of wildlife photographs. Our project offered informal education on wildlife ecology and conservation to volunteers through training materials, feedback during the project, and a natural history blog. We tested whether our education efforts and volunteer activities affected their project specific skills, wildlife knowledge, conservation attitudes, and what kind of information they shared with their social network. Volunteers accurately (> 90%) identified 15 of 20 wildlife species captured in the photos and reduced the rejection rate of camera placements over time. Our surveys showed that volunteer's attitudes toward conservation were high before joining the project and did not change after participating. However, volunteer knowledge of wildlife was higher after working with eMammal. Volunteers also became advocates for mammal conservation by sharing their new knowledge. Roughly half of our volunteers reported actively discussing some type of information related to wildlife both before (50%) and after (54%) the project. However, after volunteering they were 84% more likely to discuss local mammals or local mammal conservation. The likelihood of discussing local mammals was positively influenced by the number of predator photos captured by volunteers, showing that the type of experience can influence how information is spread through a volunteer's social network. Citizen science can connect people to the natural world while simultaneously providing reliable data for conservation. [ABSTRACT FROM AUTHOR]