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ABSTRACT Crowd‐sourced biodiversity data, such as those housed in the iNaturalist platform, are increasingly used to monitor species distributions. Such data represent unstructured biodiversity surveys that are generally comprised of incidental observations and do not report variation in sampling effort. These discrepancies may yield data that is incongruent with data from structured surveys. To assess whether mammalian iNaturalist data are reflective of data from traditional structured surveys, we calculated and compared measures of mammalian species richness and species pool similarity using data from unstructured surveys (i.e., iNaturalist) and data from structured camera trap surveys and bat acoustic surveys. We found that data from structured and unstructured surveys generally document similar mammalian species richness, but the two survey types document different species pools. Human population density and proxies for species pool breadth were most strongly associated with discrepancies in datasets, with data being most similar in areas of high human population density and lower species richness. Our analyses revealed that dataset similarity varied across geography and community metric for most taxa, but that structured and unstructured surveys produced consistently unreconcilable datasets for bats. These findings suggest that unstructured datasets like iNaturalist may offer reliable data for some taxa and geographies, but that these data are not universally applicable to all research scenarios. 

ABSTRACT Accurately estimating species distributions is critical for tracking how biodiversity is shaped by global change. While some species are expanding their ranges, the importance of factors like climate change, habitat change, and human avoidance for explaining this expansion is not well understood. Here, we used observations of 94 North American mammals on iNaturalist to (1) identify errors of omission in the existing range maps; (2) differentiate between extra‐range populations that are likely products of natural expansions vs. introductions; and (3) test hypotheses about where natural range expansions occur. We found a substantial percentage of observations were outside both IUCN (16%) and Area of Habitat (36%) maps, suggesting that integrating contemporary citizen science data would improve existing range maps. We estimated that most observations outside IUCN ranges were natural expansions and 95% of species had at least one naturally expanding population. We also identified introductions for 36% of species, which were particularly extensive for several species. We show that natural range expansions are generally associated with a lighter human footprint and less habitat change and are not associated with warming temperatures. This suggests that habitat modifications by humans constrain the ability of species to expand their range to track a changing climate. We also found substantial variation in the directionality of effects from all factors across species, meaning that our species‐specific findings will be useful for conservation planning. Our study demonstrates that citizen science data can be useful for conservation by tracking how organisms are responding, or failing to respond, to global change. 

Variation in animal abundance is shaped by scale‐dependent habitat, competition, and anthropogenic influences. CoyotesCanis latranshave dramatically increased in abundance while expanding their range over the past 100 years. Management goals typically seek to lower coyote populations to reduce their threats to humans, pets, livestock and sensitive prey. Despite their outsized ecological and social roles in the Americas, the factors affecting coyote abundance across their range remain unclear. We fit Royle–Nichols abundance models at two spatial scales in a Bayesian hierarchical framework to three years of data from 4587 camera trap sites arranged in 254 arrays across the contiguous USA to assess how habitat, large carnivores, anthropogenic development and hunting regulations affect coyote abundance. Coyote abundance was highest in southwestern USA and lowest in the northeast. Abundance responded to some factors as expected, including positive (soft mast, agriculture, grass/shrub habitat, urban–natural edge) and negative (latitude and forest cover) relationships. Colonization date had a negative relationship, suggesting coyote populations have not reached carrying capacity in recently colonized regions. Several relationships were scale‐dependent, including urban development, which was negative at local (100‐m) scales but positive at larger (5‐km) scales. Large carnivore effects were habitat‐dependent, with sometimes opposing relationships manifesting across variation in forest cover and urban development. Coyote abundance was higher where human hunting was permitted, and this relationship was strongest at local scales. These results, including a national map of coyote abundance, update ecological understanding of coyotes and can inform coyote management at local and landscape scales. These findings expand results from local studies suggesting that directly hunting coyotes does not decrease their abundance and may actually increase it. Ongoing large carnivore recoveries globally will likely affect subordinate carnivore abundance, but not in universally negative ways, and our work demonstrates how such effects can be habitat and scale dependent. 

Abstract ContextShifts in climate and land use have dramatically reshaped ecosystems, impacting the distribution and status of wildlife populations. For many species, data gaps limit inference regarding population trends and links to environmental change. This deficiency hinders our ability to enact meaningful conservation measures to protect at risk species. ObjectivesWe investigated historical drivers of environmental niche change for three North American weasel species (American ermine, least weasel, and long-tailed weasel) to understand their response to environmental change. MethodsUsing species occurrence records and corresponding environmental data, we developed species-specific environmental niche models for the contiguous United States (1938–2021). We generated annual hindcasted predictions of the species’ environmental niche, assessing changes in distribution, area, and fragmentation in response to environmental change. ResultsWe identified a 54% decline in suitable habitat alongside high levels of fragmentation for least weasels and region-specific trends for American ermine and long-tailed weasels; declines in the West and increased suitability in the East. Climate and land use were important predictors of the environmental niche for all species. Changes in habitat amount and distribution reflected widespread land use changes over the past century while declines in southern and low-elevation areas are consistent with impacts from climatic change. ConclusionsOur models uncovered land use and climatic change as potential historic drivers of population change for North American weasels and provide a basis for management recommendations and targeted survey efforts. We identified potentially at-risk populations and a need for landscape-level planning to support weasel populations amid ongoing environmental changes. 

There is an urgent need to develop global observation networks to quantify biodiversity trends for evaluating achievements of targets of Kunming-Montreal Global Biodiversity Framework. Camera traps are a commonly used tool, with the potential to enhance global observation networks for monitoring wildlife population trends and has the capacity to constitute global observation networks by applying a unified sampling protocol. The Snapshot protocol is simple and easy for camera trapping which is applied in North America and Europe. However, there is no regional camera-trap network with the Snapshot protocol in Asia. We present the first dataset from a collaborative camera-trap survey using the Snapshot protocol in Japan conducted in 2023. We collected data at 90 locations across nine arrays for a total of 6162 trap-nights of survey effort. The total number of sequences with mammals and birds was 7967, including 20 mammal species and 23 avian species. Apart from humans, wild boar, sika deer and rodents were the most commonly observed taxa on the camera traps, covering 57.9% of all the animal individuals. We provide the dataset with a standard format of Wildlife Insights, but also with Camtrap DP 1.0 format. Our dataset can be used for a part of the global dataset for comparing relative abundances of wildlife and for a baseline of wildlife population trends in Japan. It can also used for training machine-learning models for automatic species identifications. 

Abstract AimSynthesize literature on genetic structure within species to understand how geographic features and species traits influence past responses to climate change. LocationNorth America. Time PeriodWe synthesized phylogeographic studies from 1978 to 2023, which describe genetic lineages that diverged during the Pleistocene (≥11,700 years ago). Major Taxa StudiedMammals. MethodsWe conducted a literature review to map genetic breaks in species distributions, then tested a set of geographic hypotheses (e.g., mountains, rivers) to explain their position by comparing break locations to a grid within each species' sampled range using logistic regression. We then conducted a meta‐analysis using species‐specific model estimates to ask if life‐history traits explained variation in which barriers were most important in species' past response to climate change. ResultsOur findings reveal heterogeneity in both where North American mammal phylogeography has been studied and the density of genetic breaks across 229 species. We found relatively high concordance among carnivores, ungulates and lagomorphs, where breaks were associated with mountains, major water bodies and relatively even terrain. In contrast, we found high variability within rodents and shrews, and no evidence that intrinsic factors related to dispersal ability explained the importance of hypothesized barriers across all species. Main ConclusionsSouthern Mexico is a hotspot for genetic breaks that has yet to be integrated into the broader story of North American phylogeography. We show that mountains and major water bodies play particularly important roles as barriers, but substantial variation across species within orders suggests that there is more to the story besides shared climatic or phylogenetic histories. Thus, understanding the phylogeography of individual species will continue to be important given that our results suggest high variability in how species may respond to future global change. 

Abstract Small mustelids are difficult to survey due to their low density and cryptic nature. Population status of North American weasels (Mustela erminea,Mustela nivalis, andNeogale frenata) are believed to be in decline, but there are no standardized monitoring protocols to evaluate their status. To support weasel monitoring, we compared the attractiveness of various combinations of baits and lures to weasels in sites located throughout the eastern and central USA. We baited a total of 122 clusters of 4 camera traps, across 14 states, with random combinations of 4 baits and 3 scent lures in the winters of 2022 and 2023. Cameras baited with meat were 3.5 times more likely to detect both short‐ and long‐tailed weasels on average (mean percentage of cameras detecting weasels: 20–30%) than those with scent lures (3–11%). Red meat was twice as effective at attracting short‐tailed weasels (50%) as chicken or cat food (20%; Z = 2.49,p < 0.01). While red meat marginally increased detections of long‐tailed weasels (21%) compared to chicken and cat food (19%), its effectiveness was influenced by whether the bait was stolen (Z = 2.08,p = 0.04). Additionally, long‐tailed weasels were detected in half the time when raw chicken was used (median days to detection: red meat = 39.5 days, raw chicken = 14.5 days). When salmon oil was added to meat bait, it increased the likelihood of detecting short‐tailed weasels and reduced the time to detection for both species. A variety of non‐target species stole meat bait during the survey, making the camera traps less effective. The addition of salmon oil may have allowed for continual attraction of weasels until stolen meat bait could be replenished. In summary, red meat was the best all‐purpose bait for weasels, although raw chicken is similarly effective for long‐tailed weasels, and the addition of salmon oil is helpful. We also recommend a specific bait enclosure design that was the most effective at minimizing theft of bait. We propose our baiting strategy can be used as a survey standard to evaluate the distribution and population status of weasels. 

Abstract 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. 

Addressing the ongoing biodiversity crisis requires identifying the winners and losers of global change. Species are often categorized based on how they respond to habitat loss; for example, species restricted to natural environments, those that most often occur in anthropogenic habitats, and generalists that do well in both. However, species might switch habitat affiliations across time and space: an organism may venture into human-modified areas in benign regions but retreat into thermally buffered forested habitats in areas with high temperatures. Here, we apply community occupancy models to a large-scale camera trapping dataset with 29 mammal species distributed over 2,485 sites across the continental United States, to ask three questions. First, are species’ responses to forest and anthropogenic habitats consistent across continental scales? Second, do macroclimatic conditions explain spatial variation in species responses to land use? Third, can species traits elucidate which taxa are most likely to show climate-dependent habitat associations? We found that all species exhibited significant spatial variation in how they respond to land-use, tending to avoid anthropogenic areas and increasingly use forests in hotter regions. In the hottest regions, species occupancy was 50% higher in forested compared to open habitats, whereas in the coldest regions, the trend reversed. Larger species with larger ranges, herbivores, and primary predators were more likely to change their habitat affiliations than top predators, which consistently affiliated with high forest cover. Our findings suggest that climatic conditions influence species’ space-use and that maintaining forest cover can help protect mammals from warming climates.