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Conservation translocations can promote species recovery but are prone to failure due to low post-release survival. Mounting evidence suggests that intrinsic attributes like personality and stress physiology can impact how individuals cope with translocation and acclimatize to the release site. Here, we investigated relationships among personality, biomarkers of stress, post-release movement, and survival using a recent swift fox (Vulpes velox) reintroduction program as a case study. We scored pre-release behavioral responses to handling and collected fecal samples (n= 329) from 76 foxes translocated from three wild populations across Colorado and Wyoming to the Fort Belknap Reservation, Montana, in 2021-2022. Our behavioral assessments measured the degree to which foxes were proactive (i.e., active, risk-taking, less docile) or reactive (i.e., inactive, risk-averse, more docile). We quantified fecal glucocorticoid metabolite (fGM) concentrations for the first time in swift foxes and monitored foxes’ post-release movements and survival using GPS data. Generalized linear models indicated that foxes with the lowest and highest fGM concentrations were more reactive during handling. Further, foxes with higher fGM concentrations around the time of capture traveled greater cumulative distances post-release. Personality had a non-linear effect on survival such that foxes with the most proactive and reactive behaviors during handling were more likely to survive in the first 60 days post-release. Ultimately, release cohorts comprising an array of individual temperaments may best cope with the novelty of the release site through behaviorally mediated resource partitioning and risk avoidance. 

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. 

Monitoring post‐release dispersal of reintroduced wildlife informs management strategies to improve outcomes. In previous Swift fox (Vulpes velox) reintroductions, post‐release movements corresponded with survival and have been a metric for success of release strategies, but settlement patterns and resource selection by individuals from different source locations have not been compared. We fit piecewise regression models and resource selection functions to Global Positioning System collar data from Swift fox translocated to the Fort Belknap Reservation from Colorado and Wyoming. We found that 76% of studied Swift fox settled, most within 20 km of their release site. Contrary to our predictions, rates of settlement, distance and time to settlement, and resource selection did not differ by cohort or release strategy. Where Swift fox settled, we observed consistent selection of areas with high percentage cover by grass, low terrain ruggedness, intermediate clay soil content, and high Black‐tailed prairie dog suitability. Collectively, our study suggests that Swift fox are adaptable to a range of conditions within grassland ecosystems when high quality habitat is available and when pre‐release husbandry protocols are followed. However, we observed variability in post‐release behavior unexplained by the factors we assessed, possibly attributable to individual personality differences that are well documented in small canids. Swift fox are the most intensively reintroduced canid in the world, and our study highlights how science‐based advances in reintroduction practices can enhance success over time. These advances are particularly effective on Indigenous Peoples' Land, where high ecological and social suitability is present for large‐scale restoration initiatives. 

Abstract Forest canopy complexity (i.e., the three‐dimensional structure of the canopy) is often associated with increased species diversity as well as high primary productivity across natural forests. However, canopy complexity, tree diversity, and productivity are often confounded in natural forests, and the mechanisms of these relationships remain unclear. Here, we used two large tree diversity experiments in North America to assess three hypotheses: (1) increasing tree diversity leads to increased canopy complexity, (2) canopy complexity is positively related to tree productivity, and (3) the relationship between tree diversity and tree productivity is indirect and driven by the positive effects of canopy complexity. We found that increasing tree diversity from monocultures to mixtures of 12 species increases canopy complexity and productivity by up to 71% and 73%, respectively. Moreover, structural equation modeling indicates that the effects of tree diversity on productivity are indirect and mediated primarily by changes in internal canopy complexity. Ultimately, we suggest that increasing canopy complexity can be a major mechanism by which tree diversity enhances productivity in young forests. 

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. 

Abstract Tree diversity can promote both predator abundance and diversity. However, whether this translates into increased predation and top‐down control of herbivores across predator taxonomic groups and contrasting environmental conditions remains unresolved. We used a global network of tree diversity experiments (TreeDivNet) spread across three continents and three biomes to test the effects of tree species richness on predation across varying climatic conditions of temperature and precipitation. We recorded bird and arthropod predation attempts on plasticine caterpillars in monocultures and tree species mixtures. Both tree species richness and temperature increased predation by birds but not by arthropods. Furthermore, the effects of tree species richness on predation were consistent across the studied climatic gradient. Our findings provide evidence that tree diversity strengthens top‐down control of insect herbivores by birds, underscoring the need to implement conservation strategies that safeguard tree diversity to sustain ecosystem services provided by natural enemies in forests.