Aim To assess the usefulness of combining climate predictors with additional types of environmental predictors in species distribution models for rangerestricted species, using common correlative species distribution modelling approaches.Location Florida, USA Methods We used five different algorithms to create distribution models for 14 vertebrate species, using seven different predictor sets: two with bioclimate predictors only, and five 'combination' models using bioclimate predictors plus 'additional' predictors from groups representing: human influence, land cover, extreme weather or noise (spatially random data).We use a linear mixed-model approach to analyse the effects of predictor set and algorithm on model accuracy, variable importance scores and spatial predictions.Results Regardless of modelling algorithm, no one predictor set produced significantly more accurate models than all others, though models including human influence predictors were the only ones with significantly higher accuracy than climate-only models. Climate predictors had consistently higher variable importance scores than additional predictors in combination models, though there was variation related to predictor type and algorithm. While spatial predictions varied moderately between predictor sets, discrepancies were significantly greater between modelling algorithms than between predictor sets. Furthermore, there were no differences in the level of agreement between binary 'presence-absence' maps and independent species range maps related to the predictor set used. Main conclusionsOur results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.

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In March 2020, New York City (NYC) experienced an outbreak of coronavirus disease 2019 (COVID-19) which resulted in a 78-day mass confinement of all residents other than essential workers. The aims of the current study were to (1) document the breadth of COVID-19 experiences and their impacts on college students of a minority-serving academic institution in NYC; (2) explore associations between patterns of COVID-19 experiences and psychosocial functioning during the prolonged lockdown, and (3) explore sex and racial/ethnic differences in COVID-19-related experiences and mental health correlates. A total of 909 ethnically and racially diverse students completed an online survey in May 2020. Findings highlight significant impediments to multiple areas of students’ daily life during this period (i.e., home life, work life, social environment, and emotional and physical health) and a vast majority reported heightened symptoms of depression and generalized anxiety. These life disruptions were significantly related to poorer mental health. Moreover, those who reported the loss of a close friend or loved one from COVID-19 (17%) experienced significantly more psychological distress than counterparts with other types of infection-related histories. Nonetheless, the majority (96%) reported at least one positive experience since the pandemic began. Our findings add to a growing understanding of COVID-19 impacts on psychological health and contribute the important perspective of the North American epicenter of the pandemic during the time frame of this investigation. We discuss how the results may inform best practices to support students’ well-being and serve as a benchmark for future studies of US student populations facing COVID-19 and its aftermath.

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a b s t r a c tClimate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

Abstract. Distributional limits of many tropical species in Florida are ultimately determined by tolerance to low temperature. An unprecedented cold spell during 2-11 January 2010, in South Florida provided an opportunity to compare the responses of tropical American crocodiles with warm-temperate American alligators and to compare the responses of nonnative Burmese pythons with native warm-temperate snakes exposed to prolonged cold temperatures. After the January 2010 cold spell, a record number of American crocodiles (n = 151) and Burmese pythons (n = 36) were found dead. In contrast, no American alligators and no native snakes were found dead. American alligators and American crocodiles behaved differently during the cold spell. American alligators stopped basking and retreated to warmer water. American crocodiles apparently continued to bask during extreme cold temperatures resulting in lethal body temperatures. The mortality of Burmese pythons compared to the absence of mortality for native snakes suggests that the current population of Burmese pythons in the Everglades is less tolerant of cold temperatures than native snakes. Burmese pythons introduced from other parts of their native range may be more tolerant of cold temperatures. We documented the direct effects of cold temperatures on crocodiles and pythons; however, evidence of long-term effects of cold temperature on their populations within their established ranges remains lacking. Mortality of crocodiles and pythons outside of their current established range may be more important in setting distributional limits.