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1. Maximum temperatures determine the habitat affiliations of North American mammals

   https://doi.org/10.1073/pnas.2304411120  

   Tourani, Mahdieh; Sollmann, Rahel; Kays, Roland; Ahumada, Jorge; Fegraus, Eric; Karp, Daniel S (December 2023, Proceedings of the National Academy of Sciences)

   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. 

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2. Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape

   https://doi.org/10.1007/s10980-025-02105-0  

   Farner, Johannah E; Howard, Meghan; Smith, Jeffrey R; Anderson, Christopher B; Mordecai, Erin A (June 2025, Landscape Ecology)

   Context Land use change and deforestation drive both biodiversity loss and zoonotic disease transmission in tropical countrysides. For mosquito communities that can include disease vectors, forest loss has been linked to reduced biodiversity and increased vector presence. The spatial scales at which land use and tree cover shape mosquito communities present a knowledge gap relevant to both biodiversity and public health. Objectives We investigated the responses of mosquito species richness and Aedes albopictus disease vector presence to land use and to tree cover surrounding survey sites at different spatial scales. We also investigated species compositional turnover across land uses and along environmental gradients. Methods We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito richness and vector presence responses to tree cover measured across scales from 30 to 1000 m, and across land uses. We analyzed mosquito community compositional turnover between land uses and along environmental gradients of tree cover, temperature, elevation, and geographic distance. Results Tree cover was both positively correlated with mosquito species richness and negatively correlated with the presence of the common invasive dengue vector Ae. albopictus at small spatial scales of 90–250 m. Land use predicted community composition and Ae. albopictus presence. Conclusions The results suggest that local tree cover preservation and expansion can support mosquito species richness and reduce disease vector presence. The identified spatial range at which tree cover shapes mosquito communities can inform the development of land management practices to protect both ecosystem and public health. 

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3. Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence

   https://doi.org/10.1088/1748-9326/ac9dae  

   Cheng, Rui; Magney, Troy S; Orcutt, Erica L; Pierrat, Zoe; Köhler, Philipp; Bowling, David R; Bret-Harte, M Syndonia; Euskirchen, Eugénie S; Jung, Martin; Kobayashi, Hideki; et al (November 2022, Environmental Research Letters)

   Abstract Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region. 

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4. Dynamic priorities for conserving species

   https://doi.org/10.1126/science.abq0788  

   McGuire, Jenny L.; Shipley, Benjamin R. (June 2022, Science)

   Protected areas serve to preserve the remaining biodiversity on our planet. However, today, only about 14% of terrestrial lands are protected, which will not be sufficient to support the planet’s fabric of life into the future ( 1 , 2 ). Humans continue to encroach on the habitats of many plants and animals. Simultaneously, the environmental conditions within protected areas are changing because of shifting climates, pollution, and invasive species, which all fundamentally alter ecosystems globally. To effectively conserve biodiversity, researchers and policy-makers must critically reexamine both the lands being preserved and the protection strategies being used in conservation. On pages 1094 and 1101 of this issue, Allan et al. ( 3 ) and Brennan et al. ( 4 ), respectively, evaluate the preservation capacity of today’s protected areas in different but complementary ways. Allan et al. estimate the minimum land area necessary to support today’s terrestrial biodiversity, whereas Brennan et al. identify the connectedness necessary to allow wildlife to successfully adapt to global change. 

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5. Integrating anthropogenic factors into regional‐scale species distribution models—A novel application in the imperiled sagebrush biome

   https://doi.org/10.1111/gcb.14728  

   Requena‐Mullor, Juan M.; Maguire, Kaitlin C.; Shinneman, Douglas J.; Caughlin, Timothy Trevor (July 2019, Global Change Biology)

   Abstract Species distribution models (SDMs) that rely on regional‐scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local‐scale anthropogenic variables, including wildfire history, land‐use change, invasive species, and ecological restoration practices can override regional‐scale variables to drive patterns of species distribution. Incorporating these human‐induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentataNutt.) as a model species to explore whether including human‐induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field‐sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America. Models including fire attributes and restoration treatments performed better than those including only climate and topographic variables. Number of fires and fire occurrence had the strongest relative effects on big sagebrush occurrence and cover, respectively. The models predicted that the probability of big sagebrush occurrence decreases by 1.2% (95% CI: −6.9%, 0.6%) when one fire occurs and cover decreases by 44.7% (95% CI: −47.9%, −41.3%) if at least one fire occurred over the 36 year period of record. Restoration practices increased the probability of big sagebrush occurrence but had minimal effect on cover. Our results demonstrate the potential value of including disturbance and land management along with climate in models to predict species distributions. As an increasing number of datasets representing land‐use history become available, we anticipate that our modeling framework will have broad relevance across a range of biomes and species. 

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