Rarity, geography, and plant exposure to global change in the California Floristic Province

Aim: Rarity and geographic aspects of species distributions mediate their vulnerability to global change. We explore the relationships between species rarity and geography and their exposure to climate and land use change in a biodiversity hotspot.

Location: California, USA.
Taxa: One hundred and six terrestrial plants.
Methods: We estimated four rarity traits: range size, niche breadth, number of habitat patches, and patch isolation; and three geographic traits: mean elevation, topographic heterogeneity, and distance to coast. We used species distribution models to measure species exposure—predicted change in continuous habitat suitability within currently occupied habitat—under climate and land use change scenarios. Using regression models, decision-tree models and variance partitioning, we assessed the relationships between species rarity, geography, and exposure to climate and land use change.
Results: Rarity, geography and greenhouse gas emissions scenario explained >35% of va..., This dataset includes the spatial outputs for the species distribution models described in Rose, M. B., Velazco, S. J. E., Regan, H. M., & Franklin, J. (2022). Rarity, geography, and plant exposure to global change in the California Floristic Province. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13618. We selected eight SDM algorithms for ensemble predictions: generalized linear models, generalized additive models, boosted regression trees, random forests, artificial neural networks, support vector machines, maximum entropy, and gaussian process (Franklin 2010). The last two algorithms were only used for presence-only models. Ensembles, in which predictions of individual algorithms are combined to produce a consensus distribution, can reduce model uncertainty and improve model transferability (Araújo & New, 2007). For each model, we applied the model-specific suitability value that maximized the sum of sensitivity and specificity as a threshold, retaining contin..., , # SDM outputs for: Rarity, geography, and plant exposure to global change in the California Floristic Province

This dataset includes the spatial outputs for the species distribution models described in Rose, M. B., Velazco, S. J. E., Regan, H. M., & Franklin, J. (2022). Rarity, geography, and plant exposure to global change in the California Floristic Province. *Global Ecology and Biogeography*. . Importantly, the maps included in this dataset include habitat suitability projections for the extent of the Californian portion of the California Floristic Province. Results in the paper are based on habitat suitability patterns within species currently occupied range. To replicate these results, users can use the occupied habitat maps in each species \"01_current\" folder found in each zip file to crop the maps of projected future habitat suitability. Habitat suitability maps reflect continuous habitat suitability (0-1).

## Description of the data and file structure

Each zip file has ...