This dataset provides spatial predictions of the pooled-SDM residuals from a multiscale geographically weighted regression model (MGWR) and the resulting local R2 values for individuals in the subregion encompassing the genetic sampling locations used by Edwards et al. (2015). This region offered an opportunity to explore habitat selection across the ecotone between the Mojave and Sonoran deserts and the secondary contact zone between G. agassizii and G. morafkai, and is referred to as the focal study area. The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to identify multivariate clusters and map them back to geographic space. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

These data include environmental covariates used to develop species distribution models for Gopherus agassizii and Gopherus morafkai, along with PCA-reduced environmental covariates used to explore local species-environment relationships within a subregion of the ectone between the two species. We also provide the genotype association used to test the mapped clusters of multiscale geographically weighted regression coefficients against models of (i) a geographically-based taxonomic designation these two sister species, and (ii) an environmental ecoregion designation. These data support the following publication: Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

These data include environmental covariates used to develop species distribution models for Gopherus agassizii and Gopherus morafkai, along with PCA-reduced environmental covariates used to explore local species-environment relationships within a subregion of the ectone between the two species. We also provide the genotype association used to test the mapped clusters of multiscale geographically weighted regression coefficients against models of (i) a geographically-based taxonomic designation these two sister species, and (ii) an environmental ecoregion designation. These data support the following publication: Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

This dataset provides spatial predictions of clustering and the genotype association index for the Mojave genotype in local species-environment relationships of Desert Tortoises (Gopherus agassizi and Gopherus morafkaii) for individuals in the subregion encompassing the genetic sampling locations used by Edwards et al. (2015). This region offered an opportunity to explore habitat selection across the ecotone between the Mojave and Sonoran deserts and the secondary contact zone between G. agassizii and G. morafkai, and is referred to as the focal study area. The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to identify multivariate clusters and map them back to geographic space. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

This dataset provides spatial predictions of clustering and the genotype association index for the Mojave genotype in local species-environment relationships of Desert Tortoises (Gopherus agassizi and Gopherus morafkaii) for individuals in the subregion encompassing the genetic sampling locations used by Edwards et al. (2015). This region offered an opportunity to explore habitat selection across the ecotone between the Mojave and Sonoran deserts and the secondary contact zone between G. agassizii and G. morafkai, and is referred to as the focal study area. The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to identify multivariate clusters and map them back to geographic space. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

This dataset provides the environmental explanatory variables used to explore spatial patterns in species-environment relationships in Gopherus agassizii and Gopherus morafkai across the subregion encompassing the genetic sampling locations used by Edwards et al. (2015). This region offered an opportunity to explore habitat selection across the ecotone between the Mojave and Sonoran deserts and the secondary contact zone between G. agassizii and G. morafkai, and is referred to as the focal study area. The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to identify multivariate clusters and map them back to geographic space. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. xxx.xxx

This dataset provides spatial predictions of habitat suitability for Gopherus agassizii (Agassiz’s desert tortoise), Gopherus morafkai (Morafka’s desert tortoise) and a pooled-species model under current conditions (1950 – 2000 yr). The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to evaluate subtle ecological niche differences between Gopherus agassizii and Gopherus morafkai, and identify local species-environment relationships. Spatial predictions of habitat suitability were created using MaxEnt version 3.4.0 (Phillips et al., 2006), a widely-used software for SDM in presence-background frameworks. Detailed methods are provided in Inman et al. 2019. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

This dataset provides spatial predictions of habitat suitability for Gopherus agassizii (Agassiz’s desert tortoise), Gopherus morafkai (Morafka’s desert tortoise) and a pooled-species model under current conditions (1950 – 2000 yr). The raster layers contained here accompany the manuscript Inman et al. 2019 and were used to evaluate subtle ecological niche differences between Gopherus agassizii and Gopherus morafkai, and identify local species-environment relationships. Spatial predictions of habitat suitability were created using MaxEnt version 3.4.0 (Phillips et al., 2006), a widely-used software for SDM in presence-background frameworks. Detailed methods are provided in Inman et al. 2019. Inman et al. 2019. Local niche differences predict genotype associations in sister taxa of desert tortoise. Diversity and Distributions. https://doi.org/10.1111/ddi.12927

Preserving native species diversity is fundamental to ecosystem conservation. Selecting appropriate native species for use in restoration is a critical component of project design and may emphasize species attributes such as life history, functional type, pollinator services, and nutritional value for wildlife. Determining which species are likely to establish and persist in a particular environment is a key consideration. Species distribution models (SDMs) characterize relationships between species occurrences and the physical environment (e.g., climate, soil, topographic relief) and provide a mechanism for assessing which species may successfully propagate at a restoration site. In conjunction with information on species attributes, SDMs facilitate holistic ecosystem restoration by enabling practitioners to identify diverse, resilient assemblages of native species. This project develops SDMs for native species of fundamental ecosystem importance in order to guide restoration of Mojave Desert landscapes. The dataset contained herein provides an SDM for Malacothrix glabrata within its Mojave Desert range based on known occurrences.

Preserving native species diversity is fundamental to ecosystem conservation. Selecting appropriate native species for use in restoration is a critical component of project design and may emphasize species attributes such as life history, functional type, pollinator services, and nutritional value for wildlife. Determining which species are likely to establish and persist in a particular environment is a key consideration. Species distribution models (SDMs) characterize relationships between species occurrences and the physical environment (e.g., climate, soil, topographic relief) and provide a mechanism for assessing which species may successfully propagate at a restoration site. In conjunction with information on species attributes, SDMs facilitate holistic ecosystem restoration by enabling practitioners to identify diverse, resilient assemblages of native species. This project develops SDMs for native species of fundamental ecosystem importance in order to guide restoration of Mojave Desert landscapes. The dataset contained herein provides an SDM for Malacothrix glabrata within its Mojave Desert range based on known occurrences.