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INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023)
We developed habitat suitability models for invasive plant species selected by Department of Interior land management agencies. We applied the modeling workflow developed in Young et al. 2020 to species not included in the original case studies. Our methodology balanced trade-offs between developing highly customized models for a few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions (Engelstad et al. 2022 Table S1: https://doi.org/10.1371/journal.pone.0263056) and relied on human input based on natural history knowledge to further narrow the variable set for each species before...
This is a dataset containing the first and second record of georeferenced observations of introduced and invasive vascular plant species in the contiguous United States (CONUS). Non-native plant species were identified using the United States Register of Introduced and Invasive Species (US-RIIS) list. After identifying a list of plants non-native to CONUS, we obtained presence data from aggregated occurrence databases, ensuring the occurrences we acquired were georeferenced (i.e., had coordinate information) and had an observation year recorded. We also identified and removed records that might indicate cultivation. From these data, the first and second record were removed and isolated. This data set contains the...
Categories: Data;
Tags: Botany,
Contiguous United States,
First record,
Invasive species,
USGS Science Data Catalog (SDC),
This is a dataset containing the potential distribution of 259 invasive terrestrial plant species. We developed habitat suitability models for invasive plant species selected by Department of Interior land management agencies and other managers. We applied the modeling workflow developed in Young et al. (2020, https://doi.org/10.1371/journal.pone.0229253) and adapted by Jarnevich et al. (2023, https://doi.org/10.1016/j.ecoinf.2023.101997). We developed a national library of environmental variables known to physiologically limit plant distributions (Engelstad et al. 2022 Table S1: https://doi.org/10.1371/journal.pone.0263056) and relied on human input based on natural history knowledge to narrow the variable set...
Categories: Data;
Tags: Contiguous United States,
SAHM,
Species Distribution Modeling,
USGS Science Data Catalog (SDC),
United States,
This is a dataset containing the potential distribution of Japanese brome (Bromus japonicus). We developed habitat suitability models for Japanese brome, as suggested by Department of Interior land management agencies. We applied the modeling workflow developed in Young et al. 2020 to species not included in the original case studies. Our methodology balanced trade-offs between developing highly customized models for a few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions (Engelstad et al. 2022 Table S1: https://doi.org/10.1371/journal.pone.0263056) and relied on human input based...
We developed habitat suitability models for invasive plant species selected by Department of Interior land management agencies. We applied the modeling workflow developed in Young et al. 2020 to species not included in the original case studies. Our methodology balanced trade-offs between developing highly customized models for a few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions (Engelstad et al. 2022 Table S1) and relied on human input based on natural history knowledge to further narrow the variable set for each species before developing habitat suitability models. We developed...
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