Filters: Contacts: Jillian M Laroe (X)
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We developed habitat suitability models for three invasive plant species: stiltgrass (Microstegium vimineum), sericea lespedeza (Lespedeza cuneata), and privet (Ligustrum sinense). We applied the modeling workflow developed in Young et al. 2020, developing similar models for occurrence data, but also models trained using species locations with percent cover ≥10%, ≥25%, and ≥50%. We chose predictors from 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 models using...
This is a dataset containing aggregated non-native plant occurrence and abundance data for the contiguous United States. We used these data to develop habitat suitability models for species found in the Eastern United States using locations with 5% cover or greater. We adapted the INHABIT modeling workflow (Young et al. 2020), using a consistent set of climatic predictors that were important in the INHABIT models. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.2.2]. We accounted for sampling bias by using the target background approach, and constructed model ensembles using the five models for each species for three different thresholds (conservative to targeted;1st...
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