Potential distribution of Japanese brome (Bromus japonicus) across the contiguous United States (October 2023)

Dates

Publication Date: 2023-10-27
Start Date: 1980
End Date: 2023

Citation

Williams, D.A., Jarnevich, C.S., Engelstad, P., Henderson, G., Shadwell, K., Pearse, I.S., and Prevey, J.S., 2023, Potential distribution of Japanese brome (Bromus japonicus) across the contiguous United States (October 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9HSW0AI.

Summary

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 on natural history [...]

Summary

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 on natural history knowledge to further narrow the variable set for each species before developing habitat suitability models. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.2.2]. We accounted for uncertainty related to sampling bias by using two alternative sources of background samples, and constructed model ensembles using the 10 models for each species (five algorithms by two background methods) for three different thresholds (conservative to targeted). This data bundle contains a single file of tabular summaries by management unit (including each species/ ensemble type combination) and a subfolder for each species that contains the merged data sets used to create models, the six raster files associated with the species, and tabular outputs including response curve data, variable importance information, and model assessment metrics. Each of the six rasters represent the following:

1) 0.01 - one percentile threshold
2) 0.1 - ten percentile threshold
3) MaxSS - maximum sensitivity plus specificity threshold
4) 0.01 - one percentile threshold with Restricted Environmental Conditions
5) 0.1 - ten percentile threshold with Restricted Environmental Conditions
6) MaxSS - maximum sensitivity plus specificity threshold with Restricted Environmental Conditions

The bundle documentation files are:
1) 'project_metdata.xml' (this file) which contains the project-level metadata
2) managementSummaries.csv is the tabular summaries by management unit.
3) 'mergedDataset.csv' contains the merged data set used to create the models, including location and associated environmental data, for each species.
4) XX.tif where XX is the raster type explained above (threshold; masked or not).
5) responseCurves.csv is the tabular information need to produce response curves for each predictor retained in each of the 10 models produced for each species.
6) variableImportance.csv is the tabular summaries indicating predictor importance for each of the 10 models produced for each species.
7) assessmentMetrics.csv is the tabular summaries of assessment metrics for each model or ensemble for each species.

Contacts

Point of Contact :: Catherine S Jarnevich
Originator :: Demetra (Contractor) A Williams, Catherine S Jarnevich, Peder S Engelstad, Grace (Contractor) C Henderson, Keana (Contractor) S Shadwell, Ian S Pearse, Janet S Prevey
Metadata Contact :: FORT Data Management
Publisher :: U.S. Geological Survey
Distributor :: U.S. Geological Survey - ScienceBase
SDC Data Owner :: Fort Collins Science Center
USGS Mission Area :: Ecosystems

Attached Files

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project_metadata.xml Original FGDC Metadata	View	52.54 KB	application/fgdc+xml
assessmentMetrics.zip		14.11 KB	application/zip
ensemble_1st.zip		122.62 MB	application/zip
ensemble_1st_masked.zip		120.81 MB	application/zip
ensemble_10th.zip		174.8 MB	application/zip
ensemble_10th_masked.zip		172.58 MB	application/zip
ensemble_MaxSS.zip		171.13 MB	application/zip
ensemble_MaxSS_masked.zip		168.99 MB	application/zip
managementSummaries.zip		809.39 KB	application/zip
mergedDataset.zip		3.99 MB	application/zip
responseCurves.zip		18.71 MB	application/zip
variableImportance.zip		24.47 KB	application/zip

Related External Resources

Type: Related Data Release

Jarnevich, C.S., LaRoe, J., Engelstad, P., Hays, B., Henderson, G., Williams, D., Shadwell, K., Pearse, I.S., Prevey, J.S., Sofaer, H.R., 2023, INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9V54H5K.	https://doi.org/10.5066/P9V54H5K

Purpose

To provide information and documentation on the potential distribution of Japanese brome in the contiguous United States.

Potential distribution of Japanese brome (Bromus japonicus) across the contiguous United States (October 2023)

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