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The "_archive_workflow_FinalModel.zip" data bundle is comprised of the metadata and Vistrails workflow that contains the following history nodes, which contain modeling workflows: "NLCD2016 state bckgrnd" and "NLCD2016 wostate bckgrnd". These nodes produced the following 9 output rasters: 1) Probability map (without state) 2) MPP threshold (without state) 3) Five percent threshold (without state) 4) Ten percent threshold (without state) 5) Probability map (with state) 6) MPP threshold (with state) 7) Five percent threshold (with state) 8) Ten percent threshold (with state) 9) Maxent MESS map
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The 'archive_raster_inputs.zip' data bundle contains '_archive_raster_inputs_XX.tif' and archive_raster_inputs_XX.xml where XX is the name of 1 of 8 input rasters that were created and used to generate these model results. The original layers and sources used to produce each predictor, as well as processing steps, are specified in each .xml file.
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from a single VisTrails/SAHM workflow. This model specifically includes field data of thinned occurrence locations and random background locations and un-thinned occurrence locations and targeted background locations for three species of tegu lizards in South America. Predictors included bioclimatic, tree cover, season length, potential evapotranspiration and solar radiation index rasters. Details about both inputs are included in the associated manuscript. The three bundle documentation files are: 1) '_archive_bundle_metadata.xml' (this file) which contains FGDC metadata describing the archive bundle. 2) 'PredictorList.csv'...
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from a single VisTrails/SAHM workflow. This model specifically includes location data for Bombina orientalis and random background locations. Predictors include climatic, topographic, and land cover rasters. The three bundle documentation files are: 1) '_archive_bundle_metadata.xml' which contains FGDC metadata describing the archive bundle. 2) '_archive_raster_inputs.csv' a list of the raster inputs that were used to generate these model results. These are not included in the archive bundle due to size constraints but are identified in this file as well as the metadata document. 3) '_archive_workflow_Final runs.vt'...
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This data bundle contains the merged data sets to create models for bishop's goutweed and fountaingrass using the VisTrails:SAHM [SAHM 2.1.0]. We developed species distribution models for both species following a workflow designed to balance automation and human intervention to produce models for invasive plant species of concern to U.S. land managers. Location data came from existing databases aggregating species occurrence information. Predictors came from a national library of potential environmental variables based on what environmental factors might limit plant species' distributions in different parts of the U.S. including climatic, topographic, soil, land use, and anthropogenic factors. The outputs of these...
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from two VisTrails/SAHM workflow. These models specifically include field data of locations with >40% cover of cheatgrass (presence) and <40% cover of cheatgrass (absence). Predictors included rasters derived from LandSat 8 imagery (_archive_FinalModel_revised) or from a digital elevation model (_archive_TopoOnly_revised). Details about all inputs are included in the associated manuscript. The three bundle documentation files in each data bundle are: 1) '_archive_bundle_metadata.xml' (this file) which contains FGDC metadata describing the archive bundle. 2) '_archive_raster_inputs.csv' a list of the raster inputs that...
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from a single VisTrails/SAHM workflow. This model specifically includes field data of locations with >40% cover of cheatgrass (presence) and <40% cover of cheatgrass (absence) from two wildfire locations in Wyoming. Predictors included rasters derived from Landsat 8 imagery and from a digital elevation model. Details about both inputs are included in the associated manuscript described in the larger work citation of the '_archive_bundle_metadata.xml' metadata record. We developed models for each location and tested the transferability of the models to the other location. We built on previous work developing models for...
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from two VisTrails/SAHM workflows, one creating a global habitat suitability model for buffelgrass and another creating a habitat suitability model for buffelgrass in Saguaro National Park, AZ. The bundle documentation files are: 1) '_archive_bundle_metadata.xml' (this file) which contains FGDC metadata describing the archive bundle. 2) 'modelSelectionCV_MakeAbsPntsFilt100_2.csv' containing the field data used as inputs for the Saguaro National Park model. 3) '_archive_raster_inputs.csv' a list of the raster inputs that were used to generate these model results. These are not included in the archive bundle due to size...
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We developed a second iteration of habitat suitability models for Lesser Prairie Chicken leks, across their range. The first modeling iteration used lek data collected from 2002 to 2012, land cover data ranging from 2001 to 2013, and anthropogenic features from 2011. Our second iteration model used occurrence points from new lek surveys (2015 to 2019) and updated predictor layers to evaluate changes in lek suitability and to quantify current range-wide habitat suitability. We created suitability models from 2 predictor sets: one including all predictors, and the other excluding state as a predictor. All 11 predictors included in the "with state" predictor set were: average Enhanced Vegetation Index (EVI), distance...
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We developed habitat suitability models for four invasive plant species of concern to Department of Interior land management agencies. We generally followed the modeling workflow developed in Young et al. 2020, but developed models both for two data types, where species were present and where they were abundant. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.1.2]. 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 four different thresholds. This data bundle contains the presence and...
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The 'archive_raster_outputs.zip' data bundle includes 'XX.tif' and 'XX.xml' where XX is the name of 1 of 9 specific output rasters produced from '_archive_workflow_FinalModel.vt'. These outputs include continuous and thresholded probability maps for models including and excluding state as a predictor, as well as a MESS (Multivariate Environmental Similarity Surface) map that describes areas with restricted environmental conditions for this species.
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We developed habitat suitability models for four invasive plant species of concern to Department of Interior land management agencies. We generally followed the modeling workflow developed in Young et al. 2020, but developed models both for two data types, where species were present and where they were abundant. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.1.2]. 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 four different thresholds. This data bundle contains the presence and...
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We developed habitat suitability models for four invasive plant species of concern to Department of Interior land management agencies. We generally followed the modeling workflow developed in Young et al. 2020, but developed models both for two data types, where species were present and where they were abundant. We developed models using five algorithms with VisTrails: Software for Assisted Habitat Modeling [SAHM 2.1.2]. 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 four different thresholds. This data bundle contains the presence and...


    map background search result map search result map Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014 Data for cheatgrass mapping in Squirrel Creek Wildfire and Arapaho Wildfire, WY in 2014 Data for modeling tegu lizard distributions in the Americas Data for modeling fountain grass and bishop's goutweed in the contiguous US Second Iteration of Range Wide Lesser Prairie Chicken Lek Habitat Suitability in 2019, Predicted in Southern Great Plains archive_raster_inputs archive_workflow_FinalModel archive_raster_outputs Presence and abundance data and models for four invasive plant species Presence and abundance data and models for four invasive plant species: merged data set to create the models Presence and abundance models management summaries for four invasive plant species Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014 Data for cheatgrass mapping in Squirrel Creek Wildfire and Arapaho Wildfire, WY in 2014 Second Iteration of Range Wide Lesser Prairie Chicken Lek Habitat Suitability in 2019, Predicted in Southern Great Plains archive_raster_inputs archive_workflow_FinalModel archive_raster_outputs Data for modeling fountain grass and bishop's goutweed in the contiguous US Presence and abundance data and models for four invasive plant species Presence and abundance data and models for four invasive plant species: merged data set to create the models Presence and abundance models management summaries for four invasive plant species Data for modeling tegu lizard distributions in the Americas