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Note: this data release has been superseded by version 2.0, available here: https://doi.org/10.5066/P9V54H5K We developed habitat suitability models for invasive plant species selected by Department of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 and relied on human input based on natural history knowledge to further narrow the variable...
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These data were analyzed for the publication 'Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants': Aim: Exotic species’ distributions reflect patterns of human-mediated dispersal, species’ climatic tolerances, and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns. Location: Global. Methods: We used data from the Global...
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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...
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This is a spatially-explicit state-and-transition simulation model of buffelgrass dynamics in Saguaro National Park. Buffelgrass is an invasive grass spreading in the park. The model represents uninvaded and invaded parts of the desert ecosystem including transition pathways related to management activities and includes a connection to a fire behavior model. The model was built using the ST-Sim software platform linked to the FARSITE fire behavior model. The St-SIM file structure includes three components: 1) Buffelgrass.ssim.input folder that houses the input files used by St-SIM, 2) the Buffelgrass.ssim.output folder which houses the scenario outputs used by St-SIM for visualization and export of data, and 3)...
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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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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...
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We developed habitat suitability models for occurrence of three invasive riparian woody plant taxa of concern to Department of Interior land management agencies, as well as for three dominant native riparian woody taxa. Study taxa were non-native tamarisk (saltcedar; Tamarix ramosissima, Tamarix chinensis), Russian olive (Elaeagnus angustifolia) and Siberian elm (Ulmus pumila) and native plains/Fremont cottonwood (Populus deltoides ssp. monilifera and ssp. wislizenii, Populus fremontii), narrowleaf cottonwood (Populus angustifolia), and black cottonwood (Populus balsamifera ssp. trichocarpa and ssp. balsamifera). We generally followed the modeling workflow developed in Young et al. 2020. We developed models using...
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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 is a spatially-explicit state-and-transition simulation model of buffelgrass dynamics and alternative management actions in Saguaro National Park, AZ. Buffelgrass is an invasive grass spreading in the park. This work built on previous efforts that first developed a state and transition simulation model linked to FARSITE fire behavior model to describe buffelgrass dynamics in the park and a secondary effort to evaluate these dynamics in light of uncertainties in the model. This model represents uninvaded and invaded parts of the desert ecosystem and adds alternative management actions to the previously built models (cross reference). The model was built using the ST-Sim software platform linked to the FARSITE...
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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...
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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 is a spatially-explicit state-and-transition simulation model of buffelgrass dynamics in Saguaro National Park, AZ. Buffelgrass is an invasive grass spreading in the park. The model represents uninvaded and invaded parts of the desert ecosystem and includes a connection to a fire behavior model. The model was built using the ST-Sim software platform linked to the FARSITE fire behavior model. The St-SIM file structure includes three components: 1) Buffelgrass.ssim.input folder that houses the input files used by St-SIM, 2) the Buffelgrass.ssim.output folder which houses the scenario outputs used by St-SIM for visualization and export of data, and 3) Buffelgrass.ssim file which is opened by St-SIM to provide...
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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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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...
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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 State-and-Transition Simulation Model of Buffelgrass in Saguaro National Park (2014-2044) Data for modeling fountain grass and bishop's goutweed in the contiguous US State-and-Transition Simulation Models of Buffelgrass in Saguaro National Park (2014-2044) to explore ecological uncertainties INHABIT species potential distribution across the contiguous United States Second Iteration of Range Wide Lesser Prairie Chicken Lek Habitat Suitability in 2019, Predicted in Southern Great Plains archive_raster_inputs archive_workflow_FinalModel Simulation models for buffelgrass and alternative management strategies for Saguaro National Park, AZ Presence and abundance data and models for four invasive plant species 1. Occurrence data to train models for woody riparian native and invasive plant species in the conterminous western USA Data to create and evaluate distribution models for invasive species for different geographic extents INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023) Thresholded abundance models for three invasive plant species in the United States First and Second Record of US-RIIS Vascular Plant Species in Contiguous United States Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014 State-and-Transition Simulation Model of Buffelgrass in Saguaro National Park (2014-2044) 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 1. Occurrence data to train models for woody riparian native and invasive plant species in the conterminous western USA Data for modeling fountain grass and bishop's goutweed in the contiguous US INHABIT species potential distribution across the contiguous United States Presence and abundance data and models for four invasive plant species Data to create and evaluate distribution models for invasive species for different geographic extents INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023) Thresholded abundance models for three invasive plant species in the United States First and Second Record of US-RIIS Vascular Plant Species in Contiguous United States Data for modeling tegu lizard distributions in the Americas