Impacts of Downed Trees on hydrologic surface connectivity within the Mission River floodplain in Southeast Texas

This dataverse includes datasets as a result of NSF RAPID Award #1760717 that covers the ecological role and impact of downed trees on hydrologic surface connectivity within the Mission River floodplain.

There are two dataverses that have data inputs and products related to Objectives 1 and 2. These are:

Objective 1: Environmental Analyses

Objective 2: Roughness Scenarios

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21 to 30 of 32 Results

Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/AJFW6L, Texas Data Repository, V1 This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes all environmental variables (...
Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GMU4XY, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/F2U3QV, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0", https://doi.org/10.18738/T8/ILRKFQ, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...
Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/8UXWKH, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0", https://doi.org/10.18738/T8/GQYIX2, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 Jun 8, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/0PQLIB, Texas Data Repository, V1 This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes all environmental variables (veget...
Environmental Variables Used in Spatial Analysis Jun 8, 2020 - Environmental Analyses FLUD Research Group, 2020, "Environmental Variables Used in Spatial Analysis", https://doi.org/10.18738/T8/O8GYRJ, Texas Data Repository, V1 Polygon shapefiles that comprise levels of six environmental variables are used in conjunction with downed trees to inform the spatial analysis. A census of downed trees is created in each region within each environmental variable. Four environmental variables (elevation, general...
Environmental Variables Used in Maxent Machine Learning Approach Jun 8, 2020 - Environmental Analyses FLUD Research Group, 2020, "Environmental Variables Used in Maxent Machine Learning Approach", https://doi.org/10.18738/T8/MJNKOW, Texas Data Repository, V1 Six environmental variables are represented as raster maps, and they are used in conjunction with locations of downed trees to inform the variable importance and relationships derived from results of the Maxent ML approach. These variables are processed as ESRI ASCII raster maps...
Digitized Downed/Standing Trees in the Mission River Floodplain Jun 8, 2020 - Environmental Analyses FLUD Research Group, 2020, "Digitized Downed/Standing Trees in the Mission River Floodplain", https://doi.org/10.18738/T8/UUAQT7, Texas Data Repository, V1 Downed trees (N=9505) were digitized by members of the FLUD Research group (faculty and student researchers). Student researchers consist of graduate and undergraduate students. Undergraduate student researchers worked at the supervision and expertise of faulty and graduate stude...

Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/AJFW6L, Texas Data Repository, V1

This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes all environmental variables (...

Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GMU4XY, Texas Data Repository, V1

This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables...

Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/F2U3QV, Texas Data Repository, V1

Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0", https://doi.org/10.18738/T8/ILRKFQ, Texas Data Repository, V1

Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/8UXWKH, Texas Data Repository, V1

Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0", https://doi.org/10.18738/T8/GQYIX2, Texas Data Repository, V1

Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

Jun 8, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/0PQLIB, Texas Data Repository, V1

Environmental Variables Used in Spatial Analysis

Jun 8, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Environmental Variables Used in Spatial Analysis", https://doi.org/10.18738/T8/O8GYRJ, Texas Data Repository, V1

Polygon shapefiles that comprise levels of six environmental variables are used in conjunction with downed trees to inform the spatial analysis. A census of downed trees is created in each region within each environmental variable. Four environmental variables (elevation, general...

Environmental Variables Used in Maxent Machine Learning Approach

Jun 8, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Environmental Variables Used in Maxent Machine Learning Approach", https://doi.org/10.18738/T8/MJNKOW, Texas Data Repository, V1

Six environmental variables are represented as raster maps, and they are used in conjunction with locations of downed trees to inform the variable importance and relationships derived from results of the Maxent ML approach. These variables are processed as ESRI ASCII raster maps...

Digitized Downed/Standing Trees in the Mission River Floodplain

Jun 8, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Digitized Downed/Standing Trees in the Mission River Floodplain", https://doi.org/10.18738/T8/UUAQT7, Texas Data Repository, V1

Downed trees (N=9505) were digitized by members of the FLUD Research group (faculty and student researchers). Student researchers consist of graduate and undergraduate students. Undergraduate student researchers worked at the supervision and expertise of faulty and graduate stude...

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