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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761 to 770 of 821 Results

Variable_Responses.zip Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0 ZIP Archive - 134.3 KB - MD5: 95cfb69affcd63b0d5516eadb95bf011 Tables consisting of mean responses of ten replicate model runs based on subsamples of data, associated with each environmental variable and a model formed with only that specific variable (only).
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...
maxent.log Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 Plain Text - 214.1 KB - MD5: 35320f98a6dcf01ea9da32bf5a64b14a This is a log that consists of the time model is run, maxent software version, command line to invoke model, list of input environmental variables, list of input features, number of replicate runs, computational activities for each replicate, brief description of outputs
maxentResults.csv Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 Comma Separated Values - 14.6 KB - MD5: 62fbe2db4b475192118dd4879e4ca64e Contains performance metrics for each model run based on each sample replicate as well as their average. Notable Performance metrics include 1) Variable importance (contribution) for each environmental variable. 2) Variable permutation importance for each environmental variable....
Tree_0_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 109.0 MB - MD5: 9cfc544b45e035d524b79669ee9b2beb Results from a Maxent model based on one of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...
Tree_1_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 112.5 MB - MD5: 2a77b423445fa0ad7c01b2d3135b870b Results from a Maxent model based on two of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...
Tree_2_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 109.8 MB - MD5: 88585eaf45727d7339cfe19b2c9058cd Results from a Maxent model based on three of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset...
Tree_3_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 104.7 MB - MD5: 3d3b3080bdd7910c240d3169247746b4 Results from a Maxent model based on four of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset o...
Tree_4_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 112.4 MB - MD5: 515e54a2077efc866195893e89eb4c8f Results from a Maxent model based on five of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset o...
Tree_5_Results.zip Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0 ZIP Archive - 110.1 MB - MD5: 142ddbb3d102f40f16ed29ea057b5a8e Results from a Maxent model based on six of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...

Variable_Responses.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 2.0

ZIP Archive - 134.3 KB -

Tables consisting of mean responses of ten replicate model runs based on subsamples of data, associated with each environmental variable and a model formed with only that specific variable (only).

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...

maxent.log

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

Plain Text - 214.1 KB -

This is a log that consists of the time model is run, maxent software version, command line to invoke model, list of input environmental variables, list of input features, number of replicate runs, computational activities for each replicate, brief description of outputs

maxentResults.csv

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

Comma Separated Values - 14.6 KB -

Contains performance metrics for each model run based on each sample replicate as well as their average. Notable Performance metrics include 1) Variable importance (contribution) for each environmental variable. 2) Variable permutation importance for each environmental variable....

Tree_0_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 109.0 MB -

Results from a Maxent model based on one of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...

Tree_1_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 112.5 MB -

Results from a Maxent model based on two of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...

Tree_2_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 109.8 MB -

Results from a Maxent model based on three of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset...

Tree_3_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 104.7 MB -

Results from a Maxent model based on four of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset o...

Tree_4_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 112.4 MB -

Results from a Maxent model based on five of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset o...

Tree_5_Results.zip

Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0

ZIP Archive - 110.1 MB -

Results from a Maxent model based on six of ten replicates for a subset (50% training, 50% testing) of all downed trees. Consists of the following files: (*.asc) - Probability (map) based on training data from replicate sample and generated from Maxent model informed by subset of...

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