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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641 to 650 of 819 Results

Variable_Responses.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0 ZIP Archive - 32.9 KB - MD5: 85ef68afa42ce5b67ee5bd7104f1aae0 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 all digitized downed trees 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 all digitized downed trees with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/4TVY7S, 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 (...
maxent.log Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 Plain Text - 205.3 KB - MD5: 93c9e2938fae9cca9bb5c2c9913d2ace 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 Comma Separated Values - 14.6 KB - MD5: b3d272434d87e0e5e86d3c157fe0c12e 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 116.7 MB - MD5: fe8975715a6aec8205f969354c2d6aa5 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 117.6 MB - MD5: a776202a962717f971197fdfcef50ba5 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 116.5 MB - MD5: f97eb3f01b337e9f9e40f06b2e4e7123 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 117.2 MB - MD5: 8195c9c590235993267856798bd4f872 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 116.5 MB - MD5: 92894f855eaf8b1e95b9e32bfb46279b 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0 ZIP Archive - 116.6 MB - MD5: f113cdc85f875f09868b43bbade4a3d1 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 all digitized downed trees with three variables and regularization multiplier of 6.0

ZIP Archive - 32.9 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 all digitized downed trees 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 all digitized downed trees with six variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/4TVY7S, 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 (...

maxent.log

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

Plain Text - 205.3 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 116.7 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 117.6 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 116.5 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 117.2 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 116.5 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 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 1.0

ZIP Archive - 116.6 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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