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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731 to 740 of 821 Results

Variable_Responses.zip Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0 ZIP Archive - 32.7 KB - MD5: e1f5ce9e22ed36415bb0952c7752cada 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 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...
maxent.log Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0 Plain Text - 213.7 KB - MD5: 285d657177372c0f565d294f864cc880 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 Comma Separated Values - 14.6 KB - MD5: 461a8462730c4baa79e0dfa146c0a6ca 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 112.4 MB - MD5: 7bb5b44305653d7ed2dca5c3f59944bb 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 109.1 MB - MD5: 451b42eaaf432a50ba70667af62c904f 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 111.1 MB - MD5: 4042633ee8bedfc175991aefaaa9cd5b 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 113.7 MB - MD5: a3db21ec0262479665a9b9ccc5899f9c 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 113.8 MB - MD5: ae305ef87956a39d37764afbdc1a26f4 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0 ZIP Archive - 112.0 MB - MD5: a415275fe73217d31b5f27c5e11e51db 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 three variables and regularization multiplier of 7.0

ZIP Archive - 32.7 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 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...

maxent.log

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

Plain Text - 213.7 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 digitized downed trees (structure) 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 112.4 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 109.1 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 111.1 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 113.7 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 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 113.8 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 digitized downed trees (structure) with six variables and regularization multiplier of 1.0

ZIP Archive - 112.0 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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