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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681 to 690 of 819 Results

Tree_6_Results.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 115.1 MB - MD5: 82b68c0ae71b0cbbbf51f6f9a8727f3a Results from a Maxent model based on seven 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_7_Results.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 115.8 MB - MD5: 2c2ee8c484ef23eb7b964f3d286f07e4 Results from a Maxent model based on eight 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_8_Results.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 116.1 MB - MD5: 664a6b3d66e30a5d1d6e2d3daead924b Results from a Maxent model based on nine 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_9_Results.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 116.4 MB - MD5: 1d70ff0acf09be0b600c09cad4003c3b Results from a Maxent model based on ten 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_Statistics.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 578.9 MB - MD5: 20a266cb988d7f11692d1b15fe1b1a71 Maps (*.asc) of statistics (resolution of 1.0 m) for probability of occurrence from ten replicate runs based on subsamples of data (min, max, median, average, standard deviation) of model output (probability of downed tree occurrence).
Variable_Responses.zip Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0 ZIP Archive - 127.0 KB - MD5: e0d5e0cb16df0d2ce543939108c0e12d Tables (*.dat) 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 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...
maxent.log Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0 Plain Text - 118.1 KB - MD5: 0d90b68c95f849dbbf28eb3157e43d5c 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 three variables and regularization multiplier of 1.0 Comma Separated Values - 12.1 KB - MD5: c044dc0faf0609dda53d244114913829 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 three variables and regularization multiplier of 1.0 ZIP Archive - 11.5 MB - MD5: 66a8c9990f40577027bcfaff455c9d8f 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_6_Results.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 115.1 MB -

Results from a Maxent model based on seven 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_7_Results.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 115.8 MB -

Results from a Maxent model based on eight 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_8_Results.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 116.1 MB -

Results from a Maxent model based on nine 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_9_Results.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 116.4 MB -

Results from a Maxent model based on ten 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_Statistics.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 578.9 MB -

Maps (*.asc) of statistics (resolution of 1.0 m) for probability of occurrence from ten replicate runs based on subsamples of data (min, max, median, average, standard deviation) of model output (probability of downed tree occurrence).

Variable_Responses.zip

Jun 9, 2020 - Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 3.0

ZIP Archive - 127.0 KB -

Tables (*.dat) 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 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...

maxent.log

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

Plain Text - 118.1 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 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 1.0

Comma Separated Values - 12.1 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 three variables and regularization multiplier of 1.0

ZIP Archive - 11.5 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...

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