This dataverse contains data inputs and products from two complimentary analyses: a spatial analysis and a machine learning approach. Both analyses were geared towards understanding relative importance of ecological factors within the Mission River Floodplain. These datasets are broken down as follows:

Digitized Trees:

    Digitized Downed/Standing Trees in the Mission River Floodplain

Spatial Analysis

    Environmental Variables Used in Spatial Analysis

    Counts of Downed Trees for Levels of Environmental Variables: Results of Spatial Analysis

ML Approach:

    Environmental Variables Used in Maxent Machine Learning Approach

    MaxentVariableselection Inputs/Outputs

    Maxent Models (digitized downed trees with structure):

        Model output with six variables and regularization multiplier of 1.0

        Model output with six variables and regularization multiplier of 2.0

        Model output with six variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 1.0

        Model output with three variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 7.0

    Maxent Models (all digitized downed trees):

        Model output with six variables and regularization multiplier of 1.0

        Model output with six variables and regularization multiplier of 2.0

        Model output with six variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 1.0

        Model output with three variables and regularization multiplier of 3.0

        Model output with three variables and regularization multiplier of 6.0

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41 to 50 of 223 Results
Tree_7_Results.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 - 11.3 MB - MD5: b8addc646a0ac8d43d8235afd4b50247
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 three variables and regularization multiplier of 6.0
ZIP Archive - 11.3 MB - MD5: 257e9c0ac1e04e53cae98a45204cd1ab
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 three variables and regularization multiplier of 6.0
ZIP Archive - 11.2 MB - MD5: c2f3df0cb9d2c2436b95dc154acb33e9
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 three variables and regularization multiplier of 6.0
ZIP Archive - 56.5 MB - MD5: 10010632fab1a215e6ae3c4d80c5fe6c
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 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
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...
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