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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Maximum Entropy machine learning model output using all digitized downed trees with six variables and regularization multiplier of 2.0
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 2.0", https://doi.org/10.18738/T8/VMKLOK, 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 2.0
Plain Text - 206.5 KB - MD5: 8c1a3187c6b63b92642d46c7669f22b9
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 2.0
Comma Separated Values - 14.6 KB - MD5: 0f99b4a882a26fa35c6ab63bb4d8b1e5
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 2.0
ZIP Archive - 116.8 MB - MD5: c2aea39363c66f96d2aed2f4417120dc
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 2.0
ZIP Archive - 116.3 MB - MD5: 4def05b92b7215ef7bb50d9a2e6a95b6
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 2.0
ZIP Archive - 116.2 MB - MD5: d6f432928ae8cc41b37ba26033fb3840
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 2.0
ZIP Archive - 116.0 MB - MD5: a61d601a12e4fc6612f3c3727ab6a6cc
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 2.0
ZIP Archive - 117.4 MB - MD5: e67d3306e1baff79d05a3727753c96c4
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 2.0
ZIP Archive - 116.7 MB - MD5: fae026a7120fb53babbb34afee699f9b
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...
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 2.0
ZIP Archive - 116.6 MB - MD5: f758e0ed0119f94ff698e1bb6bfae014
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...
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