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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71 to 80 of 223 Results
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 2.0
ZIP Archive - 116.6 MB - MD5: 7754bc275054d9645d0d07368dc1f3ad
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 2.0
ZIP Archive - 117.9 MB - MD5: f968412b12cd5836ad4493572822ece0
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 2.0
ZIP Archive - 115.9 MB - MD5: 593e77e828e06de3e94a2c1adacf96c0
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 2.0
ZIP Archive - 581.4 MB - MD5: f6af7dc8ee8d08b16160032b2ff6dcd9
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 2.0
ZIP Archive - 130.4 KB - MD5: 311dd3637ea43db139cd541392675ec6
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 3.0
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 3.0", https://doi.org/10.18738/T8/AJFW6L, 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 3.0
Plain Text - 204.5 KB - MD5: f82a1517a8bd6f2d09d59d267c387f16
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 3.0
Comma Separated Values - 14.6 KB - MD5: 010bf637152bd5f34a876a3d117d030f
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 3.0
ZIP Archive - 116.6 MB - MD5: e63a43db569c1aed945ef07574899aed
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 3.0
ZIP Archive - 115.5 MB - MD5: 8793f38d8a02f877119bc496e7d7d14e
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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