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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101 to 110 of 223 Results
Tree_7_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: 319944aa0c13e0e00198122e0ba27adf
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 digitized downed trees (structure) with three variables and regularization multiplier of 1.0
ZIP Archive - 11.6 MB - MD5: b0c538c6b3b1fd0983330b8b8dd9e97a
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 digitized downed trees (structure) with three variables and regularization multiplier of 1.0
ZIP Archive - 11.5 MB - MD5: db5080778b65220fed7db0574c208495
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 digitized downed trees (structure) with three variables and regularization multiplier of 1.0
ZIP Archive - 57.4 MB - MD5: f1d2b81f897387e12294e02509092cc9
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 digitized downed trees (structure) with three variables and regularization multiplier of 1.0
ZIP Archive - 33.6 KB - MD5: 0116b77c876a164df6ea476e9a9ecf29
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 three variables and regularization multiplier of 3.0
Jun 9, 2020
FLUD Research Group, 2020, "Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/F2U3QV, 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 3.0
Plain Text - 119.2 KB - MD5: a654b7df7648611723d85c3f51849848
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 3.0
Comma Separated Values - 12.1 KB - MD5: c1d894abd9255d262b89e872e651b54b
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 3.0
ZIP Archive - 11.4 MB - MD5: a245a22bd02b82f2a23bdc358e624645
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 three variables and regularization multiplier of 3.0
ZIP Archive - 11.4 MB - MD5: b3f263c5d2765d4e6904effdf4848cfd
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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