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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161 to 170 of 206 Results
Tree_4_Results.zip
Jun 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 112.4 MB - MD5: 515e54a2077efc866195893e89eb4c8f
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 110.1 MB - MD5: 142ddbb3d102f40f16ed29ea057b5a8e
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 107.5 MB - MD5: f0b0386033ef78d9138af587f5a3b121
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 110.6 MB - MD5: a8a412cf8cabf96c55430f65f2ef5103
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 109.4 MB - MD5: 8213ee69b51be110fed42660424793b8
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 78.7 MB - MD5: 991ecec5cee12b57c8bfeb004e5bd657
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 541.6 MB - MD5: 593a2c0d337dc7b287a6fa250606849a
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 8, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with six variables and regularization multiplier of 3.0
ZIP Archive - 132.4 KB - MD5: 18acd6b99a363d81f115d84f78c1194e
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).
EDFR.zip
Jun 8, 2020 - Environmental Variables Used in Spatial Analysis
Shapefile as ZIP Archive - 306.9 KB - MD5: 1930e5f71f6b438879055487a3faf373
Consists of five classes that represent levels informed by the euclidean distance from the main river channel. Classification is based on a Jenks-breaks classification within ArcGIS Desktop® 10.5 and approved by expert review. Only those distance values within the model evaluatio...
Elevation.zip
Jun 8, 2020 - Environmental Variables Used in Spatial Analysis
Shapefile as ZIP Archive - 9.8 MB - MD5: cf5dbd2aa6bb00e91e7ba6adc145a876
Consists of four classes that represent levels informed by elevation values taken from topography featured in Castillo et.al. (under review). Classification is based on expert review. Only those elevation values within the model evaluation domain are used.
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