Impacts of Downed Trees on hydrologic surface connectivity within the Mission River floodplain in Southeast Texas

This dataverse includes datasets as a result of NSF RAPID Award #1760717 that covers the ecological role and impact of downed trees on hydrologic surface connectivity within the Mission River floodplain.

There are two dataverses that have data inputs and products related to Objectives 1 and 2. These are:

Objective 1: Environmental Analyses

Objective 2: Roughness Scenarios

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691 to 700 of 789 Results

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 3.0 ZIP Archive - 11.5 MB - MD5: 86465888fe04c1730e92538a0bd36dcb 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 3.0 ZIP Archive - 57.0 MB - MD5: b617113bb36f8c6e9b7fa17b982517e3 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 3.0 ZIP Archive - 33.3 KB - MD5: 02fb89e1d4b54e927c73ff84ce623742 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).
maxent.log Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0 Plain Text - 118.5 KB - MD5: 72fbad568a97560e55530c9e0395520b 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 7.0 Comma Separated Values - 12.0 KB - MD5: a1cea428060e45303e6734ed42d6840f 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 7.0 ZIP Archive - 11.0 MB - MD5: 9a7c6ba7a22cde5f016736f87cc45c01 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 7.0 ZIP Archive - 10.7 MB - MD5: b81b8f97e37b27acaffc4723a1cfd52c 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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0 ZIP Archive - 10.9 MB - MD5: 21399bdbb16ffa51f560c4dd851f7d17 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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0 ZIP Archive - 11.0 MB - MD5: 5e2ed492534be207d335959f7a96f93e 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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0 ZIP Archive - 10.1 MB - MD5: cb9ee2206fe31e4f9ba07b90cfbd1bc3 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_9_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 - 11.5 MB -

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 3.0

ZIP Archive - 57.0 MB -

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 3.0

ZIP Archive - 33.3 KB -

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).

maxent.log

Jun 9, 2020 - Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0

Plain Text - 118.5 KB -

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 7.0

Comma Separated Values - 12.0 KB -

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 7.0

ZIP Archive - 11.0 MB -

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 7.0

ZIP Archive - 10.7 MB -

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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0

ZIP Archive - 10.9 MB -

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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0

ZIP Archive - 11.0 MB -

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 digitized downed trees (structure) with three variables and regularization multiplier of 7.0

ZIP Archive - 10.1 MB -

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...

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