ESM_SIM_DATA_ANN_UNPRUNNED

ESM_sim_data_3. Estimates of contribution of MCSim parameters to variation in biodiversity metrics based on contribution statistics from artificial neural networks (ANNs) trained and validated on simulated metacommunity outcomes.

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Variables
Diversity Metric ID
  • Label:
  • Definition: Diversity Metric ID
  • Type: Nominal
  • Missing values: None specified
Predictor Variable
  • Label:
  • Definition: Predictor Variable
  • Type: Nominal
  • Missing values: None specified
Predictor contribution to variation in response variable
  • Label:
  • Definition: Predictor contribution to variation in response variable
  • Type: Nominal
  • Missing values: None specified
Contribution p value
  • Label:
  • Definition: Contribution p value
  • Type: Nominal
  • Missing values: None specified
Predictor relative importance (RI) to variatino in response variable
  • Label:
  • Definition: Predictor relative importance (RI) to variatino in response variable
  • Type: Nominal
  • Missing values: None specified
RI p value
  • Label:
  • Definition: RI p value
  • Type: Nominal
  • Missing values: None specified
Keep predictor in pruned model?
  • Label:
  • Definition: Keep predictor in pruned model?
  • Type: Nominal
  • Missing values: None specified
N permutations used to estimate p values
  • Label:
  • Definition: N permutations used to estimate p values
  • Type: Nominal
  • Missing values: None specified
Data Source Details

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