Data and code from: Non-modeling applications of MaxEnt logic can identify abiotic and biotic determinants of species’ distributions: a case study with the American Eel (Anguilla rostrata)

This fileset contains three files from "Non-modeling applications of MaxEnt logic can identify abiotic and biotic determinants of species’ distributions: a case study with the American Eel (<i>Anguilla rostrata</i>)".(1) A1_rawData. Excel file containing the subwatershed x predictor variable matrix. Sheet 1 contains the raw data for all predictor variables across all data classes. Sheet 2 contains a description and data source for each variable in the matrix. Data sources are detailed in the main text.(2) A2_traitData. Excel file containing the fish species x trait matrix. Sheet 1 contains raw data for the 139 species included in the analysis. Sheet 2 contains descriptions for each trait in the matrix. Sheet 3 contains the references used to assemble the traits database.(3) A3_Code. Text file containing code used in the analysis and data collection. This text file contains Python code to compute subwatershed trait summaries and R code to compute observed sample-background overlap (SBO) and permutations for significance of observed SBO.