Predictions for the presence of submersed aquatic vegetation in the upper Mississippi River, USA, from years 2010-2019

The datasets are to accompany a manuscript describing the prediction of submersed aquatic vegetation presence and its potential vulnerability and recovery potential. The data and accompanying analysis scripts allow users to run the final random forests predictive model and reproduce the figures reported in the manuscript. Files from several data sources (aqa_2010_lvl3_pct_oute_joined_VEG_BARCODE.csv, eco_states_near_SAV.csv, ltrm_vegsrs_thru2019_GEOMORPHIC_METRICS_final.csv, vegetation_data.csv, and water_full.csv) were combined into a single .csv file (analysis_data_for_SAV_RandomForest.csv) used as the input for the random forest model. When intersecting points with geomorphic metrics some sites were moved slightly to ensure they were contained within aquatic areas (ltrm_veg_sites_moved.csv). Outputs from the random forest model are contained in the SAV_RandomForest_results.csv and SAV_RandomForest_results_testing_set.csv files.