System-scale restoration efforts within the Upper Mississippi River Restoration Program have included annual monitoring of submersed aquatic vegetation (SAV) since 1998 in four representative reaches spanning approximately 440 river km. We developed predictive models relating monitoring data (site-scale SAV abundance indices) to diver-harvested SAV biomass, used the models to back-estimate annual standing stock biomass between 1998 and 2018 and compared biomass estimates to previous abundance measures. Two morphologically distinct groups of SAV with differing sampling efficiencies were modeled and estimated separately: the first category included only Vallisneria americana which has long, unbranched leaves and dominates lotic environments, while the second category included 17 branched morphology species (e.g. Ceratophyllum demersum and Elodea canadensis) that dominate lentic environments. Two non-native species (Myriophyllum spicatum and Potamogeton crispus) were included in the branched category for model development but were estimated separately as a fraction of branched species biomass due to a small sample size and a lack of training data.

Estimation of submersed aquatic vegetation (SAV) biomass was evaluated using field data collected in 2017, and targeted analyses of three existing data sets: 1) Yin and Kreiling (2001), Drake et al. (2016), and 3) LTRM vegetation data (1998 – 2017). Two field studies were completed in 2017. The first targeted SAV biomass in raked plots and was conducted in collaboration with USFWS annual Lake Onalaska Vallisneria americana monitoring. In the second study, fresh weights of raked SAV were recorded at approximately 10% of LTRM Pools 4 and 8 2017 sampling sites.

Estimation of submersed aquatic vegetation (SAV) biomass was evaluated using field data collected in 2017, and targeted analyses of three existing data sets: 1) Yin and Kreiling (2001), Drake et al. (2016), and 3) LTRM vegetation data (1998 – 2017). Two field studies were completed in 2017. The first targeted SAV biomass in raked plots and was conducted in collaboration with USFWS annual Lake Onalaska Vallisneria americana monitoring. In the second study, fresh weights of raked SAV were recorded at approximately 10% of LTRM Pools 4 and 8 2017 sampling sites.

The Long-Term Resource Monitoring element (LTRM) of the Upper Mississippi River Restoration program (UMRR) has conducted aquatic vegetation and water quality surveys in several navigation pools since the mid 1990’s. Over a 20-year period (1998-2017), the off-channel (i.e. backwater) areas in upper Pool 4 remained chronically turbid and supported a limited submersed macrophyte community with high between-year variability in the proportion of sites where submersed plants were observed. Water surface elevation and discharge rates also fluctuated substantially within- and between-years in the upper pool. Pearson correlation analysis indicated that between-year change in the proportion of sites where submersed macrophytes are observed is correlated to the number of high summer discharge days 1 year prior (r = -0.48); the number of low summer discharge days during the current year (r =0.46) and one year prior (r = 0.62); minimum discharge (r = 0.52) and the duration that depth at vegetation sample sites was within the estimated photic zone (i.e. a metric that reflects a combination of water clarity and water surface elevation) during the current summer (r = 0.63). Conditions more than one year prior and during the other seasons (winter, spring, fall) exhibited little correlation to subsequent fluctuations in the prevalence of submersed macrophytes.

The Long-Term Resource Monitoring element (LTRM) of the Upper Mississippi River Restoration program (UMRR) has conducted aquatic vegetation and water quality surveys in several navigation pools since the mid 1990’s. Over a 20-year period (1998-2017), the off-channel (i.e. backwater) areas in upper Pool 4 remained chronically turbid and supported a limited submersed macrophyte community with high between-year variability in the proportion of sites where submersed plants were observed. Water surface elevation and discharge rates also fluctuated substantially within- and between-years in the upper pool. Pearson correlation analysis indicated that between-year change in the proportion of sites where submersed macrophytes are observed is correlated to the number of high summer discharge days 1 year prior (r = -0.48); the number of low summer discharge days during the current year (r =0.46) and one year prior (r = 0.62); minimum discharge (r = 0.52) and the duration that depth at vegetation sample sites was within the estimated photic zone (i.e. a metric that reflects a combination of water clarity and water surface elevation) during the current summer (r = 0.63). Conditions more than one year prior and during the other seasons (winter, spring, fall) exhibited little correlation to subsequent fluctuations in the prevalence of submersed macrophytes.

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.

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.

The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. These data have been used to create a variety of products, one of which is a data set used to classify aquatic areas. The 2020 aquatic areas data sets were created by first generalizing the available land cover/use data into a land/water data set, then reinterpreting the areas classified as water to determine the type of aquatic area. Area coverage for this data set is the Upper Mississippi River between Minneapolis, MN and Cairo, IL, and the Illinois River from its confluence with the Mississippi to Joliet, IL.

The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. These data have been used to create a variety of products, one of which is a data set used to classify aquatic areas. The 2020 aquatic areas data sets were created by first generalizing the available land cover/use data into a land/water data set, then reinterpreting the areas classified as water to determine the type of aquatic area. Area coverage for this data set is the Upper Mississippi River between Minneapolis, MN and Cairo, IL, and the Illinois River from its confluence with the Mississippi to Joliet, IL.

The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. These data have been used to create a variety of products, one of which is a data set used to classify aquatic areas. The 2020 aquatic areas data sets were created by first generalizing the available land cover/use data into a land/water data set, then reinterpreting the areas classified as water to determine the type of aquatic area. Area coverage for this data set is the Upper Mississippi River between Minneapolis, MN and Cairo, IL, and the Illinois River from its confluence with the Mississippi to Joliet, IL.