This data set consists of density ratings of submersed aquatic vegetation and Bithynia tentaculata abundance in Pool 8 of the UMR in 2015.

These data are spreadsheet data which are a subset of thesis data for the Degree of Doctorate of Philosophy in Marine Science. The objectives of the study are to determine how community structure of the Mobile Tensaw Delta has changed due to invasive submerged aquatic vegetation (SAV) altering food web interactions. Data are in .csv format. Parameters include: latitude, longitude, SAV type, species caught in throw trap, species abundance in throw trap, leaf surface area within trap, meters2 surface area (leaf surface area multiplied by 4), ratio between species abundance and leaf surface area of each type of SAV, and ash-free dry weight of sampled SAV.

There is a fundamental knowledge gap on the distribution, prevalence, intensity, and ecology of salmonid myxozoan parasites in the Lake Sammamish watershed, Washington. To address this knowledge gap, we tested water samples for Ceratonova shasta, Parvicapsula minibicornis and Tetracapsuloides bryosalmonae DNA from 84 sites distributed throughout the Lake Sammamish watershed in fall 2019 and 74 sites in spring 2020. Our surveillance identified zones with high waterborne parasite loads and provides a proof of concept for this approach that could be expanded throughout the larger Lake Washington watershed.

There is a fundamental knowledge gap on the distribution, prevalence, intensity, and ecology of salmonid myxozoan parasites in the Lake Sammamish watershed, Washington. To address this knowledge gap, we tested water samples for Ceratonova shasta, Parvicapsula minibicornis and Tetracapsuloides bryosalmonae DNA from 84 sites distributed throughout the Lake Sammamish watershed in fall 2019 and 74 sites in spring 2020. Our surveillance identified zones with high waterborne parasite loads and provides a proof of concept for this approach that could be expanded throughout the larger Lake Washington watershed.

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.

A quantitative pilot study of the composition of the benthic community of macro-invertebrates on intertidal rocky platforms was undertaken to: a) provide detailed information on variation in biodiversity along the length of the Ningaloo Marine Park; and b) determine the appropriate design of a monitoring protocol powerful enough to determine predefined levels of change. As part of the larger WAMSI Node 3.2.2b study there was specific sampling of small giant clams (Tridacna maxima). Data available includes Lengths of small giant clams (Tridacna maxima) mapped at 20 sites (3119 rows x 11 columns including identifying information for each length): [WAMSI3.2.2bGiantClams.csv] GPS readings as UTM values for locations of transects used to map positions of Tridacna maxima (giant clams) (404 rows x 6 columns, including sample identification information): [WAMSI3.2.2bTridacnaUTM.csv] Shoreward, southern corners of Transect 1 and some others for areas where Tridacna maxima were measured as reported in Research Chapter 4. [WAMSI3.2.2bGiantClams.kmz] Data files come with metadata / descriptions of the column titles and codes.

The dimensions of each organism were measured with a Whipple grid and the biovolume was estimated using the simplest geometric shape (e.g., cylinder, cone, sphere, etc.) that best fit the shape of each taxon. Shapes were assigned according to Hillebrand et al. (1999). Biovolume was calculated for the first five organisms/counting units of each taxon identified in a sample. The average biovolume was then used to calculate total biovolume of each taxon in the sample.

Species Inventory project as-delivered dataset, geopackages and associated geospatial files The Upper Delaware Scenic and Recreational River (UPDE) unit of the National Park Service partnered with the Academy of Natural Sciences of Drexel University (ANS) to perform a freshwater snail inventory within the park. ANS and UPDE teams conducted field research in July and August of 2022 and 2023 using a combination of kick sampling and hand-picking methods to determine the abundance and diversity of freshwater snail populations. Fifty-four sites were chosen along the ~70 miles of the Delaware River within UPDE and included coldwater and warmwater fisheries zones. In 2022, field collections occurred at 30 sites along the river edge from Hancock, NY to the No. 2 railroad bridge near Mill Rift, PA. In 2023, field work occurred at 24 sites in more disturbed areas like river access points and boat launches, and within habitats that were not sampled in 2022 (i.e., backwater, channels, and islands). Snails were identified using traditional morphological taxonomy and DNA barcoding of the CO1 (Cytochrome c oxidase I) gene. Additional environmental DNA (eDNA) was analyzed from water collected at ten eDNA Atlas Sites. This study identified 27 taxa of snails, one of which is a non-native species, the Japanese Mystery Snail (Cipangopaludina japonica). A better understanding of the snail community and the ecosystem has been gained with the results of this inventory which will inform effective and responsible river management plans.

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.