The data consists of paired observations of relative abundances of benthic macroinvertebrates along with concurrent measurements of water chemistry variables and physical habitat variables. This dataset is associated with the following publication: Griffith, M. Development of national stressor-specific genus sensitivity values. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 895: 165121, (2023).

These are these are the data used in the paper: Assessing the relative importance of stressors to the benthic index, M-AMBI: an example from U.S. estuaries. This dataset is associated with the following publication: Pelletier, M., and M. Charpentier. Assessing the relative importance of stressors to the benthic index, M-AMBI: An example from U.S. estuaries. MARINE POLLUTION BULLETIN. Elsevier Science Ltd, New York, NY, USA, 186: 114456, (2023).

These are these are the data used in the paper: Assessing the relative importance of stressors to the benthic index, M-AMBI: an example from U.S. estuaries. This dataset is associated with the following publication: Pelletier, M., and M. Charpentier. Assessing the relative importance of stressors to the benthic index, M-AMBI: An example from U.S. estuaries. MARINE POLLUTION BULLETIN. Elsevier Science Ltd, New York, NY, USA, 186: 114456, (2023).

These are the data supporting the manuscript, "Benthic macroinvertebrate community response to environmental changes over seven decades in an urbanized estuary in the northeastern United States". This dataset is associated with the following publication: Pelletier, M., D. Cobb, K. Rocha, K. Ho, M. Cantwell, M. Perron, M.A. Charpentier, H.W. Buffum, S.S. Hale, and R. Burgess. Benthic macroinvertebrate community response to environmental changes over seven decades in an urbanized estuary in the northeastern United States. MARINE ENVIRONMENTAL RESEARCH. Elsevier Science Ltd, New York, NY, USA, 169: 105323, (2021).

These are the data supporting the manuscript, "Benthic macroinvertebrate community response to environmental changes over seven decades in an urbanized estuary in the northeastern United States". This dataset is associated with the following publication: Pelletier, M., D. Cobb, K. Rocha, K. Ho, M. Cantwell, M. Perron, M.A. Charpentier, H.W. Buffum, S.S. Hale, and R. Burgess. Benthic macroinvertebrate community response to environmental changes over seven decades in an urbanized estuary in the northeastern United States. MARINE ENVIRONMENTAL RESEARCH. Elsevier Science Ltd, New York, NY, USA, 169: 105323, (2021).

This is coefficient estimates and model performance metrics from the EPA National Rivers and Streams Assessment data.

This is coefficient estimates and model performance metrics from the EPA National Rivers and Streams Assessment data.

There are 20 supplemental data files associated with this article. These files describe the process of assigning macroinvertebrate taxa to thermal preference categories and analyses associated with them. There are spreadsheets of macroinvertebrate taxa used in the publication and the resulting calculations for thermal preferences, including taxonomic relationships and variability associated with the taxonomic relationships (parent-child). Also included are the R scripts for calculating the Macroinvertebrate Thermal Tolerance Index (MTTI) and thermal preference metrics using the macroinvertebrate data. Additional macroinvertebrate data included in the files are: • Scatterplot of total number of individuals vs total number of taxa • Full list of BMI data sources • Map of BMI sampling sites, color-coded by data source • List of taxa that were in the tolerance analysis dataset but occurred in fewer than 30 samples For the plots showing probability of occurrence of a taxa, there is also a guide to assist with interpretation of the plots. Additional information for the MTTI includes: ● Calibration (CAL) and Validation (VAL) datasets ○ Summary Statistics ○ Boxplots of natural and disturbance variables ○ PCA biplots ● Modeling techniques ○ Deshrinking and tolerance downweighting ● Comparisons between field temperature and modeled temperatures (MWMT, MTTI) ● Correlations with other stressors Thermal metric plots for each MWMT class are also included. This dataset is associated with the following publication: Hubler, S., J. Stamp, S.P. Sullivan, M. Fernandez, C. Larson, K. Macneale, R.W. Wisseman, R. Plotnikoff, and B. Bierwagen. Improved thermal preferences and a stressor index derived from modeled stream temperatures and regional taxonomic standards for freshwater macroinvertebrates of the Pacific Northwest, USA. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 160: 111869, (2024).

We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990–2010 for the population of streams in the CRB and serves as a foundation for future model development. This dataset is associated with the following publication: Johnston , J., C. Barber , K. Wolfe , M. Galvin , M. Cyterski , and R. Parmar. An integrated ecological modeling system for assessing impacts of multiple stressors on stream and riverine ecosystem services within river basins. ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam, NETHERLANDS, 354: 104-114, (2017).

This dataset is comprised of water quality data and benthic macroinvertebrate data collected from basins in Colorado, USA, and Finland. The data includes ancillary water quality characteristics but also a suite of trace metals observed at each site. Also included are modeled outputs that characterize the bioavailability of each trace metal to a biotic ligand. These data were used to explore the importance of metal toxicity and pH as stressors on benthic macroinvertebrates characterized as the number of unique Ephemeroptera + Plecoptera + Trichoptera genera observed at each site. An interpretive summary of the work follows. One of the primary goals of biological assessment of rivers is to identify whether contaminants or other stressors limit the ecological potential of running waters. Quantitative relationships between species richness and environmental gradients are useful to better understand biodiversity patterns. Many studies have focused on the effects of pH and high metals concentration on freshwater macroinvertebrate community but, due to data limitation and the lack of tools, the ecological effects of metals mixture in streams are less studied and still unclear. We address an old question: is it the low pH or the metals that are deleterious for stream ecosystems? With new tools, we can achieve improved understanding of the true importance of the two stressors. Our study quantified the limiting effects of pH and chronic metal toxicity for macroinvertebrate community richness. We verified that current environmental quality standards for metals are protective of aquatic biodiversity and proved that pH has a direct limiting effect on richness and it not acts only via modifying the availability and the toxicity of metals. These questions were applied to a dataset spanning two continents and diversity of geologies and ecosystems providing a broad basis for understanding how physico-chemical conditions limit global freshwater biodiversity.