Grantee Research Project Results
2010 Progress Report: Consequences of Global Climate Change for Stream Biodiversity and Implications for theApplication and Interpretation of Biological Indicators of Aquatic Ecosystem Condition
EPA Grant Number: R834186Title: Consequences of Global Climate Change for Stream Biodiversity and Implications for theApplication and Interpretation of Biological Indicators of Aquatic Ecosystem Condition
Investigators: Hawkins, Charles P. , Tarboton, David G. , Jin, Jiming
Institution: Utah State University
EPA Project Officer: Packard, Benjamin H
Project Period: September 1, 2009 through August 31, 2012 (Extended to July 31, 2013)
Project Period Covered by this Report: September 1, 2009 through August 31,2010
Project Amount: $789,532
RFA: Consequences of Global Change for Water Quality (2008) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Climate Change , Watersheds , Aquatic Ecosystems , Water
Objective:
The main objective of our proposed research is to assess how changes in stream temperature and hydrology associated with global/regional climate change will influence (1) site- and regional-scale biodiversity of stream ecosystems; and (2) the performance and interpretation of biological indicators, which are used to determine if streams are meeting the biological water quality goals of the Clean Water Act.
Progress Summary:
Our main accomplishments to date include: (1) completion of climate predictions for the 48 conterminous states (CONUS); (2) development of three stream water temperature models for the United States west of the Mississippi River; (3) completion of a pilot study in California that produced predictions of changes in stream invertebrate biodiversity from predicted changes in air temperature, annual precipitation and predicted changes in stream conductivity; and (4) identification of candidate flow variables that are ecologically relevant, which we will model as a function of predicted changes in precipitation and temperature and other climate insensitive variables.
Climate – For the climate modeling, we used the latest version (3.2) of the Weather Research Forecasting (WRF) model and coupled it with the Community Land Model (CLM) version 3.5 to produce climate projections for the CONUS at 50 km resolution. We generated 50-year 50-km resolution historical simulations (1949-1999) with WRF forced with both NCEP and CCSM data and 30-year 50 km resolution forecasts (2001-2010, 2056-2065 and 2090-2099) with WRF-CCSM. We also have statistically downscaled these results to 4 km resolution.
Stream temperature – We are using a non-linear, non-parametric modeling technique called Random Forests to empirically model mean daily summertime, wintertime and annual stream temperatures (MDST, MDWT and MAT, respectively). The models were based on data obtained from 1,058, 713 and 395 U.S. Geological Survey (USGS) gauging stations for which long-term temperature data were available. We used information about the natural (climate, topography, watershed area/shape, base-flow index, solar radiation, vegetation) and anthropogenic (dams, agriculture, urbanization) watershed characteristics upstream of each temperature station as predictors in these models. Validation of the models with independent data showed excellent model performances (R2 = 0.90, 0.88, 0.95; RMSE = 2.1 °C, 1.4 °C, 0.9 °C, normalized RMSE = 7%, 7%, 4% for MDST, MDWT, and MAT, respectively).
Hydrology – We have identified 1,512 USGS gauging stations with flow data for reference quality basins and have obtained the long-term flow data for each of these stations. We have identified 17 flow variables that we will calculate from the data at these stations: (1) the Baseflow Index (BFI), (2) the coefficient of variation of daily flow, (3) mean daily discharge, (4) mean number of zero flow days per year, (5) the daily flow with a 1.67 year recurrence interval, (6) Colwell’s index of predictability, (7) Colwell’s index of constancy, (8) Colwell’s index of contingency, (9) mean 7-day minimum flow, (10) mean 7-day maximum flow, (11) number of flow reversals per year, (12) flood duration (13-15) mean time at which 25%, 50%, and 75% of total flow occurs, (16) the first harmonic of flow, and (17) the mean date of peak flow.
Pilot study – We developed a multi-taxon niche model based on 327 reference-quality stream sites in California. This model predicted probabilities of capture for 340 taxa as a function of three climate sensitive variables (mean annual air temperature, mean annual precipitation, water conductivity) and two climate invariant variables (basin area and elevation range between the highest point in the basin and the sampling point). We then estimated how the probabilities of capture of each taxon would vary at each site with the changes in climate predicted by the statistically downscaled data. We also used these results to estimate how frequencies of detection of each taxon would change across the 327 sites. The results imply that substantial changes in taxonomic composition will occur at each site by 2090, that sites will lose about 10% of their richness, but that no regional loss of taxa will occur. The predicted changes in taxa composition and richness at individual sites are predicted to produce changes in indices of biological integrity that are similar in magnitude to the values observed at streams currently altered by heavy land use or pollution.
Future Activities:
We will perform extensive physical analysis of the climate predictions with both 50-km and 4-km resolution data to quantitatively understand the physical mechanisms and processes behind climate change over the CONUS. We plan to complete the stream temperature modeling for streams east of the Mississippi River and the modeling of how the 17 flow variables will respond to climate change. We also will start to build the muti-taxon niche models that will apply to the entire CONUS and thus allow us to estimate U.S.-wide changes in stream invertebrate biodiversity and indices of biotic integrity.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
Other project views: | All 73 publications | 14 publications in selected types | All 12 journal articles |
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Type | Citation | ||
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Jin J, Miller NL. Improvement of snowpack simulations in a regional climate model. Hydrological Processes 2011;25(14):2202-2210. |
R834186 (2010) R834186 (2011) R834186 (2012) R834186 (Final) |
Exit Exit |
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Jin J, Miller NL. Regional simulations to quantify land use change and irrigation impacts on hydroclimate in the California Central Valley. Theoretical and Applied Climatology 2011;104(3-4):429-442. |
R834186 (2010) R834186 (2011) R834186 (2012) R834186 (Final) |
Exit Exit Exit |
Supplemental Keywords:
EPA Regions 1-10, thermal modification, hydrologic modification, modeling, biological indicators, biological assessment, biological integrity, Air, RFA, climate change, Air Pollution Effects, Atmosphere, RFA, Air, climate change, Air Pollution Effects, AtmosphereRelevant Websites:
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.