Grantee Research Project Results
2012 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, 2011 through August 31,2012
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) refinement of climate predictions for the 48 conterminous states (CONUS), (2) expansion of three stream temperature models initially developed for the United States west of the Mississippi River to the CONUS, (3) application of these stream temperature models to historical early 20th century and forecasted 21st century climate regimes to quantify how stream thermal regimes have changed and will continue changing with climate change, (4) refinement of candidate stream flow variables to better characterize the main components of the flow regime and calculation of these variables at 1512 reference-quality U.S. Geological Survey (USGS) gauging stations, (5) analysis of historical trends in precipitation and stream flow variables, (6) characterization and mapping of major stream flow regimes within the CONUS under existing climate regimes, and (7) initial development of the multi-taxon niche models that will be used to predict biodiversity response to climate change.
Climate – For the climate modeling, we have generated three sets of 31-year historical simulations (1969-1999) with the Weather Research Forecasting (WRF) model at 50 km resolution forced with: (1) the National Centers for Environmental Predictions (NCEP) reanalysis data, (2) original Community Climate System Model (CCSM) data, and (3) bias-corrected CCSM data. The future projections were made with (2) and (3) for the periods of 2001-2010, 2056-2065, and 2090-2099. We have further downscaled these 50 km resolution climate projections to 4 km resolution through statistical techniques.
Stream temperature – We refined our models of mean summer, mean winter, and mean annual stream temperatures (MSST, MWST and MAST, respectively) to better estimate thermal reference conditions expected at individual stream reaches. The models were based on data obtained from 570 MSST, 481 MWST, and 273 MAST USGS gauging sites, respectively, for which long-term temperature data were available. We used information about the natural watershed characteristics (climate, topography, watershed area/shape, base-flow index, solar radiation, vegetation) upstream of each temperature station as predictors in these models. Evaluation of the models with bootstrapping techniques showed excellent model performances (R2 = 0.87, 0.89, 0.95 and RMSE = 1.9 °C, 1.4 °C, 1.1 °C for MSST, MWST, and MAST, respectively).
Hydrology – We refined the characterization of natural stream flow regimes based on high-quality and largely complete flow data from 607 USGS gauging stations located in reference quality basins. We applied principal components analysis to 16 ecologically relevant flow variables to identify five major, statistically independent, dimensions of the flow regime of natural streams and rivers: steadiness, magnitude, reversals, timing, and predictability. We then applied cluster analysis to these five principal component axes to identify seven major classes of flow regime. Finally, we have developed an initial empirical model to predict the flow regime class expected at a stream reach based on watershed and climatic variables.
Multi-taxon niche modeling – Since the last project report, we have developed three sets of multi-taxon niche models, which will be used to predict the effects of climate change on the biodiversity of different assemblages of freshwater organisms. These models include one set for stream/river macroinvertebrates, the primary target of the initial proposed work. We have also been able to take advantage of the availability of nationwide data for stream/river diatoms and lake benthic macroinvertebrates to build models of national (CONUS) scope for those assemblages. Once the final hydrologic data are available, we will modify the models to use both forecasted changes in water temperature and flow regimes to predict biotic responses.
Future Activities:
The remainder of the project period will be devoted to coupling climate projections with the stream temperature and flow regime models to produce the inputs required by the multi-taxon niche models to predict biological change in response to climate change.
Journal Articles on this Report : 7 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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Deng B, Liu S, Xiao W, Wang W, Jin J, Lee X. Evaluation of the CLM4 Lake Model at a large and shallow freshwater lake. Journal of Hydrometeorology 2013;14(2):636-649. |
R834186 (2012) R834186 (Final) |
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Hill RA, Hawkins CP, Carlisle DM. Predicting thermal reference conditions for USA streams and rivers. Freshwater Science 2013;32(1):39-55. |
R834186 (2011) R834186 (2012) R834186 (Final) |
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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) |
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Jin J, Wen L. Evaluation of snowmelt simulation in the Weather Research and Forecasting model. Journal of Geophysical Research-Atmospheres 2012;117(D10):D10110 (16 pp.). |
R834186 (2011) R834186 (2012) R834186 (Final) |
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Meyer JDD, Jin J. Bias correction of the CCSM4 for improved regional climate modeling of the North American monsoon. Climate Dynamics 2016;46(9):2961-2976. |
R834186 (2012) |
Exit |
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Zhao L, Jin J, Wang S-Y, Ek MB. Integration of remote-sensing data with WRF to improve lake-effect precipitation simulations over the Great Lakes region. Journal of Geophysical Research-Atmospheres 2012;117(D9):D09102 (12 pp.). |
R834186 (2011) R834186 (2012) R834186 (Final) |
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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:
The S.J. & Jessie E. Quinney College of Natural Resources Exit
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.