Grantee Research Project Results
2013 Progress Report: Combining Climate Model Predictions, Hydrological Modeling, and Ecological Niche Modeling Algorithms to Predict the Impacts of Climate Change on Aquatic Biodiversity
EPA Grant Number: R834195Title: Combining Climate Model Predictions, Hydrological Modeling, and Ecological Niche Modeling Algorithms to Predict the Impacts of Climate Change on Aquatic Biodiversity
Investigators: Knouft, Jason
Institution: Saint Louis University - Main Campus
EPA Project Officer: Packard, Benjamin H
Project Period: August 1, 2009 through July 31, 2011 (Extended to January 31, 2014)
Project Period Covered by this Report: August 1, 2012 through July 31,2013
Project Amount: $246,147
RFA: Consequences of Global Change for Water Quality (2008) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Ecological Indicators/Assessment/Restoration , Watersheds , Water , Climate Change
Objective:
The primary objective of this research has been to predict the impacts of current and future climate on the hydrology and aquatic biodiversity in United States river drainages, with a primary focus on watersheds in Illinois and Alabama. To achieve this objective, data from regionally downscaled global climate models have been integrated with the Soil Water Assessment Tool (SWAT) hydrologic model and species distribution models to test three general hypotheses: (1) climate data, when integrated with landscape hydrologic models, can accurately predict variation in current and future flow regimes; (2) species distribution models, when used in conjunction with hydrologic model outputs and species distribution data, can accurately predict current and future distributions of aquatic taxa; and (3) predicted changes in climate will differentially impact aquatic taxa, with some species experiencing decreases in future habitat availability while other species experience increases in the amount of available habitat.
The primary objectives of the research have been addressed by integrating data derived from nine regionally downscaled global climate models, including three emissions scenarios over two time periods (2051-2060 and 2086-2095) with the landscape-based SWAT hydrologic model to predict changes in flow characteristics in river drainages in Illinois and Alabama based on climate change scenarios. These hydrologic data have then been used to predict the potential impacts of climate change on distributions of fishes, crayfishes, and mollusks in Illinois and Alabama using a maximum entropy ecological niche modeling algorithm (Maxent) as well as other statistical techniques. The impact of hydrologic variation on fishes also has been assessed in major river drainages in different regions of the United States.
An additional objective of this research was added to investigate fish responses to temperature and flow regimes across the geographic range of two species (Pimephales notatus and Etheostoma nigrum). Resting metabolic rate (RMR) and swimming performance were measured at 9°C, 18°C, and 27°C in the lab at Saint Louis University from individuals from 10 populations collected throughout the ranges of P. notatus in the United States. Swimming performance (SP) was measured at 9°C, 18°C, and 27°C in the lab at Saint Louis University from individuals from 10 populations collected throughout the ranges of E. nigrum. The goal of this aspect of the research was to better understand how local populations of aquatic taxa will respond to changes in temperature and flow patterns in the aquatic environment caused by predicted changes in climate.
Progress Summary:
This award was extended by 6 months and this annual report was created by the Project Officer on behalf of the Principal Investigator using the Year 3 and Final Reports, both of which reported on portions or all of the time period of this annual report.
The Soil and Water Assessment Tool (SWAT) was calibrated and validated using distributed streamflow data from 1978-2009, and used to assess the potential impacts of climate change on future streamflow (2051-2060 and 2086-2095) for the Rock River (RRW), Illinois River (IRW), Kaskaskia River (KRW), and Wabash River (WRW) watersheds in the Midwestern United States, primarily in Illinois. The potential impacts of climate change on future water resources were assessed using SWAT streamflow simulations driven by projections from nine global climate models (GCM) under three different greenhouse gas emissions scenarios (A1B, A2, and B1). Compared with past streamflow records, predicted future streamflow based on climate change scenarios in all watersheds is expected to increase in the winter but decrease in the summer. According to 26 GCM projections, overall annual streamflows from 2051-2060 (2086-2095) are projected to decrease up to 45.2% (61.3%), 48.7% (49.8%), 48.7% (56.6%), and 41.1% (44.6%) in the RRW, IRW, KRW, and WRW, respectively. In addition, under the projected changes in climate, intra- and inter-annual streamflow variability generally does not increase over time. Results suggest that increased temperature could change the rate of evapotranspiration and the form of precipitation, subsequently influencing monthly streamflow patterns. Moreover, the spatially varying pattern of streamflow variability under future climate conditions suggests different buffering capabilities among regions.
Future Activities:
Several manuscripts are being planned as well as meeting presentations.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
| Other project views: | All 28 publications | 6 publications in selected types | All 6 journal articles |
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Chien H, Yeh PJ-F, Knouft JH. Modeling the potential impacts of climate change on streamflow in agricultural watersheds of the Midwestern United States. Journal of Hydrology 2013;491:73-88. |
R834195 (2010) R834195 (2011) R834195 (2012) R834195 (2013) R834195 (Final) |
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Niu SQ, Franczyk MP, Knouft JH. Regional species richness, hydrological characteristics and the local species richness of assemblages of North American stream fishes. Freshwater Biology 2012;57(11):2367-2377. |
R834195 (2011) R834195 (2013) R834195 (Final) |
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Supplemental Keywords:
Geographic information systems, hydrology, climate change, biodiversity, species distribution modeling, RFA, Air, Atmosphere, Air Pollution Effects, climate changeRelevant Websites:
http://knouftlab.weebly.com/
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.