| Coupling of the carbon and hydrological cycles, such as the relationship between photosynthesis and transpiration, are essential global and environmental change issues, which are interrelated to future water availability, carbon and water feedback to climate, and carbon sequestration. The goal of this dissertation is to recapitulate three projects that use independent experimental, analytical, and modeling approaches to evaluate the influence of climate change on the carbon and water cycle. In the first study, I used the Terrestrial ECOsystem (TECO) model to evaluate the ecohydrological and carbon-water coupling response to single and multiple climate change scenarios - this included combinations of warming, elevated CO2, and altered precipitation on runoff, evaporation, transpiration, rooting zone soil moisture content (RZSM), water use efficiency (WUE), and rain use efficiency (RUE) - in a North American tallgrass prairie. The 200 different scenarios, with gradual change for 100 years, showed strong responses in runoff, evaporation, transpiration, and RZSM to changes in temperature and precipitation, while effects of CO 2 changes were relatively little. For example, runoff decreased by 50% with a 10°C increase in temperature and increased by 250% with doubled precipitation. Ecosystem-level RUE increased with CO2, decreased with precipitation, and optimized at 4-6°C of warming. In contrast, plant-level WUE was highest at doubled CO2, doubled precipitation, and ambient temperature. The different response patterns of RUE and WUE signify that processes at different scales responded uniquely to climate change. Combinations of temperature, CO2, and precipitation anomalies interactively affected response magnitude and/or patterns of ecohydrological processes. Our results suggest that ecohydrological processes were considerably affected by global change factors and then likely regulate other ecosystem processes, such as carbon and nitrogen cycling.;The second experiment was conducted to assess the effects of warming and doubled precipitation on soil water dynamics in a tallgrass prairie ecosystem. Using a one year "pulse" experiment, with 4°C warming and a doubling in precipitation intensity, an analysis of annual soil moisture, soil moisture frequency, and water loss was done. There was a decrease in soil moisture frequency from 0--120 cm in both warming and warming with increased precipitation experiments. Different soil depths had similar patterns of change in soil moisture and soil temperature frequency. A statistical difference in soil moisture was found among the different treatment types. A correlation of evapotranspiration and soil moisture allowed for an estimate of changes in evapotranspiration from the wilting point (Ew) to maximum evapotranspiration (Emax). These results revealed a shift in the slope and position of Ew to Emax with experimental warming. Our results showed that the soil moisture dynamics and the ecohydrology were significantly changed by different global climate change scenarios.;The third study was an investigation the role of experimental warming on carbon-water coupling across multiple ecosystem types. Here I used a meta-analysis technique to evaluate the impact of experimental warming on rain use efficiency. These results indicate that increases in temperature cause a significant increase in RUE. Additionally, we show that experimental warming had the largest impact on shrubland and tundra sites, while grasslands, receiving the highest amount of precipitation and lowest experimental temperatures, had the second lowest response to experimental warming. Wetland biomes had the lowest response to experimental warming. This research demonstrates that there are temperature limitations that span multiple ecosystems and these results are beneficial for large-scale modeling projects.;Keywords: global climate change, carbon-water coupling, ecohydrology, terrestrial ecosystem ecology, grassland, warming, precipitation, CO2, rain use efficiency, runoff, evaporation, transpiration, soil moisture, water use efficiency, ecosystem modeling... |
