Forest management presents challenges to accurate prediction of water and carbon exchange between the land surface and atmosphere, due to its alteration of forest structure and composition. We examined how forest species types in northern Wisconsin affect landscape scale water fluxes predicted from models driven by remotely sensed forest classification. A site-specific classification was developed for the study site. Using this information and a digital soils database produced for the site we identified four key forest stand types: red pine, northern hardwoods, aspen, and forested wetland. Within these stand types, 64 trees representing 7 species were continuously monitored with sap flux sensors. Scaled stand-level transpiration from sap flux was combined with a two-source soil evaporation model and then applied over a 2.5 km × 3.0 km area around the WLEF AmeriFlux tower (Park Falls, Wisconsin) to estimate evapotranspiration. Water flux data at the tower was used as a check against these estimates. Then, experiments were conducted to determine the effects of aggregating vegetation types to International Geosphere- Biosphere Program (IGBP) level on water flux predictions. Taxonomic aggregation resulting in loss of species level information significantly altered landscape water flux predictions. However, daily water fluxes were not significantly affected by spatial aggregation when forested wetland evaporation was included. The results demonstrate the importance of aspen, which has a higher transpiration rate per unit leaf area than other forest species. However, more significant uncertainty results from not including forested wetland with its high rates of evaporation during wet summers.
All Science Journal Classification (ASJC) codes
- Global and Planetary Change
- Environmental Chemistry
- Environmental Science(all)