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Testing scale dependent assumptions in regional ecosystem simulations
Authors:Joseph D. White  Steven W. Running
Abstract:Abstract. We present a Regional Ecosystem Simulation System (RESSys) which uses satellite data to define vegetation properties, topographic and soil data to define site characteristics, and a climate generator program to build a topographically sensitive microclimate map. We use a 150-km2 mountainous forested watershed in Glacier National Park to test the consequences of modeling various ecosystems processes using different versions of RESSys with increasing simplification of the landscape: (1) spatial scaling generated using 30 m x 30 m Landsat Thematic Mapper data versus 1 km x 1 km Advanced Very High Resolution Radiometer data for vegetation definition; (2) modeling hydrologic dynamics produced by using a topographic routing model versus a simple soil ‘bucket’ model; (3) variable landscape partitioning based on patterns of topographic complexity; and (4) representation of annual net primary productivity (ANPP) using an absorbed photosynthetic active radiation (APAR) model. We evaluate results of these simulations by comparison with average values and areal distributions of photosynthesis, evapotranspiration, hydrologic outflow, and ANPP. Our primary goal is to test whether areal average flux of carbon and water can be scaled linearly over a complex landscape. We found that daily photosynthesis could be predictably estimated between modeling scales with correlation coefficients ranging between 0.89 to 0.99. ANPP was highly correlated among the modeling scales with maximum differences between ANPP prediction of ca. 0.5Mg C ha-1 yr-1. Evapotranspiration was similarly predictable between scales but was influenced by differences associated with hydrologic modeling. Hydrologic outflow was not highly correlated between different modeling scales as a function of the different hydrologic models used at different scales.
Keywords:GIS  Hydrology  Modeling  Photosynthetic  Primary productivity  Radiation  Satellite data  Spatial scale  Harlow et al. (1991)
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