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Testing scale dependent assumptions in regional ecosystem simulations
Author(s) -
White Joseph D.,
Running Steven W.
Publication year - 1994
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.2307/3235883
Subject(s) - primary production , environmental science , evapotranspiration , vegetation (pathology) , hydrological modelling , watershed , hydrology (agriculture) , photosynthetically active radiation , advanced very high resolution radiometer , ecosystem , atmospheric sciences , climatology , ecology , satellite , geology , photosynthesis , medicine , botany , geotechnical engineering , pathology , machine learning , aerospace engineering , computer science , engineering , biology
. 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‐km 2 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.