The Regionalized Sensitivity Analysis (RSA) was developed in 1978, for identifying critical unknown processes in poorly defined systems, thus directing the focus of further scientific investigations. Here, we demonstrate its application to model structure identification, by ranking the constituent hypotheses and identifying the critical elements for progressive revision of the model. Our case study is Lake Oglethorpe - a small monomictic impoundment in South-eastern Georgia, USA. Recent studies indicate that the warm temperate regional climate affords an extended growing season - typically from March to October - which promotes bacterial productivity in the lake. The result is a summer food web dominated by microbial processes, in contrast to the conventional phytoplankton-dominated food chains typically observed in the cold temperate lakes of Europe and North America. Starting with a simple phytoplankton-based food web model and a qualitative definition of system behaviour, we use the RSA procedure to establish the critical role of bacteria-mediated decomposition in Lake Oglethorpe, thus justifying the inclusion of microbial processes. Further analysis reveals the importance of size-dependent selective consumption of phytoplankton and bacteria. Finally, we discuss important practical implications of this novel application of the RSA regarding sampling efficiency and statistical robustness.
Identification of model structure for aquatic ecosystems using regionalized sensitivity analysis
O. O. Osidele, M. B. Beck; Identification of model structure for aquatic ecosystems using regionalized sensitivity analysis. Water Sci Technol 1 April 2001; 43 (7): 271–278. doi: https://doi.org/10.2166/wst.2001.0435
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