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Long-term changes in lake nutrient stoichiometry: effects on plankton productivity and species composition

Jörg Grigull (PI/York University)
Norman Yan (co-PI/York University)
Samaneh Gholami (PhD)


In mass balance modeling of C,N,P elemental fluxes in freshwater ecosystems, it is logistically and economically feasible to monitor a limited number of variables only. We reviewed the existing methodology towards developing a modeling framework for the Muskoka River Watershed and identified the Linear Inverse Modeling (LIM) paradigm as a reliable, robust and well-documented approach to infer hidden fluxes which are informative of stable or disturbed trophic relations in lake ecosystems. We proceeded with installing and have begun to train on selected modules (based on R Statistics) using this framework.

A number of datasets from freshwater and marine biology studies were identified in which LIM or similar methods are pivotal for estimating fluxes between bacteria, phytoplankton, cladocerans and copepods, under equilibrium conditions and in the detection of changing fluxes indicative of stress factors.

Of specific interest for our project is the incorporation of empirical knowledge (lake-specific information) as Linear Programming constraints in inverse modeling, and the implementation of sensitivity analysis in the computational exploration of the space of flux profiles that are compatible with the constraints.