As a part of the Mercury in Temperate Lakes (MTL) study in Wisconsin, U.S., we have developed a mechanistic model of the biogeochemical cycle of mercury in lakes. The Mercury Cycling Model (MCM) is a deterministic simulation model that incorporates the major processes that transport mercury across lake boundaries–atmospheric deposition, gas exchange, inflow and outflow of water, and burial in sediments; chemically transform it-reduction, methylation, and demethylation; and lead to its accumulation in aquatic biota-uptake, depuration, and trophic level transfer. In this chapter, we discuss the theory of mercury biogeochemical cycling, apply a simplified, steady-state version of the MCM to analyze field data from the MTL study, and examine mechanistic issues using the dynamic MCM model. Theories of mercury biogeochemistry are based on knowledge of the aqueous speciation of mercury and the mechanisms of its reactions-considerable gaps in our knowledge of both remain, however. Our approach, therefore, is to use what is known about mercury biogeochemistry to formulate hypothetical rate and equilibrium expressions. Using a simplified, steady-state version of the MCM model, we then examine the ability of these expressions to describe the field data of the M1L study. For example, although it is known that Hg2 and CH3Hg+ ions are complexed by the hydroxide, chloride, sulfide, and humic acids present in lakewater, uncertainties in the strength of organic complexation and the concentrations of competing metals make equilibrium calculations speculative. Applying our model of seston-water partitioning for Hg0 and CH3Hg11 to the MTL data, we examine potential mechanisms of mercury uptake by phytoplankton and the strength of organic complexation in these lakes. Our analysis suggests greater than 70\% organic complexation of both Hg0 and CH3Hg0 and significant accumulation of CH3Hg0 by plankton. To model the in-lake cycling of mercury, we derive theoretical rate laws, corresponding to a variety of hypothesized mechanisms for the reactions of the lacustrine mercury cycle and test their ability to predict the observed concentrations of HgO, Hg0, and CH3Hg0 in lakewater. Only a limited number of mechanisms were consistent with the data. In modeling bioconcentration factors (BCFAsH) for CH g0 in fish, we found that the binding of CH3Hg0 by DOC explains the observed dependence of BCFAsH on DOC, and that calcium inhibits bioaccumulation, likely at trophic levels above phytoplankton. Our results suggest observed correlations between lake pH and fish mercury content arise from generally higher CH gn concentrations at low pH and lower bioconcentration factors at high pH. To investigate issues relating to food chain accumulation and the generation of CH g0 in anoxic waters in greater detail, we employed the dynamic MCM model. We hypothesize that passive uptake of the neutral Hg(SH)02 species by methylating bacteria is an explanation for the apparently high methylation rate of HgII in sub- and anoxic waters.