Mesozooplankton are significant consumers of phytoplankton, and have a significant impact on the oceanic biogeochemical cycles of carbon and other elements. Their contribution to vertical particle flux is much larger than that of microzooplankton, yet most global biogeochemical models have lumped these two plankton functional types together. In this paper we bring together several newly available data syntheses on observed mesozooplankton concentration and the biogeochemical fluxes they mediate, and perform data synthesis on flux rates for which no synthesis was available. We update the equations of a global biogeochemical model with an explicit representation of mesozooplankton (PISCES). We use the rate measurements to constrain the parameters of mesozooplankton, and evaluate the model results with our independent synthesis of mesozooplankton concentration measurements. We also perform a sensitivity study to analyze the impact of uncertainty in the flux rates. The standard model run was parameterized on the basis of the data synthesis of flux rates. The results of mesozooplankton concentration in the standard run are slightly lower than the independent databases of observed mesozooplankton concentrations, but not significantly. This shows that structuring and parameterizing biogeochemical models on the basis of observations without tuning is a strategy that works. The sensitivity study showed that by using a maximum grazing rate of mesozooplankton that is only 30% higher than the poorly constrained fit to the observations, the model mesozooplankton concentration gets closer to the observations, but mesozooplankton grazing becomes higher than what is currently accounted for. This is an indication that food selection by mesozooplankton is not sufficiently quantified at present. Despite the amount of effort that is represented by the data syntheses of all relevant processes, the good results that were obtained for mesozooplankton indicate that this effort needs to be applied to all components of marine biogeochemistry. The development of ecosystem models that better represent key plankton groups and that are more closely based on observations should lead to better understanding and quantification of the feedbacks between marine ecosystems and climate.