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[1] We present new empirical and mechanistic models for predicting the export of organic carbon out of the surface ocean by sinking particles. To calibrate these models, we have compiled a synthesis of field observations related to ecosystem size structure, primary production and particle export from around the globe. The empirical model captures 61% of the observed variance in the ratio of particle export to primary production (the pe ratio) using sea-surface temperature and chlorophyll concentrations (or primary productivity) as predictor variables. To describe the mechanisms responsible for pe-ratio variability, we present size-based formulations of phytoplankton grazing and sinking particle export, combining them into an alternative, mechanistic model. The formulation of grazing dynamics, using simple power laws as closure terms for small and large phytoplankton, reproduces 74% of the observed variability in phytoplankton community composition wherein large phytoplankton augment small ones as production increases. The formulation for sinking particle export partitions a temperature-dependent fraction of small and large phytoplankton grazing into sinking detritus. The mechanistic model also captures 61% of the observed variance in pe ratio, with large phytoplankton in high biomass and relatively cold regions leading to more efficient export. In this model, variability in primary productivity results in a biomass-modulated switch between small and large phytoplankton pathways.Citation: Dunne, J. P., R. A. Armstrong, A. Gnanadesikan, and J. L. Sarmiento (2005), Empirical and mechanistic models for the particle export ratio, Global Biogeochem. Cycles, 19, GB4026,

[1] Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical onedimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways. Citation: Friedrichs, M. A. M., et al. (2007), Assessment of skill and portability in regional marine biogeochemical models: Role of multiple planktonic groups,