This dataset provides observation-informed latitudinal estimates of apparent grazing parameters used to constrain community-integrated zooplankton grazing dynamics. The products were developed to represent large-scale variation in zooplankton grazing using three independent approaches that draw on observational datasets, empirical grazing relationships and inverse modelling.

The first estimate combines latitudinal patterns in zooplankton community composition with empirically derived grazing characteristics. Zooplankton biomass distributions were informed by the MAREDAT database and the statistically interpolated biomass distribution model of Clerc et al. (2024), while grazing parameters were derived from laboratory dilution experiments. Micro- and mesozooplankton contributions were combined according to their relative abundance and empirical grazing characteristics, with temperature-dependent adjustment of grazing parameters.

Two additional estimates were derived from inverse-modelling experiments using the WOMBAT biogeochemical model (Rohr et al., 2024). Grazing dynamics were optimised to reproduce satellite-observed phytoplankton phenology while physical transport and bottom-up environmental controls were constrained. Independent optimisations were undertaken using satellite-derived phytoplankton carbon biomass from MODIS backscatter and chlorophyll concentration from VIIRS ocean colour, producing separate carbon-based and chlorophyll-based estimates of community-integrated grazing dynamics.

Together, the three products provide alternative observation-informed estimates of the latitudinal structure of apparent zooplankton grazing parameters.