Abstract. Zooplankton play an important role in global biogeochemistry and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton abundances cannot be estimated using remote sensing techniques. Hence, coupled physical-biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton abundance estimates from PBMs has been a major challenge as a result of sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993–2012 and validate the model against an extensive combination of in situ biomass and rate measurements including total mesozooplankton biomass, size-fractionated mesozooplankton biomass and grazing rates, microzooplankton specific grazing rates, surface chlorophyll, deep chlorophyll maximum depth, phytoplankton specific growth rates, and net primary production. Spatial variability in mesozooplankton biomass climatology observed in a multi-decadal database for the northern GoM is well resolved by the model with a statistically significant (p 

Abstract. Zooplankton play an important role in global biogeochemistry, and their secondary production supports valuable fisheries of the world's oceans. Currently, zooplankton standing stocks cannot be estimated using remote sensing techniques. Hence, coupled physical–biogeochemical models (PBMs) provide an important tool for studying zooplankton on regional and global scales. However, evaluating the accuracy of zooplankton biomass estimates from PBMs has been a major challenge due to sparse observations. In this study, we configure a PBM for the Gulf of Mexico (GoM) from 1993 to 2012 and validate the model against an extensive combination of biomass and rate measurements. Spatial variability in a multidecadal database of mesozooplankton biomass for the northern GoM is well resolved by the model with a statistically significant (p < 0.01) correlation of 0.90. Mesozooplankton secondary production for the region averaged 66±8×109 kg C yr−1, equivalent to ∼10 % of net primary production (NPP), and ranged from 51 to 82×109 kg C yr−1, with higher secondary production inside cyclonic eddies and substantially reduced secondary production in anticyclonic eddies. Model results from the shelf regions suggest that herbivory is the dominant feeding mode for small mesozooplankton (< 1 mm), whereas larger mesozooplankton are primarily carnivorous. In open-ocean oligotrophic waters, however, both mesozooplankton groups show proportionally greater reliance on heterotrophic protists as a food source. This highlights an important role of microbial and protistan food webs in sustaining mesozooplankton biomass in the GoM, which serves as the primary food source for early life stages of many commercially important fish species, including tuna.

In contrast to its productive coastal margins, the open-ocean Gulf of Mexico (GoM) is notable for highly stratified surface waters with extremely low nutrient and chlorophyll concentrations. Field campaigns in 2017 and 2018 identified low rates of turbulent mixing, which combined with oligotrophic nutrient conditions, give very low estimates for diffusive flux of nitrate into the euphotic zone (< 1 µmol N m−2 d−1). Estimates of local N2-fixation are similarly low. In comparison, measured export rates of sinking particulate organic nitrogen (PON) from the euphotic zone are 2 – 3 orders of magnitude higher (i.e. 462 – 1144 µmol N m−2 d−1). We reconcile these disparate findings with regional scale dynamics inferred independently from remote-sensing products and a regional biogeochemical model and find that laterally-sourced organic matter is sufficient to support >90% of open-ocean nitrogen export in the GoM. Results show that lateral transport needs to be closely considered in studies of biogeochemical balances, particularly for basins enclosed by productive coasts.

Upper ocean responses to tropical storms/hurricanes have been extensively studied using satellite observations. However, resolving concurrent sea surface temperature (SST) and chlorophyll a (chl a) responses along storm tracks remains a major challenge due to extensive cloud coverage in satellite images. Here we produce daily cloud‐free SST and chl a reconstructions based on the Data INterpolating Empirical Orthogonal Function method over a 10 year period (2003–2012) for the Gulf of Mexico and Sargasso Sea regions. Daily reconstructions allow us to characterize and contrast previously obscured subweekly SST and chl a responses to storms in the two main storm‐impacted regions of the Atlantic Ocean. Statistical analyses of daily SST and chl a responses revealed regional differences in the response time as well as the response sensitivity to maximum sustained wind speed and translation speed. This study demonstrates that SST and chl a responses clearly depend on regional ocean conditions and are not as universal as might have been previously suggested.

The highly stratified, oligotrophic regions of the oceans are predominantly nitrogen limited in the surface ocean and light limited at the deep chlorophyll maximum (DCM). Hence, determining light and nitrogen co-limitation patterns for diverse phytoplankton taxa is crucial to understanding marine primary production throughout the euphotic zone. During two cruises in the deep-water Gulf of Mexico, we measured primary productivity (H13CO3−), nitrate uptake (15NO3−) and ammonium uptake (15NH4+) throughout the water column. Primary productivity declined with depth from the mixed layer to the DCM, averaging 27.1 mmol C m−2 d−1. The fraction of growth supported by NO3− was consistently low, with upper euphotic zone values ranging from 0.01 to 0.14 and lower euphotic zone values ranging from 0.03 to 0.44. Nitrate uptake showed strong diel patterns (maximum during the day), whereas ammonium uptake exhibited no diel variability. To parameterize taxon-specific phytoplankton nutrient and light utilization, we used a data assimilation approach (Bayesian Markov Chain Monte Carlo) including primary productivity, nutrient uptake and taxon-specific growth rate measurements. Parameters derived from this analysis define distinct niches for five phytoplankton taxa (Prochlorococcus, Synechococcus, diatoms, dinoflagellates and prymnesiophytes) and may be useful for constraining biogeochemical models of oligotrophic open-ocean systems.