Geochemistry, minerals, color, rare earth elements and d18O at DSDP Hole 92-504B

Investigations of borehole waters sampled in Hole 504B during Leg 92 revealed changes in major-ion composition similar to changes observed previously (during Leg 83). The uniformity of chloride concentrations with increasing depth suggests efficient downhole mixing processes along density gradients caused by large temperature gradients. Chemical and mineralogical studies of suspended drilling mud (bentonite) suggest that this material has undergone substantial alteration and that CaSO4 (anhydrite/gypsum) has precipitated in the deeper parts of the hole. Rare earth element studies suggest contributions of both the bentonites and the basalts to the REE distributions. Studies of the isotopic composition (87Sr/86Sr) of dissolved strontium indicate a strong contribution of basaltic nonradiogenic strontium, although differences between the Leg 83 and Leg 92 data indicate an influence of bentonite during Leg 92. The oxygen isotope composition of the water does not change appreciably downhole. This uniformity can be understood in terms of high water-rock ratios and suggests that the chemical changes observed are due either to alteration processes involving bentonites and basaltic material from the walls of the hole or to exchange with formation fluids from the surrounding basement, which may have altered in composition at relatively high water-rock ratios.

Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in netCDF format

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.