A Global Model for Methylmercury Formation and Uptake at the Base of Marine Food Webs

The MerR family is a group of transcriptional activators with similar N-terminal helix-turn-helix DNA binding regions and C-terminal effector binding regions that are specific to the effector recognised. The signature of the family is amino acid similarity in the first 100 amino acids, including a helix-turn-helix motif followed by a coiled-coil region. With increasing recognition of members of this class over the last decade, particularly with the advent of rapid bacterial genome sequencing, MerR-like regulators have been found in a wide range of bacterial genera, but not yet in archaea or eukaryotes. The few MerR-like regulators that have been studied experimentally have been shown to activate suboptimal sigma(70)-dependent promoters, in which the spacing between the -35 and -10 elements recognised by the sigma factor is greater than the optimal 17+/-1 bp. Activation of transcription is through protein-dependent DNA distortion. The majority of regulators in the family respond to environmental stimuli, such as oxidative stress, heavy metals or antibiotics. A subgroup of the family activates transcription in response to metal ions. This subgroup shows sequence similarity in the C-terminal effector binding region as well as in the N-terminal region, but it is not yet clear how metal discrimination occurs. This subgroup of MerR family regulators includes MerR itself and may have evolved to generate a variety of specific metal-responsive regulators by fine-tuning the sites of metal recognition.

This paper presents the ECCO v4 non-linear inverse modeling framework and its baseline solution for the evolving ocean state over the period 1992–2011. Both components are publicly available and subjected to regular, automated regression tests. The modeling framework includes sets of global conformal grids, a global model setup, implementations of data constraints and control parameters, an interface to algorithmic differentiation, as well as a grid-independent, fully capable Matlab toolbox. The baseline ECCO v4 solution is a dynamically consistent ocean state estimate without unidentified sources of heat and buoyancy, which any interested user will be able to reproduce accurately. The solution is an acceptable fit to most data and has been found to be physically plausible in many respects, as documented here and in related publications. Users are being provided with capabilities to assess model–data misfits for themselves. The synergy between modeling and data synthesis is asserted through the joint presentation of the modeling framework and the state estimate. In particular, the inverse estimate of parameterized physics was instrumental in improving the fit to the observed hydrography, and becomes an integral part of the ocean model setup available for general use. More generally, a first assessment of the relative importance of external, parametric and structural model errors is presented. Parametric and external model uncertainties appear to be of comparable importance and dominate over structural model uncertainty. The results generally underline the importance of including turbulent transport parameters in the inverse problem.