Implications of streamlining theory for microbial ecology

Whether a small cell, a small genome or a minimal set of chemical reactions with self-replicating properties, simplicity is beguiling. As Leonardo da Vinci reportedly said, 'simplicity is the ultimate sophistication'. Two diverging views of simplicity have emerged in accounts of symbiotic and commensal bacteria and cosmopolitan free-living bacteria with small genomes. The small genomes of obligate insect endosymbionts have been attributed to genetic drift caused by small effective population sizes (Ne). In contrast, streamlining theory attributes small cells and genomes to selection for efficient use of nutrients in populations where Ne is large and nutrients limit growth. Regardless of the cause of genome reduction, lost coding potential eventually dictates loss of function. Consequences of reductive evolution in streamlined organisms include atypical patterns of prototrophy and the absence of common regulatory systems, which have been linked to difficulty in culturing these cells. Recent evidence from metagenomics suggests that streamlining is commonplace, may broadly explain the phenomenon of the uncultured microbial majority, and might also explain the highly interdependent (connected) behavior of many microbial ecosystems. Streamlining theory is belied by the observation that many successful bacteria are large cells with complex genomes. To fully appreciate streamlining, we must look to the life histories and adaptive strategies of cells, which impose minimum requirements for complexity that vary with niche.

Comparison of new and primary production models using SeaWiFS data in contrasting hydrographic zones of the northern North Atlantic.

The accuracy of two satellite models of marine primary (PP) and new production (NP) were assessed against 14C and 15N uptake measurements taken during six research cruises in the northern North Atlantic. The wavelength resolving model (WRM) was more accurate than the Vertical General Production Model (VGPM) for computation of both PP and NP. Mean monthly satellite maps of PP and NP for both models were generated from 1997 to 2010 using SeaWiFS data for the Irminger basin and North Atlantic. Intra- and inter-annual variability of the two models was compared in six hydrographic zones. Both models exhibited similar spatio-temporal patterns: PP and NP increased from April to June and decreased by August. Higher values were associated with the East Greenland Current (EGC), Iceland Basin (ICB) and the Reykjanes Ridge (RKR) and lower values occurred in the Central Irminger Current (CIC), North Irminger Current (NIC) and Southern Irminger Current (SIC). The annual PP and NP over the SeaWiFS record was 258 and 82 gC m-2 yr-1 respectively for the VGPM and 190 and 41 gC m-2 yr-1 for the WRM. Average annual cumulative sum in the anomalies of NP for the VGPM were positively correlated with the North Atlantic Oscillation (NAO) in the EGC, CIC and SIC and negatively correlated with the multivariate ENSO index (MEI) in the ICB. By contrast, cumulative sum of the anomalies of NP for the WRM were significantly correlated with NAO only in the EGC and CIC. NP from both VGPM and WRM exhibited significant negative correlations with Arctic Oscillation (AO) in all hydrographic zones. The differences in estimates of PP and NP in these hydrographic zones arise principally from the parameterisation of the euphotic depth and the SST dependence of photo-physiological term in the VGPM, which has a greater sensitivity to variations in temperature than the WRM. In waters of 0 to 5C PP using the VGPM was 43% higher than WRM, from 5 to 10C the VGPM was 29% higher and from 10 to 15C the VGPM was 27% higher.

Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to fish and coasts to ocean

It has long been recognised that there are strong interactions and feedbacks between climate, upper ocean biogeochemistry and marine food webs, and also that food web structure and phytoplankton community distribution are important determinants of variability in carbon production and export from the euphotic zone. Numerical models provide a vital tool to explore these interactions, given their capability to investigate multiple connected components of the system and the sensitivity to multiple drivers, including potential future conditions. A major driver for ecosystem model development is the demand for quantitative tools to support ecosystem-based management initiatives. The purpose of this paper is to review approaches to the modelling of marine ecosystems with a focus on the North Atlantic Ocean and its adjacent shelf seas, and to highlight the challenges they face and suggest ways forward. We consider the state of the art in simulating oceans and shelf sea physics, planktonic and higher trophic level ecosystems, and look towards building an integrative approach with these existing tools. We note how the different approaches have evolved historically and that many of the previous obstacles to harmonisation may no longer be present. We illustrate this with examples from the on-going and planned modelling effort in the Integrative Modelling Work Package of the EURO-BASIN programme.