Temporal changes in plankton of the North Sea: community shifts and environmental drivers

This paper analyses long-term and seasonal changes in the North Sea plankton community during the period 1970 to 2008. Based on Continuous Plankton Recorder (CPR) data covering 38 yr, major changes in both phytoplankton and zooplankton abundance and community structure were identified. Regime changes were detected around 1978, 1989 and 1998. The first 2 changes have been discussed in the literature and are defined as a cold episodic event (1978) and a regime shift towards a warm dynamic regime (1989). The effect of these 2 regime changes on plankton indicators was assessed and checked against previous studies. The 1998 change represents a shift in the abundance and seasonal patterns of dinoflagellates and the dominant zooplankton group, the neritic copepods. Furthermore, environmental factors such as air temperature, wind speed and the North Atlantic water inflow were identified as potential drivers of change in seasonal patterns, and the most-likely environmental causes for detected changes were assessed. We suggest that a change in the balance of dissolved nutrients driven by these environmental factors was the cause of the latest change in plankton community structure, which in turn could have affected the North Sea fish community.

Response of an Arctic Sediment Nitrogen Cycling Community to Increased CO2

Ocean acidification influences sediment/water nitrogen fluxes, possibly by impacting on the microbial process of ammonia oxidation. To investigate this further, undisturbed sediment cores collected from Ny Alesund harbour (Svalbard) were incubated with seawater adjusted to CO2 concentrations of 380, 540, 760, 1,120 and 3,000 μatm. DNA and RNA were extracted from the sediment surface after 14 days' exposure and the abundance of bacterial and archaeal ammonia oxidising (amoA) genes and transcripts quantified using quantitative polymerase chain reaction. While there was no change to the abundance of bacterial amoA genes, an increase to 760 μatm pCO2 reduced the abundance of bacterial amoA transcripts by 65 %, and this was accompanied by a shift in the composition of the active community. In contrast, archaeal amoA gene and transcript abundance both doubled at 3,000 μatm, with an increase in species richness also apparent. This suggests that ammonia oxidising bacteria and archaea in marine sediments have different pH optima, and the impact of elevated CO2 on N cycling may be dependent on the relative abundances of these two major microbial groups. Further evidence of a shift in the balance of key N cycling groups was also evident: the abundance of nirS-type denitrifier transcripts decreased alongside bacterial amoA transcripts, indicating that NO3 − produced by bacterial nitrification fuelled denitrification. An increase in the abundance of Planctomycete-specific 16S rRNA, the vastmajority of which grouped with known anammox bacteria, was also apparent at 3,000 μatm pCO2. This could indicate a possible shift from coupled nitrification–denitrification to anammox activity at elevated CO2.

Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling

In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.

The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM

Ecosystem models are often assessed using quantitative metrics of absolute ecosystem state, but these model-data comparisons are disproportionately vulnerable to discrepancies in the location of important circulation features. An alternative method is to demonstrate the models capacity to represent ecosystem function; the emergence of a coherent natural relationship in a simulation indicates that the model may have an appropriate representation of the ecosystem functions that lead to the emergent relationship. Furthermore, as emergent properties are large-scale properties of the system, model validation with emergent properties is possible even when there is very little or no appropriate data for the region under study, or when the hydrodynamic component of the model differs significantly from that observed in nature at the same location and time. A selection of published meta-analyses are used to establish the validity of a complex marine ecosystem model and to demonstrate the power of validation with emergent properties. These relationships include the phytoplankton community structure, the ratio of carbon to chlorophyll in phytoplankton and particulate organic matter, the ratio of particulate organic carbon to particulate organic nitrogen and the stoichiometric balance of the ecosystem. These metrics can also inform aspects of the marine ecosystem model not available from traditional quantitative and qualitative methods. For instance, these emergent properties can be used to validate the design decisions of the model, such as the range of phytoplankton functional types and their behaviour, the stoichiometric flexibility with regards to each nutrient, and the choice of fixed or variable carbon to nitrogen ratios.