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Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

Overview presentation of the AWI's AUV project PAUL3000 of the HGF-MPG bridge-group for deep-sea ecology and technology.

A critical challenge in paleoclimate data analysis is the fact that the proxy data are heterogeneously distributed in space, which affects statistical methods that rely on spatial embedding of data. In the paleoclimate network approach nodes represent paleoclimate proxy time series, and links in the network are given by statistically significant similarities between them. Their location in space, proxy and archive type is coded in the node attributes. We develop a semi-empirical model for Spatio-Temporally AutocoRrelated Time series, inspired by the interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble of transition runs of this START model to test whether and how spatio–temporal climate transitions could be detectable from (paleo)climate networks. We sample model time series both on a grid and at locations at which paleoclimate data are available to investigate the effect of the spatially heterogeneous availability of data. Node betweenness centrality, averaged over the transition region, does not respond to the transition displayed by the START model, neither in the grid-based nor in the scattered sampling arrangement. The regionally defined measures of regional node degree and cross link ratio, however, are indicative of the changes in both scenarios, although the magnitude of the changes differs according to the sampling. We find that the START model is particularly suitable for pseudo-proxy experiments to test the technical reconstruction limits of paleoclimate data based on their location, and we conclude that (paleo)climate networks are suitable for investigating spatio–temporal transitions in the dependence structure of underlying climatic fields.

During the course of AtlantOS, our ability to provide biogeochemical (BGC) time series and Eulerian data which is of sufficient quality and quantity to approach basin-scale capacity has improved in a major way in some areas but has declined or not progressed in others. Indeed, the increased coordination achieved through AtlantOS has both increased our capacity to collectively further a basin-scale operation, and revealed new challenges in implementation. These outcomes are synthesised in this report to improve future planning for Eulerian capacities in BGC observation. Areas of significant progress 1. Development of capacity for emerging BGC variables 2. Establishment of a system for developing “Best practice” recording. 3. Transatlantic MOU with Canada 4. Data management and dissemination The ways to address the areas in which progress has not been made are conceptually simple but practically demanding. In all cases this needs to be carried out at the global scale and therefore under the auspices of OceanSITES. A coherent system which can provide data of sufficient quality and quantity to address societal needs cannot be achieved in isolation by any one Nation state or by Europe and must not be restricted by discipline. It will become self-evident that such an integrated approach will lead to a system which performs at a much higher level than the sum of its component parts. With continuous pressure from the European Commission, further and additional support from member states, continuing political and scientific dialogue with South Atlantic countries and strong management encouragement at all levels, the establishment of an effective eulerian observatory network is anticipated within the coming decade.

Phytoplankton are one of the key players in the ocean and contribute approximately 50% to global primary production. They serve as the basis for marine food webs, drive chemical composition of the global atmosphere and thereby climate. Seasonal environmental changes and nutrient availability naturally influence phytoplankton species composition. Since the industrial era, anthropogenic climatic influences have increased noticeably – also within the ocean. Our changing climate, however, affects the composition of phytoplankton species composition on a long-term basis and requires the organisms to adapt to this changing environment, influencing micronutrient bioavailability and other biogeochemical parameters. At the same time, phytoplankton themselves can influence the climate with their responses to environmental changes. Due to its key role, phytoplankton has been of interest in marine sciences for quite some time and there are several methodical approaches implemented in oceanographic sciences. There are ongoing attempts to improve predictions and to close gaps in the understanding of this sensitive ecological system and its responses.