Integrating biogeochemistry and ecology into ocean data assimilation systems

Monitoring and predicting the biogeochemical state of the ocean and marine ecosystems is an important application of operational oceanography that needs to be expanded. The accurate depiction of the ocean's physical environment enabled by Global Ocean Data Assimilation Experiment (GODAE) systems, in both real-time and reanalysis modes, is already valuable for various for various applications, such as the fishing industry and fisheries management. However, most of these applications require accurate estimates of both physical and biogeochemical ocean conditions over a wide range of spatial and temporal scales. In this paper, we discuss recent developments that enable coupling new biogeochemical models and assimilation components with the existing GODAE systems, and we examine the potential of such systems in several areas of interest: phytoplankton biomass monitoring in the open ocean, ocean carbon cycle monitoring and assessment, marine ecosystem management at seasonal and longer time scales, and downscaling in coastal areas. A number of key requirements and research priorities are then identified for the future, GODAE systems will need to improve their representation of physical variables that are not yet considered essential, such as upper-ocean vertical fluxes that are critically important to biological activity. Further, the observing systems will need to be expanded in terms of in situ platforms (with intensified deployments of sensors for O-2 and chlorophyll, and inclusion of new sensors for nutrients, zooplankton, micronekton biomass, and others), satellite missions (e.g., hyperspectral instruments for ocean color, lidar systems for mixed-layer depths, and wide-swath altimeters for coastal sea level), and improved methods to assimilate these new measurements

Strategic technology policy as a supplement to renewable energy standards

acceptedVersio

Framework of stock-recovery strategies: analyses of factors affecting success and failure

The EU FP6 UNCOVER project was aimed at producing a rational scientific basis for developing recovery strategies for some ecologically and socio-economically important fish stocks/fisheries in European seas. The immediate objectives were to identify changes experienced during stock depletion/collapses, to understand prospects for recovery, to enhance the scientific understanding of the mechanisms of recovery, and to formulate recommendations on how best to implement long-term management/recovery plans. We extended an earlier analysis conducted within the project of 13 performance criteria in relation to the recovery of more than 30 fish stocks/fisheries worldwide by multivariate exploratory analysis (canonical correspondence analysis), followed by model building [discriminant analysis (DA)] to quantify the relative importance of key performance criteria, singly or combined. Using the existing database, DA indicated that the four best additive predictors of successful recovery were "rapid reduction in fishing mortality", "environmental conditions during the recovery period", "life-history characteristics" of the target stock, and "management performance criteria". The model classified the status "recovered" and "non-recovered" assigned originally with nearly 100% accuracy