A comparison of the degree of implementation of marine biodiversity indicators by European countries in relation to the Marine Strategy Framework Directive (MSFD)

The degree of development and operability of the indicators for the Marine Strategy Framework Directive (MSFD) using Descriptor 1 (D1) Biological Diversity was assessed. To this end, an overview of the relevance and degree of operability of the underlying parameters across 20 European countries was compiled by analysing national directives, legislation, regulations, and publicly available reports. Marked differences were found between countries in the degree of ecological relevance as well as in the degree of implementation and operability of the parameters chosen to indicate biological diversity. The best scoring EU countries were France, Germany, Greece and Spain, while the worst scoring countries were Italy and Slovenia. No country achieved maximum scores for the implementation of MSFD D1. The non-EU countries Norway and Turkey score as highly as the top-scoring EU countries. On the positive side, the chosen parameters for D1 indicators were generally identified as being an ecologically relevant reflection of Biological Diversity. On the negative side however, less than half of the chosen parameters are currently operational. It appears that at a pan-European level, no consistent and harmonized approach currently exists for the description and assessment of marine biological diversity. The implementation of the MSFD Descriptor 1 for Europe as a whole can therefore at best be marked as moderately successful.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-abased models

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.