The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depthintegrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 C, and chlorophyll concentration exceeding 1 mg Chl m À3 . Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. r

In 2009, following approval of the European Marine Strategy Framework Directive (MSFD, 2008/56/EC), the European Commission (EC) created task groups to develop guidance for eleven quality descriptors that form the basis for evaluating ecosystem function. The objective was to provide European countries with practical guidelines for implementing the MSFD, and to produce a Commission Decision that encapsulated key points of the work in a legal framework. This paper presents a review of work carried out by the eutrophication task group, and reports our main findings to the scientific community. On the basis of an operational, management-oriented definition, we discuss the main methodologies that could be used for coastal and marine eutrophication assessment. Emphasis is placed on integrated approaches that account for physico-chemical and biological components, and combine both pelagic and benthic symptoms of eutrophication, in keeping with the holistic nature of the MSFD. We highlight general features that any marine eutrophication model should possess, rather than making specific recommendations. European seas range from highly eutrophic systems such as the Baltic to nutrient-poor environments such as the Aegean Sea. From a Highlights ► Eutrophication guidance for the EU Marine Strategy Framework Directive (MSFD). ► Operational, management-oriented definition of eutrophication. ► Integrated assessment of physico-chemical and biological components. ► Assessment models combine both pelagic and benthic symptoms of eutrophication. ► Innovative approaches required for meaningful monitoring and assessment.

Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved

[1] Results of a single-blind round-robin comparison of satellite primary productivity algorithms are presented. The goal of the round-robin exercise was to determine the accuracy of the algorithms in predicting depth-integrated primary production from information amenable to remote sensing. Twelve algorithms, developed by 10 teams, were evaluated by comparing their ability to estimate depth-integrated daily production (IP, mg C m À2 ) at 89 stations in geographically diverse provinces. Algorithms were furnished information about the surface chlorophyll concentration, temperature, photosynthetic available radiation, latitude, longitude, and day of the year. Algorithm results were then compared with IP estimates derived from 14 C uptake measurements at the same stations. Estimates from the best-performing algorithms were generally within a factor of 2 of the 14 C-derived estimates. Many algorithms had systematic biases that can possibly be eliminated by reparameterizing underlying relationships. The performance of the algorithms and degree of correlation with each other were independent of the algorithms' complexity.

ABSTRACT-Absorption spectra of several phytoplankton species were decomposed, after correction for the particle effect, to estimate in vivo absorption properties of the major light-harvesting pigments in algae. A Gaussian shape is suitable, theoretically and empirically, to represent the absorption spectra of individual photosynthetic components. The Gaussian parameters agreed well with the expected pigment compositions of 3 groups of algae, and the peak heights were linearly correlated with the concentrations of any one of the 4 major pigments measured in the samples. The linear relationship did not vary with phytoplankton species. We present here the first estimates of the 'true' in vivo specific absorption coefficients of 4 major pigments, after correction for particle effect. The results are used to reconstruct the in vivo absorption spectrum of a multi-species sample.