Spatial changes in the sensitivity of Atlantic cod to climate-driven effects in the plankton

Recent strategies to sustain fish stocks have suggested a move towards an ecosystem based fisheries management (EBFM) approach. While EBFM considers the effect of fishing at the ecosystem level, it generally struggles with climate-driven environmental variability. In this study we show that the position of a fish stock within its distributional range or thermal niche (we use Icelandic and North Sea cod as examples of stocks at the centre and edge of their niche, respectively) will influence the relative importance of fishing and climate on abundance. At the warmer edge of the thermal niche of cod in the North Sea, we show a prominent influence of climate on the cod stock that is mediated through temperature effects on the plankton. In contrast, the influence of climate through its effects on plankton appears much less important at the present centre of the niche around Iceland. Recognising the potentially strong effect of climate on fish stocks, at a time of rapid global climate change, is probably an important prerequisite towards the synthesis of a cod management strategy.

Regional ocean-colour chlorophyll algorithms for the Red Sea

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.