A 3D coupled biogeochemical–hydrodynamic model (MIRO-CO2&CO) is implemented in the English Channel (ECH) and the Southern Bight of the North Sea (SBNS) to estimate the present-day spatio-temporal distribution of air–sea CO2 fluxes, surface water partial pressure of CO2 (pCO2) and other components of the carbonate system (pH, saturation state of calcite (Xca) and of aragonite (Xar)), and the main drivers of their variability. Over the 1994–2004 period, air–sea CO2 fluxes show significant interannual variability, with oscillations between net annual CO2 sinks and sources. The inter annual variability of air–sea CO2 fluxes simulated in the SBNS is controlled primarily by river loads and changes of biological activities (net autotrophy in spring and early summer, and net heterotrophy in winter and autumn), while in areas less influenced by river inputs such as the ECH, the inter annual variations of air–sea CO2 fluxes are mainly due to changes in sea surface temperature and in near-surface wind strength and direction. In the ECH, the decrease of pH, of Xca and of Xar follows the one expected from the increase of atmospheric CO2 (ocean acidification), but the decrease of these quantities in the SBNS during the considered time period is faster than the one expected from ocean acidification alone. This seems to be related to a general pattern of decreasing nutrient river loads and net ecosystem production (NEP) in the SBNS. Annually, the combined effect of carbon and nutrient loads leads to an increase of the sink of CO2 in the ECH and the SBNS, but the impact of the river loads varies spatially and is stronger in river plumes and nearshore waters than in offshore waters. The impact of organic and inorganic carbon (C) inputs is mainly confined to the coast and generates a source of CO2 to the atmosphere and low pH, of Xca and of Xar values in estuarine plumes, while the impact of nutrient loads, highest than the effect of C inputs in coastal nearshore waters, also propagates offshore and, by stimulating primary production, drives a sink of atmospheric CO2 and higher values of pH, of Xca and of Xar.
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Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species– habitat relationships can improve the assessment of trends and distribution by explicitly allowing high- resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat- based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005–2013) by means of dedicated line- transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on- effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for “season,” allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large- scale international SCANS II survey with the more frequent, small- scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are especially relevant for marine spatial planning, which requires accurate fine- scale maps of species distribution to assess risks of increasing human activities at sea.
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RBINS Staff Publications 2016
