Combined Effects Of Body Size Food Concentration And Season On Physiology Of Mytilus-Edulis

Multivariate experiments are used to study the effects of body size, food concentration, and season on the oxygen consumption, ammonia excretion, food assimilation efficiency and filtration rate of Mytilus edulis adults. Food concentrations and season affect both the intercept and the slope of the allometric equation describing oxygen uptake as a function of body size. Multiple regression and response surface techniques are used to describe and illustrate the complex relationship between metabolic rate, ration, season and the body size of M. edulis. Filtration rate has a relatively low weight exponent Q> = 038) and the intercept for the allometric equation is not significantly affected by food concentration, season or acclimation temperatures between 5 and 20 °C. Food assimilation efficiency declines exponentially with increasing food concentration and is dependent on body size at high food levels. The rate of ammonia excretion shows a similar seasonal cycle to that of oxygen consumption. They are both minimal in the autumn/winter and reach a maximum in the spring /summer.

On the temporal consistency of chlorophyll products derived from three ocean-colour sensors

Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.