Effects of increases in temperature and nutrients on phytoplankton community structure and photosynthesis in the Western English Channel

Anthropogenic climate change is exerting pressures on coastal ecosystems through increases in temperature, precipitation and ocean acidification. Phytoplankton community structure and photo-physiology are therefore adapting to these conditions. Changes in phytoplankton biomass and photosynthesis in relation to temperature and nutrient concentrations were assessed using a 14 year dataset from a coastal station in the Western English Channel (WEC). Dinoflagellate and coccolithophorid biomass exhibited a positive correlation with temperature, reaching the highest biomass at between 15 and 17°C. Diatoms showed a negative correlation with temperature, with highest biomass at 10°C. Chlorophyll a (chl a) normalised light-saturated photosynthetic rates (PBm) exhibited a hyperbolic response to increasing temperature, with an initial linear increase from 8 to 11°C, and reaching a plateau from 12°C. There was however no significant positive correlation between nutrients and phytoplankton biomass or PBm, which reflects the lag time between nutrient input and phytoplankton growth at this coastal site. The major phytoplankton groups that occurred at this site occupied distinct thermal niches, which in turn modified PBm. Increasing temperature, and higher water column stratification, was major factors in the initiation of dinoflagellates blooms at this site. Dinoflagellates blooms during summer also co-varied with silicate concentration, and acted as a tracer of dissolved inorganic nitrogen and phosphate from river run-off, which were subsequently reduced during these blooms. The data implies that increasing temperature and high river runoff during summer, will promote dinoflaglellates blooms in the WEC.

Both respiration and photosynthesis determine the scaling of plankton metabolism in the oligotrophic ocean

Despite its importance to ocean–climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for 415 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including 14C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean’s metabolic state.

Recovery of photosynthesis parameters fromin situprofiles of phytoplankton production

We examine a model of the rate of phytoplankton production in the ocean and its dependence on depth. The model is analysed as a function of photosynthesis parameters and it is shown that: (i) production profiles with depth are determined uniquely by the parameter values; (ii) daily water column production is not uniquely determined by the parameter values; (iii) a unique combination of parameters exists for which the model best fits a measured production profile. An inverse procedure is developed to recover photosynthesis parameters from measured profiles of primary production, and its performance tested by application to profiles of primary production collected at the Hawaii Ocean Time Series. For each profile tested, the method is successful in recovery of the photosynthesis parameters. The method can be applied to the estimation of photosynthesis parameters from data on in situ production profiles, which have been collected globally for more than half a century, thereby augmenting the world archive of these parameters for application in ecosystem modelling and estimation of primary production from remotely sensed data.