How well does the Continuous Plankton Recorder (CPR) sample zooplankton? A comparison with the Longhurst Hardy Plankton Recorder (LHPR) in the northeast Atlantic

The Continuous Plankton Recorder (CPR) survey has collected data on basin- scale zooplankton abundance in the North Atlantic since the 1930s. These data have been used in many studies to elucidate seasonal patterns and long-term change in plankton populations, as well as more recently to validate ecosystem models. There has, however, been relatively little comparison of the data from the CPR with that from other samplers. In this study we compare zooplankton abundance estimated from the CPR in the northeast Atlantic with near-surface samples collected by a Longhurst-Hardy Plankton Recorder (LHPR) at Ocean Weather Station India (59 degree N, 19 degree W) between 1971 and 1975. Comparisons were made for six common copepods in the region: Acartia clausi, Calanus finmarchicus, Euchaeta norvegica, Metridia lucens, Oithona sp. and Pleuromamma robusta. Seasonal cycles based on CPR data were similar to those recorded by the LHPR. Differences in absolute abundances were apparent, however, with the CPR underestimating abundances by a factor of between 5 and 40, with the exception of A. clausi. Active avoidance by zooplankton is thought to be responsible. This avoidance is species specific, so that care must be taken describing communities, as the CPR emphasises those species that are preferentially caught, a problem common to many plankton samplers.

The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

An interlaboratory comparison for the quantification of aqueous dimethylsulfide

An interlaboratory comparison (ILC) was conducted to evaluate the proficiency of multiple laboratories to quantify dimethylsulfide (DMS) in aqueous solution. Ten participating laboratories were each supplied with blind duplicate test solutions containing dimethylsulfoniopropionate hydrochloride (DMSP HCl) dissolved in acidified artificial seawater. The test solutions were prepared by the coordinating laboratory from a DMSP HCl reference material that was synthesized and purity certified for this purpose. A concentration range was specified for the test solutions and the participating laboratories were requested to dilute them as required for their analytical procedure, together with the addition of excess alkali under gas-tight conditions to convert the DMSP to DMS. Twenty-two DMS concentrations and their estimated expanded measurement uncertainties (95% confidence level) were received from the laboratories. With two exceptions, the within-laboratory variability was 5% or less and the between-laboratory variability was ~ 25%. The magnitude of expanded measurement uncertainties reported from all participants ranged from 1% to 33% relative to the result. The information gained from this pilot ILC indicated the need for further test sample distribution studies of this type so that participating laboratories can identify systematic errors in their analysis procedures and realistically evaluate their measurement uncertainty. The outcome of ILC studies provides insights into the comparability of data in the global surface seawater DMS database.

Ocean acidification has different effects on the production of DMS and DMSP measured in cultures of Emiliania huxleyi and a mesocosm study: a comparison of laboratory monocultures and community interactions

The human-induced rise in atmospheric carbon dioxide since the industrial revolution has led to increasing oceanic carbon uptake and changes in seawater carbonate chemistry, resulting in lowering of surface water pH. In this study we investigated the effect of increasing CO2 partial pressure (pCO2) on concentrations of volatile biogenic dimethylsulfide (DMS) and its precursor dimethylsulfoniopropionate (DMSP), through monoculture studies and community pCO2 perturbation. DMS is a climatically important gas produced by many marine algae: it transfers sulfur into the atmosphere and is a major influence on biogeochemical climate regulation through breakdown to sulfate and formation of subsequent cloud condensation nuclei (CCN). Overall, production of DMS and DMSP by the coccolithophore Emiliania huxleyi strain RCC1229 was unaffected by growth at 900 matm pCO2, but DMSP production normalised to cell volume was 12% lower at the higher pCO2 treatment. These cultures were compared with community DMS and DMSP production during an elevated pCO2 mesocosm experiment with the aim of studying E. huxleyi in the natural environment. Results contrasted with the culture experiments and showed reductions in community DMS and DMSP concentrations of up to 60 and 32% respectively at pCO2 up to 3000 matm, with changes attributed to poorer growth of DMSP-producing nanophytoplankton species, including E. huxleyi, and potentially increased microbial consumption of DMSand dissolvedDMSPat higher pCO2.DMSandDMSPproduction differences between culture and community likely arise from pH affecting the inter-species responses between microbial producers and consumers.