Hemolymph Functions In Mytilus-Californianus - Cytochemistry Of Hemocytes And Their Responses To Foreign Implants And Hemolymph Factors In Phagocytosis

The hemocytes of Mytilus californianus are of three types: small and large basophils and large granular acidophils. The basophils contain lysosomal enzymes and phagocytose colloidal carbon. Agglutinins for yeast and human A Rh+ve erythrocytes are present in plasma, but are not needed for effective phagocytosis; in vitro both acidophilic and basophilic hemocytes rapidly phagocytose these particles. Plasma proteins, analyzed electrophoretically, are under strong homeostatic control. When Mya arenaria mantle is placed orthotopically on M. californianus mantle, the implant is invaded by host hemocytes in a manner consistent with that described in other published reports on molluscan graft rejection. Steady state is achieved by 26 days postimplant. Second- and third-set implants are rejected more rapidly than are first-set implants, but this is not a specific response. Third-set implants elicit a host cellular response that is more localized than the response to first-set implants. These data do not permit conclusions with respect to memory in these molluscan immune responses, but do imply a qualitative “improvement” in this quasi-immune response of M. californianus.

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.