Revista de biología marina y oceanografía
versão On-line ISSN 0718-1957
MOLINET, Carlos; NIKLITSCHEK, Edwin; SEGUEL, Miriam e DIAZ, Patricio. Trends of natural accumulation and detoxification of paralytic shellfish poison in two bivalves from the Northwest Patagonian inland sea. Rev. biol. mar. oceanogr. [online]. 2010, vol.45, n.2, pp. 195-204. ISSN 0718-1957. http://dx.doi.org/10.4067/S0718-19572010000200001.
The accumulation of marine toxins in aquatic filterers is a recurrent event that imposes serious risks to human health and important economic losses. While direct monitoring of seafood toxicity will remain as a priority for human health protection, a better understanding of toxin accumulation and detoxification dynamics might allow for forecasting tools to design better cost-effective mitigation strategies for bivalve farming and fisheries. In this study we explore monitoring data to extract temporal trends in natural accumulation and detoxification of paralytic shellfish poison (PSP) for two important mytilids from the Northwest Patagonian inland sea: Mytilus chilensis and Aulacomya atra. The data were collected between 1995 and 1998 in 13 stations, during two Alexandrium catenella blooms. The generalized linear models approach applied indicated A. catenella concentration, exposure time, salinity, temperature and zone had significant effects upon PSP concentration during the accumulation phase. Time, salinity, temperature and zone had significant effects upon PSP concentration during the detoxification phase. To obtain quantitative descriptors for accumulation and detoxification dynamics, we construct a simplified one-box model, defined by two parameters: 1) the proportionality constant between A. catenella concentration and PSP and 2) the instantaneous PSP decay rate. In spite of the limited nature of available data, the proposed model described significantly the observed variation in accumulation and detoxification trends of PSP. It remains. However, an evident need to validate the model against independent data sets from the same area and to identify and quantify sources of variability, uncertainty and bias that may affect model parameters.
Palavras-chave : Alexandrium catenella; Aulacomya atra; Mytilus chilensis; modelling; harmful algae blooms.