Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems.

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur.

Chlorophyll-deficient propagules of Avicennia marina and apparent longer term deterioration of mangrove fitness in oil-polluted sediments.

A correlation between petroleum hydrocarbon concentrations in sediments and chlorophyll-deficient mutations in mangroves may occur also in Australian mangroves. Earlier reports of such mutations in the Caribbean area were evident in viviparous propagules of the common mangrove genera, Rhizophora, borne on otherwise normal trees. These mutant propagules were termed albinos' since they lacked chlorophyll and normal green coloration, leaving them white, yellow or red.