The distribution of Biomphalaria (Gastropoda: Planorbidae) in Lake Victoria with ecological and spatial predictions using Bayesian modelling
2012
Intestinal schistosomiasis is a global disease of enormous public health importance. Assessing the local risk of transmission of the parasite causing the disease requires an appraisal of the distribution of its intermediate snail hosts, Biomphalaria spp.. In East Africa, the Lake Victorian Basin is a major freshwater ecosystem and highly endemic for intestinal schistosomiasis, although detailed distribution data for Biomphalaria have not been collected. We used on-the-ground malacological surveys and conjoint measurement of environmental determinants to develop models for analysis of variables associated with distribution and predictive snail mapping into data-deficient areas. Four expeditions were undertaken to collect snails along the Lake Victoria shoreline, visiting 223 sites overall. Environmental measurements were recorded at the time of inspection and water samples taken for quantification of anion and cation concentrations. The spatial distributions of Biomphalaria choanomphala and Biomphalaria sudanica were modelled in two Bayesian multivariate models: one non-spatial and one spatial with random effects. The results showed that chloride, nitrate, sulphate and the number of sympatric snail species were significant predictors of B. choanomphala whereas habitat, water depth, pH and sulphate were significant predictors for B. sudanica. The range of spatial autocorrelation was large (572.9 km for B. choanomphala and 175.3 km for B. sudanica). Interpolating snail abundance data by kriging revealed two ‘hot-spots’ of high abundance of Biomphalaria. These areas should be targeted in future expeditions to ground-truth the model’s predictions. Our study is the first to use Bayesian methods for determination of biomedically important snail distributions and sets crucial limnological baseline data for assessment of future changes in snail biodiversity in the Lake Victoria Basin.
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