Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate

Submitted: 9 December 2014
Accepted: 9 December 2014
Published: 1 May 2014
Abstract Views: 2930
PDF: 1428
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The environment, the on-going global climate change and the ecology of animal species determine the localisation of habitats and the geographical distribution of the various species in nature. The aim of this study was to explore the effects of such changes on snail species not only of interest to naturalists but also of importance to human and animal health. The spatial distribution of freshwater snail intermediate hosts involved in the transmission of schistosomiasis, fascioliasis and paramphistomiasis (i.e. Bulinus globosus, Biomphalaria pfeifferi and Lymnaea natalensis) were modelled by the use of a maximum entropy algorithm (Maxent). Two snail observation datasets from Zimbabwe, from 1988 and 2012, were com- pared in terms of geospatial distribution and potential distributional change over this 24-year period investigated. Climate data, from the two years were identified and used in a species distribution modelling framework to produce maps of pre- dicted suitable snail habitats. Having both climate- and snail observation data spaced 24 years in time represent a unique opportunity to evaluate biological response of snails to changes in climate variables. The study shows that snail habitat suit- ability is highly variable in Zimbabwe with foci mainly in the central Highveld but also in areas to the South and West. It is further demonstrated that the spatial distribution of suitable habitats changes with variation in the climatic conditions, and that this parallels that of the predicted climate change.

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Pedersen, U. B., Midzi, N., Mduluza, T., Soko, W., Stensgaard, A.-S., Vennervald, B. J., Mukaratirwa, S., & Kristensen, T. K. (2014). Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate. Geospatial Health, 8(2), 335–343. https://doi.org/10.4081/gh.2014.23

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