4.6 Article Proceedings Paper

Host-parasite distribution patterns under simulated climate: implications for tick-borne diseases

期刊

INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 29, 期 7, 页码 993-1000

出版社

WILEY
DOI: 10.1002/joc.1801

关键词

tick-host assemblages; climate change; East Coast fever; Rhipicephalus appendiculatus; dilution effect

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Ticks are known to depend intimately on both climate and the presence of suitable animal host populations for reproduction, survival and population establishment. In response to the reported probable impacts of climate change on ticks and tick-borne diseases, current and future predicted distribution maps of ticks and animal species have been produced. However, there have been no known attempts to link climate change, the predicted future distribution of ticks and the vertebrates that act as hosts and/or reservoirs for ticks and tick-borne diseases. Yet knowledge of this link provides an in-depth understanding of the impacts of climate change on this complex system. Using a modelling approach, this paper provides the predicted change in distribution range of an economically important tick, Rhipicephalus appendiculatus and ten vertebrate species that act as its hosts. Results obtained using a predictive species model and climate variables provided by a nested regional climate model, Division of Atmospheric Area Model (DARLAM) show reduction in tick-range and statistically significant differences between the current and future predicted ranges (probability of occurrence) for individual host species. The results also demonstrate a reduction in the range of the total host assemblage while the ranges of hosts intimately involved in East Coast fever (ECF) transmission were altered to different degrees in different areas in sub-Saharan Africa. Increased probability of occurrences for the tick-host assemblage was predicted in Tanzania, Angola and Mozambique. The implications of these results for future tick abundances and ECF transmission tinder a changing climate scenario are discussed using the Lyme disease 'dilution effect' model. Copyright (C) 2008 Royal Meteorological Society

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