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Univariate analysis of tsetse habitat in the common fly belt of Southern Africa using climate and remotely sensed vegetation data
Author(s) -
ROBINSON TIMOTHY,
ROGERS DAVID,
WILLIAMS BRIAN
Publication year - 1997
Publication title -
medical and veterinary entomology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 82
eISSN - 1365-2915
pISSN - 0269-283X
DOI - 10.1111/j.1365-2915.1997.tb00400.x
Subject(s) - tsetse fly , glossina morsitans , range (aeronautics) , biology , ecology , habitat , vegetation (pathology) , univariate , livestock , species distribution , environmental science , physical geography , multivariate statistics , zoology , statistics , geography , mathematics , medicine , materials science , pathology , composite material
Tsetse are vectors of trypanosomes that cause diseases both in humans and livestock. Traditional tsetse surveys, using sampling methods such as Epsilon traps and black screen fly rounds, are often logistically difficult, costly and time‐consuming. The distribution of tsetse, as revealed by such survey methods, is strongly influenced by environmental conditions, such as climate and vegetation cover, which may be readily mapped using satellite data. These data may be used to make predictions of the probable distribution of tsetse in unsurveyed areas by determining the environmental characteristics of areas of tsetse presence and absence in surveyed areas. The same methods may also be used to characterize differences between tsetse species and subspecies. In this paper we analyse the distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes in southern Africa with respect to single environmental variables. For G.m.centralis the best predictions were made using the average NDVI (75% correct predictions; range > 0.37) and the average of the maximum temperature (70% correct predictions; 27.0–29.2°C). For G.m.morsitans the best prediction was given by the maximum of the minimum temperature (84% correct predictions; range > 18.8°C), and for G.pallidipes , also by the maximum of the minimum temperature (86% correct predictions; range > 19.6 °C). The following paper compares a range of multivariate techniques for making predictions about the distribution of these species in the same region.