Tsetse Population Dynamics and Distribution: A New Analytical Approach

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Abstract
A method based on Moran curves is presented for determining monthly changes in density independent mortality acting on tsetse fly populations under natural conditions. The method of analysis is tested on the output of a simple population model for tsetse and predicts qualitative changes in mortality under all conditions and quantitative changes when the mortality acts equally on all life stages. Fly round records for female G. morsitans submorsitans from the Yankari Game Reserve, northern Nigeria, for the period 1964-1973, are analyzed using the new method. Mean monthly density independent mortalitites are calculated and are most closely related to mean monthly saturation deficit. Values of density independent mortality are superimposed on an annual climogram for Bauchi, near the study site, and mortality contours are drawn enclosing regions of equal mortality. This procedure identifies an environmental optimum for the subspecies, between 24 and 26.degree. C and 5-13 mm Hg saturation deficit. Less complete data from Zambia are also analyzed and identify a similar optimum for G. m. morsitans, at between 22 and 23.degree. C and 7-11 mm Hg saturation deficit. These 2 optima are compared with previous estimates derived by different methods. Vertical sections taken through the mortality contours give rise to mortality profiles which, in conjunction with the population model, can be used to define the bioclimatic limits of the species. Weather records for 91 sites throughout tropical Africa, in both tsetse and non-tsetse areas, are summarized: 94% of the sites within the present or recently known distribution of G. morsitans fall within the predicted bioclimatic limits, while only 50% of non-tsetse areas (an average of < 200 km away from the tsetse area nearest to each of them) do so. The construction of bioclimatic limits also identifies an optimum saturation deficit at each temperature. The possibility of tsetse control in, or eradication from, any area is related to the distance of the mean environmental conditions from the predicted optimum at the same mean temperature. The problems of applying the analytical method to other data are discussed.