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利用气候和遥感植被数据对非洲南部常见采采蝇带的采采蝇栖息地进行单变量分析。

Univariate analysis of tsetse habitat in the common fly belt of southern Africa using climate and remotely sensed vegetation data.

作者信息

Robinson T, Rogers D, Williams B

机构信息

Department of Zoology, University of Oxford, U.K.

出版信息

Med Vet Entomol. 1997 Jul;11(3):223-34. doi: 10.1111/j.1365-2915.1997.tb00400.x.

Abstract

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 degrees C). For G.m.morsitans the best prediction was given by the maximum of the minimum temperature (84% correct predictions; range > 18.8 degrees C), and for G.pallidipes, also by the maximum of the minimum temperature (86% correct predictions; range > 19.6 degrees C). The following paper compares a range of multivariate techniques for making predictions about the distribution of these species in the same region.

摘要

采采蝇是锥虫的传播媒介,锥虫会导致人类和牲畜患病。传统的采采蝇调查,采用诸如ε型诱捕器和黑幕蝇圈等采样方法,在后勤方面往往困难重重,成本高昂且耗时费力。通过此类调查方法揭示的采采蝇分布,会受到气候和植被覆盖等环境条件的强烈影响,而这些环境条件可以很容易地利用卫星数据进行绘制。这些数据可用于通过确定已调查区域中采采蝇存在和不存在区域的环境特征,来预测未调查区域中采采蝇可能的分布。同样的方法也可用于描述采采蝇物种和亚种之间的差异。在本文中,我们分析了非洲南部的中黄采采蝇、莫桑比克采采蝇和淡足采采蝇相对于单一环境变量的分布情况。对于中黄采采蝇,使用平均归一化植被指数(预测正确率75%;范围>0.37)和最高温度平均值(预测正确率70%;27.0 - 29.2摄氏度)能做出最佳预测。对于莫桑比克采采蝇,最低温度最大值给出了最佳预测(预测正确率84%;范围>18.8摄氏度),而对于淡足采采蝇,同样是最低温度最大值给出了最佳预测(预测正确率86%;范围>19.6摄氏度)。接下来的论文比较了一系列用于预测同一区域这些物种分布的多变量技术。

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