Mapping the potential distribution of Phlebotomus martini and P-orientalis (Diptera: Psychodidae), vectors of kala-azar in East Africa by use of geographic information systems
Mapping the potential distribution of Phlebotomus martini and P-orientalis (Diptera: Psychodidae), vectors of kala-azar in East Africa by use of geographic information systems
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DOI：
10.1016/j.actatropica.2003.09.021
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发表时间：
2004-03-01
期刊：
影响因子：
2.7
通讯作者：
Herzi, AA
中科院分区：
文献类型：
--
作者：
Gebre-Michael, T;Malone, JB;Herzi, AA
利用地理信息系统分析了东非黑热病的两种主要媒介-马丁白蛉和东方白蛉的分布情况，其依据是：（1）地球观测卫星传感器数据：利用美国地质调查局全球陆地1公里项目的高级甚高分辨率辐射计（AVHRR）反演的归一化植被指数（NDVI）和正午地表温度（LST），（2）来自政府间发展组织（伊加特）分区域粮农组织作物生产系统区的农业气候数据，（3）粮农组织1998年伊加特分区域土壤数字地图。其目的是为这两个向量建立一个预测风险模型。用于分析的数据是基于该地区（主要是埃塞俄比亚，肯尼亚和索马里）以前调查收集的两个物种的存在和不存在。建立了年、雨季和旱季模型。尽管所有模型对这两个物种的阳性预测值都超过85%，但最适合马蒂尼分布的是旱季组合（NDVI 0.07-0.38，LST 22- 33 ℃），预测值为93.8%，对侧柏的预测效果最好的是湿季组合（NDVI为-0.01 ~0.34，LST为23- 34 ℃），预测值为96.3%。从卫星数据得出的两个季节性复合模型与根据CPSZ气候数据开发的最佳拟合模型基本相似：平均海拔（12- 1900米），年平均气温（15- 30 ℃），年降雨量（274- 1212 mm），年均潜在蒸散量（1264- 1938 mm）和土壤速效水分（62-113毫米）用于马提尼酒;平均海拔（200-2200 m）、年降雨量（180-1050 mm）、年平均气温（16- 36 ℃）和土壤有效含水量（67-108 mm）。Logistic回归分析表明，卫星资料的旱季LST合成、CPSZ资料的平均姿态、年均温度和土壤有效水分是马蒂尼的最佳生态决定因子，而LST年合成是东方马蒂尼唯一重要的生态决定因子。斯皮尔曼的等级相关性揭示了几个因素是两个向量的分布的重要决定因素。分析的土壤类型似乎是两个物种在东非的重要决定因素，不像在苏丹，P. orientalis主要是与eutric变性土（黑棉粘土）。(C)2003 Elsevier B. V.保留所有权利。
The distribution of two principal vectors of kala-azar in East Africa, Phlebotomus martini and Phlebotomus orientalis were analysed using geographic information system (GIS) based on (1) earth observing satellite sensor data: Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) derived from advanced very high resolution radiometer (AVHRR) of the global land 1 km project of United States Geological Survey (USGS), (2) agroclimatic data from the FAO Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region, and (3) the FAO 1998 soils digital map for the IGAD sub-region. The aim was to produce a predictive risk model for the two vectors. Data used for the analysis were based on presence and absence of the two species from previous survey collections in the region (mainly Ethiopia, Kenya and Somalia). Annual, wet season and dry season models were constructed. Although all models resulted in more than 85% positive predictive values for both species, the best fit for the distribution of P. martini was the dry season composite (NDVI 0.07-0.38 and LST 22-33degreesC) with a predictive value of 93.8%, and the best fit for P orientalis was the wet season composite (NDVI -0.01 to 0.34 and LST 23-34degreesC) with a predictive value of 96.3%. The two seasonal composites models derived from satellite data were largely similar with best fit models developed based on the CPSZ climate data: average attitude (12-1900m), average annual mean temperature (15-30degreesC), annual rainfall (274-1212mm), average annual potential evapotranspiration (1264-1938mm) and readily available soil moisture (62-113 mm) for P. martini; and average altitude (200-2200 m), annual rainfall (180-1050 mm), annual mean temperature (16-36degreesC) and readily available soil moisture (67-108 mm) for P. orientalis. Logistic regression analysis indicated LST dry season composite of the satellite data, average attitude, mean annual temperature and readily available soil moisture of the CPSZ data as the best ecological determinants for P. martini while LST annual composite was the only important ecological determinant for P. orientalis. Spearman's rank correlation revealed several factors to be important determinants for the distribution of the two vectors. None of the soil types analysed appeared to be important determinant for the two species in East Africa, unlike in Sudan where P. orientalis is mainly associated with eutric vertisol (black cotton clay soil). (C) 2003 Elsevier B.V. All rights reserved.