Linking land cover and species distribution models to project potential ranges of malaria vectors: an example using Anopheles arabiensis in Sudan and Upper Egypt
Linking land cover and species distribution models to project potential ranges of malaria vectors: an example using Anopheles arabiensis in Sudan and Upper Egypt
复制标题
DOI：
10.1186/1475-2875-11-264
复制
发表时间：
2012-08-06
期刊：
影响因子：
3
通讯作者：
Beier, John C.
中科院分区：
文献类型：
--
作者：
Fuller, Douglas O.;Parenti, Michael S.;Beier, John C.
背景资料：阿拉伯按蚊是非洲恶性疟原虫的一种特别机会性的取食者和有效的传播媒介，可能侵入其正常范围以外的地区，包括被广阔的贫瘠沙漠隔开的地区。本文的目的是展示如何空间模型可以预测未来的灌溉农田和潜在的，新的合适的栖息地，如一个载体。方法：将两个不同但互补的空间模型联系起来，以证明它们在评估An的再入侵潜力方面的协同作用。到2050年，阿拉伯的灌溉农田扩展的功能。第一个模型（土地变化模型）是用来模拟变化的灌溉农田使用马尔可夫链的方法，而第二个模型（MaxEnt）使用物种发生点，土地覆盖和其他环境层项目的物种存在的概率。两个基本的变化情景进行了分析，一个涉及到一个更保守的一切照旧（BAU）的假设，第二个与沙漠到农田的过渡（绿色尼罗河）的高概率，以评估到2050年的广泛的潜在结果。阿拉伯尼罗河的范围介于一切照旧情景和绿色尼罗河情景之间。BAU情景揭示了一组高度分散的小的潜在栖息地斑块，这些斑块被相对较大的距离分开（最大距离= 64.02 km，平均值= 12.72 km，SD = 9.92），而绿色尼罗河情景产生的景观特征是由相对较短的间隙分隔的大斑块（最大距离= 49.38，km，平均值= 4.51 km，SD = 7.89），其可能由vector.Conclusions桥接：本研究提供了土地变化和物种分布模型如何可能与项目潜在的矢量栖息地分布和入侵潜力的变化的第一个示范。虽然潜在的栖息地补丁之间的差距仍然很大，在绿色尼罗河的情况下，该模型揭示了未来的栖息地连接，可能有利于再次入侵的大面积。从苏丹到上埃及的阿拉伯种。所使用的方法广泛适用于其他土地覆被变化，因为这些变化影响病媒分布，特别是与热带森林砍伐和城市化进程有关的变化。
Background: Anopheles arabiensis is a particularly opportunistic feeder and efficient vector of Plasmodium falciparum in Africa and may invade areas outside its normal range, including areas separated by expanses of barren desert. The purpose of this paper is to demonstrate how spatial models can project future irrigated cropland and potential, new suitable habitat for vectors such as An. arabiensis.Methods: Two different but complementary spatial models were linked to demonstrate their synergy for assessing re-invasion potential of An. arabiensis into Upper Egypt as a function of irrigated cropland expansion by 2050. The first model (The Land Change Modeler) was used to simulate changes in irrigated cropland using a Markov Chain approach, while the second model (MaxEnt) uses species occurrence points, land cover and other environmental layers to project probability of species presence. Two basic change scenarios were analysed, one involving a more conservative business-as-usual (BAU) assumption and second with a high probability of desert-to-cropland transition (Green Nile) to assess a broad range of potential outcomes by 2050.Results: The results reveal a difference of 82,000 sq km in potential An. arabiensis range between the BAU and Green Nile scenarios. The BAU scenario revealed a highly fragmented set of small, potential habitat patches separated by relatively large distances (maximum distance = 64.02 km, mean = 12.72 km, SD = 9.92), while the Green Nile scenario produced a landscape characterized by large patches separated by relatively shorter gaps (maximum distance = 49.38, km, mean = 4.51 km, SD = 7.89) that may be bridged by the vector.Conclusions: This study provides a first demonstration of how land change and species distribution models may be linked to project potential changes in vector habitat distribution and invasion potential. While gaps between potential habitat patches remained large in the Green Nile scenario, the models reveal large areas of future habitat connectivity that may facilitate the re-invasion of An. arabiensis from Sudan into Upper Egypt. The methods used are broadly applicable to other land cover changes as they influence vector distribution, particularly those related to tropical deforestation and urbanization processes.