Szyniszewska Anna M, Tatem Andrew J
Department of Geography, University of Florida, Gainesville, Florida, United States of America.
Department of Geography and Environment, University of Southampton, Highfield, Southampton, United Kingdom; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
PLoS One. 2014 Nov 6;9(11):e111582. doi: 10.1371/journal.pone.0111582. eCollection 2014.
The Mediterranean fruit fly (Medfly) is one of the world's most economically damaging pests. It displays highly seasonal population dynamics, and the environmental conditions suitable for its abundance are not constant throughout the year in most places. An extensive literature search was performed to obtain the most comprehensive data on the historical and contemporary spatio-temporal occurrence of the pest globally. The database constructed contained 2328 unique geo-located entries on Medfly detection sites from 43 countries and nearly 500 unique localities, as well as information on hosts, life stages and capture method. Of these, 125 localities had information on the month when Medfly was recorded and these data were complemented by additional material found in comprehensive databases available online. Records from 1980 until present were used for medfly environmental niche modeling. Maximum Entropy Algorithm (MaxEnt) and a set of seasonally varying environmental covariates were used to predict the fundamental niche of the Medfly on a global scale. Three seasonal maps were also produced: January-April, May-August and September-December. Models performed significantly better than random achieving high accuracy scores, indicating a good discrimination of suitable versus unsuitable areas for the presence of the species.
地中海实蝇是世界上对经济危害最大的害虫之一。它呈现出高度季节性的种群动态,而且在大多数地方,适合其大量繁殖的环境条件并非全年恒定。我们进行了广泛的文献检索,以获取有关该害虫在全球历史和当代时空分布的最全面数据。构建的数据库包含来自43个国家和近500个独特地点的2328个关于地中海实蝇检测地点的独特地理位置记录,以及有关寄主、生活阶段和捕获方法的信息。其中,125个地点有关于记录到地中海实蝇的月份的信息,这些数据通过在线综合数据库中找到的其他资料得到补充。1980年至今的记录用于地中海实蝇环境生态位建模。使用最大熵算法(MaxEnt)和一组随季节变化的环境协变量来预测全球范围内地中海实蝇的基础生态位。还制作了三张季节性地图:1月至4月、5月至8月和9月至12月。模型的表现显著优于随机模型,获得了高精度分数,表明对该物种存在的适宜区域和不适宜区域有良好的区分。