De Meyer M, Robertson M P, Mansell M W, Ekesi S, Tsuruta K, Mwaiko W, Vayssières J-F, Peterson A T
Royal Museum for Central Africa, Entomology Section, Tervuren, B-3080 Tervuren, Belgium.
Bull Entomol Res. 2010 Feb;100(1):35-48. doi: 10.1017/S0007485309006713. Epub 2009 Mar 27.
Two correlative approaches to the challenge of ecological niche modeling (genetic algorithm, maximum entropy) were used to estimate the potential global distribution of the invasive fruit fly, Bactrocera invadens, based on associations between known occurrence records and a set of environmental predictor variables. The two models yielded similar estimates, largely corresponding to Equatorial climate classes with high levels of precipitation. The maximum entropy approach was somewhat more conservative in its evaluation of suitability, depending on thresholds for presence/absence that are selected, largely excluding areas with distinct dry seasons; the genetic algorithm models, in contrast, indicate that climate class as partly suitable. Predictive tests based on independent distributional data indicate that model predictions are quite robust. Field observations in Benin and Tanzania confirm relationships between seasonal occurrences of this species and humidity and temperature.
基于已知发生记录与一组环境预测变量之间的关联,采用两种与生态位建模挑战相关的方法(遗传算法、最大熵法)来估计入侵果蝇——入侵果实蝇的潜在全球分布。这两种模型得出了相似的估计结果,主要对应于降水丰富的赤道气候类型。最大熵法在适宜性评估上更为保守,这取决于所选择的存在/不存在阈值,很大程度上排除了有明显旱季的地区;相比之下,遗传算法模型则表明该气候类型部分适宜。基于独立分布数据的预测测试表明,模型预测相当可靠。在贝宁和坦桑尼亚的实地观察证实了该物种季节性出现与湿度和温度之间的关系。