Department of Biology, Washington University, St. Louis, Missouri 63130, USA.
Ecol Appl. 2011 Mar;21(2):329-34. doi: 10.1890/10-0543.1.
Risk models for vector-borne diseases rely on accurate quantification of the relationship between vector abundance and habitat, but this relationship can be obscured if habitats are modified by invasive species in ways that alter vector behavior but are undetectable in remotely sensed data. At a forest in eastern Missouri we assessed whether the presence of an invasive shrub, Amur honeysuckle, Lonicera maackii, affects oviposition by treehole mosquitoes, Aedes triseriatus, a primary vector of La Crosse virus in the United States. Oviposition significantly decreased with increasing density of L. maackii. Moreover, our results indicate that L. maackii may hinder the efficacy of models that use remotely sensed data to predict vector abundance: there was a strong relationship between landscape composition around plots and oviposition, but only in plots not invaded by L. maackii. Overlooking potentially important but cryptic effects of invasive plants on habitat selection by vectors may undermine accurate forecasting of disease risk.
虫媒疾病风险模型依赖于对媒介丰度与栖息地之间关系的准确量化，但如果入侵物种以改变媒介行为但在遥感数据中无法检测到的方式改变栖息地，则这种关系可能会变得模糊。在密苏里州东部的一片森林中，我们评估了入侵灌木，毛樱桃，忍冬（Lonicera maackii）的存在是否会影响树孔蚊，美国拉什克病毒的主要媒介，三斑按蚊（Aedes triseriatus）的产卵。随着 L. maackii 密度的增加，产卵显著减少。此外，我们的结果表明，L. maackii 可能会阻碍使用遥感数据预测媒介丰度的模型的有效性：在不被 L. maackii 入侵的样地中，样地周围的景观组成与产卵之间存在很强的关系，但在被 L. maackii 入侵的样地中则没有。忽视入侵植物对媒介对栖息地选择的潜在重要但隐蔽影响，可能会破坏疾病风险的准确预测。
