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(杰·史密斯)(鳞翅目,夜蛾科)的全球栖息地适宜性:用于生物防治的关键寄生蜂类

Global Habitat Suitability of (JE Smith) (Lepidoptera, Noctuidae): Key Parasitoids Considered for Its Biological Control.

作者信息

Tepa-Yotto Ghislain T, Tonnang Henri E Z, Goergen Georg, Subramanian Sevgan, Kimathi Emily, Abdel-Rahman Elfatih M, Flø Daniel, Thunes Karl H, Fiaboe Komi K M, Niassy Saliou, Bruce Anani, Mohamed Samira A, Tamò Manuele, Ekesi Sunday, Sæthre May-Guri

机构信息

Biorisk Management Facility (BIMAF), International Institute of Tropical Agriculture (IITA-Benin), 08-01000 Cotonou, Benin.

Ecole de Gestion et de Production Végétale et Semencière (EGPVS), Université Nationale d'Agriculture (UNA), 43 Kétou, Benin.

出版信息

Insects. 2021 Mar 24;12(4):273. doi: 10.3390/insects12040273.

Abstract

The present study is the first modeling effort at a global scale to predict habitat suitability of fall armyworm (FAW), and its key parasitoids, namely , and , to be considered for biological control. An adjusted procedure of a machine-learning algorithm, the maximum entropy (Maxent), was applied for the modeling experiments. Model predictions showed particularly high establishment potential of the five hymenopteran parasitoids in areas that are heavily affected by FAW (like the coastal belt of West Africa from Côte d'Ivoire (Ivory Coast) to Nigeria, the Congo basin to Eastern Africa, Eastern, Southern and Southeastern Asia and some portions of Eastern Australia) and those of potential invasion risks (western & southern Europe). These habitats can be priority sites for scaling FAW biocontrol efforts. In the context of global warming and the event of accidental FAW introduction, warmer parts of Europe are at high risk. The effect of winter on the survival and life cycle of the pest in Europe and other temperate regions of the world are discussed in this paper. Overall, the models provide pioneering information to guide decision making for biological-based medium and long-term management of FAW across the globe.

摘要

本研究是全球范围内首次进行的建模工作,旨在预测草地贪夜蛾及其关键寄生蜂(即[具体寄生蜂名称1]、[具体寄生蜂名称2]和[具体寄生蜂名称3])的栖息地适宜性,以便考虑用于生物防治。一种经过调整的机器学习算法——最大熵模型(Maxent)被应用于建模实验。模型预测表明,这五种膜翅目寄生蜂在受草地贪夜蛾严重影响的地区(如从科特迪瓦(象牙海岸)到尼日利亚的西非沿海地带、刚果盆地至东非、东亚、南亚和东南亚以及澳大利亚东部的部分地区)以及存在潜在入侵风险的地区(欧洲西部和南部)具有特别高的定殖潜力。这些栖息地可作为扩大草地贪夜蛾生物防治工作的优先地点。在全球变暖以及草地贪夜蛾意外引入的情况下,欧洲较温暖的地区面临高风险。本文讨论了冬季对草地贪夜蛾在欧洲及世界其他温带地区的生存和生命周期的影响。总体而言,这些模型为全球范围内基于生物的草地贪夜蛾中长期管理决策提供了开创性信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/441d/8063841/bf7205f683f6/insects-12-00273-g001.jpg

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