Assessing the multi-pathway threat from an invasive agricultural pest: Tuta absoluta in Asia.
Assessing the multi-pathway threat from an invasive agricultural pest: Tuta absoluta in Asia.
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评估亚洲入侵性农业害虫 Tuta Absolutea 的多途径威胁。
DOI：
10.1098/rspb.2019.1159
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Adiga,Abhijin
中科院分区：
文献类型：
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作者：
McNitt,Joseph;Chungbaek,YoungYun;Mortveit,Henning;Marathe,Madhav;Campos,MateusR;Desneux,Nicolas;Brévault,Thierry;Muniappan,Rangaswamy;Adiga,Abhijin
现代食物系统通过多种途径促进害虫和病原体的快速传播。传播动态的复杂性和数据的不足使得对这种现象进行建模和为新出现的入侵做好准备具有挑战性。我们提出了一个通用框架来研究入侵物种的时空传播，作为一个考虑气候、生物、季节性生产、贸易和人口信息的时变网络的多尺度传播过程。机器学习技术以一种新颖的方式用于捕获模型可变性和分析参数敏感性。我们应用这个框架来了解一种毁灭性的番茄害虫——绝对番茄病（Tuta absoluta）在南亚和东南亚的传播，该地区处于番茄病目前传播范围的前沿。对历史入侵记录的分析表明，即使具有适度的自我传播能力，这种害虫也可以通过国内城市间的蔬菜贸易迅速扩大其范围。我们的模型预测，在5-7年内，绝对Tuta将入侵东南亚大陆所有主要蔬菜种植区。监测高消费地区有助于早期发现，在主要生产地区采取有针对性的干预措施可以有效降低传播速度。
Modern food systems facilitate rapid dispersal of pests and pathogens through multiple pathways. The complexity of spread dynamics and data inadequacy make it challenging to model the phenomenon and also to prepare for emerging invasions. We present a generic framework to study the spatio-temporal spread of invasive species as a multi-scale propagation process over a time-varying network accounting for climate, biology, seasonal production, trade and demographic information. Machine learning techniques are used in a novel manner to capture model variability and analyse parameter sensitivity. We applied the framework to understand the spread of a devastating pest of tomato,Tuta absoluta, in South and Southeast Asia, a region at the frontier of its current range. Analysis with respect to historical invasion records suggests that even with modest self-mediated spread capabilities, the pest can quickly expand its range through domestic city-to-city vegetable trade. Our models forecast that within 5–7 years,Tuta absolutawill invade all major vegetable growing areas of mainland Southeast Asia assuming unmitigated spread. Monitoring high-consumption areas can help in early detection, and targeted interventions at major production areas can effectively reduce the rate of spread.