Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt), causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents ^1-11 . Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research ^12-14 . We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high air-borne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum) ^10,15 , and regions with genetic similarities in related pathogen populations ^16,17 . We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as 'Ug99' ^5,6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time ³ .

中文翻译：

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量化病原体在空气中的传播途径，以保护全球小麦供应。

蔓延到大片农业地区的农作物传染病对粮食安全构成威胁。专性致病性真菌Puccinia graminis f.sp.的攻击性菌株。在东非和中东发现了导致小麦茎锈病的小麦病，导致了巨大的经济损失并威胁到农民的生计。全世界大多数商业种植的小麦品种都容易受到这些新兴菌株的影响，这对全球小麦的生产构成了风险，因为传播该病的真菌孢子可以风散布在各个地区，甚至是^1-11大洲。有针对性的监视和控制需要病原体在空气中传播的知识，但长距离传播的复杂性给定量研究带来重大挑战^12-14。我们结合国际现场调查，全球气象数据，拉格朗日色散模型和高性能计算资源来模拟一组疾病暴发情景，在数十年来动态变化的宿主和环境景观上追踪数十亿条真菌孢子的随机轨迹。这是对南部/东非，中东和中亚/南亚所有小麦生产国中孢子传播频率和数量的首次定量评估。我们确定了高空气传播连通性的区域，这些区域在地理上与先前假定的小麦锈病流行病学区域（以地方病和接种物的自由流动为特征）^10,15以及在相关病原体种群中具有遗传相似性的区域^16,17。我们量化了诸如Ug99 ^5,6之类的致病性强毒株在远东从东非扩散到巴基斯坦和印度的小麦大产区所构成的威胁的情况（路线，时间，爆发规模）。总结了域内所有国家的长期平均孢子扩散趋势（主要方向，频率，数量）（补充数据）。我们的机械建模框架可以应用于其他地理区域，适用于其他病原体，并可以用于实时提供风险评估³。