Maximizing the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialized. The factors that interact with and determine the magnitude of this spatial suppressive effect are not currently well understood, however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multiseason semidiscrete epidemiological model tracks spatial spread of wild-type and resistance-breaking pathogen strains, and incorporates a localized reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance-breaking trait, the efficacy of host resistance, and the length of the timeframe of interest all influence the strength of the spatial diversification effect. A key result is that spatial diversification has the strongest beneficial effect at intermediate fitness costs of the resistance-breaking trait, an effect driven by a complex set of nonlinear interactions. On the other hand, however, if the resistance-breaking strain is not fit enough to invade the landscape, then a partially effective resistance gene can result in spatial diversification actually worsening the epidemic. These results allow us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modeling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host−pathogen disease systems.

Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

面对病原体进化，使农作物抗病基因的持久性最大化是现代农业流行病学的主要挑战。预计在易感性和抗性领域更加紧密混合的抗性基因的部署中，空间多样化将在进化的时间尺度上推动较低的流行强度。这是由于病原体接种物挑战了宿主组织，而稀释作用的强度却提高了，而宿主组织还没有被专门化。但是，目前尚不十分了解与这种空间抑制作用相互作用并决定其大小的因素，这导致了这种策略最有可能具有成本效益的病理系统的不确定性。我们对空间异质性对景观尺度疾病动态变化的影响进行建模，以种植易感或抗性品种的田地为基础，以及这种影响方式取决于控制感兴趣的病理系统的参数。我们的多季节半离散流行病学模型跟踪了野生型和抗性病原体菌株的空间传播，并纳入了局部接种物库，以及田间传播之间和之间的影响。病原体的传播特性，抗性突破特性的适应性成本，宿主抗性的功效以及所关注的时间长度都影响着空间多样化效应的强度。一个关键的结果是，空间多样化在抵抗性状的中间适应性代价上具有最强的有益效应，这种效应是由一组复杂的非线性相互作用驱动的。但是，另一方面，如果抗性破坏菌株的适应性不足以侵入地貌，则部分有效的抗性基因可能导致空间多样化，实际上使该流行病恶化。这些结果使我们能够对空间多样化最有可能具有成本效益的系统类型做出一般性预测，从而为潜在的经济建模和病理系统特定评估铺平了道路。这些结果强调了研究遗传因素对宿主病原体疾病系统内景观尺度空间动态的影响的重要性。由一组复杂的非线性相互作用驱动的效果。但是，另一方面，如果抗性破坏菌株的适应性不足以侵入地貌，则部分有效的抗性基因可能导致空间多样化，实际上使该流行病恶化。这些结果使我们能够对空间多样化最有可能具有成本效益的系统类型做出一般性预测，从而为潜在的经济建模和病理系统特定评估铺平了道路。这些结果强调了研究遗传因素对宿主病原体疾病系统内景观尺度空间动态的影响的重要性。由一组复杂的非线性相互作用驱动的效果。但是，另一方面，如果抗性破坏菌株的适应性不足以侵入地貌，则部分有效的抗性基因可能导致空间多样化，实际上使该流行病恶化。这些结果使我们能够对空间多样化最有可能具有成本效益的系统类型做出一般性预测，从而为潜在的经济建模和病理系统特定评估铺平了道路。这些结果强调了研究遗传因素对宿主病原体疾病系统内景观尺度空间动态的影响的重要性。则部分有效的抗药性基因会导致空间多样化，实际上使疫情恶化。这些结果使我们能够对空间多样化最有可能具有成本效益的系统类型做出一般性预测，从而为潜在的经济建模和病理系统特定评估铺平了道路。这些结果强调了研究遗传因素对宿主病原体疾病系统内景观尺度空间动态的影响的重要性。则部分有效的抗药性基因会导致空间多样化，实际上使疫情恶化。这些结果使我们能够对空间多样化最有可能具有成本效益的系统类型做出一般性预测，从而为潜在的经济建模和病理系统特定评估铺平了道路。这些结果强调了研究遗传因素对宿主病原体疾病系统内景观尺度空间动态的影响的重要性。

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