Data from: Invasiveness of plant pathogens depends on the spatial scale of host distribution

Plant diseases often cause serious yield losses in agriculture. A pathogen’s invasiveness can be quantified by the basic reproductive number, R0. Since pathogen transmission between host plants depends on the spatial separation between them, R0 is strongly influenced by the spatial scale of the host distribution.We present a proof of principle of a novel approach to estimate the basic reproductive number, R0, of plant pathogens as a function of the size of a field planted with crops and its aspect ratio. This general approach is based on a spatially explicit population dynamical model. The basic reproductive number was found to increase with the field size at small field sizes and to saturate to a constant value at large field sizes. It reaches a maximum in square fields and decreases as the field becomes elongated. This pattern appears to be quite general: it holds for dispersal kernels that decrease exponentially or faster, as well as for fat-tailed dispersal kernels that decrease slower than exponential (i.e., power-law kernels).We used this approach to estimate R0 in wheat stripe rust (an important disease caused by Puccinia striiformis), where we inferred both the transmission rates and the dispersal kernels from the measurements of disease gradients. For the two largest datasets, we estimated R0 of P. striiformis in the limit of large fields to be of the order of 30. We found that the spatial extent over which R0 changes strongly is quite fine-scaled (about 30 m of the linear extension of the field). Our results indicate that in order to optimize the spatial scale of deployment of fungicides or host resistances, the adjustments should be made at a fine spatial scale. We also demonstrated how the knowledge of the spatial dependence of R0 can improve recommendations with regard to fungicide treatment.

植物病害常给农业生产带来严重的产量损失。病原体的入侵能力可通过基本再生数R₀（basic reproductive number, R₀）量化。由于宿主植物间的病原体传播依赖于二者的空间间距，宿主分布的空间尺度对R₀具有显著影响。本文提出了一种全新方法的原理性验证，该方法可基于作物种植田块的面积与长宽比，估算植物病原体的基本再生数R₀。该通用方法以空间显式种群动力学模型（spatially explicit population dynamical model）为理论基础。研究发现，基本再生数R₀在田块规模较小时随面积增大而上升，在田块规模较大时则趋于饱和并维持恒定；其在方形田块中达到最大值，随田块趋于狭长而逐渐降低。这一规律具有普适性：无论是指数衰减或衰减更快的扩散核（dispersal kernels），还是衰减速率慢于指数的厚尾扩散核（即幂律核，power-law kernels），均遵循该规律。我们将该方法应用于小麦条锈病（wheat stripe rust，由条形柄锈菌Puccinia striiformis引发的重要病害）的R₀估算，通过病害梯度测量同时推断了传播速率与扩散核。针对两个最大规模的数据集，我们估算得出大尺度田块条件下条形柄锈菌的R₀约为30量级。研究发现，R₀发生显著变化的空间尺度较为精细（约对应田块线性延伸30米）。研究结果表明，若要优化杀菌剂或宿主抗性的施用空间尺度，需在精细空间尺度上进行调整。此外，我们还演示了如何通过掌握R₀的空间依赖性，优化杀菌剂施用的相关推荐方案。