Organisms susceptible to disease, from humans to crops, inevitably have spatial geometry that influence disease dynamics. Understanding how spatial structure emerges through time in ecological systems and how that structure influences disease dynamics is of practical importance for natural and human management systems. Here we use the perennial crop, coffee, Coffea arabica, along with its pathogen, the coffee leaf rust, Hemileia vastatrix, as a model system to understand how spatial structure is created in agroecosystems and its subsequent influence on the dynamics of the system. Here, we create a simple null model of the socio-ecological process of death and stochastic replanting of coffee plants on a plot. We then use spatial networks to quantify the spatial structures and make comparisons of our stochastic null model to empirically observed spatial distributions of coffee. We then present a simple model of pathogen spread on spatial networks across a range of spatial geometries emerging from our null model and show how both local and regional management of agroecosystems interact with space and time to alter disease dynamics. Our results suggest that our null model of evolving spatial structure can capture many critical features of how the spatial arrangement of plants changes through time in coffee agroecosystems. Additionally, we find small changes in management factors that can influence the scale of pathogen transmission, such as shade tree removal, and result in a rapid transition to epidemics with lattice-like spatial arrangements but not with irregular planting geometries. The results presented here may have practical implications for farmers in Latin America who are in the process of replanting and overhauling management of their coffee farms in response to a coffee leaf rust epidemic in 2013. We suggest that shade reduction in conjunction with more lattice-like planting schemes may result in coffee being more prone to epidemic-like dynamics of the coffee leaf rust in the future.

从人类到农作物，易患疾病的生物不可避免地具有影响疾病动态的空间几何形状。了解空间结构如何随着时间在生态系统中出现，以及该结构如何影响疾病动态对于自然和人为管理系统具有实际意义。在这里，我们使用多年生作物咖啡，阿拉伯咖啡（Coffea arabica）及其病原体，咖啡叶锈病，Hemileia hugeatrix，作为模型系统，以了解如何在农业生态系统中创建空间结构及其对系统动力学的后续影响。在这里，我们创建了一个简单的无效模型，用于模拟某地块上咖啡植物死亡和随机重新种植的社会生态过程。然后，我们使用空间网络来量化空间结构，并对我们的随机null模型与根据经验观察到的咖啡的空间分布进行比较。然后，我们提出了一个简单的病原体模型，该模型在从我们的null模型出现的一系列空间几何结构的空间网络中传播，并展示了农业生态系统的局部和区域管理如何与空间和时间相互作用来改变疾病动态。我们的结果表明，我们不断变化的空间结构的模型可以捕获咖啡农业生态系统中植物的空间排列如何随时间变化的许多关键特征。此外，我们发现管理因素的细微变化会影响病原体传播的规模，例如遮荫树的去除，并导致以格子状的空间排列迅速过渡到流行病，但种植几何形状不规则。此处提出的结果可能会对拉丁美洲的农民产生实际的影响，他们正在为应对2013年的咖啡叶锈病而对咖啡农场进行重新种植和大修管理。