Presented here is a new approach to quantify spatial patterns of plant disease in complex fruit tree canopies using point pattern analysis. This work provides a framework for quantitative analysis of three-dimensional spatial patterns within the finite tree canopy, applicable to many fields of research.

To better understand the fine-scale spatial dynamics of brown rot disease and corresponding fungal genotypes, we analyzed three-dimensional spatial patterns of pre-harvest fruit rot caused by Monilinia fructicola in individual peach tree canopies and developed microsatellite markers for canopy-level population genetics analyses. Using a magnetic digitizer, high-resolution maps of fruit rot development in five representative trees were generated, and M. fructicola was isolated from each affected fruit. To characterize disease aggregation, nearestneighbor distances among symptomatic fruit were calculated and compared with appropriate random simulations. Within-canopy disease aggregation correlated negatively with the number of diseased fruit per tree (r = −0.827, P = 0.0009), i.e., aggregation was greatest when the number of diseased fruit was lowest. Sixteen microsatellite primers consistently amplified polymorphic regions in a geographically diverse test population of 47 M. fructicola isolates. None of the test isolates produced identical multilocus genotypes, and the number of alleles per locus ranged from 2 to 16. We are applying these markers to determine fine-scale population structure of the pathogen within and among canopies. Accepted for publication 23 May 2012. Published 23 July 2012.

Tree canopies are architecturally complex and pose several challenges for measuring and characterizing spatial patterns of disease. Recently developed methods for fine-scale canopy mapping and three-dimensional spatial pattern analysis were applied in a 3-year study to characterize spatio-temporal development of pre-harvest brown rot of peach, caused by Monilinia fructicola, in 13 trees of different maturity classes. We observed a negative correlation between an index of disease aggregation and disease incidence in the same tree (r = −0.653, P < 0.0001), showing that trees with higher brown rot incidence had lower aggregation of affected fruit in their canopies. Significant (P ≤ 0.05) within-canopy aggregation among symptomatic fruit was most pronounced for early-maturing cultivars and/or early in the epidemic. This is consistent with the notion of a greater importance of localized, withintree sources of inoculum at the beginning of the epidemic. Four of five trees having >10 blossom blight symptoms per tree showed a significant positive spatial association of pre-harvest fruit rot to blossom blight within the same canopy. Spatial association analyses further revealed one of two outcomes for the association of new fruit rot symptoms with previous fruit rot symptoms in the same tree, whereby the relationship was either not significant or exhibited a significant negative association. In the latter scenario, the newly diseased fruit were farther apart from previously symptomatic fruit than expected by random chance. This unexpected result could have been due to uneven fruit ripening in different sectors of the canopy, which could have affected the timing of symptom development and thus led to negative spatial associations among symptoms developing over time in a tree.