Plant Pathology Department



Sydney E. Everhart

Date of this Version



Annals of Botany 108 (2011), pp. 1195–1202;



© 2011 Sydney E. Everhart, Ashley Askew, Lynne Seymour, Imre J. Holb, and Harald Scherm. Published by Oxford University Press on behalf of the Annals of Botany Company. Used by permission.


Characterization of spatial patterns of plant disease can provide insights into important epidemiological processes such as sources of inoculum, mechanisms of dissemination, and reproductive strategies of the pathogen population. While two-dimensional patterns of disease (among plants within fields) have been studied extensively, there is limited information on three-dimensional patterns within individual plant canopies. Reported here are the detailed mapping of different symptom types of brown rot (caused by Monilinia laxa) in individual sour cherry tree (Prunus cerasus) canopies, and the application of spatial statistics to the resulting data points to de-termine patterns of symptom aggregation and association. Methods – A magnetic digitizer was uti-lized to create detailed three-dimensional maps of three symptom types (blossom blight, shoot blight, and twig canker) in eight sour cherry tree canopies during the green fruit stage of develop-ment. The resulting point patterns were analyzed for aggregation (within a given symptom type) and pairwise association (between symptom types) using a three-dimensional extension of nearest-neighbor analysis. Key Results – Symptoms of M. laxa infection were generally aggregated within the canopy volume, but there was no consistent pattern for one symptom type to be more or less aggre-gated than the other. Analysis of spatial association among symptom types indicated that previous year’s twig cankers may play an important role in influencing the spatial pattern of current year’s symptoms. This observation provides quantitative support for the epidemiological role of twig can-kers as sources of primary inoculum within the tree. Conclusions – Presented here is a new approach to quantify spatial patterns of plant disease in complex fruit tree canopies using point pattern anal-ysis. This work provides a framework for quantitative analysis of three-dimensional spatial patterns within the finite tree canopy, applicable to many fields of research.