Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e During Brown Rot Epidemics Within Individual Peach Tree Canopies

The purpose of this study was to determine the fine-scale genetic structure of populations of the brown rot pathogen Monilinia fructicola within individual peach tree canopies to better understand within-tree plant pathogen diversity and to complement previous work on spatiotemporal development of brown rot disease at the canopy level. Across 3 years in a total of six trees, we monitored disease development, collected isolates from every M. fructicola symptom during the course of the season, and created high-resolution three-dimensional maps of all symptom and isolate locations within individual canopies using an electromagnetic digitizer. Each canopy population (65 to 173 isolates per tree) was characterized using a set of 13 microsatellite markers and analyzed for evidence of spatial genetic autocorrelation among isolates during the epidemic phase of the disease. Results showed high genetic diversity (average uh = 0.529) and high genotypic diversity (average D = 0.928) within canopies. The percentage of unique multilocus genotypes within trees was greater for blossom blight isolates (78.2%) than for fruit rot isolates (51.3%), indicating a greater contribution of clonal reproduction during the preharvest epidemic. For fruit rot isolates, between 54.2 and 81.7% of isolates were contained in one to four dominant clonal genotypes per tree having at least 10 members. All six fruit rot populations showed positive and significant spatial genetic autocorrelation for distance classes between 0.37 and 1.48 m. Despite high levels of within-tree pathogen diversity, the contribution of locally available inoculum combined with short-distance dispersal is likely the main factor generating clonal population foci and associated spatial genetic clustering within trees

Spatio-temporal Patterns of Pre-harvest Brown Rot Epidemics within Individual Peach Tree Canopies

Tree canopies are architecturally complex and pose several challenges for measuring and character-izing 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 \u3c 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, within-tree sources of inoculum at the beginning of the epidemic. Four of five trees having \u3e10 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 out-comes 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 associa-tion. 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 devel-opment and thus led to negative spatial associations among symptoms developing over time in a tree

Spatio-temporal Patterns of Pre-harvest Brown Rot Epidemics within Individual Peach Tree Canopies

Tree canopies are architecturally complex and pose several challenges for measuring and character-izing 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 \u3c 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, within-tree sources of inoculum at the beginning of the epidemic. Four of five trees having \u3e10 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 out-comes 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 associa-tion. 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 devel-opment and thus led to negative spatial associations among symptoms developing over time in a tree

Spatial Patterns of Brown Rot Epidemics and Development of Microsatellite Markers for Analyzing Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e Populations Within Peach Tree Canopies

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, nearest-neighbor 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

Spatial Patterns of Brown Rot Epidemics and Development of Microsatellite Markers for Analyzing Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e Populations Within Peach Tree Canopies

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, nearest-neighbor 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

Constraints on new interactions from neutron scattering experiments

Constraints for the constants of hypothetical Yukawa-type corrections to the Newtonian gravitational potential are obtained from analysis of neutron scattering experiments. Restrictions are obtained for the interaction range between 10^{-12} and 10^{-7} cm, where Casimir force experiments and atomic force microscopy are not sensitive. Experimental limits are obtained also for non-electromagnetic inverse power law neutron-nucleus potential. Some possibilities are discussed to strengthen these constraints.Comment: 18 pages, 3 figure

A perspective on the measurement of time in plant disease epidemiology

The growth and development of plant pathogens and their hosts generally respond strongly to the temperature of their environment. However, most studies of plant pathology record pathogen/host measurements against physical time (e.g. hours or days) rather than thermal time (e.g. degree-days or degree-hours). This confounds the comparison of epidemiological measurements across experiments and limits the value of the scientific literature

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods