Location: Subtropical Plant Pathology Research2013 Annual Report
1a. Objectives (from AD-416):
1. Develop spatial and temporal models and assessment of disease control/mitigation strategies via incorporation of variable meteorological conditions. 2. Utilize these models to test alternative disease control strategies and to conduct scenario testing.
1b. Approach (from AD-416):
1. Collect, analyze, and interpret initial HLB epidemic data. 2. Conduct field trials to determine the efficacy of rouging, insect control, and treatment combinations. 3. Conduct field trials to determine the efficacy of Murraya paniculata as a trap plant. 4. Develop preliminary spatial and temporal models and preliminary assessment of disease control/mitigation strategies. 5. Initiate development of stochastic models to estimate the temporal increase and spatial spread of HLB that are plastic and adaptable to other pest and pathogen systems. 6. Incorporate model parameters that allow the use of variable meteorological conditions, for instance in local conditions in citrus growing regions in various citrus producing states. 7. Utilize these models and statistical methods to test alternative disease control strategies via stochastic simulation and select those strategies which maximize the probability of success prior to test/deployment of control methods in the field. 8. Conduct scenario testing and the ability to estimate citriculture economic parameters such as estimates of fiscal and manpower requirements for yearly planning and budgetary requirements.
3. Progress Report:
This research is related to inhouse project objective 3. Develop or improve comprehensive integrated disease management strategies. This FY, particular attention was given to the three primary objectives of the project: 1) Develop a generic epidemiological model that can be used to compare control scenarios and to optimize the probability of controlling and managing high-risk pathogens of agricultural significance; 2) Development and testing of efficient methods of statistical inference to estimate epidemiological parameters from maps of emerging epidemics; and 3) Develop user friendly model ‘front ends’ that can be used by researchers and regulatory agencies. Following an extensive period of testing methods to parameterize stochastic models for HLB and citrus canker, and the development of flexible models for spread of epidemics through heterogeneous landscapes, we have focused on: (i) the practical use of the models to compare control scenarios at the landscape scale; (ii) to allow for uncertainties in the location of hosts at different scales in the landscape and in a policy makers knowledge of parameter estimates; and (iii) to incorporate meteorological dynamics in the models, particularly to allow for real weather in dispersal events. One of the principal challenges – also addressed in the development of user-friendly models - is to be able to run the models sufficiently fast to enable the user to compare a range of ‘what-if’ control scenarios with different levels of uncertainty, allowing rapid presentation of results within real time. Substantial progress has been made through the development and testing of efficient computational methods (to allow finely-resolved computation of multi-county and state-wide spread of disease/ Two approaches have been used, the familiar individual-tree--based models and meta-population models. We have also analyzed the effectiveness of greatly increasing the speed of execution of stochastic, spatially-extended model using dedicated multi-core computers available to the Epidemiology and Modeling Group. The additional computing power has also allowed the incorporation of meteorological dispersal models into the epidemiological toolbox in objective (1) above. These models can be used to track intermediate and long-distance movement of vectors: providing measures of primary introduction of inoculum. Turning to detailed models within plantations, analysis of the effects of host planting age on the transmission of HLB has been completed. We have also completed the analysis of how to allow for removal or treatment of infected trees in a region in which the dispersal and transmission are being estimated for an emerging epidemic. We are continuing to test the risk-based method to show where disease is most likely to spread in order to optimize control that involves removal of more susceptible hosts around key infected sites. Recent work on citrus canker has examined weather-driven variability in the transmission rate of infection by extracting signals from Markov chain Monte Carlo estimates of parameters averaged over different time-scales of one to several months and correlating these with weather variables. The method suggests that it will be possible to use Florida data to estimate the spread of disease under different environmental conditions, for example those typical of Texas or California and to compare the risk of spread under different runs of months/years of favorable or unfavorable weather conditions. Building on a model for HLB within individual plants, we have compared the relative importance of pathogen transmission within the vascular system of the tree and transmission between leaves via psyllid vectors. The model is being used to compare the efficacy of roguing, application of insecticide and the use of nutritional products and thermotherapy for disease control and mitigation.