Huanglongbing (HLB) is the most devastating disease of citrus and has spread to the main growing areas worldwide, including Brazil, USA and China. There is still no viable curative strategy or resistant citrus variety to control HLB and management is based in the reduction of inoculum, i.e. eradication of symptomatic trees, utilization of healthy seedlings and chemical control of vector populations. However, even in well managed orchards, HLB and its spread by the psyllid can cause infection in 100% of trees in 2 to 5 years. The pathogen dissemination by the vector is the main difficultly related with management of the disease. This occurs because HLB epidemics spread via two types of dissemination: secondary spread, i.e., the transmission of the pathogen to trees on the same orchard; and primary spread, i.e., the transmission of the pathogen on long distances, from trees of another orchard. The primary spread is the most dangerous kind of dissemination because it indicates a spatial process of long distance or regional spread, and then, it explains why HLB control efforts on a local scale have failed. As a consequence of the primary dissemination, most of the tree eradications are made on orchard edges and a border effect can be seen on HLB afected properties. In order to reduce the incidence and consequences of the border effect, some measures have been introduced on HLB management as the area-wide control, more frequently insecticide application on orchard borders, ultra-high density plantings, edge parallel planting and frequent seedlings replanting. From producer's perspective, this must delay the disease progress and also reduce the negative impact of eradications on borders. However, there are no studies that measure the width of the border effect, i.e., the length of the strip where there is a higher HLB incidence and the effectiveness of these strategies. Understand the HLB spatial-temporal spread dynamics, i.e., primary and secondary spread, and the effect it has in an area with HLB and vector management are essential tools to better understanding the pathosistem HLB - vector - Citrus. These informations are critical to predict the likelihood and extent of further spread, to describe and understand the development of diseases, developing sampling plans, planning controlled experiments, to characterize losses caused and determining the effectiveness of possible control measurements. In this sense, parameter estimation techniques such as Markov chain Monte Carlo (MCMC) or Approximate Bayesian Computation (ABC) are important computational tools for estimating model parameters. In this project, we intend to use parameterization methods (e.g. MCMC and ABC) to estimates and to compare the primary and secondary HLB spread of 13 (~25 ha) plots with strict HLB and vector management. Also, because of the unprecedented size of the data set (~325 ha), this project presented a unique opportunity to determine HLB and D. citri spatial pattern under age and plot localization (border or internal) variables on a 'regional' scale and determine the length of HLB border effect.
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