Spatial and temporal analyses of citrus tristeza virus in eastern Spain

Abstract

Citrus tristeza virus (CTV) was monitored for up to 14 years by monoclonal antibody probes via enzyme-linked immunosorbent assay in five orange and grapefruit orchards with symptomless trees in Valencia and Alicante provinces, Spain. Linear, exponential, logistic, or Gompertz nonlinear temporal models were selected as the most appropriate, depending on the phase of the epidemic during the assessment period and based on correlation of observed versus predicted values and examination of the patterns of residual error. Ordinary runs analysis for within- or across-row association of CTV-positive trees indicated that the disease status of immediately adjacent trees was unpredictable. The beta-binomial index of dispersion for different quadrat sizes indicated a tendency for aggregations of infected trees at quadrat sizes of 2 x 2 or 4 x 4 CTV-positive trees in some plots, which when viewed with ordinary runs suggested the possible presence of longer distance spatial relationships. Two-dimensional distance class (2DCLASS) analysis indicated a random spatial pattern of CTV incidence and general lack of association of infection among adjacent trees. Spatio-temporal distance class (STCLASS) analysis further indicated a lack of spatial dependency among adjacent CTV-positive trees over time. Significant edge effects detected by both 2DCLASS and STCLASS analyses suggested possible spread of CTV from inoculum originating outside the area of the individual plots. Semi-variograms from spatio-temporal geostatistical analyses of four directions of orientation confirmed a lack of spatial dependency of infection among adjacent or nearby trees over time. These combined spatial and temporal analyses gave some insight into possible underlying processes of CTV spread and suggested CTV spread must be predominantly to trees farther away rather than to immediately adjacent trees. If a nonrandom spatial structure of CTV incidence does exist, it may well be of a complexity beyond the detection ability of the spatial analysis methods employed or perhaps on a scale that is larger than the dimensions of the plots studied.