This work studied the spatial dispersion of cases of fatal yellowing (FY) in an oil palm plantation in Acará, Pará State, Brazil. Data were collected monthly from two areas, divided in 16 quadrants each, for a 24 month period (2012-2013). In each quadrant, 138 plants were evaluated. The number of diseased plants was counted in twenty planting lines, and the spatial pattern of the disease was analyzed. The following spatial analysis techniques were used: common sequences of “runs”, “doublets” and quadrants. We also determined the levels of disease aggregation in the sectors. Plants with FY had a spatial distribution aggregated in a lower line number when using the “run” analysis than when using the “doublets” method. Aggregation of FY cases was observed in 30% of the evaluated lines. The quadrant analysis confirmed the existence of case aggregation, with vertical and horizontal distribution. The existence of disease forming foci suggests that FY probably has biotic origin. Additional studies are required to confirm this hypothesis.

Fatal yellowing (FY) is a lethal and poorly understood disease that threatens the sustainability of oil palm (Elaeis guineensis Jacq.) cultivation in the Amazon region. Despite decades of research, its etiology remains unknown, and its spatial dynamics are still unclear, particularly under different cultivation systems. This study aimed to characterize and compare the spatial distribution of FY cases in oil palm plantations under organic and conventional cultivation systems in the Eastern Amazon. Field data were collected monthly from December 2012 to March 2014 in four plots located in Acará, Pará State, Brazil. Each plant was evaluated for the presence or absence of FY symptoms, and geostatistical analyses were applied to assess spatial dependence and disease aggregation patterns using spherical, exponential, and Gaussian models. The results indicated a predominance of aggregated spatial distribution in both cultivation systems, with stronger spatial dependence observed in plots with higher FY incidence. The disease tended to cluster within a radius of up to 220 m, with hotspot formation often near access roads. These findings suggest the possibility of a biotic dissemination mechanism and support the development of targeted surveillance strategies. By quantifying the spatial behavior of FY, this study provides a technical basis for implementing localized monitoring and management practices in oil palm plantations, contributing to early detection and more effective disease control.

The aim of this study was to verify the spatial and temporal behavior of corn leaf aphid (Rhopalosiphum maidis Fitch.) and hoverflies in corn crop in the municipality of Igarapé-Açu, northeast of Pará, Brazil, as well as the influence of adjacent areas on the occurrence of these insects. An experimental area of 1.0 ha (100 x 100 m) was used in the years 2015 and 2016, adjacent areas consisted of mango agroecosystem, pasture and secondary forest. The area was divided into grid with 100 plots of 100 m² (10 x 10 m). Ten plants were randomly selected, totaling 1,000 plants per sampling date. Corn leaf aphid colonies (= or> 15 aphid) and syrphid flies adult was visually analyzed throughout the aerial parts of the plants. The spatial behavior was analyzed by semivariogram modeling and kriging interpolation maps. The semivariograms and kriging maps were made by the R software for Windows. Gaussian, spherical and exponential models were the best fit for corn leaf aphid in both harvests, showing aggregate behavior. The strong and moderate spatial dependence index prevailed, with range ranging from 12.46 to 93.04 m for R. maidis. The syrphids flies showed spatial interaction with the corn leaf aphid and they also show aggregate behavior, confirmed by most adjustments in the spherical and exponential models. The spatial dependence index of the prevailing syrphids flies were moderate and weak, ranging from 14.00 to 101.33 m. Adjacent areas showed influence on occurrence and dispersal of both corn leaf aphid and syrphids flies.