El Niño-Southern Oscillation (ENSO) effects on Hessian fly (Diptera: Cecidomyiidae) infestation in the southeastern United States.

Climate variability is expected to have an influence on the population of Hessian fly, Mayetiola destructor Say (Diptera: Cecidomyiidae), a serious insect pest of winter wheat in the southeastern United States. This study had two objectives: 1) to examine the effects of El Niño-Southern Oscillation (ENSO) on Hessian fly infestation and 2) to develop a weather-based Hessian fly infestation model for wheat yield loss prediction. At least 20 years of Hessian fly infestation and wheat yield records from two locations in South Georgia were used for this study. The yearly values of infestation were separated by ENSO phase and tested to assess the infestation differences across ENSO phases. Each year, yield losses from infestation were calculated by subtracting the yields of resistant varieties from those of susceptible ones. The yield losses were then separated by ENSO phase and tested. Multiple regression analyses were conducted to identify the contribution of monthly weather variables and changes in wheat acreage to Hessian fly infestation. Results showed that Hessian fly infestation and yield losses were greatest during the La Niña and least during the El Niño phase. The weather conditions that significantly increased the risk for infestation were those of the August-February period. The risk of infestation was higher during August-September under wetter, cooler conditions and during October-February under drier, warmer conditions. These findings could help wheat growers reduce the risk of infestation in the years that are expected to have more infestation through the adoption of necessary mitigation measures before the crop season.

Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties.

Identifying the spatial variability and risk areas for southern root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) is key for site-specific management (SSM) of cotton (Gossypium hirsutum L.) fields. The objectives of this study were to: (i) determine the soil properties that influence RKN occurrence at different scales; and (ii) delineate risk areas of RKN by indicator kriging. The study site was a cotton field located in the southeastern coastal plain region of the USA. Nested semivariograms indicated that RKN samples, collected from a 50×50 m grid, exhibited a local and regional scale of variation describing small and large clusters of RKN population density. Factorial kriging decomposed RKN and soil properties variability into different spatial components. Scale dependent correlations between RKN data showed that the areas with high RKN population remained stable though the growing season. RKN data were strongly correlated with slope (SL) at local scale and with apparent soil electrical conductivity deep (EC(a-d)) at both local and regional scales, which illustrate the potential of these soil physical properties as surrogate data for RKN population. The correlation between RKN data and soil chemical properties was soil texture mediated. Indicator kriging (IK) maps developed using either RKN, the relation between RKN and soil electrical conductivity or a combination of both, depicted the probability for RKN population to exceed the threshold of 100 second stage juveniles/100 cm(3) of soil. Incorporating EC(a-d) as soft data improved predictions favoring the reduction of the number of RKN observations required to map areas at risk for high RKN population.