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Relationship Between Climatic Factors and Distribution of Pratylenchus spp. in the Dryland Wheat-Production Areas of Eastern Washington

November 2013 , Volume 97 , Number  11
Pages  1,448 - 1,456

Shyam L. Kandel, Department of Plant Pathology, Washington State University, Pullman 99164-6430; Richard W. Smiley, Columbia Basin Agricultural Research Center, Oregon State University, Pendleton 97801; Kimberly Garland-Campbell, United States Department of Agriculture–Agricultural Research Service (USDA-ARS), Wheat Genetics, Quality, Physiology and Disease Research Unit, Pullman, WA 99164; Axel A. Elling, Department of Plant Pathology, Washington State University; John Abatzoglou, Department of Geography, University of Idaho, Moscow 83844; David Huggins, USDA-ARS Land Management and Water Conservation Research Unit, Pullman, WA 99164; Richard Rupp, Department of Crop and Soil Sciences, Washington State University, Pullman; and Timothy C. Paulitz, USDA-ARS, Root Disease and Biological Control Research Unit, Pullman, WA 99164

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Accepted for publication 7 May 2013.

Field surveys were conducted by collecting soil samples to estimate nematode densities in soil from winter wheat, spring wheat, spring barley, and spring legumes (lentil, chickpea, and pea) fields during 2010 and 2011. Pratylenchus spp. were observed in 60% of sampled fields. However, nematodes were detected in nearly all of the survey fields in high numbers where crops were grown every year. To identify climatic variables associated with density of Pratylenchus spp. in soil, correlation and regression analyses were performed using climate data of survey sites from 1979 to 2010. Fifty-seven climate variables were significantly correlated with densities of Pratylenchus spp. All precipitation variables were significantly positively correlated with nematode abundance. Summer maximum air temperature was negatively correlated and winter minimum air temperature was positively correlated with nematode densities. In addition, both years' nematode densities were significantly correlated with cropping intensity. Five multivariate regression models for 2010 and seven models for 2011 nematode abundance levels were developed. The majority of the climate variables selected in the models were related to precipitation. Knowledge of root-lesion nematode distribution in the dryland region of eastern Washington and associated climate variables may be helpful to determine risk and apply management practices to minimize crop damage.

This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. The American Phytopathological Society, 2013.