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Spatial pattern of the Río Cuarto corn disease vector, Delphacodes kuscheli Fennah (Hom., Delphacidae), in oat fields in Argentina and design of sampling plans
Authors:O. Garat  E. V. Trumper  D. E. Gorla   N. Perez-Harguindeguy
Affiliation:Universidad Nacional de Córdoba, Facultad de Ciencias Agropecuarias, Laboratorio de Ciencias Exactas Físicas y Natureles, Escuela de Biologia, Córdoba;;Instituto Nacional de Tecnología Agropecuaria, Estación Experimental Agropecuaria Manfredi, Sección Entomolgía, Manfredi;;Universidad Nacional de Córdoba, Facultad de Ciencias Agropecuarias, Laboratorio de Ecología de Insectos, Ciudad Universitaria, Cordóba, Republica Argentina
Abstract:The spatial pattern of the Río Cuarto Corn Disease vector, Delphacodes kuscheli (Hom., Delphacidae), was analysed in oat fields within the endemic area of the disease, during the growing seasons 1993 and 1994. The spatial pattern was analysed by fitting the probabilistic models Poisson and negative binomial and estimation of single-date and overall aggregation indices. The population of the different stage classes, sex, and wing forms showed a significant trend to aggregation as the negative binomial model fitted the observed frequency distributions in more than 78% of the cases (sampling dates) while the Poisson model fitted well in only 28% of cases or less. Single-date aggregation index, C A, ranged from 0.3 to 0.84. Overall (whole season) aggregation index, C A*, estimated through the Bliss and Owen's regression method, ranged from 0.18 (female adults) to 1.08 (nymphs I–II), indicating a moderate degree of aggregation compared with other planthopper species. There were no significant relationships between aggregation and population density. The minimum number of sampling units and critical lines for sequential sampling plans were calculated based on the estimation of C A* for the precision levels ( D ) 0.1, 0.2 and 0.3. Even low degrees of aggregation, like that of adults, demand much more sampling effort than randomly distributed populations, particularly at high densities. General implications and limitations of the proposed sampling plans for monitoring the vector population abundance are discussed.
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