Spatial and numerical relationships of arthropod communities associated with key pests of maize

Pest management largely focuses on managing individual pest species with little concern for the diverse communities that co-occur with key pests and potentially shape their population dynamics. During anthesis, we described the foliar arthropod communities on 53 maize farms throughout the region of eastern South Dakota. The resulting communities were examined for trends in local associations in the abundances of taxa with key pests in the system (rootworms [Diabrotica spp.], European corn borers [Ostrinia nubilalis], aphids and Western bean cutworm [Striacosta albicosta]) using regression analyses. Regional spatial clustering in the abundances of key pests with members of the community was explored using Moran's I test statistic. The distributions of rootworms and European corn borer were mapped. A total of 37185 arthropods representing at least 91 taxa were collected in South Dakota maize; there was an average of 5.06 predators and 8.29 herbivores found per plant. Key pests were never found at economically threatening levels (with one exception for Diabrotica). Numerous species were consistently numerically associated with each of the key pests across the farms during anthesis. Occasionally, these pests shared species with which they were locally associated with; for example, coccinellid egg abundances were predictive of the abundances of all key pest species except rootworm adults. Spatial analysis across the region suggested that species co-occurred with key pests based on local characteristics surrounding the fields, rather than as a result of regional characteristics. Exceptions were documented; namely aphids and Western bean cutworms that spatially clustered with a handful of other members of the community. The results of the study point out that the abundances of key pests of maize were interconnected through indirect associations in the abundances of other members of the community. These associations may be useful for manipulating maize agroecosystems to minimize the effects of maize pests.