Dissertation Research: Pteromalid Phylogeny and the Diversification of Parasitic Chalcid Wasps

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A grant has been awarded to Dr. Charles Mitter and Mr. Christopher Desjardins of the University of Maryland to study the classification and evolutionary history of a group of parasitoid wasps known as the pteromalids. Pteromalids belong to a biologically diverse and economically important parasitoid group known as the chalcidoids, which include over 20,000 described species. At present, however, evolutionary relationships are very poorly understood for parasitoid wasps generally and for pteromalids in particular. In this study we seek to advance the state of parasitoid classification by using both anatomical characteristics and DNA sequences to reconstruct evolutionary relationships in pteromalids and related chalcidoids. As previous attempts using other genes have not solved the problem, three nuclear genes not previously examined in these wasps, but potentially of great utility for wasp classification, will be studied. In addition, a previously enigmatic subset of pteromalids, known as the diparines, will be reclassified in more detail, enabling entomologists worldwide to identify these wasps.Parasitoid wasps are minute insects that prey on immature stages of other insects, including many pests. They are a dominant feature of terrestrial biodiversity, possibly numbering several hundred thousand species. They are also critical to environmentally sound agriculture, often providing control of agricultural pests that reduces or eliminates the need for insecticides. Hundreds of millions of dollars are saved annually by parasitoid wasps controlling pests of crops as varied as range grass in Texas and cassava in Africa. A phylogenetic classification of parasitoid wasps, in which species are grouped by their degree of evolutionary relatedness, will be essential for understanding how the great diversity of parasitoids has arisen; for organizing current knowledge of the varied ecology, physiology, and behavior of these wasps; and for allowing intelligent prediction of which species are the most promising biological control agents for a given pest.