The influence of host suitability on the range of grasshopper species utilized by Blaesoxipha atlanis (Diptera: Sarcophagidae) in the field

Abstract

Blaesoxipha atlanis (Aldrich) is a common parasitic fly of agriculturally important grasshoppers in Canada. The suitability of Camnula pellucida (Scudder), Melanoplus bivittatus (Say), Melanoplus packardii Scudder, and Melanoplus sanguinipes (Fabricius) as hosts was studied in the laboratory. Grasshoppers were singly-parasitized or left unparasitized and reared for 9 days. Melanoplus bivittatus and M. packardii did not support parasite development, i.e. were non-permissive hosts. In both species, parasite larvae were melanized and encapsulated, but development proceeded further in M. packardii. Melanoplus sanguinipes and C. pellucida were permissive host species with, respectively, 70% and 35% of the implanted larvae emerging from their hosts of which 86% and 50% developed into adults. Parasite development time was longer in C. pellucida. Adult B. atlanis dry mass varied with host species and host mass at parasitism, but not with host sex. Parasites developing in M. sanguinipes were larger in terms of dry mass than counterparts developing in C. pellucida. In permissive species, unparasitized grasshoppers gained in body mass while parasitized insects lost mass during the 9-day observation period. In non-permissive species, all insects gained in body mass, but parasitized females gained less mass than unparasitized conspecifics. All unparasitized grasshoppers survived while 75-95% of permissive and 30-40% of non-permissive hosts died. Variation in the intensity of field parasitism among grasshopper species may be explained, at least in part, by qualitative differences in suitability between potential host species. Novel pest management strategies emphasize preservation of a small proportion of the pest population for natural enemies. Consideration of the outcome of specific host-parasite interactions should improve the understanding of grasshopper population dynamics and increase the predictive value of models that assess potential crop losses.