The olfactory response of Trigonotylus caelestialium, to rice, Oryza sativa L., and two species of gramineous weeds, Poa annua and Digitaria ciliaris, was investigated with an olfactometer to clarify the role of host-plant odours as olfactory cues in their host-finding behaviour. Third-instar nymphs and adult males were significantly attracted to whole plants (above ground parts) of P. annua. However, adult females were not significantly attracted to whole plants of P. annua. Attractancy of rice to T. caelestialium differed with the growth stage and part of the plant. Adult females were significantly attracted to stems and leaves in the panicle-formation stage, and panicles in the flowering stage. They were not attracted to stems and leaves in the fourth-leaf stage and flowering stage, or to panicles in the milk-and fullripe stages. Although adult males were significantly attracted to stems and leaves in the panicle-formation stage, they were not attracted to the other rice structures tested. Both females and males were significantly attracted to stems and leaves, as well as panicles of D. ciliaris in the flowering stage. The findings suggest that T. caelestialium use host-plant volatiles as olfactory cues to find their host plants and their invasion to paddy fields were caused by olfactory responses to rice plant.
Climate change may disrupt species–species interactions via phenological changes in one or both species. To predict and evaluate the influence of climate change on these interactions, long-term monitoring and sampling over large spatial areas are required; however, funding and labor constraints limit data collection. In this study, we predict and evaluate the plant–insect interactions with limited data sets. We examined plant–insect interaction using observational data for development of the crop plant rice (Oryza sativa) and an effective accumulated temperature (EAT) model of two mirid bugs (Stenotus rubrovittatus and Trigonotylus caelestialium). We combined 11 years of records monitoring rice phenology and the predicted phenology of mirid bugs using spatially–explicit EAT models based on both spatially and temporally high resolutions temperature data sets, then evaluated their accuracy using actual pest damage records. Our results showed that the predicted interactions between rice and mirid bugs explained rice damage to some degree. Our approach may apply predicting changes to plant–insect interactions under climate change. As such, combining plant monitoring records and theoretical predictions of insect phenology may be effective for predicting species–species interactions when available data are limited.
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