D0355 Predicting voltinism and its variation under different climate change scenario: a case study on grape berry moth at Lake Erie area

Tuesday, December 15, 2009
Hall D, First Floor (Convention Center)
Shi Chen , Department of Entomology, Pennsylvania State University, State College, PA
Shelby Fleischer , Department of Entomology, Pennsylvania State University, University Park, PA
Michael C. Saunders , Department of Entomology, Pennsylvania State University, University Park, PA
Patrick C. Tobin , Northern Research Station, USDA, Forest Service, Morgantown, WV
We use Grape Berry Moth as a model population system to explore changes in biology that may occur with climate projections for both high greenhouse gas emission scenario and low emission scenario (IPCC 4th report 2007) at Lake Erie. Previous studies have elucidated important aspects of GBM population dynamics including diapause termination, temperature dependent development, and photoperiod induced diapause initiation. Based on both historical data from 1960 and predicted downscaled climate data until 2099 under both scenarios as well as GBM biology, we ran an individual based Monte Carlo simulation for each year with a population size of 10,000 individuals. We compare mean number of annual generations,its variability in different years and emergence times for each generation. The simulation results show significant differences in adult emergence time and mean number of generations between the emission scenarios developing strongly after an approximately 20-30 year period. Following this lag under low emission scenario, GBM emergence from diapause is slightly earlier, and annual generations increase slightly from ca. 2.8 to 3.1 per year. Under high emission scenario, on the other hand, by the end of this century GBM display about 3.8 generations per year on average in northern Pennsylvania, about one more than the current 2.8 per year, which will likely cause a significant economic impact to viticulture along the shore of Lake Erie. We have also discovered another interesting phenomenon that for low emission scenario the variability of number of annual generation increases with time monotonically but for high emission scenario it reaches the maximum variability around 2060 and then declines.

doi: 10.1603/ICE.2016.42284