| Abstract Detail
Ecology Glass, Patrick Xavier [1], Krakos, Kyra [2]. Predicting Bloom dates at Shaw Nature Reserve Using Growing Degree Day (GDD) Computer Models. The plant phenology, or bloom times, of Missouri native plants experience year to year variation due to numerous natural and human factors (J. Xia and S. Wan, 2012). Uncertainty in phenology can cause issues in studying pollination systems. Computers models are used by biologists and farmers to create phenological predictions for plants (R. Gordon & A. Bootsma, 1993). Growing Degree Days (GDD) is a method used in the agricultural and horticultural industry to map out planting, harvesting, and fertilizer application times (R. Gordon & A. Bootsma, 1993). This method uses the average temperature, as a unit of heating over time, within a threshold to define GDD models (Fig 1.). Many current GDD calculators only use average temperatures of months, which do not give exact days of bloom time. While this method is sufficient for agriculture, it does not provide the precision needed for pollination biology. This study will focus creating a more accurate model, which uses the average temperature daily, to predict the bloom times for 5 Missouri native plants at Shaw Nature reserve. Log in to add this item to your schedule
1 - Maryville University, 16874 Hickory Crest Drive, Wildwood, Missouri, 63011, United States 2 - Maryville University, Biology, 650 Maryville University, St Louis, MO, 63141, United States
Keywords: none specified
Presentation Type: Poster Session: P, Ecology Posters Location: Arizona Ballroom/Starr Pass Date: Monday, July 29th, 2019 Time: 5:30 PM This poster will be presented at 5:30 pm. The Poster Session runs from 5:30 pm to 7:00 pm. Posters with odd poster numbers are presented at 5:30 pm, and posters with even poster numbers are presented at 6:15 pm. Number: PEC015 Abstract ID:497 Candidate for Awards:None |