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Abstract Detail


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.

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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

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

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