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Abstract Detail


Taylor, Shawn [1], White, Ethan P. [2].

Can we forecast phenology like the weather? Implementing a near-term plant phenology forecast system.

As an integral part of ecological systems phenology has impacts on activities from management to tourism and agriculture. Thus, there are many use cases for forecasts of when phenological events will occur. However, despite the large availability of phenology data, and numerous phenology models, there has been no automated species-level forecasts of plant phenology. This is largely due to the challenges of building a system that integrates large volumes of climate data, applies phenology models, and consistently disseminates the results of these forecasts in interpretable ways. Combining data from the USA National Phenology Network and NOAA we implemented a new near-term phenology forecasting system that makes predictions for the timing of budburst, flowers, ripe fruit, and fall colors for 77 species across the United States ( The forecasts are made up to 6 months in advance and automatically updated every four days. They provide users with a predicted day, along with a confidence interval, for given phenology event across a species range. Preliminary evaluation of 2019 forecasts, as of early April 2019, show error rates of 2 - 60 days, depending on the species and when a forecast was issued. Using open source data and tools this system provides a useable proof of concept for near-term plant phenology forecasts.

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Related Links:
Phenology Forecast Site

1 - University of Florida, School of Natural Resources and Environment, 103 Black Hall , Gainesville, FL, 32611, United States
2 - University of Florida, 110 Newins-Ziegler Hall, Gainesville, FL, 32611, United States


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: PEC021
Abstract ID:778
Candidate for Awards:Ecological Section Best Graduate Student Poster


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