@conference {JRN55250,
	title = {The pipeline of phenological data in large scale automated forecasts},
	booktitle = {Ecological Society of America},
	year = {2020},
	month = {08/2020},
	address = {Virtual Conference},
	abstract = {I built a near-term phenology-forecasting system which predicts the timing of budburst, flowers, ripe fruit, and fall colors for 78 species up to 6 months in advance and is updated every four days. Here I describe the flow of phenological data from raw observations to model output and presentation, addressing the challenges of continuous large data integration. Using open source tools and formats allows for robust workflows and pipelines, where adding new species, tracking model progression, and integrating the newest data is streamlined. Outlining these best practices will allow for the rapid development of robust forecasting tools in ecology. Poster $\#$82199},
	author = {Shawn D. Taylor}
}
