Automated Data-Intensive Forecasting of Plant Phenology

First published: 2019

Brief summary

Study introducing near-term phenology forecasting for budburst, flowers, fruit and fall colours across many species.

Article

Plant phenology forecasting estimates the future timing of recurring events such as budburst, flowering, fruiting and autumn colour. These forecasts can be updated as new observations and environmental data become available.

The study developed an automated forecasting workflow designed to operate across multiple species and phenological stages. It combined observation records with statistical models and repeatedly evaluated predictions against subsequent data.

Forecast performance varied among species, events and locations. Accuracy was influenced by the amount and distribution of available observations, the environmental variables used and differences in biological response.

An automated framework allows forecasts to be produced and assessed consistently across many datasets. This approach supports repeated model updating and comparison as phenological monitoring networks accumulate additional observations.

Source details and credits

• Source / publisher: Ecological Applications
• Source type: Research article
• URL type: WWW
• Credits: Ecological Applications
• URL: https://esajournals.onlinelibrary.wiley.com/doi/10.1002/eap.2025