PhenoForecaster

PhenoForecaster predicts flowering times of angiosperm taxa using multivariate phenoclimatic models to provide species-specific phenological forecasts for 2320 angiosperm species.

Key Features:

• Species-specific elastic net models: Uses elastic net regression to build models tailored to individual species, enabling precise prediction of flowering dates for 2320 angiosperm species.
• Multivariate phenoclimatic modeling: Integrates multiple phenoclimatic variables into multivariate models to represent climatic drivers of flowering phenology.
• Prediction accuracy estimation: Provides numerical estimates of prediction accuracy for each forecast.

Scientific Applications:

• Plant biology and ecology: Enables analysis of flowering timing, ecological interactions, and plant phenological responses to climate change.
• Horticulture and agriculture: Supports planning of planting schedules, crop management, and breeding decisions through predicted flowering dates.
• Invasive species management: Informs predictions of invasive plant growth and spread by forecasting phenological events under changing climatic conditions.

Methodology:

Applies elastic net regression to construct species-specific multivariate phenoclimatic models and outputs per-forecast accuracy estimates.