Improved Modeling of Vegetation Phenology Using Soil Enthalpy

Area of Science:

• Ecology
• Earth System Science
• Environmental Modeling

Background:

• Traditional vegetation phenology models often overlook soil characteristics and water availability, limiting accuracy in water-limited regions.
• Existing models primarily rely on temperature, failing to capture complex environmental interactions influencing plant life cycles.

Purpose of the Study:

• To develop and validate a novel phenological modeling approach using soil enthalpy, integrating soil moisture, temperature, and texture.
• To assess the performance of the soil enthalpy-based model against traditional temperature-based models across the Northern Hemisphere.
• To project future vegetation phenology shifts under climate change scenarios using the new modeling approach.

Main Methods:

• Utilized a comprehensive dataset including FLUXNET observations, solar-induced fluorescence (SIF), and meteorological data from 2001-2020.
• Analyzed temporal trends of soil enthalpy and their correlation with leaf onset date (LOD) and leaf senescence date (LSD).
• Developed and validated a soil enthalpy-based phenological model, comparing its accuracy with a temperature-only model.

Main Results:

• Soil enthalpy exhibited significant temporal trends correlating with vegetation phenological shifts (LOD and LSD).
• The soil enthalpy-based model improved LSD simulation accuracy by over 15% and LOD projections by over 12% in shrub and grassland ecosystems.
• Future climate projections (CMIP6) indicated potential overestimation of growing season length by temperature-only models.

Conclusions:

• Soil enthalpy is a valuable metric for improving vegetation phenological modeling, especially in water-limited environments.
• Incorporating soil moisture and texture alongside temperature is essential for accurate phenological predictions.
• This study provides a more robust framework for understanding and predicting vegetation phenology under global climate change.