Experiments Are Necessary in Process-Based Tree Phenology Modelling.

Area of Science:

• Ecology
• Plant Physiology
• Climate Change Science

Background:

• Air temperature is a primary driver of spring phenological events in boreal and temperate trees, influencing physiological processes like bud burst.
• Process-based tree phenology models, often based on experimental findings, are widely used to assess climate change impacts.
• A growing trend involves developing these models using only observational phenological records from natural settings.

Purpose of the Study:

• To highlight the risks associated with developing process-based tree phenology models solely from observational data.
• To advocate for experimental designs that ensure the development of biologically realistic models for tree spring phenology.

Main Methods:

• Review of established experimental research on tree phenology and temperature response.
• Analysis of current trends in process-based phenology model development.
• Discussion of experimental design principles for robust model creation.

Main Results:

• Models derived purely from observational data may not accurately reflect underlying tree physiological processes.
• Experimental data is essential for validating and refining process-based phenology models.
• Specific experimental approaches can facilitate the development of more realistic models.

Conclusions:

• Developing process-based tree phenology models requires careful consideration of the data sources used.
• Experimental research is vital for ensuring that models accurately represent tree physiology and phenological responses.
• Future model development should prioritize integrating experimental findings with observational data for improved accuracy and predictive power in climate change assessments.