Coarse Woody Debris Decomposition Assessment Tool: Model validation and application.

Area of Science:

• Forest Ecology
• Biogeochemistry
• Computational Modeling

Background:

• Coarse woody debris (CWD) is a crucial component of forest biomass and plays a vital role in carbon and nutrient cycling.
• Predicting CWD decomposition is essential for understanding forest ecosystem dynamics under changing environmental conditions.

Purpose of the Study:

• To develop and validate a process-based model, CWDDAT (Coarse Woody Debris Decomposition Assessment Tool), for predicting CWD decomposition.
• To assess the model's accuracy using data from the FACE Wood Decomposition Experiment and evaluate its applicability for large-scale assessments.

Main Methods:

• Calibration and validation of the CWDDAT model using data from nine Experimental Forests across the continental USA.
• Utilizing data from the FACE (Free Air Carbon Dioxide Enrichment) Wood Decomposition Experiment with pine, aspen, and birch.
• Evaluating model predictions against measured log mass loss over a 6-year period.

Main Results:

• The CWDDAT model demonstrated high accuracy in predicting CWD decomposition, with R2 values of 0.80 for calibration and 0.82 for validation (P<0.01).
• The model accurately simulated CWD decomposition in a subtropical setting (Santee Experimental Forest) and predicted an average dissolved organic carbon (DOC) input of 1.01 g C m-2 y-1.
• Fungi (72.0%) and termites (24.5%) were identified as the primary agents of CWD mass loss.

Conclusions:

• The CWDDAT model is a reliable tool for accurately predicting CWD decomposition across diverse forest types and conditions.
• The model's findings highlight the significant role of CWD in forest carbon dynamics and nutrient cycling.
• CWDDAT is applicable for both large-scale assessments of CWD dynamics and fine-scale analyses of carbon fate in forest ecosystems.