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Wood density, a critical trait for both the quality and function of plant species, plays a significant role in predicting vegetation distributions and ecosystem dynamics. However, current global models typically treat wood density as a uniform constant across plant functional types, such as broadleaf trees, needle-leaf trees, and shrubs. This generalization can lead to inaccuracies when predicting how different plant types interact with their environments.

"Our research shows that this simplification in current models could introduce serious biases," explained Dr. Song. "By incorporating the variability in wood density across different plant functional types and environmental gradients, we can greatly enhance the accuracy of simulations, particularly for tree morphology and forest dynamics."

The team conducted an extensive analysis of 138,604 wood density observations from around the globe, examining how climate and soil factors influence wood density across six different functional types. Their findings reveal that for tree species, climate factors play a more dominant role than soil characteristics in determining wood density. In contrast, both climate and soil exert nearly equal influence on shrub species.

The models developed by the researchers showed strong predictive power, with correlation coefficients between observed and predicted wood density values ranging from 0.49 to 0.93 across all functional types. Notably, the predictions aligned well with actual wood density measurements across different climate conditions, underscoring the robustness of the findings.

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