Global meta-analysis of field-observed leaf area index for woody species

Background/Question/Methods

Leaf area index (LAI) is a key in determining the exchange of energy, water vapor, and carbon dioxide between terrestrial ecosystems and the atmosphere, but the global patterns in relation to climate and plant species distribution remain poorly understood. We newly developed a global database of field-observed LAI in vegetation of woody species including 2922 published values. We standardized LAI definition as half of the total surface area and classified data according to the measuring methods (direct; D, indirect optical; IR) and plant functional type (PFT: deciduous broadleaf; DB, evergreen conifer; EC, evergreen broadleaf; EB). We could thus evaluate interrelationship between climate variables (mean annual temperature; MAT, wetness index; WI), measuring methods, PFTs and LAI on global scale. 

Results/Conclusions

 D estimates of LAI were generally higher than the IR estimates independent of climate conditions and PFTs, supporting a widely accepted notion that IR method underestimates LAI. However, our results did not support another general notion that the degree of underestimation is higher for highly clumped canopy as EC than less clumped canopy as broadleaf species. Consequently, the most common bias-correction approach, application of typical clumping index derived from standard literature, has not improved the biases observed in EC and EB. Global dependency of LAI on MAT and WI showed reverse S-shape and saturation pattern, respectively. A general hypothesis that species with longer leaf life span have higher LAI was not supported in temperate conditions (MAT = 10~20 °C). Furthermore, there was significant inter-PFT difference in WI-LAI relationship under cool-wet conditions; LAI for EC increased with WI, but those for DB were fairly constant to WI, suggesting that LAI of the individual PFTs may differently respond to global climate change. Overall, these findings provide a broad empirical basis for predicting global distribution of LAI and for analyzing effects of global climate change on vegetation structure and functioning.