Global dependence of field-observed leaf area index in woody species on climate: a systematic review


  • Editor: Ian Wright



Leaf area index (LAI) is one of the key variables related to carbon, water and nutrient cycles in terrestrial ecosystems, but its global distribution patterns remain poorly understood. We evaluated the dependence of LAI on mean annual temperature (MAT) and wetness index (WI; a ratio of annual precipitation to potential evapotranspiration) for three plant functional types (PFTs: deciduous broadleaf, DB; evergreen conifer, EC; evergreen broadleaf, EB) at the global scale.




We developed a new global database of unprecedented size (2606 published values) of field-observed LAI (site-specific maximum) values for vegetation of woody species. To maximize the generic applicability of our analysis, we standardized the definition of LAI, and corrected or excluded potentially erroneous data obtained from indirect optical methods.


The global dependence of LAI on MAT showed a reverse S-shaped pattern, in which LAI peaked at around 8.9 and 25.0°C and was lowest at around −10.0 and 18.8°C. The dependence on WI followed a saturation curve levelling off at around log WI = 0.30. LAI for evergreen forests increased linearly with increasing WI, but that for DB showed a curvilinear pattern saturating at log WI = 0.03. EC forests had higher LAI values than those of DB forests under cool conditions (MAT ≤ 8.9°C), but similar values under temperate conditions (MAT = 8.9–18.8°C).

Main conclusions

This analysis of global LAI−climate relationships supports the general belief that temperature limits LAI under cool conditions whereas water availability plays a predominant role under other conditions. We also found that these patterns differed significantly between PFTs, suggesting that the LAI of different PFTs may respond differently to climate change. Our study provides a broad empirical basis for predicting the global distribution of LAI and for analysing the effects of global climate change on vegetation structure and function.