Evaluation of the Community Land Model-Simulated Specific Leaf Area with Observations over China: Impacts on Modeled Gross Primary Productivity

Abstract

Specific leaf area (SLA) is a key leaf functional trait associated with the ability to acquire light. Substantial variations in SLA have not been well described in the community land model (CLM) and similar terrestrial biosphere models. How these SLA variations influence the simulation of gross primary productivity (GPP) remains unclear. Here, we evaluated the mismatch in SLA between the CLM4.5 and observed data collected from China and quantified the impacts of SLA variation calculated from both observations and the default values across seven terrestrial biosphere models on modeled GPP using CLM4.5. The results showed that CLM4.5 tended to overestimate SLA values at the top and gradient of the canopy. The higher default SLA values could cause an underestimation of the modeled GPP by 5–161 g C m−2 yr−1 (1%–7%) for temperate needleleaf evergreen tree (NET), temperate broadleaf deciduous tree (BDT), and C3 grass and an overestimation by 50 g C m−2 yr−1 (2%) for temperate broadleaf evergreen tree (BET). Moreover, the observed SLA variation among species ranged from 21% to 59% for 14 plant functional types (PFTs), which was similar to the variation in default SLA values across models (9%–60%). These SLA variations would lead to greater changes in modeled GPP by 7%–19% for temperate NET and temperate BET than temperate BDT and C3 grass (2%–9%). Our study suggested that the interspecific variation in SLA and its responses to environmental factors should be involved in terrestrial biosphere models; otherwise, it would cause substantial bias in the prediction of ecosystem productivity.