Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe-Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon-use efficiency (CUE), vegetation C turnover time (tau(veg)), leaf C fraction (F-leaf), specific leaf area (SLA), and leaf area index (LAI)-level photosynthesis (P-LAI), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901-2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 21.3%), tau(veg) (18.2 26.9%), and SLA (27.436.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.
1.East China Normal Univ, Zhejiang Tiantong Natl Forest Ecosyst Observat &, Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Sch Ecol & Environm Sci,Ctr Global Change & Ecol, Shanghai, Peoples R China 2.Inst Ecochongming, Shanghai, Peoples R China 3.McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada 4.McMaster Univ, McMaster Ctr Climate Change, Hamilton, ON, Canada 5.CALTECH, Jet Prop Lab, Pasadena, CA USA 6.No Arizona Univ, Sch Earth Sci & Environm Sustainabil, Flagstaff, AZ 86011 USA 7.Natl Inst Environm Studies, Tsukuba, Ibaraki, Japan 8.No Arizona Univ, Dept Biol Sci, Ctr Ecosyst Sci & Soc, Flagstaff, AZ 86011 USA 9.Univ Illinois, Dept Atmospher Sci, Urbana, IL USA 10.Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA 11.Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN USA 12.Carnegie Inst Sci, Dept Global Ecol, Stanford, CA USA 13.Univ Chinese Acad Sci, Dept Resources & Environm, Beijing, Peoples R China 14.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China 15.Univ Quebec Montreal, Inst Environm Sci, Dept Biol Sci, Montreal, PQ, Canada 16.Northwest A&F Univ, Ctr Ecol Forecasting & Global Change, Coll Forestry, Yangling, Shaanxi, Peoples R China 17.Peking Univ, Coll Urban & Environm Sci, Sino French Inst Earth Syst Sci, Beijing, Peoples R China 18.Montana State Univ, Dept Ecol, Bozeman, MT 59717 USA 19.Univ Colorado, Cooperat Inst Res Environm Sci, Natl Snow & Ice Data Ctr, Boulder, CO 80309 USA 20.Woods Hole Res Ctr, Falmouth, MA USA 21.Auburn Univ, Int Ctr Climate & Global Change Res, Auburn, AL 36849 USA 22.Auburn Univ, Sch Forestry & Wildlife Sci, Auburn, AL 36849 USA 23.NASA, Ames Res Ctr, Moffett Field, CA 94035 USA 24.Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA
Recommended Citation:
Cui, Erqian,Huang, Kun,Arain, Muhammad Altaf,et al. Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region[J]. GLOBAL BIOGEOCHEMICAL CYCLES,2019-01-01,33(6):668-689