Global patterns of woody residence time and its influence on model simulation of aboveground biomass. Issue 5 (13th May 2017)

• Record Type: Journal Article
• Authors: Xue, Bao‐Lin; Guo, Qinghua; Hu, Tianyu; Xiao, Jingfeng; Yang, Yuanhe; Wang, Guoqiang; Tao, Shengli; Su, Yanjun; Liu, Jin; Zhao, Xiaoqian
• Is Part Of: Global biogeochemical cycles. Volume 31:Issue 5(2017:May)
• Page Start: 821
• Page End: 835
• Publication Date: 2017-05-13
• Subjects: biomass -- woody residence time -- dynamitic global vegetation model -- global forest -- carbon cycle -- climate change; Biogeochemical cycles -- Periodicals; Electronic journals; 577.1405
• DOI: 10.1002/2016GB005557
• Languages: English
• ISSNs: 0886-6236

Abstract

Abstract: Woody residence time ( τ w ) is an important parameter that expresses the balance between mature forest recruitment/growth and mortality. Using field data collected from the literature, this study explored the global forest τ w and investigated its influence on model simulations of aboveground biomass (AGB) at a global scale. Specifically, τ w was found to be related to forest age, annual temperature, and precipitation at a global scale, but its determinants were different among various plant function types. The estimated global forest τ w based on the filed data showed large spatial heterogeneity, which plays an important role in model simulation of AGB by a dynamic global vegetation model (DGVM). The τ w could change the resulting AGB in tenfold based on a site‐level test using the Monte Carlo method. At the global level, different parameterization schemes of the Integrated Biosphere Simulator using the estimated τ w resulted in a twofold change in the AGB simulation for 2100. Our results highlight the influences of various biotic and abiotic variables on forest τ w . The estimation of τ w in our study may help improve the model simulations and reduce the parameter's uncertainty over the projection of future AGB in the current DGVM or Earth System Models. A clearer understanding of the responses of τ w to climate change and the corresponding sophisticated description of forest growth/mortality in model structure is also needed for the improvement of carbon stock prediction in future studies. Key Points: Woody residence time ( τ w, years) is related to forest age, annual temperature, and precipitation Influences of meteorological drivers on τ w are different among various plant functional types The estimated global forest τ w shows large spatial heterogeneity, and this strongly influences model simulation of AGB