Impacts of climate change on the potential forest productivity based on a climate-driven biophysical model in northeaste
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ORIGINAL PAPER
Impacts of climate change on the potential forest productivity based on a climate-driven biophysical model in northeastern China Wen-Qiang Gao1 • Xiang-Dong Lei1 • Li-Yong Fu1
Received: 21 November 2018 / Accepted: 16 January 2019 The Author(s) 2019
Abstract Climate warming is expected to influence forest growth, composition and distribution. However, accurately estimating and predicting forest biomass, potential productivity or forest growth is still a challenge for forest managers dealing with land-use at the stand to regional levels. In the present study, we predicted the potential productivity (PP) of forest under current and future climate scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) in Jilin province, northeastern China by using Paterson’s Climate Vegetation and Productivity (CVP) index model. The PP was validated by comparing it with the mean and maximum net primary production calculated from light energy utilization (GLM_PEM). Our results indicated that using the CVP index model is partially valid for predicting the potential forest productivity in northeastern China. PP exhibited obvious spatial heterogeneity varying from 4.6 to 8.9 m3 ha-1 year-1 with an increasing tendency from northwest to southeast driven by the precipitation across the region. The number of vegetation-active months, precipitation and insolation coefficient were identified as the
Project funding: This work was supported by the Forestry Public Welfare Scientific Research Project (No. 201504303) and the Fundamental Research Funds for the Central Non-profit Research Institute of CAF (CAFYBB2018SY022). The online version is available at http://www.springerlink.com. Corresponding editor: Chai Ruihai. & Xiang-Dong Lei [email protected] 1
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Key Laboratory of Forest Management and Growth Modelling, State Forestry and Grassland Administration, Beijing 100091, People’s Republic of China
primary factors affecting PP, but no significant relationship was found for warmest temperature or temperature fluctuation. Under future climate scenarios, PP across the Jilin Province is expected to increase from 1.38% (RCP2.6 in 2050) to 15.30% (RCP8.5 in 2070), especially in the eastern Songnen Plain (SE) for the RCP8.5 scenarios. Keywords Climate vegetation and productivity index Potential productivity Climate change
Introduction Because forests are so important as carbon (C) sinks for mitigating climate change and provide other essential ecosystem services (Chapin et al. 2008; Coomes et al. 2014), climate warming is expected to directly influence forest structure and functions, such as productivity, by altering abiotic conditions (e.g., temperature, precipitation and atmospheric CO2 concentration) (Morin et al. 2018; Correia et al. 2018; Wang et al. 2019). This effect is especially considerable in boreal forests of China (Fang and Wang 2001; Fang et al. 2003, 2017; Gao et al. 2017) because tree establishment and growth in this kind of ecosystem will b
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