Affiliation:
1. Joint Innovation Center for Modern Forestry Studies, College of Forestry, Nanjing Forestry University, Nanjing 210037, China
2. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
3. State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, Hohai University, Nanjing 210098, China
Abstract
China’s forest ecosystem plays a crucial role in carbon sequestration, serving as a cornerstone in China’s journey toward achieving carbon neutrality by 2060. Yet, previous research primarily emphasized climate change’s influence on forest carbon sequestration, neglecting tree species’ suitable area changes. This study combinates the Lund–Potsdam–Jena model (LPJ) and the maximum entropy model (MaxENT) to reveal the coupling impacts of climate and tree species’ suitable area changes on forest aboveground biomass carbon (ABC) in China. Key findings include the following: (1) China’s forests are distributed unevenly, with the northeastern (temperate coniferous broad-leaved mixed forest, TCBMF), southwestern, and southeastern regions (subtropical evergreen broad-leaved forest, SEBF) as primary hubs. Notably, forest ABC rates in TCBMF exhibited a worrisome decline, whereas those in SEBF showed an increasing trend from 1993 to 2012 based on satellite observation and LPJ simulation. (2) Under different future scenarios, the forest ABC in TCBMF is projected to decline steadily from 2015 to 2060, with the SSP5-8.5 scenario recording the greatest decline (−4.6 Mg/ha/10a). Conversely, the forest ABC in SEBF is expected to increase under all scenarios (2015–2060), peaking at 1.3 Mg/ha/10a in SSP5-8.5. (3) Changes in forest ABC are highly attributed to climate and changes in tree species’ highly suitable area. By 2060, the suitable area for Larix gmelinii in TCBMF will significantly reduce to a peak of 65.71 × 104 km2 under SSP5-8.5, while Schima superba Gardner & Champ and Camphora officinarum in SEBF will expand to peaks of 94.07 × 104 km2 and 104.22 × 104 km2, respectively. The geographic detector’s results indicated that the climate and tree species’ suitable area changes showed bi-variate and nonlinear enhanced effects on forest ABC change. These findings would offer effective strategies for achieving carbon neutrality.
Funder
Key Research and Development Program of Xinjiang Uygur Autonomous Region, China
National Natural Science Foundation of China
West Light Foundation of the Chinese Academy of Sciences
Flexible Talent Introduction Project of Xinjiang Uygur Autonomous Region
Priority Academic Program Development of Jiangsu Higher Education Institutions