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Chinese Journal of Ecology ›› 2024, Vol. 43 ›› Issue (6): 1521-1530.doi: 10.13292/j.1000-4890.202406.048

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Productivity and carbon budget dynamics of forests under different topographic conditions on Tibetan Plateau.

DOU Jiahui1,2, LIANG Yu2,3*, HUAI Baojuan1, WU Miaomiao2, LIU Bo2, MA Tianxiao2, WANG Yao2,4   

  1. (1College of Geography and Environment, Shandong Normal University, Jinan 250358, China; 2CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Shenyang 110016, China; 3Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China; 4University of Chinese Academy of Sciences, Beijing 100049, China).

  • Online:2024-06-10 Published:2024-06-12

Abstract: Topography is a main environmental factor affecting the spatial distribution of productivity and carbon budget of forests. Tibetan Plateau is an ideal place to study the effects of topography on the pattern of forest carbon budget due to its complex topography and abundant forest types. However, due to the difficulty of field investigation in the Tibetan Plateau forest area, there is a lack of comprehensive understanding of the impacts of topographic factors on forest carbon budget dynamics on Tibetan Plateau. Therefore, this study aimed to simulate the spatiotemporal variations of forest carbon budget on the Tibetan Plateau and analyze the differences of forest productivity and carbon budget dynamics under different topographic conditions. The temporal and spatial dynamics of gross primary productivity (GPP), above-ground biomass (AGB), and net ecosystem exchange (NEE) in middle-high altitude forests were simulated by using process-based model (FORMIND) under different topographic conditions, and the model applicability in the study area and the accuracy of the simulation results were verified. We analyzed current (2000-2014) and future (2015-2040) productivity and carbon budget. Furthermore, we quantified the relative importance of topographic factors on GPP, AGB, and NEE using XGBoost machine learning algorithm. The results showed that  GPP (6.73±0.53 t C·hm-2·a-1), AGB (167.23±17.45 t·hm-2), and NEE (0.32±0.12 t C·hm-2·a-1) simulated by FORMIND model were basically consistent with the data of plot survey and remote sensing observation, which verified the accuracy of the simulation results. In the future (2014-2040), there is an obvious increase in AGB, a slight increase in GPP, and a decreased but positive value in NEE, which indicated that forests would be carbon sinks. AGB and GPP were negatively correlated with elevation. AGB and NEE were weakly positively correlated with slope. The  GPP, AGB, and NEE of forests on sunny slope were higher than those on shady slope. Compared with slope and aspect, elevation had a greater effect on productivity and carbon budget dynamics of forests on the Tibetan Plateau. Our results are helpful to further understand the spatial distribution of forest productivity and carbon budget on the Tibetan Plateau.


Key words: forest carbon budget, gross primary productivity, above-ground biomass, net ecosystem exchange, topographical factor, Tibetan Plateau forest