Characteristic of tradeoffs between timber production and carbon storage for plantation under harvesting impact: A case study of Huitong National Research Station of Forest Ecosystem

doi:10.1007/s11442-018-1543-4

Abstract

Abstract:

The tradeoffs and optimizations of ecosystem services are the key research fields of ecology and geography. It is necessary to maximize the overall benefit of timber production and carbon storage for forest ecological development in China. We selected the Huitong National Research Station of Forest Ecosystem as our study area, and used InVEST model to evaluate timber production and carbon storage quantitatively. The results showed that: (1) While timber production increased with harvesting intensity over the planning horizon, carbon storage decreased. There were tradeoffs between timber production and carbon storage according to the significant negative relationship. (2) While the overall benefit of timber production and carbon storage increased with harvesting intensity, the value of tradeoffs decreased. T1 and T2 scenarios, with harvesting intensity of 10%-20% every 10 years, are the optimum management regimes for the two ecosystem services to gain more benefit and less tradeoffs. (3) The current harvesting intensity in Huitong County was slightly higher than the optimum harvesting intensity. On practical dimension, these findings suggested that obvious objectives are needed to formulate the corresponding countermeasures of tradeoffs, in order to realize the improvement of ecosystem services and the optimization of ecosystem structures.

Key words: timber production, carbon storage, plantation, tradeoffs analysis, Huitong eco-station

Jianjia ZHU, Erfu DAI, Du ZHENG, Xiaoli WANG. Characteristic of tradeoffs between timber production and carbon storage for plantation under harvesting impact: A case study of Huitong National Research Station of Forest Ecosystem[J].Journal of Geographical Sciences, 2018, 28(8): 1085-1098.

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Forest types	Organs	Stand growth models	Correlation coefficient and significance level	Number of trees of stand plots
Pinus massoniana	Stem	y=e^{5.666-33.687/}^x	R² = 0.994, P < 0.001	42
	Branch	y=e^{4.851-42.961/}^x	R² = 0.994, P < 0.001
	Leaf	y=e^{4.557-45.786/}^x	R² = 0.994, P < 0.001
	Bark	y=e^{3.404-33.639/}^x	R² = 0.994, P < 0.001
	Root	y=e^{4.911-39.678/}^x	R² = 0.994, P < 0.001
Michelia macclurei	Stem	y=e^{5.485-27.760/}^x	R² = 0.991, P < 0.001	37
	Branch	y=e^{4.626-26.297/}^x	R² = 0.991, P < 0.001
	Leaf	y=e^{3.191-24.898/}^x	R² = 0.991, P < 0.001
	Bark	y=e^{3.340-23.831/}^x	R² = 0.991, P < 0.001
	Root	y=e^{4.536-23.927/}^x	R² = 0.991, P < 0.001
Schima superba	Stem	y=e^{5.025-32.623/}^x	R² = 0.990, P < 0.001	37
	Branch	y=e^{4.191-30.904/}^x	R² = 0.990, P < 0.001
	Leaf	y=e^{2.632-25.874/}^x	R² = 0.991, P < 0.001
	Bark	y=e^{2.946-28.006/}^x	R² = 0.990, P < 0.001
	Root	y=e^{4.140-28.119/}^x	R² = 0.990, P < 0.001
Cunninghamia lanceolata	Stem	y=e^{5.462-22.408/}^x	R² = 0.982, P < 0.001	20
	Branch	y=e^{3.606-23.411/}^x	R² = 0.982, P < 0.001
	Leaf	y=e^{4.692-18.100/}^x	R² = 0.982, P < 0.001
	Bark	y=e^{3.248-15.805/}^x	R² = 0.982, P < 0.001
	Root	y=e^{2.459-10.460/}^x	R² = 0.975, P < 0.001
Cinnamomum camphora	Stem	y=e^{6.810-43.013/}^x	R² = 0.994, P < 0.001	24
	Branch	y=e^{5.881-40.748/}^x	R² = 0.994, P < 0.001
	Leaf	y=e^{4.450-39.484/}^x	R² = 0.991, P < 0.001
	Bark	y=e^{4.478-36.926/}^x	R² = 0.994, P < 0.001
	Root	y=e^{5.678-37.075/}^x	R² = 0.994, P < 0.001

Management regimes	Cutting area percentages/%	Rotations/year	Harvest principles
T0	0	10	small-area clear-cutting (cutting areas ≤5 hm² and interval areas between cutting areas ≥cutting area)
T1	10
T2	20
T3	30
T4	40
T5	50

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