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Scientia Silvae Sinicae ›› 2024, Vol. 60 ›› Issue (10): 1-11.doi: 10.11707/j.1001-7488.LYKX20220738

• Research papers •     Next Articles

Long-Term Effects of Harvest Quota on Forest Carbon Sink Intensity of Pangu Forest Farm in Great Xing’an Mountain, Northeast China

Lingbo Dong(),Xueying Lin,Zhaogang Liu*   

  1. Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education College of Forestry, Northeast Forestry University Harbin 150040
  • Received:2022-10-21 Online:2024-10-25 Published:2024-11-05
  • Contact: Zhaogang Liu E-mail:farrell0503@126.com

Abstract:

Objective: This study aims to explore the rule and mechanism of the influence of logging quotas on the intensity and duration of forest carbon sequestration at the forest farm scale, which would help to quantify the impact of different logging quotas on multi-objective forest management decisions at forest farm scale, so as to provides a theoretical basis for improving forest quality and carbon sink function. Method: A management planning model that aims to maximize the comprehensive benefits of timber production, biomass energy production and carbon sequestration was developed using simulated annealing algorithm for Pangu Forest Farm of Tahe Forestry Bureau in Greater Xing’an Mountains, in which the carbon pools of living biomass, dead wood, annually litter, wood products, logging/processing and the substitution effects of wood production and bioenergy were considered simultaneously. Then, the effects of four different logging quotas(scenario 1: 0 m3 per period ; scenario 2:19 000 m3 per period; scenario 3: 38 000 m3 per period; scenario 4: 56 000 m3 per period) on economic benefits, wood production, biomass energy production, carbon sequestration and management activities were quantified for a horizon of 100 years (10 10-year periods). Result: The total economic benefits of Pangu Forest Farm during the planning horizon was 15 416.19×104 yuan, when only the benefits of carbon sequestration were considered. With the increases of the logging quota, the total economic benefits during the planning horizon showed significant increase trends, which were approximately 19.74%、39.14% and 58.81% when compared with Scenario 1. The net carbon sequestration of each period decreased significantly with the increases of planning periods, while significant increasing trends were observed for the carbon stocks of each period. The average carbon sequestration during the entire planning horizon were about 0.16-0.24 t·hm?2a?1, and the carbon stocks at the ending of planning horizon on forestland were as large as 77.47-77.90 t·hm?2, namely approximately 48.07% increases were observed when compared that with the beginning of planning horizon. During the planning horizon, the proportion of medium-size timber increased significantly with the planning period (from 5.80% to 36.18%), while significant decreased trends on the proportion of small-size timber could be observed (from 45.74% to 16.09%), but the proportion of short- and small-size timber was always relatively stable (43.98% on average). The production of biomass energy was highly related with wood production for each scenario, and the ratios between bioenergy and wood production were 0.243 7,0.249 7 and 0.247 7, respectively, where the harvesting mainly focused on the trunk- (45.70%) and roots- (36.03%) components. The assigned average harvest area for scenarios 2?4 were 890, 1 742 and 2 385 hm2 per period, respectively. The harvested areas mainly focused on the mild-selective cutting (from 75.08% to 67.65%), but the proportion of moderate- (from 17.98% to 22.25%) and severe- (from 6.95% to 10.10%) selective cutting both increased significantly with the increases of planning periods. Conclusion: From the long perspective of viewpoint, improving the logging quota appropriately within the region of Greater Xing’an Mountains can not only increase the intensity of forest carbon sequestration, but also significantly extend the duration of carbon sequestration.

Key words: harvest quota, carbon sink intensity, timber production, bioenergy, simulated annealing algorithm

CLC Number: