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“双碳”目标下广东省西江林场森林碳汇价值评价

Value Assessment of Forest Carbon Sequestration of Xijiang Forest Farm in Guangdong Province under the Goal of "Double Carbon" Strategy

  • 摘要: 对国有林场的森林资源碳储量和价值量进行核算,有助于摸清国有林场改革前后的森林资源家底,了解森林资源状况,合理制定森林资源保护管理措施,为提升国有林场林业碳汇能力及碳达峰碳中和目标的实现提供参考。基于广东省西江林场2015—2018 年国有林场改革前后的森林资源清查数据,采用森林蓄积量扩展法核算其森林资源碳储量及其变化情况,并按照不同林种分类核算森林资源的碳储量和价值量。结果显示:①国有林场改革后,广东省西江林场的森林面积增加了420.19 hm2,森林蓄积量增加了10 100 m3,森林碳储量由603 707 t增加到 615 408 t,从起源来看,森林以人工林为主,其碳储量增加了1.74%。②从森林碳储量的价值来看,2015—2018年,广东省西江林场碳储量价值从5 705.58万元增加到6 180.26万元,增加了474.68万元,增长率为8.32%。由此可见,国有林场改革加大了森林资源保护和建设,促使林场资源结构不断优化,森林碳储量和价值量都呈增加态势。

     

    Abstract: Accounting the carbon stock and value of forest resources in state-owned forest farms helps to clarify the forest resources before and after the reform of state-owned forest farms, to understand the status of forest resources, to reasonably formulate forest resources protection and management measures, and to provide a reference for forestry carbon sink emission reduction and carbon peak and carbon neutrality goal achievement in state-owned forest farms. Using the collected forest resources inventory data before and after the reform of state-owned forest farms between 2015 and 2018, the total carbon stock of forest resources and its fluctuation in the Xijiang Forest Farm were calculated by the forest stock method. According to the classification of different forest types, the carbon stock and value of forest resources were also calculated. The results are as follows: ① After the reform of state-owned forest farms, the forest area increased by 420.19 hm2, and the forest stock increased by 10 100 m3, and the forest carbon stock increased from 603 707 to 615 408 tons. Planted forests contributed mainly to these improvements, whose carbon stock increased by 1.74%. ② The value of carbon stocks increased from 57.055 8 to 61.802 6 million yuan from 2015 to 2018, with a growth rate of 8.32%. In conclusion, the reform of state-owned forest farms improved the protection and construction of forest farms, and optimized the forest structure, and as a result, both forest carbon stock and value presented increasing patterns.

     

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