CAJ | 학술논문

森林生态系统是地球陆地生物圈的主体,也是陆地表面最大的碳库,在全球碳循环研究中扮演着重要角色,它通过同化作用吸收固定大气中的CO_2,抑制其浓度上升的功能对于应对气候变化问题具有积极的现实意义.准确地估算森林生态系统的碳汇储量,不仅有利于解释全球碳收支不平衡的问题,也有利于促进林业碳汇交易的快速发展.但是目前的估算方法在具有一定适用性的同时也都存在着各自的不足.评述了目前国内外应用最为广泛的样地清查法、涡度相关法及应用遥感技术的模型模拟法三种森林碳汇估算方法的发展历史和应用现状,并分析了各方法的优点与局限性.最后指出:应根据实际情况选择适合的单一方法或几种方法的结合来估算森林碳汇,以便提高估算精度;应加强森林生态系统内部联系及数据时空转换、插补的研究,并充分发挥各方法的优势,采取多种方法相结合的方式完善连续观测系统和区域监测网络的建设,降低估算方法中的不确定性,为大尺度估算提供合理的参数和数据分析基础.
삼림생태계통시지구륙지생물권적주체,야시륙지표면최대적탄고,재전구탄순배연구중분연착중요각색,타통과동화작용흡수고정대기중적CO_2,억제기농도상승적공능대우응대기후변화문제구유적겁적현실의의.준학지고산삼림생태계통적탄회저량,불부유리우해석전구탄수지불평형적문제,야유리우촉진임업탄회교역적쾌속발전.단시목전적고산방법재구유일정괄용성적동시야도존재착각자적불족.평술료목전국내외응용최위엄범적양지청사법、와도상관법급응용요감기술적모형모의법삼충삼림탄회고산방법적발전역사화응용현상,병분석료각방법적우점여국한성.최후지출:응근거실제정황선택괄합적단일방법혹궤충방법적결합래고산삼림탄회,이편제고고산정도;응가강삼림생태계통내부련계급수거시공전환、삽보적연구,병충분발휘각방법적우세,채취다충방법상결합적방식완선련속관측계통화구역감측망락적건설,강저고산방법중적불학정성,위대척도고산제공합리적삼수화수거분석기출.
Forest ecosystem, as the main body of the Earth's terrestrial biosphere and the largest terrestrial carbon pool, plays an important role in fixing atmospheric CO_2 and mitigating climate change. Accurate estimation of the forest ecosystem carbon sequestration, is conducive not only to the explanation of global carbon budget imbalance, but also to the development of forest carbon sequestration trading. Although the current estimation method can be used under the certain conditions, they also have some flaws. This paper summarized three main estimation methods of forest sequestration: inventories, eddy covariance and application of re-mote sensing modeling, with their advantages and shortages. A suitable single method or a combination of several methods can be selected for forest sequestration estimation according to the actual situation. The internal relations and data temporal-spatial scaling conversion, interpolation of the forest ecosystem, and comprehensive application of several methods should be further studied to consummate a long-term continuous observation system and regional monitoring network construction. These studies will improve estimation accuracy, reduce the uncertainties and provide reasonable parameters and data analysis for large-scale estimation.