植物生态学报 ›› 2017, Vol. 41 ›› Issue (9): 953-963.DOI: 10.17521/cjpe.2017.0102

• 研究论文 • 上一篇    下一篇

陕西省森林土壤固碳特征及其影响因素

李茜1,2, 王芳3, 曹扬4,5, 彭守璋4,5, 陈云明4,5,*()   

  1. 1中国科学院教育部水土保持与生态环境研究中心, 陕西杨凌 712100
    2中国科学院大学, 北京 100049
    3延安市宝塔区水务局水土保持监督管理站, 陕西延安 716009
    4西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌 712100
    5中国科学院水利部水土保持研究所, 陕西杨凌 712100
  • 收稿日期:2017-04-14 修回日期:2017-07-09 出版日期:2017-09-10 发布日期:2017-10-23
  • 通讯作者: 陈云明
  • 基金资助:
    国家自然科学基金(41371506、41201088和41601058)和国家重点研发计划项目(2016YFC0501703)

Soil carbon storage and its determinants in the forests of Shaanxi Province, China

Xi LI1,2, Fang WANG3, Yang CAO4,5, Shou-Zhang PENG4,5, Yun-Ming CHEN4,5,*()   

  1. 1Research Center of Institute of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education, Yangling, Shaanxi 712100, China

    2University of Chinese Academy of Sciences, Beijing 100049, China

    3Water and Soil Conservation Supervision and Management Station of Baota District, Yanan, Shaanxi 716009

    4State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China;

    5Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China
  • Received:2017-04-14 Revised:2017-07-09 Online:2017-09-10 Published:2017-10-23
  • Contact: Yun-Ming CHEN

摘要:

森林土壤碳库在全球碳循环中发挥着重要的作用。为明确陕西省森林土壤固碳特征及其影响因素, 基于2009年森林清查资料和2011年样地实测数据, 分析了陕西省森林土壤碳储量、碳密度及其分布特征和影响因素。结果表明: 陕西省森林土壤碳储量为579.68 Tg, 以软阔与硬阔类林土壤碳储量占比最大, 占全省森林土壤碳储量的36.35%。天然林的碳储量为467.17 Tg, 是人工林的4.15倍。各龄组中, 幼龄林和中龄林是陕西省森林土壤总碳储量的主要贡献者, 约占总碳储量的57.30%。陕西省森林土壤平均碳密度为90.68 t∙hm-2, 以桦木林最高, 为141.74 t∙hm-2。不同龄组森林的土壤碳密度以中龄林最高; 同一龄组中, 天然林的土壤碳密度高于人工林, 说明天然林的碳固存能力高于人工林。陕西省森林土壤碳储量和碳密度的地理空间分布格局不尽相同, 体现了森林覆盖面积对土壤碳储量的影响, 其中, 榆林市的森林土壤碳储量和碳密度均处于陕西省最低水平, 在此地可适当加强人工造林, 科学管理森林能显著提升区域的碳汇能力。陕西省森林土壤碳密度随经纬度和年平均气温的增加逐渐降低, 随海拔高度与年降水量的增加逐渐升高。该研究为我国省域尺度上森林土壤碳库的精确估算提供了一定的数据基础。

关键词: 森林土壤, 碳储量, 碳密度, 空间分布, 影响因素

Abstract:

Aims The bank of soil carbon of forests plays an important role in the global carbon cycle. Our aim is to understand the characteristics of soil carbon storage and its determinants in the forests in Shaanxi Province.Methods The data of forest inventory in 2009 and resampling in 2011 were used to analyze the characteristics of soil carbon storage and its determinants in the forest soil in Shaanxi Province.Important findings The soil carbon storage in the forests in Shaanxi Province was 579.68 Tg. Soil carbon storage of Softwood and Hardwood forests were the highest among all forest types, accounting for 36.35% of the whole province forest soil carbon storage. The forest soil carbon storage was 4.15 times greater in the natural forest (467.17 Tg) than that in the plantations. The young and middle-aged forests were the main contributors to the total carbon storage across all age groups, accounting for about 57.30% of the total forest soil carbon storage. The average soil carbon density of forests in Shaanxi Province was 90.68 t∙hm-2, in which the soil carbon density of Betula forests was the highest (141.74 t∙hm-2). Soil carbon density of different forest types were gradually decreased with soil depth. In addition, it was highest in middle-aged forest. Soil carbon density was higher in the natural forest ecosystems than that in the plantations within the each age group, indicating natural forest ecosystems have higher capacity of carbon sequestration. Differences in the spatial patterns between carbon storage and density indicated that carbon storage was related to forest coverage. The soil carbon density and storage of forests in Yulin were the lowest across the province. This suggests that, in order to enhance the regional carbon sequestration capacity in this region, we need to appropriately strengthen artificial afforestation activities and manage them scientifically and rationally. The soil carbon density of forests in Shaanxi Province decreased with the increase of longitude, latitude, and annual temperature, but increased with the increase of altitude and annual rainfall. This study provides data basis for provincial estimation of forest soil carbon bank in China.

Key words: forest soils, carbon storage, carbon density, spatial distribution, influencing factors