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地理研究 >

2011 , Vol. 30 >Issue 1: 172 - 184

DOI: https://doi.org/10.11821/yj2011010017

地球信息科学

基于森林详查与遥感数据降尺度技术估算中国林龄的空间分布

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  • 1. 地表过程与资源生态国家重点实验室 (北京师范大学),北京 100875;
    2. 民政部/教育部减灾与应急管理研究院,北京 100875;
    3. 中国科学院东亚区域气候－环境重点实验室,北京 100029
戴铭(1986-),男,浙江省开化县人,研究生,主要从事遥感监测与森林生态系统碳循环研究。E-mail :daiming@mail.bnu.edu.cn

收稿日期: 2009-12-07

  修回日期: 2010-05-26

  网络出版日期: 2011-01-20

基金资助

国家自然科学基金(30970514、40671173、30590384);中国科学院东亚区域气候-环境重点实验室开放课题

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Spatial pattern of forest ages in China retrieved from national-level inventory and remote sensing imageries

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  • 1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;
    2. Academy of Disaster Reduction and Emergency Management,Ministry of Civil Affairs & Ministry of Education, Beijing 100875, China;
    3. Key Laboratory of Regional Climate -Environment Research for Temperate East Asia (RCE-TEA), CAS, Beijing 100029, China

Received date: 2009-12-07

  Revised date: 2010-05-26

  Online published: 2011-01-20

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摘要

森林的林龄结构及空间分布是评估区域尺度森林生态系统碳汇潜力的重要参数。以第五次全国森林详查获取的省级优势树种的平均林龄及分布面积为基础,以同期生长季节的NOAA/AVHRR NDVI遥感数据为辅助,在空间降尺度统计技术的支持下,得出了全国8 km分辨率下的森林林龄的定量分布。结果表明:中国林龄在空间分布具有很大异质性。东南地区的林龄较低,省平均林龄主要介于20~30年。林龄大于120年的森林主要分布在四川中部及新疆西北部地区。西藏东南部、黑龙江西北部、内蒙古东北部以及云南南部地区的林龄介于两者之间,其值大多介于70~120年。从全国范围看,森林的林龄主要介于10~80年,其面积占森林总面积的85.4%,其中林龄在20~40年之间的森林面积占35.3%。全国总的平均林龄为40.6年,标准差为26.6年,在概率分布上呈现单峰非正态分布。

关键词： 林龄; 森林详查; 降尺度; NDVI; 碳汇

本文引用格式

戴铭, 周涛, 杨玲玲, 贾根锁 . 基于森林详查与遥感数据降尺度技术估算中国林龄的空间分布[J]. 地理研究, 2011 , 30(1) : 172 -184 . DOI: 10.11821/yj2011010017

Abstract

The structure and spatial distribution of forest age are important parameters for assessing carbon sequestration potential of forest ecosystems at regional scale.In this study, we tried to estimate those parameters based on survey data of the average forest age and area of dominant tree species retrieved from detailed investigation of the fifth national forest at provincial level, along with the growing season NDVI data derived from NOAA AVHRR sensors in the same period. We then analyzed the spatial patterns of forest ages in China with remote sensing downscaling techniques. The results indicate that the spatial distribution of forest ages showed significant heterogeneity. The forest age of southeast China was lower than that of rest of the country, with average values ranging from 20 to 30 years. The forests aged over 120 years are mainly distributed in central Sichuan and northwestern Xinjiang. And the forest ages of the southeastern Tibet, northwestern Heilongjiang, northeastern Inner Mongolia and southern Yunnan are mostly between 70-120 years. From the national-level perspective, the main forest age is ranged from 10 to 80 years, with their area accounting for 85.4% of the total forest area. The area of forest aged 20-40 years accounted for 35.3% of the total forest area. The average forest age was 40.6 years in China, whose standard deviation is 26.6 years. As for the probability, Chinese forest ages showed a single peak of abnormal distribution.

Key words： forest age; national-evel inventory; downscaling; NDVI; carbon sink

参考文献

[1] Denman K L,Brasseur G,Chidthaisong A,et al. Couplings between changes in the climate system and biogeochemistry. In:Solomon S,Qin D,Manning M,et al. Climate Change 2007:The Physical Science Basis. New York:Cambridge University Press,2007. 499~587.

[2] Goodale C L,Apps M J,Birdsey R A,et al. Forest carbon sinks in the Northern Hemisphere. Ecological Appications,2002,12(3):891~899.

[3] Houghton R A,Hackler J L,Lawrence K T. The U.S. carbon budget:Contributions from land-use change. Science, 1999,285:574~578.

[4] 刘国华,傅伯杰,方精云. 中国森林碳动态及其对全球碳平衡的贡献. 生态学报,2000,20(5):733~740.

[5] Song C H,Woodcock C E. A regional forest ecosystem carbon budget modle:Impacts of forest age structure and landuse history. Ecological Modelling,2003,164(1):33~47.

[6] 王兴昌,王传宽,于贵瑞. 基于全球涡度相关的森林碳交换的时空格局. 中国科学(D辑),2008,38(9):1092~1102.

[7] Cramer W,Kicklighter D W,Bondeau A,et al. Comparing global models of terrestrial net primary productivity (NPP):Overview and key results. Global Change Biology,1999,5:1~15.

[8] Wang S Q,Chen J M,Ju W M,et al. Carbon sinks and sources in China’s forests during 1901~2001. Journal of Environmental Management,2007,85:524~537.

[9] Ni J,Zhang X S,Scurlock J M O. Synthesis and analysis of biomass and net primary productivity in Chinese forests. Annals of Forest Science,2001,58(4):351~384.

[10] Zhao M,and Zhou G S. Estimation of biomass and net primary productivity of major planted forest in China based on forest inventory data. Forest Ecology and Management,2005,207:295~313.

[11] Neeff T, Lucas R M,Santos J R D,et al. Area and age of secondary forests in Brazilian Amazonia 1978~2002: An empirical estimate. Ecosystems, 2006, 9:609~623.

[12] 王殿中,孙国清,过志峰. 天然林林龄的模拟估算及案例. 生态环境,2008,17(5):1999~2003.

[13] 张月丛,赵志强,李双成,等. 基于SPOT NDVI的华北北部地表植被覆盖变化趋势. 地理研究,2008,27(4):745~754.

[14] Kristiina A V,Robert L E,Charles C G. Biomass and nutrient concentrations of sporocarps produced by mycorrhizal and decomposer fungi in Abies amabilis Stands. Oecologia (Berl),1981,50:170~175.

[15] Piao S L,Fang J Y,Zhu B,et al. Forest biomass carbon stocks in China over the past two decades:estimation based on integrated inventory and satellite data. Journal of Geophysical Research-Biogeoscience,2005,110,G01006,doi:10.1029/2005JG000014.

[16] 李崇贵,赵宪文,李春干. 森林蓄积量遥感估测理论与实现. 北京:科学出版社,2006.

[17] 杨存建,刘纪远,黄河,等. 热带森林植被生物量与遥感地学数据之间的相关性分析.地理研究,2005,24(3):473~479.

[18] 赵芳芳,徐宗学. 统计降尺度方法和Delta方法建立黄河源区气候情景的比较分析. 气象学报,2007,65(4):653~662.

[19] Wetterhall F,Halldin S,Xu C. Statistical precipitation downscaling in central Sweden with the analogue method. Journal of Hydrology,2005,306 :174~190.

[20] Wilby R L,Hay L E,Leavesley G H. A comparison of downscaled and raw GCM output:Implications for climate change scenarios in the San Juan River basin,Colorado. Journal of Hydrology,1999,225:67~91.

[21] Kindermann G E,McCallum I, Fritz S,et al. A global forest growing stock,biomass and carbon map based on FAO statistics. Silva Fennica,2008,32(3):387~396.

[22] Tucker C J,Pinzon J E,and Brown M E. Global Inventory Modeling and Mapping Studies, NA94apr15b.n11-VIg, 2.0, Global Land Cover Facility, University of Maryland, College Park, Maryland. http://glcf.umiacs.umd.edu/data/gimms,1994-04-15, 2004.

[23] 中国科学院植物研究所. 中国植被图. 北京: 中国地图出版社,1979.

[24] Pan Y,Luo T,Birdsey R,et al. New estimates of carbon storage and sequestration in China forests:Impacts of age and method in inventory-based carbon estimation. Climate Change,2004,67:211~236.

[25] Dong J,Kaufmann R K,Myneni R B,et al. Remote sensing estimates of boreal and temperate forest woody biomass:Carbon pools,sources and sinks. Remote Sensing of Environment,2003,84:393~410.

[26] Noormets A,Chen J,Crow T R. Age-dependent changes in ecosystem carbon fluxes in managed forests in northern Wisconsin. Ecosystems,2007,10:187~203.

[27] 方精云,陈安平. 中国森林植被碳库的动态变化及其意义. 植物学报,2001,43(9):967~973.

[28] 罗天祥.中国主要森林类型生物生产力格局及其数学模型. 北京:中国科学院自然资源综合考察委员会,博士学位论文,1996.

[29] 白云庆. 人工落叶松林生物量估算. 东北林学院学报, 1982,(增刊):29~37.

[30] 李学明. 日本落叶松的生物产量测定. 四川林业科技,1984,5(1):27~29.

[31] 丁宝永,刘世荣,蔡体久. 落叶松人工林群落生物生产力的研究. 植物生态学与地植物学学报,1990,14(3):226~236.

[32] 刘世荣,柴一新,蔡体久,等. 兴安落叶松人工群落生量物与净初级生产力的研究. 东北林业大学学报,1990,18(2):40~46.

[33] Xiao Y. Comparative studies on biomass and productivity of Pinus tabulaeformis plantations in different climatic zones in Shaanxi Province. Acta Phytoecologica Et Geobotanica Sinica,1990,14(3):237~246.

[34] 彭少麟,余作岳,张文其,等. 鹤山亚热带丘陵人工林群落分析. 植物生态学与地植物学学报,1992,16(1):1~10.

[35] 江波,袁位高,朱光泉,等. 马尾松、湿地松和火炬松人工林生物量与生产结构的初步研究. 浙江林业科技,1992,12(5):1~8.

[36] 黄宇,冯宗炜,汪思龙,等. 杉木、火力楠纯林及其混交林生态系统C、N贮量. 生态学报, 2005,25(12):3146~3154.

[37] 段文霞,朱波,刘锐,等. 人工柳杉林生物量及其土壤碳动态分析. 北京林业大学学报,2007,29(2):55~59.

[38] 吴鹏飞,朱波,刘世荣,等. 不同林龄桤-柏混交林生态系统的碳储量及其分配. 应用生态学报,2008,19(7):1419~1424.
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