2000—2015年中国东北森林生产力和碳素利用率的时空变异

doi:10.13287/j.1001-9332.201905.033

应用生态学报 ›› 2019, Vol. 30 ›› Issue (5): 1625-1632.doi: 10.13287/j.1001-9332.201905.033

2000—2015年中国东北森林生产力和碳素利用率的时空变异

陈智^1,2*

¹中国生态系统研究网络综合研究中心, 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京 100101;
²中国科学院大学资源与环境学院, 北京 100049

收稿日期:2019-02-19 修回日期:2019-02-19 出版日期:2019-05-15 发布日期:2019-05-15
通讯作者: E-mail: chenz@igsnrr.ac.cn
作者简介:陈智,女,1986年生,博士.主要从事生态学研究.E-mail: chenz@igsnrr.ac.cn
基金资助:
国家自然科学基金项目(31600347)、国家重点研发专项(2016YFA0600103)和中国科学院战略性先导科技专项(XDA19020302)

Spatiotemporal variation of productivity and carbon use efficiency of forests in Northeast China from 2000 to 2015.

CHEN Zhi^1,2*

¹Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
²College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-02-19 Revised:2019-02-19 Online:2019-05-15 Published:2019-05-15
Supported by:
This work was supported by the National Natural Science Foundation of China (31600347), the National Key Research and Development Program of China (2016YFA0600103) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302).

摘要/Abstract

摘要： 中国东北森林生态系统是重要的碳汇功能区,也是对环境变化响应的敏感区,分析其植被生产力和碳素利用效率的变化特征及其对气候变化的响应对于区域碳收支的准确评估和预测具有重要意义.本研究利用MODIS的长期监测数据,结合植被类型分布数据,对中国东北森林生态系统2000—2015年生产力(净初级生产力NPP、总初级生产力GPP)和碳素利用率(NPP/GPP)时空变化特征进行分析.结果表明: 研究期间,东北森林生态系统平均NPP和GPP分别为346.4和773 g C·m^-2·a^-1,平均NPP/GPP为0.45.不同森林类型的NPP和GPP依次为针阔混交林>落叶阔叶林>针叶林,NPP/GPP在不同森林类型间无显著差异.NPP和GPP呈现出东南高、西北低的空间分布特点.2000—2015年间,东北森林生态系统NPP、GPP和NPP/GPP呈波动增加趋势,固碳能力逐步增强.NPP、GPP和NPP/GPP的变化趋势和变化速率表现出空间差异性,在大兴安岭南部地区显著增加,在大兴安岭北部地区显著下降,其余区域呈微弱增加趋势.与气候因子的相关性分析表明,年降水量的增加是驱动东北森林生态系统NPP、GPP和NPP/GPP波动增加的主要因素.

Abstract: Understanding changes in vegetation productivity and carbon use efficiency and their responses to climate change is significant to accurately assess and predict regional carbon budget in Northeast forest area, a region being an important carbon sink and sensitive to global change. Based on MODIS monitoring data and vegetation type distribution data, I analyzed the spatiotemporal varia-tions of ecosystem productivity (net primary productivity (NPP), gross primary productivity (GPP)) and carbon use efficiency (NPP/GPP) of Northeast forest from 2000 to 2015. Results showed that the average NPP and GPP were 346.4 and 773 g C·m^-2·a^-1, respectively, and the average NPP/GPP was 0.45 during 2000 and 2015. NPP and GPP of different forest types were following the order: coniferous and broad-leaved mixed forests > deciduous broad-leaved forests > coniferous forests, while the difference in NPP/GPP was not significant among different forest types. NPP and GPP were high in Southeast part and low in Northwest part. From 2000 to 2015, the NPP, GPP and NPP/GPP of Northeast forest showed a fluctuating increase, suggesting the carbon sequestration capacity was gradually enhanced. However, the trends and rates of NPP, GPP and NPP/GPP showed spatial variation. NPP, GPP and NPP/GPP increased significantly in the southern part of the Daxing’anling while decreased significantly in the northern part of the Daxing’anling, and showed a weak increasing trend in the rest of Northeast forest. The increase of annual precipitation was the main factor driving the fluctuating increase of NPP, GPP and NPP/GPP in Northeast forest.

陈智. 2000—2015年中国东北森林生产力和碳素利用率的时空变异[J]. 应用生态学报, 2019, 30(5): 1625-1632.

CHEN Zhi. Spatiotemporal variation of productivity and carbon use efficiency of forests in Northeast China from 2000 to 2015.[J]. Chinese Journal of Applied Ecology, 2019, 30(5): 1625-1632.

参考文献

[1] Chapin FS Ⅲ, Matson PA, Mooney HA. Principles of Terrestrial Ecosystem Ecology. New York: Springer-Verlag, 2002
[2] Gao Y-N (高艳妮), Yu G-R (于贵瑞), Zhang L (张黎), et al. The changes of net primary productivity in Chinese terrestrial ecosystem: Based on process and parameter models. Progress in Geography (地理科学进展), 2012, 31(1): 109-117 (in Chinese)
[3] DeLucia EH, Drake JE, Thomas RB, et al. Forest carbon use efficiency: Is respiration a constant fraction of gross primary production? Global Change Biology, 2007, 13: 1157-1167
[4] Potter CS, Randerson JT, Field CB, et al. Terrestrial ecosystem production: A process model-based on global satellite and surface data. Global Biogeochemical Cycles, 1993, 7: 811-841
[5] Li Z-Q (李振泉), Shi Q-W (石庆武). Geography Pandect of Northeast Economy Region. Changchun: Northeast Normal University Press, 1998 (in Chinese)
[6] Zhao J-F (赵俊芳), Yan X-D (延晓冬), Jia G-S (贾根锁). Simulation of carbon stocks of forest ecosystems in Northeast China from 1981 to 2002. Chinese Journal of Applied Ecology (应用生态学报), 2009, 20(2): 241-249 (in Chinese)
[7] Guo Z-X (国志兴), Wang Z-M (王宗明), Zhang B (张柏), et al. Analysis of temporal-spatial characteri-stics and factors influencing vegetation NPP in Northeast China from 2000 to 2006. Resources Science (资源科学), 2008, 30(8): 1226-1235 (in Chinese)
[8] Zhao J-F (赵俊芳), Yan X-D (延晓冬), Jia G-S (贾根锁). Simulating the responses of forest net primary productivity and carbon budget to climate change in Northeast China. Acta Ecologica Sinica (生态学报), 2008, 28(1): 92-102 (in Chinese)
[9] Li M-Z (李明泽), Wang B (王斌), Fan W-Y (范文义), et al. Simulation of forest net primary production and the effects of fire disturbance in Northeast China. Chinese Journal of Plant Ecology (植物生态学报), 2015, 39(4): 322-332 (in Chinese)
[10] Yu Y (于颖). Temporal and Spatial Analysis of Northeast Forest Carbon Sources and Sinks Distribution based on InTEC Model. PhD Thesis. Harbin: Northeast Forestry University, 2013 (in Chinese)
[11] Wang P (王萍). Simulation of forest net primary productivity in Northeastern China with IBIS. Acta Ecologica Sinica (生态学报), 2009, 29(6): 3213-3220 (in Chinese)
[12] Hou X-H (侯学会), Niu Z (牛铮), Gao S (高帅). Phenology of forest vegetation in Northeast of China in ten years using remote sensing. Spectroscopy and Spectral Analysis (光谱学与光谱分析), 2014, 34(2): 515-519 (in Chinese)
[13] Zhao MS, Running SW. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science, 2010, 329: 940-943
[14] Zhang YJ, Xu M, Chen H, et al. Global pattern of NPP to GPP ratio derived from MODIS data: Effects of ecosystem type, geographical location and climate. Global Ecology and Biogeography, 2009, 18: 280-290
[15] Zhang YJ, Yu GR, Yang J, et al. Climate-driven global changes in carbon use efficiency. Global Ecology and Biogeography, 2014, 23: 144-155
[16] Heinsch FA, Zhao MS, Running SW, et al. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44: 1908-1925
[17] Zhao MS, Running SW, Nemani RR. Sensitivity of mo-derate resolution imaging spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses. Journal of Geophysical Research, 2006, 111: G01002
[18] Beer C, Reichstein M, Tomelleri E, et al. Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate. Science, 2010, 329: 834-838
[19] Chinese Academy of Sciences (中国科学院). Vegetation Atlas of China. Beijing: Science Press, 2001 (in Chinese)
[20] Wang J-B (王军邦), Wang J-W (王居午), Ye H (叶辉), et al. An interpolated temperature and precipitation dataset at 1-km grid resolution in China (2000-2012). China Scientific Data (中国科学数据), 2017, 2(1): doi: 10.11922/csdata.170.2016.0112 (in Chinese)
[21] Yu GR, Zhu XJ, Fu YL, et al. Spatial pattern and climate drivers of carbon fluxes in terrestrial ecosystems of China. Global Change Biology, 2013, 19: 798-810
[22] Wu JB, Xiao XM, Guan DX, et al. Estimation of the GPP of an old-growth temperate mixed forest using eddy covariance and remote sensing. International Journal of Remote Sensing, 2009, 30: 463-479
[23] Zhou L-Y (周丽艳), Jia B-R (贾丙瑞), Zhou G-S (周广胜), et al. Carbon exchange of Chinese boreal forest during its growth season and related regulation mechanisms. Chinese Journal of Applied Ecology (应用生态学报), 2010, 21(10): 2449-2456 (in Chinese)
[24] Piao S-L (朴世龙), Fang J-Y (方精云), Guo Q-H (郭庆华). Application of CASA model to the estimation of Chinese terrestrial net primary productivity. Acta Phytoecologica Sinica (植物生态学报), 2001, 25(5): 603-608 (in Chinese)
[25] Tao B (陶波), Li K-R (李克让), Shao X-M (邵雪梅), et al. Temporal and spatial pattern of net primary production of terrestrial ecosystems in China. Acta Geographica Sinica (地理学报), 2003, 58(3): 372-380 (in Chinese)
[26] He Y (何勇), Dong W-J (董文杰), Ji J-J (季劲均), et al. The net primary production simulation of terrestrial ecosystems in China by AVIM. Advances in Earth Science (地球科学进展), 2005, 20(3): 345-349 (in Chinese)
[27] Waring RH, Landseberg JJ, Williams M. Net primary production of forests: A constant fraction of gross primary production? Tree Physiology, 1998, 18: 129-113
[28] Ciais P, Reichstein M, Viovy N, et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature, 2005, 437: 529-533
[29] Chambers JQ, Tribuzy ES, Toledo LC, et al. Respiration from a tropical forest ecosystem: Partitioning of sources and low carbon use efficiency. Ecological Applications, 2004, 14: S72-S88
[30] Piao SL, Luyssaert S, Ciais P, et al. Forest annual carbon cost: A global-scale analysis of autotrophic respiration. Ecology, 2010, 91: 652-661
[31] Metcalfe DB, Meir P, Aragâo LEO, et al. Shifts in plant respiration and carbon use efficiency at a large-scale drought experiment in the eastern Amazon. New Phytologist, 2010, 187: 608-621
[32] Lieth H. Primary production: Terrestrial ecosystems. Human Ecology, 1973, 1: 303-332
[33] Ryan MG, Hubbard RM, Pongracic S, et al. Foliage, fine-root, woody-tissue and stand respiration in Pinus radiata in relation to nitrogen status. Tree Physiology, 1996, 16: 333-343
[34] IPCC. Climate Change 2014: Synthesis Report. Geneva: IPCC, 2014

2000—2015年中国东北森林生产力和碳素利用率的时空变异

Spatiotemporal variation of productivity and carbon use efficiency of forests in Northeast China from 2000 to 2015.

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价