浙江省竹林地上碳储量的时空动态模拟及影响因素

doi:10.13287/j.1001-9332.201905.035

应用生态学报 ›› 2019, Vol. 30 ›› Issue (5): 1743-1753.doi: 10.13287/j.1001-9332.201905.035

浙江省竹林地上碳储量的时空动态模拟及影响因素

刘腾艳, 毛方杰^*, 李雪建, 邢璐琪, 董落凡, 郑钧泷, 张梦, 杜华强

亚热带森林培育国家重点实验室/浙江省森林生态系统碳循环与固碳减排重点实验室/浙江农林大学环境与资源学院, 杭州 311300

收稿日期:2018-10-26 修回日期:2018-10-26 出版日期:2019-05-15 发布日期:2019-05-15
通讯作者: E-mail: mfangjie@gmail.com
作者简介:刘腾艳,女,1992年生,硕士研究生.主要从事森林资源遥感监测与信息技术研究.E-mail: 706695603@qq.com
基金资助:
浙江省与中国林业科学研究院省院合作林业科技项目(2017SY04)、国家自然科学基金项目(31670644)、亚热带森林培育国家重点实验室项目(ZY20180201)、浙江省竹资源与高效利用协同创新中心(S2017011)和浙江农林大学科研发展基金人才启动项目(2034020075)

Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China.

LIU Teng-yan, MAO Fang-jie^*, LI Xue-jian, XING Lu-qi, DONG Luo-fan, ZHENG Jun-long, ZHANG Meng, DU Hua-qiang

State Key Laboratory of Subtropical Silviculture/Zhejiang Province Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration/School of Environmental and Resources Science, Zhejiang A＆F University, Hangzhou 311300, China

Received:2018-10-26 Revised:2018-10-26 Online:2019-05-15 Published:2019-05-15
Supported by:
The work was supported by the Joint Forestry Research Fund of Forestry Department of Zhejiang Province and Chinese Academy of Forestry (2017SY04), the National Natural Science Foundation of China (31670644), the State Key Laboratory of Subtropical Silviculture (ZY20180201), the Zhejiang Provincial Collaborative Innovation Center for Bamboo Resources and High-efficiency Utilization (S2017011) and the Startup Scientific Research Fund for Scholars of Zhejiang A & F University (2034020075).

摘要/Abstract

摘要： 竹林具有高效的固碳能力,在应对全球气候变化中扮演重要角色.然而,目前大尺度竹林碳储量估算误差大,导致竹林碳储量时空格局存在较大的不确定性.本研究以浙江省为例,耦合遥感数据和BIOME-BGC生态系统过程模型模拟1984—2014年浙江省竹林地上碳储量,并利用森林资源清查数据进行精度验证,分析浙江省竹林地上碳储量时空格局以及环境因子对竹林地上碳储量的影响.结果表明: 模拟得到的竹林地上碳储量精度较高,平均相关系数(r)、均方根误差(RMSE)和相对偏差(rBIAS)分别达到了0.75、7.24 Mg C·hm^-2和-2.57 Mg C·hm^-2,全省竹林地上碳储量总体呈上升趋势,碳密度在13.10～17.14 Mg C·hm^-2,总碳储量在9.94～17.19 Tg C,其中,竹林地上碳储量高值区域主要分布在安吉、临安、龙游等竹产业发达地区.竹林地上碳储量的变化与温度、降水、辐射、CO₂浓度、大气N沉降5个环境因子显著相关,降水量和温度与碳储量的偏相关系数较大.

关键词: 竹林, 地上碳储量, 时空模拟, 环境因子, BIOME-BGC模型

Abstract: Bamboo forests have an efficient carbon sequestration capacity and play an important role in responding to global climate change. However, the current estimation of bamboo carbon storage has some errors, leading to uncertainty in the spatiotemporal pattern of bamboo forest carbon storage. This study simulated aboveground carbon storage of Zhejiang Province, China, during 1984-2014 based on the combination of an improved BIOME-BGC (biogeochemical cycles) model and remote sensing data, with the accuracy being verified with forest resource inventory data. The spatio-temporal distribution and environmental factors of aboveground carbon storage were analyzed. The results showed that the simulated carbon storage was accurate, with average correlation coefficient (r), root mean square error (RMSE) and relative bias (rBIAS) being 0.75, 7.24 Mg C·hm^-2 and -2.57 Mg C·hm^-2, respectively. Generally, the aboveground carbon storage of bamboo forests in the whole province tended to increase from 1984 to 2014, the range of aboveground carbon density was 13.10-17.14 Mg C·hm^-2, and that of the total aboveground carbon storage was between 9.94-17.19 Tg C. The high aboveground carbon storage of bamboo was mainly distributed in developed bamboo industry areas, such as Anji, Lin’an, and Longyou. The change of aboveground carbon storage in bamboo forest was significantly correlated with temperature, precipitation, radiation, CO₂ concentration and nitrogen deposition, with higher partial correlation coefficients between precipitation and temperature and carbon storage.

Key words: BIOME-BGC model, aboveground carbon storage, spatiotemporal simulation, environmental factor., bamboo forest

刘腾艳, 毛方杰, 李雪建, 邢璐琪, 董落凡, 郑钧泷, 张梦, 杜华强. 浙江省竹林地上碳储量的时空动态模拟及影响因素[J]. 应用生态学报, 2019, 30(5): 1743-1753.

LIU Teng-yan, MAO Fang-jie, LI Xue-jian, XING Lu-qi, DONG Luo-fan, ZHENG Jun-long, ZHANG Meng, DU Hua-qiang. Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China.[J]. Chinese Journal of Applied Ecology, 2019, 30(5): 1743-1753.

参考文献

[1] Fang JY, Guo ZD, Hu HF, et al. Forest biomass carbon sinks in East Asia, with special reference to the relative contributions of forest expansion and forest growth. Global Change Biology, 2014, 20: 2019-2030
[2] Bonan GB. Forests and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 2008, 320: 1444-1449
[3] Mitchard ETA. The tropical forest carbon cycle and climate change. Nature, 2018, 559: 527-534
[4] Brown S. Measuring carbon in forests: Current status and future challenges. Environmental Pollution, 2002, 116: 363-372
[5] Yu G-R (于贵瑞). Global Change, Carbon Cycle and Storage in Terrestrial Ecosystems. Beijing: China Meteorological Press, 2003 (in Chinese)
[6] Mao F-J (毛方杰). Construction and Application of Spatiotemporal Carbon Cycle Model of Moso Bamboo Forest Ecosystem. Master Thesis. Lin’an: Zhejiang A & F University, 2016 (in Chinese)
[7] Mickler RA, Earnhardt TS , Moore JA. Regional estimation of current and future forest biomass. Environmental Pollution, 2002, 116: S7-S16
[8] Chave J, Condit R, Lao S, et al. Spatial and temporal variation of biomass in a tropical forest: Results from a large census plot in panama. Journal of Ecology, 2010, 91: 240-252
[9] Yang H-X (杨洪晓), Wu B (吴波), Zhang J-T (张金屯), et al. Progressof research into carbon fixation and storage of forest ecosystems. Journal of Beijing Normal University (Natural Science) (北京师范大学学报:自然科学版), 2005, 41(2): 172-177 (in Chinese)
[10] Steven W, Running E, Raymond H. Generalization of a forest ecosystem process model for other Biomes, BIOME-BGC, and an application for global-scale models// Running E, Raymond H, eds. Scaling Physiological Processes. New York: Elsevier, 1993: 141-158
[11] He L-H (何丽鸿), Wang H-Y (王海燕), Lei X-D (雷相东). Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model. Chinese Journal of Applied Ecology (应用生态学报), 2016, 27(2): 412-420 (in Chinese)
[12] Liu W-W (刘魏魏), Wang X-K (王效科), Lu F (逯非), et al. Regional and global estimates of carbon stocks and carbon sequestration capacity in forest ecosystems: A review. Chinese Journal of Applied Ecology (应用生态学报), 2015, 26(9): 2881-2890 (in Chinese)
[13] Mao FJ, Li XJ, Du HQ, et al. Comparison of two data assimilation methods for improving MODIS LAI time series for bamboo forests. Remote Sensing, 2017, 9: 401
[14] Du HQ, Mao FJ, Zhou GM, et al. Estimating and analyzing the spatiotemporal pattern of aboveground carbon in bamboo forest by combining remote sensing data and improved BIOME-BGC model. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2018, 99: 1-14
[15] Li PH, Zhou GM, Du HQ, et al. Current and potential carbon stocks in moso bamboo forests in China. Journal of Environmental Management, 2015, 156: 89-96
[16] Zhou GM, Meng CF, Jiang PK, et al. Review of carbon fixation in bamboo forests in China. Botanical Review, 2011, 77: 262
[17] Han N, Du HQ, Zhou GM, et al. Spatiotemporal heterogeneity of moso bamboo aboveground carbon storage with Landsat thematic mapper images: A case study from Anji county, China. International Journal of Remote Sensing, 2013, 34: 4917-4932
[18] Mao FJ, Li PH, Zhou GM, et al. Development of the BIOME-BGC model for the simulation of managed moso bamboo forest ecosystems. Journal of Environmental Management, 2016, 172: 29-39
[19] Mao FJ, Du HQ, Zhou GM, et al. Coupled LAI assimilation and BEPS model for analyzing the spatiotemporal pattern and heterogeneity of carbon fluxes of the bamboo forest in Zhejiang province, China. Agricultural Forest Meteorology, 2017, 242: 96-108
[20] Li XJ, Du HQ, Mao FJ, et al. Estimating bamboo forest aboveground biomass using EnKF-assimilated MODIS LAI spatiotemporal data and machine learning algorithms. Agricultural and Forest Meteorology, 2018, 256-257: 445-457
[21] Forestry Department of Zhejiang Province (浙江省林业厅). Announcement of value of forest rescources and ecological functions of Zhejiang Province in 2016. Zhejiang Daily (浙江日报), 2017-03-10 (in Chinese)
[22] Zhou G-M (周国模). Carbon Storage, Fixation and Distribution in Mao Bamboo (Phyllostachys pubescens) Stands Ecosystem. PhD Thesis. Hangzhou: Zhejiang University, 2006 (in Chinese)
[23] Zhou G-M (周国模), Jiang P-K (姜培坤). Density, storage, and spatial distribution of carbon in phyllostachy pubescens forest. Scientia Silvae Sinicae (林业科学), 2004, 40(6): 20-24 (in Chinese)
[24] White MA, Thornton PE, Running SW, et al. Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: Net primary production controls. Earth Interactions, 2000, 4: 1-85
[25] Wu Y-L (吴玉莲), Wang X-P (王襄平), Li Q-Y (李巧燕), et al. Response of broad-leaved Korean pine forest productivity of Mt. Changbai to climate change: An analysis based on BIOME-BGC modeling. Acta Scientiarum Naturalium Universitatis Pekinensis (北京大学学报:自然科学版), 2014, 50(3): 577-586 (in Chinese)
[26] Hidy D, Barcza Z, Marjanovi H, et al. Terrestrial ecosystem process model Biome-BGC MuSo: Summary of improvements and new modeling possibilities. Geoscientific Model Development, 2017, 10: 1-60
[27] Mao FJ, Zhou GM, Li PH, et al. Optimizing selective cutting strategies for maximum carbon stocks and yield of moso bamboo forest using BIOME-BGC model. Journal of Environmental Management, 2017, 191: 126-135
[28] Chen X-F (陈雪峰), Tang X-P (唐小平), Weng G-Q (翁国庆). Some thoughts on the inventory for planning and design of forest rescources under the new situation-suggestion on revision of technical regulations for forest rescources planning and design. Forestry Resource Management (林业资源管理), 2004(1): 9-14 (in Chinese)
[29] Shen X-C (沈雪初). Supplementary analysis of forest resources planning and design survey: Utilization of a county (city) level “continuous inventory of forest resources” sample site. East China Forest Management (华东森林经理), 1997(4): 1-5 (in Chinese)
[30] Li YG, Han N, Li XJ, et al. Spatiotemporal estimation of bamboo forest aboveground carbon storage based on Landsat data in Zhejiang, China. Remote Sensing, 2018, 10: 898
[31] Shang ZZ, Zhou GM, Du HQ, et al. Moso bamboo forest extraction and aboveground carbon storage estimation based on multi-source remotely sensed images. International Journal of Remote Sensing, 2013, 34: 5351-5368
[32] Cao B, Gruber S, Zhang TJ. REDCAPP (v1.0): Parameterizing valley inversions in air temperature data downscaled from reanalyses. Geoscientific Model Development, 2017, 10: 2905-2923
[33] Dentener FJ. Global Maps of Atmospheric Nitrogen Deposition, 1860, 1993, and 2050. Oak Ridge, TN, USA: ORNL DAAC, 2006
[34] Lu E (卢伟), Fan W-Y (范文义), Tian T (田甜). Parameter optimization of BEPS model based on the flux data of the temperate deciduous broad-leaved forest in northeast China. Chinese Journal of Applied Ecology (应用生态学报), 2016, 27(5): 1353-1358 (in Chinese)
[35] Xiao F-M (肖复明). A Study on the Characteristics of Carbon Balance on Phyllostachys edulis Plantation Ecosystem. PhD Thesis. Beijing: Chinese Aeademy of Forestry, 2007 (in Chinese)
[36] Liu ZJ , Fei BH , Yu Y, et al A comparative study of thermal properties of Sinocalamus affinis and moso bamboo. Journal of Thermal Analysis & Calorimetry, 2013, 111: 393-399
[37] Fan Y-Q (范叶青), Zhou G-M (周国模), Shi Y-J (施拥军), et al. Relationship of slope aspect and position on biomass and carbon storage in a Phyllostachys edulis stand. Journal of Zhejiang A ＆ F University (浙江农林大学学报), 2012, 29(3): 321-327 (in Chinese)
[38] Liu G-L (刘广路), Fan S-H (范少辉), Su W-H (苏文会), et al. Distribution charcateristics and coupling relationship of organic carbon and total nitrogen in Phyllostachys pubescens forest switch different operations and management modes. Journal of Soil and Water Conservation (水土保持学报), 2010, 24(5): 218-222 (in Chinese)
[39] Thornton P. Biome BGC Version 4.2: Theoretical Framework of Biome-BGC. Missoula, MT, USA: Numerical Terradynamic Simulation Group, 2010
[40] Ji B-Y (季碧勇), Tao J-X (陶吉兴), Zhang G-J (张国江), et al. Zhejiang Province’s forest vegetation biomass assessment for guaranteed accuracy. Journal of Zhejiang A＆F University (浙江农林大学学报), 2012, 29(3): 328-334 (in Chinese)
[41] Liu E-B (刘恩斌), Shi Y-J (施拥军), Li Y-F (李永夫), et al. Carbon sequestration potential of moso bamboo forest in Zhejiang Province based on the non-spatial structure. Scientia Silvae Sinicae (林业科学), 2012, 48(11): 9-14 (in Chinese)
[42] Zhang H-X (张厚喜), Zhuang S-Y (庄舜尧), Ji H-B (季海宝), et al. Estimating carbon storage of moso bamboo forest ecosystem in southern China. Soils (土壤), 2014, 46(3): 413-418 (in Chinese)
[43] Sun S-B (孙少波). Retrieval of Canopy Parameters and Estimation of Aboveground Carbon Storage for Typical Types of Subtropical Forest Using Remote Sensing Data. PhD Thesis. Lin’an: Zhejiang A & F University, 2016 (in Chinese)
[44] Xu X-J (徐小军). Study on Estimation of Aboveground Carbon Storage of Moso Bamboo Forest Based on LANDSAT TM Image. Master Thesis. Lin’an: Zhejiang Forestry University, 2009 (in Chinese)
[45] Du HQ, Zhou GM, Fan WY, et al. Spatial heterogeneity and carbon contribution of aboveground biomass of moso bamboo by using geostatistical theory. Plant Ecology, 2010, 207: 131-139
[46] Ji H-B (季海宝), Zhuang S-Y (庄舜尧), Zhang H-X (张厚喜), et al. Zonality variation of carbon storage in Phyllostachy edulis plantation ecosystems in China. Ecology and Environmental Sciences (生态环境学报), 2013, 22(1): 1-5 (in Chinese)
[47] Gao G-L (高国龙). Object-based Estimation Method of Multi-scale Bamboo Forest Carbon Storage Using Remote Sensing Imagery with High Spatial Reslution. Master Thesis. Lin’an: Zhejiang A ＆ F University, 2016 (in Chinese)
[48] Fan Y-Q (范叶青). An Analysis on the Differences of Carbon Storage of Phyllostachys edulis Ecosystem under the Terrain Conditions and Management Intensity. Master Thesis. Lin’an: Zhejiang A & F University, 2012 (in Chinese)
[49] Hu J-Q (胡俊靖), Chen W-J (陈卫军), Guo Z-W (郭子武), et al. Review of the water stress on the physiological characteristics of bamboo. Journal of Southwest forestry University (西南林业大学学报), 2015, 35(1): 91-95 (in Chinese)
[50] Xiao L-P (肖立平). Research on planting technology of abound production for pubescens. Journal of Bamboo Reaearch (竹子研究汇刊), 2002, 21(2): 36-40 (in Chinese)
[51] Gu D-X (顾大形), Chen S-L (陈双林), Zheng W-M (郑炜曼), et al. Review of the ecologicol adaptability of bamboo. Journal of Bamboo Research (竹子研究汇刊), 2010, 29(1): 17-23 (in Chinese)
[52] Xu X-J (徐小军), Zhou G-M (周国模), Du H-Q (杜华强), et al. Interannual variabilty of moso bamboo forest GPP and its driving factors: A case study of Anji county. Acta Ecologica Sinica (生态学报), 2016, 36(6): 1636-1644 (in Chinese)
[53] Li Y (李应), Chen S-L (陈双林), Li Y-C (李迎春), et al. Review reaearch review in the effects of climate factors on bamboo growth. Journal of Bamboo Reaearch (竹子研究汇刊), 2011, 30(3): 9-12 (in Chinese)
[54] Tu L-H (涂利华), Hu T-X (胡庭兴), Zhang J (张健), et al. Effects of simulated nitrogen deposition on the fine root characteristics and soil respiration in a Pleioblastus amarus plantation in rainy area of west China. Chinese Journal of Applied Ecology (应用生态学报), 2010, 21(10): 2472-2478 (in Chinese)
[55] Xu J-Q (徐家琦), Tan Z-C (谈成忠). Preliminary study on the relationship between climate factors and bamboo yield. Anhui Forestry Science and Technology (安徽林业科技), 1992(4): 13-16 (in Chinese)

浙江省竹林地上碳储量的时空动态模拟及影响因素

Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China.

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