新疆绿洲生态系统固碳潜力研究

doi:10.13866/j.azr.2024.06.09

Abstract

Abstract:

Net Primary Productivity (NPP) is an essential indicator of the terrestrial carbon (C) cycle, which can reflect the carbon sink capacity of terrestrial ecosystems. In the face of China’s “double carbon” goal of “carbon peak” and “carbon neutrality,” improving the carbon sequestration capacity of the terrestrial ecosystems is one of the crucial ways. Due to its vast geographical area and considerable vegetation restoration potential, it is of great practical significance to evaluate the current situation of carbon sequestration in Xinjiang and explore the potential of carbon sequestration so as to respond positively and realize the national “double carbon” goal. This study combined the Carnegie Ames Stanford Approach (CASA) model with the land use, remote sensing, and meteorological (temperature, precipitation, and solar radiation) data, and NPP in Xinjiang from 2001 to 2020 for the simulation. The Sen-MK method was used to analyze the trend in NPP changes. Pearson correlation analysis was used to identify the relationship between NPP variations and climatic factors. Further, different land use and vegetation scenarios from 2001 to 2020, as well as the pattern of NPP variations under pure climate scenarios simulated by the Miami model, were used to derive the final maximum potential of NPP and the maximum increment of NPP in Xinjiang. The results showed that: (1) The NPP in Xinjiang showed an upward trend with fluctuations from 2001 to 2020; (2) Among the climatic factors, precipitation had the maximal impact on NPP in Xinjiang; (3) Among the primary land use types in Xinjiang, cultivated land had a large NPP which showed an increasing trend; (4) The increment potential of NPP in Xinjiang was 79.43 g C·m^-2. This study can provide a reference for Xinjiang to respond to the national call for “carbon peak” and “carbon neutrality” and to implement ecological restoration and cultivated land protection measures.

Key words: oasis, net primary productivity, carbon sequestration potential, CASA model, Xinjiang

ZHANG Haozhe, XUE Yayong, MA Yuanyuan, XUE Guoxuan. Carbon sequestration potential of oasis ecosystem in Xinjiang, China[J].Arid Zone Research, 2024, 41(6): 998-1009.

Figures/Tables 9

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

References 48

[1]	赵俊芳, 曹云, 马建勇, 等. 基于遥感和FORCCHN的中国森林生态系统NPP及生态服务功能评估[J]. 生态环境学报, 2018, 27(9): 1585-1592. doi: 10.16258/j.cnki.1674-5906.2018.09.001
	[Zhao Junfang, Cao Yun, Ma Jianyong, et al. Evaluation of NPP and ecological service function of China’s forest ecosystem based on remote sensing and FORCCHN[J]. Ecology and Environmental Sciences, 2018, 27(9): 1585-1592. ]
[2]	刘宪锋, 任志远, 林志慧. 青藏高原生态系统固碳释氧价值动态测评[J]. 地理研究, 2013, 32(4): 663-670.
	[Liu Xianfeng, Ren Zhiyuan, Lin Zhihui. Dynamic assessment of the values of CO₂ fixation and O₂ release in Qinghai-Tibet Plateau ecosystem[J]. Geographical Research, 2013, 32(4): 663-670. ]
[3]	Gu F X, Zhang Y D, Huang M, et al. Climate-driven uncertainties in modeling terrestrial ecosystem net primary productivity in China[J]. Agricultural and Forest Meteorology, 2017, 246(11): 123-132.
[4]	Ouyang Z Y, Zheng H, Xiao Y, et al. Improvements in ecosystem services from investments in natural capital[J]. Science, 2016, 352(6292): 1455-1459. doi: 10.1126/science.aaf2295 pmid: 27313045
[5]	Hong S B, Yin G D, Piao S L, et al. Divergent responses of soil organic carbon to afforestation[J]. Nature Sustainability, 2020, 3(9): 694-700.
[6]	Li T J, Ren B W, Wang D H, et al. Spatial variation in the storages and age-related dynamics of forest carbon sequestration in different climate zones-Evidence from black locust plantations on the Loess Plateau[J]. Plos One, 2015, 10(3): 0121862.
[7]	Choi Y, Lim C H, Chung H I, et al. Forest management can mitigate negative impacts of climate and land-use change on plant biodiversity: Insights from the Republic of Korea[J]. Journal of Environmental Management, 2021, 288: 112400.
[8]	Xue Y, Liang H, Zhang B, et al. Vegetation restoration dominated the variation of water use efficiency in China[J]. Journal of Hydrology, 2022, 612: 128257.
[9]	Baldocchi D. ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems[J]. Australian Journal of Botany, 2008, 56(1): 1-26.
[10]	Chapin F S, Matson P A, Mooney H A. Principle of Terrestrial Ecosystem Ecology[M]. Principle of Terrestrial Ecosystem Ecology, Springer, 2011: 123-156.
[11]	Yu G R, Zhu X J, Fu Y L, et al. Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China[J]. Global Change Biology, 2013, 19(3): 798-810.
[12]	闫敏, 李增元, 田昕, 等. 黑河上游植被总初级生产力遥感估算及其对气候变化的响应[J]. 植物生态学报, 2016, 40(1): 1-12. doi: 10.17521/cjpe.2015.0253
	[Yan Min, Li Zengyuan, Tian Xin, et al. Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin[J]. Chinese Journal of Plant Ecology, 2016, 40(1): 1-12. ] doi: 10.17521/cjpe.2015.0253
[13]	Law B E, Falge E, Gu L, et al. Environment controls over carbon dioxide and water vapor exchange of terrestrial vegetation[J]. Agricultural and Forest Meteorology, 2002, 113(1-4): 97-120.
[14]	Ciais P, Reichstein M, Viovy N, et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003[J]. Nature, 2005, 437(7058): 529-533.
[15]	Wang H J, Chen Y N, Xun S, et al. Changes in daily climate extremes in the arid area of northwestern China[J]. Theoretical and Applied Climatology, 2013, 112(1): 15-28.
[16]	陈春波, 李刚勇, 彭建. 近20 a新疆天然草地NPP时空分析[J]. 干旱区地理, 2022, 45(2): 522-534.
	[Chen Chunbo, Li Gangyong, Peng Jian, et al. Spatiotemporal analysis of net primary productivity for natural grassland in Xinjiang in the past 20 years[J]. Arid Land Geography, 2022, 45(2): 522-534. ]
[17]	刘卫国, 魏文寿, 刘志辉. 新疆气候变化下植被净初级生产力格局分析[J]. 干旱区研究, 2009, 26(2): 206-211.
	[Liu Weiguo, Wei Wenshou, Liu Zhihui. NPP change in vegegtation in Xinjiang under climate change[J]. Arid Zone Research, 2009, 26(2): 206-211. ]
[18]	万华伟, 李灏欣, 高吉喜, 等. 我国植被生态系统固碳能力提升潜力空间格局研究[J]. 生态学报, 2022, 42(21): 8568-8580.
	[Wan Huawei, Li Haoxin, Gao Jixi, et al. Spatial pattern analysis of carbon sequestration potential of vegetation ecosystem in China[J]. Acta Ecologica Sinica, 2022, 42(21): 8568-8580. ]
[19]	王昭生. 基于ERA5的1982—2020年中国太阳净辐射数据集[EB/OL]. https://cstr.cn/15732.11.ecodb.00058, 2022.
	[Wang Zhaosheng. China’s Net Solar Radiation Data Set Based on ERA5 from 1982 to 2020[EB/OL]https://cstr.cn/15732.11.ecodb.00058, 2022. ]
[20]	Peng Shouzhang, Ding Yongxia, Liu Wenzhao, et al. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017[J]. Earth System Science Data, 2019, 11: doi:10.5194/essd-11-1931-2019.
[21]	骆成凤, 王长耀, 刘永洪, 等. 利用BP算法进行新疆MODIS数据土地利用分类研究[J]. 干旱区地理, 2005, 28(2): 258-262.
	[Luo Chengfeng, Wang Changyao, Liu Yonghong, et al. Classification of land use in Xinjiang with BP classifier using MODIS imagery[J]. Arid Land Geography, 2005, 28(2): 258-262. ]
[22]	米尔扎提江·木艾塔尔江, 古丽米热·艾尔肯, 阿依吐尔逊·沙木西. 基于MODIS数据的新疆土地利用/覆被时空变化及驱动因素分析[J]. 湖北农业科学, 2022, 61(16): 58-63.
	[Mierzhatijiang Muaitaerjiang, Gulimire Aierken, Ayituerxun Shamuxi. Land use/land cover change and its driving factors in Xinjiang based on MODIS data[J]. Hubei Agricultural Sciences, 2022, 61(16): 58-63. ]
[23]	卜祥, 张永福, 梁田田, 等. 基于MODIS数据2001—2019年NDVI时空变化及驱动力分析——以阿克苏地区为例[J]. 中国农学通报, 2022, 38(11): 75-83. doi: 10.11924/j.issn.1000-6850.casb2021-0399
	[Bu Xiang, Zhang Yongfu, Liang Tiantian, et al. Analysis of spatial-temporal changes and driving forces of NDVI from 2001 to 2019 based on MODIS data: Taking Aksu as an example[J]. Chinese Agricultural Science Bulletin, 2022, 38(11): 75-83. ] doi: 10.11924/j.issn.1000-6850.casb2021-0399
[24]	王祎婷, 邹蕊, 王欣悦, 等. 塔拉滩地区光伏电站建设对植被净初级生产力的影响[J]. 农业工程学报, 2022, 38(24): 153-161.
	[Wang Yiting, Zou Rui, Wang Xinyue, et al. Impact of photovoltaic power plant construction on the net primary productivity of vegetation in the Tala Schoal areas[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(24): 158-161. ]
[25]	Xu H, Wang X, Zhang X. Alpine grasslands response to climatic factors and anthropogenic activities on the Tibetan Plateau from 2000 to 2012[J]. Ecological Engineering, 2016, 92: 005.
[26]	朱文泉. 中国陆地生态系统植被净初级生产力遥感估算及其与气候变化关系的研究[D]. 北京: 北京师范大学, 2005.
	[Zhu Wenquan. Estimation of Net Promar Productivity of Chinese Terrstrial Vegetation Baseds on Remote Sensing and Its Relashionship with Global Climate Change[D]. Beijing: Beijing Normal University, 2005. ]
[27]	张镱锂, 祁威, 周才平, 等. 青藏高原高寒草地净初级生产力(NPP)时空分异[J]. 地理学报, 2013, 68(9): 1197-1211. doi: 10.11821/dlxb201309004
	[Zhang Yili, Qi Wei, Zhou Caiping, et al. Spatial and temporal variability in the net primary production (NPP) of alpine grassland on Tibetan Plateau from 1982 to 2009[J]. Acta Gegraphica Sinica, 2013, 68(9): 1197-1211. ]
[28]	邹德富. 基于CASA模型的青藏高原NPP时空分布动态研究[D]. 兰州: 兰州大学, 2012.
	[Zou Defu. Spatio-temporal Dynamics of Tibet Plateau Net Primary Production Using CASA Model[D]. Lanzhou: Lanzhou University, 2012. ]
[29]	张金亭, 董艳超, 叶宗达. 基于地形改进NPP指数的县域耕地产能测算[J]. 农业工程学报, 2020, 36(10): 227-234, 326.
	[Zhang Jinting, Dong Yanchao, Ye Zongda. Calculation of county-level cultivated land productivity based on NPP index corrected by topography[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(10): 227-234, 326. ]
[30]	周刊社, 杜军, 沈旭, 等. 气候变化背景下羌塘国家自然保护区植被净初级生产力时空变化[J]. 中国农业气象, 2021, 42(8): 627-641.
	[Zhou Kanshe, Du Jun, Shen Xu, et al. Spatial and temporal variability of vegetation net primary productivity in Qiangtang National Nature Reserve under climate change[J]. Chinese Journal of Agrometeorology, 2021, 42(8): 627-641. ]
[31]	赵俊芳, 孔祥娜, 姜月清, 等. 基于高时空分辨率的气候变化对全球主要农区气候生产潜力的影响评估[J]. 生态环境学报, 2019, 28(1): 1-6. doi: 10.16258/j.cnki.1674-5906.2019.01.001
	[Zhao Junfang, Kong Xiangna, Jiang Yueqing, et al. Impact Assessment of climate change on climatic potential productivity in global major agricultural regions based on high spatial and temporal resolution data[J]. Ecology and Environmental Sciences, 2019, 28(1): 1-6. ]
[32]	文想成, 张泰, 王学梅, 等. 长江中下游地区气候生产潜力及粮食产量响应[J]. 江苏农业科学, 2021, 49(6): 196-203.
	[Wen Xiangcheng, Zhang Tai, Wang Xuemei, et al. Climate productivity potential and food production response in the middle and lower reaches of Yangtze River[J]. Jiangsu Agricultural Sciences, 2021, 49(6): 196-203. ]
[33]	Shahid S, Hazarika M K. Groundwater drought in the northwestern districts of Bangladesh[J]. Water Resources Management, 2010, 24(10): 1989-2006.
[34]	Li C, Walter L F, Wang J, et al. An analysis of precipitation extremes in the Inner Mongolian Plateau: Spatial-temporal patterns, causes, and 17 implications[J]. Atmosphere, 2018, 9(8): 322.
[35]	黄观荣, 杜晓阳, 郭永婷, 等. 粤北NPP时空分布特征及其对降水和气温的响应[J]. 气象与环境科学, 2023, 46(3): 38-46.
	[Huang Guanrong, Du Xiaoyang, Guo Yongting, et al. Spatio-temporal distribution of NPP and its response to precipitation and temperature in the north of Guangdong Province[J]. Meteorological and Environmental Sciences, 2023, 46(3): 38-46. ]
[36]	贾俊鹤, 刘会玉, 林振山. 中国西北地区植被NPP多时间尺度变化及其对气候变化的响应[J]. 生态学报, 2019, 39(14): 5058-5069.
	[Jia Junhe, Liu Huiyu, Lin Zhenshan. Multi-time scale changes of vegetation NPP in six provinces of Northwest China and their responses to climate change[J]. Acta Ecologica Sinica, 2019, 39(14): 5058-5069. ]
[37]	徐虹, 程晋昕, 何雨芩, 等. 气候变化和人类活动对云南省植被净初级生产力的影响[J/OL]. 高原气象. https://link.cnki.net/urlid/62.1061.p.20231008.1002.002, 2023-10-10.
	[Xu Hong, Cheng Jinxin, He Yuqin, et al. Effects of climate change and human activities on net primary productivity in Yunnan Province[J/OL]. Plateau Meteorology. https://link.cnki.net/urlid/62.1061.p.20231008.1002.002, 2023-10-10. ]
[38]	陈玉森, 艾柯代·艾斯凯尔, 王永东, 等. 1994—2018年哈萨克斯坦首都圈植被NPP时空变化特征及驱动因素[J]. 干旱区研究, 2022, 39(6): 1917-1929.
	[Chen Yusen, AkidaAskarl, Wang Yongdong, et al. Characteristics and drivers of the spatial-temporal change of net primary productivity in the capital area of Kazakhstan from 1994 to 2018[J]. Arid Zone Research, 2022, 39(6): 1917-1929. ]
[39]	张赟鑫, 郝海超, 范连连, 等. 中亚草地NPP时空动态及其驱动因素研究[J]. 干旱区研究, 2022, 39(3): 698-707.
	[Zhang Yunxin, Hao Haichao, Fan Lianlian, et al. Study on spatio-temporal dynamics and driving factors of NPP in Central Asian grassland[J]. Arid Zone Research, 2022, 39(3): 698-707. ]
[40]	刘婵, 刘冰, 赵文智, 等. 中亚地区植被净初级生产力时空动态及其与气候因子关系[J]. 遥感技术与应用, 2020, 35(4): 924-933. doi: 10.11873/j.issn.1004-0323.2020.4.0924
	[Liu Chan, Liu Bing, Zhao Wenzhi, et al. Temporal-spatial variation analysis of net primary productivity and its relationship with climate in Central Asia[J]. Remotesensing Technology Andapplication, 2020, 35(4): 924-933. ]
[41]	Xue Y Y, Liang H B, Zhang H Z, et al. Quantifying the policy-driven large scale vegetation restoration effects on evapotranspiration over drylands in China[J]. Journal of Environmental Management, 2023, 345: 118723.
[42]	王莺, 夏文韬, 梁天刚, 等. 基于MODIS植被指数的甘南草地净初级生产力时空变化研究[J]. 草业学报, 2010, 19(1): 201-210.
	[Wang Ying, Xia Wentao, Liang Tiangang, et al. Spatial and temporal dynamic changes of net primary product based on MODIS vegetation index in Gannan grassland[J]. Acta Prataculturae Sinica, 2010, 19(1): 201-210. ]
[43]	陈宸, 井长青, 邢文渊, 等. 近20年新疆荒漠草地动态变化及其对气候变化的响应[J]. 草业学报, 2021, 30(3): 1-14. doi: 10.11686/cyxb2020143
	[Chen Chen, Jing Changqing, Xing Wenyuan, et al. Desert grassland dynamics in the last 20 years and its response to climate change in Xinjiang[J]. Acta Prataculturaesinica, 2021, 30(3): 1-14. ]
[44]	Xue Y Y, Liang H B, Ma Y Y, et al. The impacts of climate and human activities on grassland productivity variation in China[J]. Remote Sensing, 2023, 15: 3864.
[45]	徐丽萍, 李鹏辉, 李忠勤, 等. 新疆山地冰川变化及影响研究进展[J]. 水科学进展, 2020, 31(6): 946-959.
	[Xu Liping, Li Penghui, Li Zhongqin, et al. Advances in research on changes and effects of glaciers in Xinjiang mountains[J]. Advances in Water Science, 2020, 31(6): 946-959. ]
[46]	Li L, Zhang Y, Zhou T, et al. Mitigation of China’s carbon neutrality to global warming[J]. Nature Communications, 2022, 5315: doi: 10.1038/s41467-022-33047-9.
[47]	Peng B, Zhou Z, Cai W, et al. Maximum potential of vegetation carbon sink in Chinese forests[J]. Science of the Total Environment, 2023, 905: 167325.
[48]	常学礼, 吕世海, 冯朝阳, 等. 地形对草甸草原植被生产力分布格局的影响[J]. 生态学报, 2015, 35(10): 3339-3348.
	[Chang Xueli, Lv Shihai, Feng Zhaoyang, et al. Impact of topography on the spatial distribution pattern of net primary productivity in a meadow[J]. Acta Ecologica Sinica, 2015, 35(10): 3339-3348. ]

Carbon sequestration potential of oasis ecosystem in Xinjiang, China

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 48

Related Articles 15

Metrics

Comments

Recommended 0

[1]	SUN Linlin, LIU Qiong, HUANG Guan, CHEN Yonghang, WEI Xin, GUO Yulin, ZHANG Taixi, GAO Tianyi, XU Yunhong. Analysis of surface solar radiation under different cloud conditions in Xinjiang and the surrounding “Belt and Road” regions [J]. Arid Zone Research, 2024, 41(9): 1480-1490.
[2]	ZHENG Liuna, JIANG Hongnan, SUN Mengting. Correlations between soil water content, salinity, and fractional vegetation cover in the Ugan-Kuqa River Delta Oasis of Xinjiang ascertained based on remote sensing images [J]. Arid Zone Research, 2024, 41(7): 1131-1139.
[3]	JIAN Zhengbo, LUO Hao, SHAN Nana. A study on the spatial and temporal evolution and carbon effects of production-living-ecological in Xinjiang under carbon peak and carbon neutrality goals [J]. Arid Zone Research, 2024, 41(7): 1238-1248.
[4]	LIU Huaqing, WANG Bo, JIA Yanyan, XIE Xinran, ZHANG Wei. Characterization of the freezing injury to Juglans regia at different slope positions in the West Tianshan valley of Xinjiang, China [J]. Arid Zone Research, 2024, 41(6): 1079-1088.
[5]	MA Yuanzhi, QIN Xiaolin, LING Hongbo, YAN Junjie, ZHANG Guangpeng. Spatio-temporal characteristics and trends of area changes in the small and medium-sized lakes in Xinjiang, China, from 1991 to 2020 [J]. Arid Zone Research, 2024, 41(6): 905-916.
[6]	XU Chaojie, DOU Yan, MENG Qilin. Prediction of the standardized precipitation evapotranspiration index in the Xinjiang region using the EMD-GWO-LSTM model [J]. Arid Zone Research, 2024, 41(4): 527-539.
[7]	SI Qi, FAN Haoran, DONG Wenming, LIU Xinping. Landscape ecological risk assessment and prediction for the Yarkant River Basin, Xinjiang, China [J]. Arid Zone Research, 2024, 41(4): 684-696.
[8]	BAO Jiayu, LI Xianglong, HU Qiwen, LI Tao. Spatiotemporal characteristics of carbon emissions from energy consumption and the approach to energy structure adjustment in Xinjiang [J]. Arid Zone Research, 2024, 41(3): 490-498.
[9]	YAO Junqiang. Change in atmospheric and surface water resource in Xinjiang [J]. Arid Zone Research, 2024, 41(2): 181-190.
[10]	XU Yunhong, LIU Qiong, CHEN Yonghang, WEI Xin, LIU Xin, ZHANG Taixi, SHAO Weiling, YANG Hequn, ZHANG Chengming. Impact of land cover variations on surface albedo in Xinjiang and its surrounding Central Asian region [J]. Arid Zone Research, 2024, 41(10): 1649-1661.
[11]	JIN Chenyang, DU Hongru. Characteristics of spatial and temporal changes and zoning of cultivated land resilience in Xinjiang [J]. Arid Zone Research, 2024, 41(10): 1778-1788.
[12]	LI Xiaofeng, HUI Tingting, LI Yaoming, MAO Jiefei, WANG Guangyu, FAN Lianlian. Effects of different grazing management strategies on plant diversity in the mountain grassland of Xinjiang, China [J]. Arid Zone Research, 2024, 41(1): 124-134.
[13]	LIU Yidan, YAO Xiaojun, LI Zongxing, HU Jiayu. Impacts of climate change and land use/cover change on the net primary productivity of vegetation in Hexi Region, Northwest China [J]. Arid Zone Research, 2024, 41(1): 169-180.
[14]	WANG Xiang, LYU Haishen, ZHU Yonghua, GUO Chenyu. Application and comparison of two channel flood routing methods in Xinjiang mountainous areas [J]. Arid Zone Research, 2023, 40(8): 1240-1247.
[15]	WANG Chao, MA Zhancang, PAN Chengnan, WU Xingyue, SONG Wendan, YAN Ping. New records of Amaranthus in Xinjiang [J]. Arid Zone Research, 2023, 40(8): 1280-1288.