干旱区研究

干旱区研究 >

2023 , Vol. 40 >Issue 10: 1644 - 1660

DOI: https://doi.org/10.13866/j.azr.2023.10.11

植物生态

干旱对中国北方草原总初级生产力影响的时滞和累积效应

  • 乌日娜 ,
  • 刘步云 ,
  • 包玉海
展开
  • 1.辽宁师范大学地理科学学院，辽宁 大连 116029
    2.内蒙古师范大学地理科学学院，内蒙古 呼和浩特 010022
    3.内蒙古自治区遥感与地理信息系统重点实验室，内蒙古 呼和浩特 010022
乌日娜（1988-），女，博士，讲师，主要从事自然灾害风险评价. E-mail: wurina@lnnu.edu.cn

收稿日期: 2023-03-23

  修回日期: 2023-08-23

  网络出版日期: 2023-11-01

基金资助

2021年大连市科技之星工程(2021RQ101);国家自然科学基金(42261144746)

收起

Time lag and cumulative effect of drought on gross primary productivity in the grasslands of northern China

  • Rina WU ,
  • Buyun LIU ,
  • Yuhai BAO
Expand
  • 1. School of Geographical Sciences, Liaoning Normal University, Dalian 116029, Liaoning, China
    2. School of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, Inner Mongolia, China
    3. Key Laboratory of Remote Sensing and Geographic Information System of Inner Mongolia Autonomous Region, Hohhot 010022, Inner Mongolia, China

Received date: 2023-03-23

  Revised date: 2023-08-23

  Online published: 2023-11-01

Fold

摘要

近年来随着全球变暖，干旱事件的增加对植被的光合作用产生更加重要的影响，同时也严重影响了陆地生态系统的平衡。本文基于标准化降水蒸散指数(SPEI base v.2.7)和总初级生产力数据集（GOSIF GPP）研究了干旱对中国北方草原GPP的累积和时滞效应，利用Sen’s斜率、Mann-Kendall(MK)趋势检验、Mann-Kendall突变检验研究了GPP和SPEI在研究期内的时空变化，利用Pearson相关分析方法探究了干旱对北方草原GPP的累积和时滞效应。结果表明：（1）2001—2020年期间北方草原多年平均GPP呈现东北地区高、西南地区低的空间分布格局，多年平均SPEI呈现东北地区低、西南地区高的空间分布格局，且SPEI和GPP的年平均值都随时间变化呈现上升趋势。（2）干旱对北方草原84.99%的区域有累积效应，最长累积时间尺度主要集中在3~4个月，覆盖北方草原的39.82%；干旱对北方草原63.11%的区域有滞后效应，且主要发生在7个月，覆盖北方草原的19.73%。（3）通过对比不同水分条件下二者的变化趋势，发现干旱对草原GPP的累积效应强于时滞效应。

关键词： 中国北方草原; 干旱; 总初级生产力; 时滞效应; 累积效应

本文引用格式

乌日娜 , 刘步云 , 包玉海 . 干旱对中国北方草原总初级生产力影响的时滞和累积效应[J]. 干旱区研究, 2023 , 40(10) : 1644 -1660 . DOI: 10.13866/j.azr.2023.10.11

Abstract

In recent years, with global warming, the increase of drought events has a more important impact on the photosynthesis of vegetation, and also seriously affects the balance of terrestrial ecosystems. Based on SPEI base v.2.7 and GOSIF GPP data set, this paper studies the cumulative and time-delay effects of drought on GPP in northern grassland. Sen’s slope test, MK trend test and Mann-Kendall mutation test were used to study the temporal and spatial changes of GPP and SPEI during the study period. Pearson correlation analysis method was used to explore the cumulative and time-delay effects of drought on GPP in the north grasslands. The results showed that: (1) From 2001 to 2020, the annual average GPP of the northern grasslands showed a spatial distribution pattern of high in the northeast and low in the southwest, and the annual average SPEI showed a spatial distribution pattern of low in the northeast and high in the southwest, and the annual average of SPEI and GPP showed an upward trend over time. (2) Drought has a cumulative effect on 84.99% of the northern grassland, and the longest cumulative time scale is mainly concentrated in 3-4 months, covering 39.82% of the northern grassland; Drought had a lagging effect on 63.11% of the northern grassland, and mainly occurred in 7 months, covering 19.73% of the northern grasslands. (3) By comparing the variation trends of drought and drought under different water conditions, we found that the cumulative effect of drought on grassland GPP was stronger than the time-lag effect.

Key words： grasslands of northern China; drought; gross primary productivity; time-lag effect; cumulative effect

参考文献

[1] Pan S, Tian H, Dangal S R S, et al. Impacts of climate variability and extremes on global net primary production in the first decade of the 21st century[J]. Journal of Geographical Sciences, 2015, 25: 1027-1044.
[2] 王莺, 王健顺, 张强. 中国草原干旱灾害风险特征研究[J]. 草业学报, 2022, 31(8): 1-12.
[2] [Wang Ying, Wang Jianshun, Zhang Qiang. Drought risk status of grassland in China[J]. Acta Prataculturae Sinica, 2022, 31(8): 1-12.]
[3] 李稚, 李玉朋, 李鸿威, 等. 中亚地区干旱变化及其影响分析[J]. 地球科学进展, 2022, 37(1): 37-50.
[3] [Li Zhi, Li Yupeng, Li Hongwei, et al. Analysis of drought change and its impact in Central Asia[J]. Advances in Earth Science, 2022, 37(1): 37-50.]
[4] 袁文平, 蔡文文, 刘丹, 等. 陆地生态系统植被生产力遥感模型研究进展[J]. 地球科学进展, 2014, 29(5): 541-550.
[4] [Yuan Wenping, Cai Wenwen, Liu Dan, et al. Satellite-based vegetation production models of terrestrial ecosystem: An overview[J]. Advances in Earth Science, 2014, 29(5): 541-550.]
[5] 吕锦心, 梁康, 刘昌明, 等. 无定河流域土地覆被空间分异机制及相关水碳变量变化[J]. 干旱区研究, 2023, 40(4): 563-572.
[5] [Lv Jinxin, Liang Kang, Liu Changming, et al. Spatial differentiation mechanism of land cover and related changes in water-carbon variables in Wuding River Basin[J]. Arid Zone Research, 2023, 40(4): 563-572.]
[6] 杜文丽, 孙少波, 吴云涛, 等. 1980—2013年中国陆地生态系统总初级生产力对干旱的响应特征[J]. 生态学杂志, 2020, 39(1): 23-35.
[6] [Du Wenli, Sun Shaobo, Wu Yuntao, et al. The responses of gross primary production to drought in terrestrial ecosystems of China during 1980-2013[J]. Chinese Journal of Ecology, 2020, 39(1): 23-35.]
[7] Vicente-Serrano S M, Gouveia C, Camarero J J, et al. Response of vegetation to drought time-scales across global land biomes[J]. Proceedings of the National Academy of Sciences, 2013, 110(1): 52-57.
[8] Zhao X, Xia H, Liu B, et al. Spatiotemporal comparison of drought in Shaanxi-Gansu-Ningxia from 2003 to 2020 using various drought indices in google earth engine[J]. Remote Sensing, 2022, 14(7): 1570.
[9] 朱光磊. 嫩江流域植被动态变化及其对气象干旱的响应研究[D]. 延边: 延边大学, 2021.
[9] [Zhu Guanglei. Study on Dynamic Change of Vegetation and Its Response to Meteorological Drought in Nenjiang River Basin[D]. Yanbian: Yanbian University, 2021.]
[10] Tong S, Bao Y, Te R, et al. Analysis of drought characteristics in Xilingol grassland of Northern China based on SPEI and its impact on vegetation[J]. Mathematical Problems in Engineering, 2017, 2017: 1-11.
[11] Zhang Z, Ju W, Zhou Y, et al. Revisiting the cumulative effects of drought on global gross primary productivity based on new long-term series data (1982-2018)[J]. Global Change Biology, 2022, 28(11): 3620-3635.
[12] Frank D, Reichstein M, Bahn M, et al. Effects of climate extremes on the terrestrial carbon cycle: Concepts, processes and potential future impacts[J]. Global Change Biology, 2015, 21(8): 2861-2880.
[13] 逯金鑫. 黄土高原植被恢复成效评估与气候变化及干旱的时滞效应[D]. 杨凌: 西北农林科技大学, 2022.
[13] [Lu Jinxin. Evaluation of Vegetation Restoration in Loess Plateau and Time-lag Effect of Climate Change and Drought[D]. Yangling: North West Agriculture and Forestry University, 2022.]
[14] Kolus H R, Huntzinger D N, Schwalm C R, et al. Land carbon models underestimate the severity and duration of drought’s impact on plant productivity[J]. Scientific Reports, 2019, 9(1): 2758.
[15] Peng J, Wu C, Zhang X, et al. Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere[J]. Global Change Biology, 2019, 25(6): 2174-2188.
[16] Braswell B H, Schimel D S, Linder E, et al. The response of global terrestrial ecosystems to interannual temperature variability[J]. Science, 1997, 278(5339): 870-873..
[17] Zuo D, Han Y, Xu Z, et al. Time-lag effects of climatic change and drought on vegetation dynamics in an alpine river basin of the Tibet Plateau, China[J]. Journal of Hydrology, 2021, 600: 126532.
[18] 范倩倩. 海河流域植被覆盖时空演变及其对多时间尺度干旱响应[D]. 邯郸: 河北工程大学, 2020.
[18] [Fan Qianqian. Spatiotemporal Evolution of Vegetation Cover and Its Response to Multi-time Scale Drought in the Haihe River Basin[D]. Handan: Hebei University of Engineering, 2020.]
[19] 顾锡羚, 郭恩亮, 银山, 等. 干旱对内蒙古植被生长的累积与滞后影响评估研究[J]. 草地学报, 2021, 29(6): 1301-1310.
[19] [Gu Xiling, Guo Enliang, Yin Shan, et al. Assessment of the cumulative and lagging effects of drought on vegetation growth in Inner Mongolia[J]. Acta Agrestia Sinica, 2021, 29(6): 1301-1310.]
[20] van der Molen M K, Dolman A J, Ciais P, et al. Drought and ecosystem carbon cycling[J]. Agricultural and Forest Meteorology, 2011, 151(7): 765-773.
[21] Wagle P, Xiao X, Torn M S, et al. Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought[J]. Remote Sensing of Environment, 2014, 152: 1-14.
[22] 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.
[23] 杨铭珂. 贵州省总初级生产力的时空分布特征及对干旱变化的响应[D]. 贵阳: 贵州师范大学, 2022.
[23] [Yang Mingke. Spatiotemporal Distribution of Gross Primary Productivity and Its Response to Drought Change in Guizhou Province[D]. Guiyang: Guizhou Normal University, 2022.]
[24] 杨昭明, 张调风. 1961—2017年青藏高原东北部雨季降水量变化及其贡献度分析[J]. 干旱区研究, 2021, 38(1): 22-28.
[24] [Yang Zhaoming, Zhang Tiaofeng. Analysis of precipitation change and its contribution in the rainy season in thenortheast Qinghai-Tibet Plateau from 1961 to 2017[J]. Arid Zone Research, 2021, 38(1): 22-28.]
[25] 赵欢. 中国北方草原物候的时空动态变化及其对气候的响应[D]. 成都: 成都理工大学, 2020.
[25] [Zhao Huan. Spatiotemporal Dynamics of Vegetation Phenology and Its Response to Climate Change in Northern China’s grasslands[D]. Chengdu: Chengdu University of Technology, 2020.]
[26] 罗馨. 青藏高原碳和水分利用效率的时空演变特征及其对气候变化和人类活动的响应[D]. 成都: 成都信息工程大学, 2020.
[26] [Luo Xin. Temporal and Spatial Evolution of Carbon and Water Use Efficiency over the Tibetan Plateau in Response to Climate Change and Human Activities[D]. Chengdu: Chengdu University of Information Technology, 2020.]
[27] 滑永春, 萨如拉, 王冰. 内蒙古草原NPP时空变化及驱动力[J]. 中国沙漠, 2021, 41(5): 130-139.
[27] [Hua Yongchun, Sa Rula, Wang Bing. Spatial and temporal variation of grassland NPP and its driving forces in Inner Mongolia[J]. Journal of Desert Research, 2021, 41(5): 130-139.]
[28] Li X, Xiao J. Mapping photosynthesis solely from solar-induced Chlorophyll fluorescence: A global, fine-resolution dataset of gross primary production derived from OCO-2[J]. Remote Sensing, 2019, 11(21): 2563.
[29] Vicente-Serrano S M, Beguería S, Lorenzo-Lacruz J, et al. Performance of drought indices for ecological, agricultural, and hydrological applications[J]. Earth Interactions, 2012, 16(10): 1-27.
[30] 刘扬, 杨永春, 张轲, 等. 1960—2011年河西走廊地表干湿状况的时空变化及影响因素[J]. 水土保持通报, 2015, 35(1): 54-60.
[30] [Liu Yang, Yang Yongchun, Zhang Ke, et al. Temporal and spatial variation of humidity and its influential factors in Hexi Corridor during 1960-2011[J]. Bulletin of Soil and Water Conservation, 2015, 35(1): 54-60.]
[31] 胡琦, 马雪晴, 胡莉婷, 等. Matlab在气象专业教学中的应用——气象要素的M-K检验突变分析[J]. 实验室研究与探索, 2019, 38(12): 48-51, 107.
[31] [Hu Qi, Ma Xueqing, Hu Liting, et al. Application of matlab in meteorological teaching: M-K test for the abrupt change analysis of meteorological elements[J]. Research and Exploration in Laboratory, 2019, 38(12): 48-51, 107.]
[32] Zhao A, Yu Q, Feng L, et al. Evaluating the cumulative and time-lag effects of drought on grassland vegetation: A case study in the Chinese Loess Plateau[J]. Journal of Environmental Management, 2020, 261: 110214.
[33] 薛联青, 肖颖, 刘远洪, 等. 黄河流域植被水分利用效率对干旱的时空累积响应[J]. 水资源保护, 2023, 39(4): 32-41.
[33] [Xue Lianqing, Xiao Ying, Liu Yuanhong, et al. Spatiotemporal accumulation response of vegetation water use efficiency to drought in the Yellow River Basin[J]. Water Resources Protection, 2023, 39(4): 32-41.]
[34] Wei X, He W, Zhou Y, et al. Global assessment of lagged and cumulative effects of drought on grassland gross primary production[J]. Ecological Indicators, 2022, 136: 108646.
[35] Reichstein M, Bahn M, Ciais P, et al. Climate extremes and the carbon cycle[J]. Nature, 2013, 500(7462): 287-295.
[36] Pei F, Li X, Liu X, et al. Assessing the impacts of droughts on net primary productivity in China[J]. Journal of Environmental Management, 2013, 114: 362-371.
[37] Zhang T, Xu M, Zhang Y, et al. Grazing-induced increases in soil moisture maintain higher productivity during droughts in alpine meadows on the Tibetan Plateau[J]. Agricultural and Forest Meteorology, 2019, 269: 249-256.
[38] 韩芳, 刘朋涛, 牛建明, 等. 50a来内蒙古荒漠草原气候干燥度的空间分布及其演变特征[J]. 干旱区研究, 2013, 30(3): 449-456.
[38] [Han Fang, Liu Pengtao, Niu Jianming, et al. Spatial distribution and evolution of climatic aridity in desert steppe in Inner Mongolia in recent 50 years[J]. Arid Zone Research, 2013, 30(3): 449-456.]
[39] 徐清宸. 锡林郭勒盟草地碳循环对干旱的响应[D]. 曲阜: 曲阜师范大学, 2021.
[39] [Xu Qingchen. Response of Grassland Carbon Cycle to Drought in Xilin Gol League[D]. Qufu: Qufu Normal University, 2021.]
[40] Xu K, Yang D, Yang H, et al. Spatio-temporal variation of drought in China during 1961-2012: A climatic perspective[J]. Journal of Hydrology, 2015, 526: 253-264.
[41] Zhan C, Liang C, Zhao L, et al. Drought-related cumulative and time-lag effects on vegetation dynamics across the Yellow River Basin, China[J]. Ecological Indicators, 2022, 143: 109409.
[42] Hoffmann A A, Camac J S, Williams R J, et al. Phenological changes in six Australian subalpine plants in response to experimental warming and year-to-year variation[J]. Journal of Ecology, 2010, 98(4): 927-937.
[43] 姚檀栋, 朱立平. 青藏高原环境变化对全球变化的响应及其适应对策[J]. 地球科学进展, 2006, 21(5): 459-464.
[43] [Yao Tandong, Zhu Liping. The response of environmental changes on Tibet an plateau to global changes and adaptation strategy[J]. Advances in Earth Science, 2006, 21(5): 459-464.]
Options
文章导航

/

〈 〉