塔里木河流域草地净初级生产力时空分异特征研究

doi:10.11686/cyxb2019427

摘要/Abstract

摘要： 采用MODIS数据和改进的光能利用率模型(CASA模型)对2006-2016年塔里木河流域植被生长季草地净初级生产力(NPP)进行估算,通过一元线性回归趋势分析、变异系数、Hurst指数等方法,分别从时间特征、空间特征、空间稳定性和未来变化趋势4个方面对其时空变化过程进行分析,阐述了2006-2016年塔里木河流域草地NPP的时空格局与变化特征。结论如下:1)时间特征上,2006-2016年塔里木河流域草地NPP总体呈波动上升趋势,其中增长区域占64.1%,负增长区域占35.9%,NPP总量平均增长速度为1.31×10¹¹ g C·m^-2·yr^-1;6-8月为流域内草地的主要生长期,NPP总量占生长季总量的47.3%。2)空间特征上,2006-2016年塔里木河流域草地NPP分布呈现明显空间分异特征,总体分布特征为西北向东南呈递减趋势,草地NPP多年平均值为13.62 g C·m^-2·yr^-1。在垂直变化(海拔)上,呈现出随海拔升高NPP呈“降低-升高-降低”的特点;在水平变化上(经、纬度),草地NPP变化没有明显特征。3)空间稳定性上,塔里木河流域草地NPP变异系数介于0.19~3.17。草地NPP存在明显的空间差异性,草地NPP变异系数大部分地区均属于低值区,其中变异系数在0.5以下的占总面积的94.6%。高波动区域主要集中在“四源一干”和车尔臣诸小河流域。4)未来变化趋势上,塔里木河流域草地NPP Hurst指数介于0.10~0.97,均值为0.57。未来变化趋势呈持续性特征面积占71.6%,反持续性特征面积占28.4%,除开孔河流域北部及车尔臣诸小河西南大部呈反持续性特征,其余草地均呈现出持续性特征,预示着流域草地NPP未来处于持续增加趋势。草地NPP时空分布特征显示,塔里木河流域草地生态系统健康状况总体好转,局部恶化。

关键词: 净初级生产力, 塔里木河流域, 草地, CASA模型, 时空变化

Abstract: We analyzed spatio-temporal changes in grassland net primary productivity (NPP) in the Tarim River basin, based on an improved light use efficiency model (Carnegie-Ames-Stanford approach model, CASA) and moderate resolution imaging spectroradiometer (MODIS) data from 2006 to 2016. To study the temporal pattern, spatial characteristics, spatial stability and the time trend in grassland NPP were used to formulate a simple linear regression model, and derive the coefficient of variation and the Hurst index. The model analyses the temporal variation in grassland NPP in the Tarim River basin from 2006 to 2016. This analysis of the temporal pattern over the 11 years showed that the grassland NPP was variable with 64.1% of the total area, showing increased NPP and for 35.9% of the total area exhibiting falling NPP in the past 11 years. Overall, the grassland NPP of the Tarim basin was 1.31×10¹¹ g C·m^-2·yr^-1. The main growing season for grassland in the basin is from June to August each year, and NPP during this period accounts for 47.3% of the total annual NPP. A geographic gradient of decreasing grassland NPP from northwest to southeast was observed for these 2006-2016 Tarim River basin data. In the whole basin, the average annual grassland NPP estimated by the CASA model for 2006-2016, was 13.62 g C·m^-2·yr^-1. The altitudinal change in grassland NPP for the 11 years followed a “decreased-raised-lowered” pattern with increasing altitude, and also some smaller features related to latitude and longitude. The coefficient of variation of grassland NPP over the 11 years ranged from 0.19 to 3.17, in various localities, which indicated the grassland NPP has obvious spatial differentiation. The land area for which the coefficient of variation of grassland NPP is less than 0.5 accounts for 94.6% of the total surveyed land area. Areas of high NPP fluctuation include the Kaikong river basin, the Aksu river basin, the Yarkant river basin, the Hetian river basin, the Tarim River main stream basin, and the Qarqan river basin. The Hurst index of grassland NPP for the 11 years ranged from 0.10 to 0.97 and the mean value was 0.57. This indicates the grassland NPP is expected to maintain the same change-trend in the future. In summary, the patterns of spatio-temporal change in grassland NPP showed that the health status of the grassland ecosystem is improving in the majority of the Tarim River basin, but deteriorating in some local areas.

Key words: net primary productivity, Tarim river basin, grassland, CASA model, spatio-temporal changes

崔博超, 郑江华, 吐尔逊·哈斯木, 段素素, 杜梦洁. 塔里木河流域草地净初级生产力时空分异特征研究[J]. 草业学报, 2020, 29(6): 1-13.

CUI Bo-chao, ZHENG Jiang-hua, TUERXUN·Hasimu, DUAN Su-su, DU Meng-jie. Spatio-temporal characteristics of grassland net primary productivity (NPP) in the Tarim River basin[J]. Acta Prataculturae Sinica, 2020, 29(6): 1-13.

参考文献

[1] Yang H F, Gang C C, Mu S J, et al. Analysis of the spatio-temporal variation in net primary productivity of grassland during the past 10 years in Xinjiang. Acta Prataculturae Sinica, 2014, 23(3): 39-50.
杨红飞, 刚成诚, 穆少杰, 等. 近10年新疆草地生态系统净初级生产力及其时空格局变化研究. 草业学报, 2014, 23(3): 39-50.
[2] Field C B, Randerson J T, Almstrom C M. Global net primary production: Combining ecology and remote sensing. Remote Sensing of Environment, 1995, 51: 74-88.
[3] Cramer W, Ield C B. Omparing global models of terrestrial net primary productivity (NPP): Introduction. Global Change Biology, 1999, (5): 3-4.
[4] Field C J, Behrenfeld M T, Randerson J T, et al. Falkowski, paul. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science, 1998, 281: 237-240.
[5] 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(S1): 1-15.
[6] Imhoff M L, Ounoua L, Efries R, et al.The consequences of urban land transformation on net primary productivity in the United States. Remote Sensing of Environment, 2004, 89: 434-443.
[7] Del G S, Parton W, Stohlgren T, et al. Global potential net primary production predicted from vegetation class, precipitation, and temperature. Ecology, 2008, 89(8): 2117-2126.
[8] Wang Y B, Zhao Y H, Han L, et al. Spatiotemporal variation of vegetation net primary productivity and its driving factors in Qinling-Daba Mountains, China from 2000 to 2015. Chinese Journal of Applied Ecology, 2018, 29(7): 2373-2381.
王耀斌, 赵永华, 韩磊, 等. 2000—2015年秦巴山区植被净初级生产力时空变化及其趋动因子. 应用生态学报, 2018, 29(7): 2373-2381.
[9] Wang Z, Li D K. Spatial-temporal distribution of vegetation net primary productivity and its driving factors from 2000 to 2015 in Shaanxi, China. Chinese Journal of Applied Ecology, 2018, 29(6): 1876-1884.
王钊, 李登科. 2000—2015年陕西植被净初级生产力时空分布特征及其驱动因素. 应用生态学报, 2018, 29(6): 1876-1884.
[10] Chi Y, Shi H H, Sun J K, et al. Spatio-temporal characteristics and main influencing factors of vegetation net primary productivity in the Yellow River Delta in recent 30 years. Acta Ecologica Sinica, 2018, 38(8): 2683-2697.
池源, 石洪华, 孙景宽, 等. 近30年来黄河三角洲植被净初级生产力时空特征及主要影响因素. 生态学报, 2018, 38(8): 2683-2697.
[11] Sun R, Zhu Q J. Distribution and seasonal change of net primary productivity in china from April, 1992 to March, 1993. Acta Geographica Sinica, 2000, (1): 36-45.
孙睿, 朱启疆. 中国陆地植被净第一性生产力及季节变化研究. 地理学报, 2000, (1): 36-45.
[12] Sun J W, Guan D X, Wu J B, et al. Research advances in net primary productivity of terrestrial vegetation. World Forestry Research, 2012, 25(1): 1-6.
孙金伟, 关德新, 吴家兵, 等. 陆地植被净初级生产力研究进展. 世界林业研究, 2012, 25(1): 1-6.
[13] Monteith J L. Olar radiation and productivity in tropical ecosystems. Journal of Applied Ecology, 1972, 9: 747-766.
[14] Potter C S, Randerson J T, Field C B, et al. Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, 1993, 7(4): 811-841.
[15] Zhang R P. Analysis of grassland NPP and phenology in response to climate change in Xinjiang. Lanzhou: Lanzhou University, 2017.
张仁平. 新疆地区草地NPP和物候对气候变化的响应研究. 兰州: 兰州大学, 2017.
[16] Ren X. Study on correlation between net primary productivity of grassland and climatie factors in Xinjiang based on improved CASA model. Urumchi: Xinjiang University, 2017.
任璇. 基于改进CASA模型的新疆草地净初级生产力及与气象因子的相关性研究. 乌鲁木齐: 新疆大学, 2017.
[17] Du M J, Zheng J H, Ren X, et al. Effects of topography on the distribution pattern of net primary productivity of grassland in Changji Prefecture, Xinjiang. Acta Ecologica Sinica, 2018, 38(13): 4789-4799.
杜梦洁, 郑江华, 任璇, 等. 地形对新疆昌吉州草地净初级生产力分布格局的影响. 生态学报, 2018, 38(13): 4789-4799.
[18] Ju Q, Nuerbayi A, Pan X L. Degeneration and strategies for management of grassland of Xinjiang. Environmental Protection of Xinjiang, 2004, 24(3): 43-46.
鞠强, 努尔巴衣·阿不都沙勒克, 潘晓玲. 新疆草地退化及其治理. 新疆环境保护, 2004, 24(3): 43-46.
[19] Lin H L, Chang S H, Li F. Research progress on grassland net primary productivity (NPP) model. Pratacultural Science, 2007, 24(12): 26-29.
林慧龙, 常生华, 李飞. 草地净初级生产力模型研究进展. 草业科学, 2007, 24(12): 26-29.
[20] Fu A H, Chen Y N, Li W H. Assessment on ecosystem health in the Tarim River Basin. Acta Ecologica Sinica, 2009, 29(5): 2418-2426.
付爱红, 陈亚宁, 李卫红. 塔里木河流域生态系统健康评价. 生态学报, 2009, 29(5): 2418-2426.
[21] Gao X, Zhang S Q, Ye B S, et al. Glacier runoff change in the upper stream of Yarkant river and its impact on river runoff during 1961-2006. Journal of Glaciology and Geocryology, 2010, 32(3): 445-453.
高鑫, 张世强, 叶柏生, 等. 1961—2006年叶尔羌河上游流域冰川融水变化及其对径流的影响. 冰川冻土, 2010, 32(3): 445-453.
[22] Ren X, Zheng J H, Mu C, et al. Correlation analysis of the apatial-temporal variation of grassland net primary productivity and climate factors in Xinjiang in the past 15 years. Ecological Science, 2017, 36(3): 43-51.
任璇, 郑江华, 穆晨, 等. 新疆近15年草地NPP动态变化与气象因子的相关性研究. 生态科学, 2017, 36(3): 43-51.
[23] Bartholomé E, Belward A S. GLC2000: A new approach to global land cover mapping from earth observation data. International Journal of Remote Sensing, 2005, 26(9): 1959-1977.
[24] Zhu W Q, Pan Y Z, Long Z H, et al. Estimating net primary productivity of terrestrial vegetation based on GIS and RS: A case study in Inner Mongolia, China. Journal of Remote Sensing, 2005, (3): 300-307.
朱文泉, 潘耀忠, 龙中华, 等. 基于GIS和RS的区域陆地植被NPP估算——以中国内蒙古为例. 遥感学报, 2005, (3): 300-307.
[25] John R, Chen J, Lu N, et al. Predicting plant diversity based on remote sensing products in the semi-arid region of Inner Mongolia. Remote Sensing of Environment, 2008, 112: 2018-2032
[26] Wu H, An R, Li X X, et al. Remote sensing monitoring of grassland degradation based on NPP change in the Maduo County of the sources region of Yellow River. Pratacultural Science, 2011, 28(4): 536-542.
吴红, 安如, 李晓雪, 等. 基于净初级生产力变化的草地退化监测研究. 草业科学, 2011, 28(4): 536-542.
[27] Dong Y, Yan H M, Du W P, et al. Spatio-temporal analysis of grassland carrying capacity in Mongolian Plateau based on supply-consumption relationship. Journal of Natural Resources, 2019, 34(5): 1093-1107.
董昱, 闫慧敏, 杜文鹏, 等. 基于供给—消耗关系的蒙古高原草地承载力时空变化分析. 自然资源学报, 2019, 34(5): 1093-1107.
[28] Cao D, Yu F, Zhu W Q, et al. Valuation of economic losses from grassland ecosystem degradation using remote sensing data. Acta Scientiae Circumstantiae, 2011, 31(8): 1799-1807.
曹东, 於方, 朱文泉, 等. 遥感技术支持下的草地生态系统破坏经济损失评价. 环境科学学报, 2011, 31(8): 1799-1807.
[29] Abdimijit A, Alimujiang K, Alishir K, et al. The Cherchen River watershed in Xinjiang: Macroscopic spatiotemporal variation, controlling and driving effects. Journal of Glaciology and Geocryology, 2015, 37(2): 480-492.
阿布都米吉提·阿布力克木, 阿里木江·卡斯木, 艾里西尔·库尔班, 等. 新疆车尔臣河流域水域的宏观变化及其影响和驱动因素. 冰川冻土, 2015, 37(2): 480-492.
[30] Bai Y F, Xu H L, Wang X Y, et al. A primary investigation on net primary productivity model of herbaceous plant in the lower reaches of Tarim river, Xinjiang. Journal of Arid Land Resources and Environment, 2015, 29(9): 92-96.
白玉锋, 徐海量, 王希义, 等. 塔里木河下游荒漠草地植被净初级生产力模型初探. 干旱区资源与环境, 2015, 29(9): 92-96.
[31] Chen X, Bao A M, Wang X P, et al. Ecological effect evaluation of comprehensive control project in Tarim River Basin. Bulletin of the Chinese Academy of Sciences, 2017, 32(1): 20-28.
陈曦, 包安明, 王新平, 等. 塔里木河近期综合治理工程生态成效评估. 中国科学院院刊, 2017, 32(1): 20-28.
[32] Wei J B, Xiao D N, Xie F J. Evaluation and regulation principles for the effects of human activities on ecology and environment. Progress in Geography, 2006, (2): 36-45.
魏建兵, 肖笃宁, 解伏菊. 人类活动对生态环境的影响评价与调控原则. 地理科学进展, 2006, (2): 36-45.
[33] Du J Y, Yu D Y. Impacts of climate change and human activities on net primary productivity of grassland in agro-pastoral transitional zone in northern China. Journal of Beijing Normal University (Natural Science), 2018, 54(3): 365-372.
杜金燊, 于德永. 气候变化和人类活动对中国北方农牧交错区草地净初级生产力的影响. 北京师范大学学报(自然科学版), 2018, 54(3): 365-372.
[34] Diffenbaugh N S, Singh D, Mankin J S, et al. Quantifying the influence of global warming on unprecedented extreme climate events. Proceedings of the National Academy of Sciences, 2017, 114(19): 4881-4886.