青藏高原植被降水利用效率的空间格局及其对降水和气温的响应

doi:10.3724/SP.J.1258.2012.01237

摘要/Abstract

摘要：

植被降水利用效率(precipitation use efficiency, PUE)是反映生态系统水、碳循环相互关系的重要指标。该文利用GLOPEM-CEVSA模型模拟了青藏高原2000-2008年植被净初级生产力(net primary production, NPP), 以97个野外草地样点实测地上净初级生产力(above-ground net primary productivity, ANPP)对模拟NPP进行验证, 模拟NPP与ANPP线性显著相关(R ² = 0.49, p < 0.001)。利用降水量空间插值数据, 分析了近9年青藏高原植被PUE的空间分布、主要植被类型的PUE及其与降水量之间的变化关系。结果表明: 2000-2008年青藏高原地区植被年平均PUE沿东南向西北递减, 降水量和气温对植被PUE有着重要的影响; PUE在不同植被类型间差异较大, 其中农田PUE最高, 高寒草甸PUE高于高寒草原。在不同降水区域植被PUE与降水量的关系不同, 降水量低于90 mm的区域, 植被PUE值最低((0.026 ± 0.190) g C·m ^-2·mm ^-1, 平均值±标准偏差)、波动最大(变异系数CV = 721%), 与降水量和气温不相关(p = 0.38)。降水量为90-300 mm的地区, 植被PUE较低((0.029 ± 0.074) g C·m ^-2·mm ^-1, 平均值±标准偏差)、波动较大(CV = 252%), 与降水量和气温显著相关(p < 0.001), 降水量和气温能够解释PUE空间变化的43.4%, 其中降水量的影响是气温的1.7倍。降水量为300-650 mm的区域占整个研究区的45%, 主要植被类型为高寒草原, 植被PUE较高((0.123 ± 0.191) g C·m ^-2·mm ^-1, 平均值±标准偏差), CV为155%; 植被PUE的空间变化与降水量和气温极显著相关(p < 0.001), 降水量和气温能够解释植被PUE空间变化的97.8%, 但以气温影响为主导, 其影响是降水量的1.5倍。降水量为650 mm的区域, 植被PUE达到最高(0.26 g C·m ^-2·mm ^-1)。降水量为650-845 mm的区域主要是西藏林芝地区, 植被以常绿针叶林为主, PUE最高((0.210 ± 0.246) g C·m ^-2·mm ^-1, 平均值±标准偏差)、波动最小(CV = 117%); 降水量和气温可解释植被PUE空间变化的93.1% (p < 0.001), 降水量的影响是气温的3.5倍, 但其影响为负。

关键词: GLOPEM-CEVSA模型, 降水利用效率(PUE), 青藏高原

Abstract:

Aims Precipitation use efficiency (PUE) is a key to understanding the coupling between ecosystem carbon and water cycles. Our objective was to probe the spatial PUE pattern and its response to climate on the Qinghai- Xizang Plateau to better understand mechanisms of vegetation productivity and improve ecosystem process models. Methods GLOPEN-CEVSA model was applied to estimate net primary production (NPP) by using the Fraction of Photosynthetically Active Radiation Absorbed by Vegetation (MOD15A2), and spatially interpolated meteorological data in 2000-2008. The modeled NPP was significantly correlated with the observed above-ground net primary productivity (R ² = 0.49, p < 0.001, n = 97). The PUE was calculated as the ratio of NPP to the annual sum of precipitation. Important findings The spatial pattern of PUE showed large differences among vegetation types. Crops had the highest PUE, and alpine meadow had higher PUE than alpine steppe. These differences were related to the precipitation and temperature distribution on the plateau. The PUE was relatively stable and the lowest value of (0.026 ± 0.190) g C·m ^-2·mm ^-1 (mean ± standard deviation) with the highest coefficient of variance (CV) of 721% was where precipitation was < 90 mm. Where precipitation was 90-300 mm, PUE was relatively stable and also low ((0.029 ± 0.074) g C·m ^-2·mm ^-1) with relatively high CV (252%). Together precipitation and air temperature in this precipitation range explained 43.4% of the spatial variance of PUE, and the effect of precipitation was 1.7 times that of temperature (p < 0.001). The area with precipitation from 300-650 mm, mainly covered by alpine steppe (45%), had relatively high PUE ((0.123 ± 0.191) g C·m ^-2·mm ^-1) with a CV of 155%. The significant correlation of PUE with climate factors explained 97.8% spatial variance of PUE. Temperature had the dominant role, having 1.5 times the effect of precipitation. With increasing precipitation, PUE reached a peak of 0.26 g C·m ^-2·mm ^-1 at 650 mm of precipitation and then showed a decreasing trend. The precipitation of the mountainous Nyingchi region, Xizang, is >845 mm, and the region is mainly covered with evergreen needleleaf forest. It has relatively high PUE ((0.210 ± 0.246) g C·m ^-2·mm ^-1) with a minimum CV of 117%. Temperature and precipitation together explained 93.1% of the spatial variation of PUE for Nyingchi. Precipitation was negatively correlated with PUE and its effect was 3.5 times that of temperature.

Key words: GLOPEM-CEVSA model, precipitation use efficiency (PUE), Qinghai-Xizang Plateau

叶辉, 王军邦, 黄玫, 齐述华. 青藏高原植被降水利用效率的空间格局及其对降水和气温的响应. 植物生态学报, 2012, 36(12): 1237-1247. DOI: 10.3724/SP.J.1258.2012.01237

YE Hui, WANG Jun-Bang, HUANG Mei, QI Shu-Hua. Spatial pattern of vegetation precipitation use efficiency and its response to precipitation and temperature on the Qinghai-Xizang Plateau of China. Chinese Journal of Plant Ecology, 2012, 36(12): 1237-1247. DOI: 10.3724/SP.J.1258.2012.01237

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2012.01237

https://www.plant-ecology.com/CN/Y2012/V36/I12/1237

图/表 7

图1 研究区位置示意图及用于气象数据空间插值的气象观测台站空间分布、数字高程模型(DEM) (A)及用于GLOPEM- CEVESA模型输入的青藏高原地区植被类型图(B)。审图号: GS(2012)1602号

Fig. 1 Location of study sites and meteorological station and digital elevation model (DEM) data (A) used in meteorological data interpolation, and vegetation map (B) as an input data in GLOPEM-CEVSA model. DBF, deciduous broad-leaved forest; DNF, deciduous needleleaf forest; EBF, evergreen broad-leaved forest; ENF, evergreen needleleaf forest.

图2 GLOPEM-CEVSA模型模拟青藏高原植被净初级生产力(NPP) (A)和MOD17A3遥感产品NPP (B)与实测地上净初级生产力(ANPP)间存在极显著线性相关性。LCL, 置信下限; UCL, 置信上限。

Fig. 2 Simulated net primary productivity (NPP) by GLOPEM-CEVSA model (A) and the land product (MOD17A3) of MODIS (B) was significantly correlated with the observed above-ground net primary productivity (ANPP) on Qinghai-Xizang Plateau. LCL, lower confidence limit; UCL, upper confidence limit.

图3 2000-2008年青藏高原地区年降水量(A)、年平均气温(B)、植被净初级生产力(NPP) (C)和植被降水利用效率(PUE) (D)的空间格局。审图号: GS(2012)1602号

Fig. 3 Spatial patterns of annual precipitation (A), annual mean air temperature (B), net primary productivity (NPP) (C) and precipitation use efficiency (PUE) (D) of the vegetation on the Qinghai-Xizang Plateau from 2000 to 2008.

图4 青藏高原整个地区(A)和不同温度区(B)降水利用效率(PUE)随降水量的变化模式。

Fig. 4 Change pattern of precipitation use efficiency (PUE) with precipitation in the whole region (A) and different temperature areas (B) in the Qinghai-Xizang Plateau.

表1 2000-2008年青藏高原不同植被类型分布区域的年降水量、植被净初级生产力(NPP)及降水利用效率(PUE)

Table 1 Annual precipitation, net primary production (NPP) and precipitation use efficiency (PUE) for different vegetation distribution regions on the Qinghai-Xizang Plateau from 2000 to 2008

植被类型 Vegetation type	面积 Area (×10⁴km²)	年降水量 Annual precipitation (mm)	NPP (g C·m^-2·a^-1)	PUE (g C·m^-2·mm^-1)
植被类型 Vegetation type	面积 Area (×10⁴km²)	年降水量 Annual precipitation (mm)	NPP (g C·m^-2·a^-1)	平均值 Mean	标准偏差 SD
常绿针叶林 ENF	2.16	713.37	318.26	0.481	0.444
常绿阔叶林 EBF	6.77	753.59	352.16	0.507	0.422
落叶阔叶林 DBF	0.21	719.68	173.93	0.255	0.206
草地 Grass	119.41	451.17	55.26	0.107	0.149
灌丛 Shrub	33.18	481.06	56.77	0.116	0.112
荒漠 Desert	22.09	218.70	0.49	0.002	0.016
农田 Cropland	0.86	658.27	432.33	0.690	0.586

表2 2000-2008年青藏高原主要草地类型所在区域的年降水量、植被净初级生产力(NPP)及降水利用效率(PUE)

Table 2 Annual precipitation, net primary production (NPP) and precipitation use efficiency (PUE) for the region of main grass type regions on the Qinghai-Xizang Plateau from 2000 to 2008

植被类型 Vegetation type	面积 Area (×10⁴km²)	年降水量 Annual precipitation (mm)	NPP (g C·m^-2·a^-1)	PUE (g C·m^-2·mm^-1)
植被类型 Vegetation type	面积 Area (×10⁴km²)	年降水量 Annual precipitation (mm)	NPP (g C·m^-2·a^-1)	平均值 Mean	标准偏差 SD
高寒草原 Alpine steppe	26.47	289.75	9.42	0.033	0.046
高寒荒漠 Alpine desert	0.63	316.54	0.80	0.003	0.012
高寒草甸 Alpine meadow	38.96	507.62	53.98	0.100	0.103

图5 年降水量为300-470 mm (A)和470-535 mm (B)的区域内降水利用效率(PUE)与气温和降水量的关系。

Fig. 5 Relationships between precipitation use efficiency (PUE) and air temperature and precipitation in the areas with mean annual precipitation of 300-470 mm (A) and 470-535 mm (B).

参考文献 41

1	Austin AT, Vitousek PM (1998). Nutrient dynamics on a precipitation gradient in Hawai’i. Oecologia, 113, 519-529.
2	Bai YF, Wu JG, Qi X, Pan QM, Huang JH, Yang DL, Han XG ( 2008). Primary production and rain use efficiency across a precipitation gradient on the Mongolia Plateau. Ecology, 89, 2140-2153.
3	Cao MK, Woodward FI ( 1998a). Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their response to climatic change. Global Change Biology, 4, 185-198.
4	Cao MK, Woodward FI ( 1998b). Dynamic responses of terrestrial ecosystem carbon cycling to global climate change. Nature, 393, 249-252.
5	Cao MK ( 曹明奎), Yu GR ( 于贵瑞), Liu JY ( 刘纪远), Li KR ( 李克让 ) ( 2004). Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle. Science in China Series D: Earth Sciences (中国科学D辑: 地球科学), 48, 17-32. (in Chinese)
6	Chapin FS, Matson PA, Mooney HA (2002). Principles of Terrestrial Ecosystem Ecology. Translated by Li B (李博), Zhao B (赵斌), Peng RH (彭容豪)( 2005). Higher Education Press, Beijing. (in Chinese)
7	Fan JW ( 樊江文), Shao QQ ( 邵全琴), Wang JB ( 王军邦), Chen ZQ ( 陈卓奇), Zhong HP ( 钟华平 ) ( 2011). An analysis of temporal-spatial dynamics of grazing pressure on grassland in Three Rivers Headwater Region. Chinese Journal of Grassland (中国草地学报), 33(3), 64-72. (in Chinese with English abstract)
8	Fan JW, Wang K, Zhong HP, Hu ZM, Han B, Zhang WY, Wang JB ( 2009). Allocation of vegetation biomass across a climate-related gradient in the grasslands of Inner Mongolia. Journal of Arid Environments, 73, 521-528.
9	Fan JW, Zhong HP, Harris W, Yu GR, Wang SQ, Hu ZM, Yue YZ ( 2008). Carbon storage in the grasslands of China based on field measurements of above- and below-ground biomass. Climatic Change, 86, 375-396.
10	Fang JY ( 方精云), Liu GH ( 刘国华), Xu SL ( 徐嵩龄 ) ( 1996a). Biomass and net production of forest vegetation in China. Acta Ecologica Sinica (生态学报), 16, 497-508. (in Chinese with English abstract)
11	Fang JY ( 方精云), Liu GH ( 刘国华), Xu SL ( 徐嵩龄 ) (1996b). Carbon storage in terrestrial ecosystem in China (中国陆地生态系统的碳库). In: Wang GC (王庚辰), Wen YP (温玉璞) eds. The Measurement of Greenhouse Gas and Their Release and Related Processes (温室气体浓度和排放监测及相关过程). Environment Science Press, Beijing. 109-128. (in Chinese)
12	Feng S ( 冯松), Tang MC ( 汤懋苍), Wang DM ( 王冬梅 ) ( 1998). New evidence of the Tibet Plateau as promoter area of Chinese climate change. Chinese Science Bulletin (科学通报), 43, 633-636. (in Chinese)
13	Feng ZW ( 冯宗炜), Wang XK ( 王效科), Wu G ( 吴刚 ) ( 1999). Biomass and Productivity of Forest Ecosystem in China (中国森林生态系统的生物量和生产力). Science Press, Beijing. (in Chinese)
14	Fischer RA, Turner NC ( 1978). Plant productivity in the arid and semiarid zones. Annual Review of Plant Physiology, 29, 277-317.
15	Halse SA, Scanlon MD, Cocking JS, Smith MJ, Kay WR ( 2007). Factors affecting river health and its assessment over broad geographic ranges: the Western Australian experience. Environmental Monitoring and Assessment, 134, 161-175.
16	Hutchinson MF ( 2001). Anusplin Version 4.2 User Guide. Centre for Resource and Environmental Studies, Australian National University, Canberra.
17	Hu ZM, Yu GR, Fan JW, Zhong HP, Wang SQ, Li SG ( 2010). Precipitation-use efficiency along a 4500-km grassland transect. Global Ecology and Biogeography, 19, 842-851.
18	Hu ZM ( 胡中民), Yu GR ( 于贵瑞), Wang QF ( 王秋凤), Zhao FH ( 赵风华 ) ( 2009). Ecosystem level water use efficiency: a review. Acta Ecologica Sinica (生态学报), 29, 1498-1507. (in Chinese with English abstract)
19	Huxman TE, Smith MD, Fay PA, Knapp AK, Shaw MR, Loik ME, Smith SD, Tissue DT, Zak JC, Weltzin JF, Pockman WT, Sala OE, Haddad BM, Harte J, Koch GW, Schwinning S, Small EE, Williams DG ( 2004). Convergence across biomes to a common rain-use efficiency. Nature, 429, 651-654.
20	Lauenroth WK, Burke IC, Paruelo JM ( 2000). Patterns of production and precipitation-use efficiency of winter wheat and native grasslands in the central Great Plains of the United States. Ecosystems, 3, 344-351.
21	Le Houérou HN ( 1984). Rain use efficiency: a unifying concept in arid-land ecology. Journal of Arid Environments, 7, 213-247.
22	Lieth H (1975). Modeling the primary production of the world. In: Lieth H, Whittaker RH eds. Primary Productivity of the Biosphere. Springer-Verlag, Berlin. 237-263.
23	Liu ML ( 刘明亮 ) ( 2001). Land-Use/Land-Cover Change and Terrestrial Ecosystem Phytomass Carbon Pool and Production in China (中国土地利用/土地覆盖变化与陆地生态系统植被碳库和生产力研究). PhD dissertation, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing. (in Chinese with English abstract)
24	Liu XD, Chen BD ( 2000). Climatic warming in the Tibetan Plateau during recent decades. International Journal of Climatology, 20, 1729-1742.
25	Liu YH ( 刘勇洪), Niu Z ( 牛铮), Xu YM ( 徐永明), Wang CY ( 王长耀), Li GC ( 李贵才 ) ( 2006). Design of land cover classification system for China and its application research based on MODIS data. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), 22(5), 99-104. (in Chinese)
26	Lu L ( 卢玲), Li X ( 李新), Huang CL ( 黄春林 ), Veroustraete F ( 2007). Analysis of the spatio-temporal characteristics of water use efficiency of vegetation in West China. Journal of Glaciology and Geocryology (冰川冻土), 29, 777-784. (in Chinese with English abstract)
27	Paruelo JM, Lauenroth WK, Burke IC, Sala OE ( 1999). Grassland precipitation-use efficiency varies across a resource gradient. Ecosystems, 2, 64-68.
28	Prince SD, Goward SN ( 1995). Global primary production: a remote sensing approach. Journal of Biogeography, 22, 815-835.
29	Rosenzweig ML ( 1968). Net primary productivity of terrestrial communities: prediction from climatological data. The American Naturalist, 102, 67-74.
30	Sala OE, Parton WJ, Joyce LA, Lauenroth WK ( 1988). Primary production of the central grassland region of the United States. Ecology, 69, 40-45.
31	Tang MC ( 汤懋苍), Li CQ ( 李存强 ) (1992). Evidence analysis on the Tibet Plateau as promoter area of Chinese climate change. In: The China Society on Tibet Plateau (中国青藏高原研究会) eds. Proceedings of the 1st International Symposium on the Tibetan Plateau (中国青藏高原研究会第一届学术论文会论文选). Sciences Press, Beijing. 42-48. (in Chinese)
32	Wang JB, Liu JY, Cao MK, Liu YF, Yu GR, Li GC, Qi SH, Li KR ( 2011). Modelling carbon fluxes of different forests by coupling a remote-sensing model with an ecosystem process model. International Journal of Remote Sensing, 32, 6539-6567.
33	Wang JB ( 王军邦), Liu JY ( 刘纪远), Shao QQ ( 邵全琴), Liu RG ( 刘荣高), Fan JW ( 樊江文), Chen ZQ ( 陈卓奇 ) ( 2009). Spatial-temporal patterns of net primary productivity for 1988-2004 based on GLOPEM-CEVSA model in the “Three-river Headwaters” region of Qinghai Pro- vince, China. Chinese Journal of Plant Ecology (植物生态学报), 33, 254-269. (in Chinese with English abstract)
34	Wang Y ( 王英), Cao MK ( 曹明奎), Tao B ( 陶波), Li KR ( 李克让 ) ( 2006). The characteristics of spatio-temporal patterns in precipitation in China under the background of global climate change. Geographical Research (地理研究), 25, 1031-1041. (in Chinese with English abstract)
35	Yang YH, Fang JY, Fay PA, Bell JE, Ji CJ ( 2010). Rain use efficiency across a precipitation gradient on the Tibetan Plateau. Geophysical Research Letters, 37, L15702.
36	Yao TD ( 姚檀栋), Zhu LP ( 朱立平 ) ( 2006). The response of environmental changes on Tibetan Plateau to global changes and adaptation strategy. Advances in Earth Science (地球科学进展), 21, 459-464. (in Chinese with English abstract)
37	Yu GR ( 于贵瑞 ) (2009). Scientific Frontier on Human Activities and Ecosystem Changes (人类活动与生态系统变化的前沿科学问题). Higher Education Press, Beijing. (in Chinese)
38	Yu GR, Song X, Wang QF, Liu YF, Guan DX, Yan JH, Sun XM, Zhang LM, Wen XF ( 2008). Water use efficiency of forest ecosystems in eastern China and its relations to climatic variables. New Phytologist, 177, 927-937.
39	Yu GR ( 于贵瑞), Wang QF ( 王秋凤 ) (2010). Ecophysiology of Plant Photosynthesis, Transpiration, and Water Use (植物光合、蒸腾与水分利用的生理生态学). Science Press, Beijing. (in Chinese)
40	Zhao J ( 赵济), Chen CK ( 陈传康 ) (1999). Geography of China (中国地理). Higher Education Press, Beijing. (in Chinese)
41	Zheng D ( 郑度), Li BY ( 李炳元 ) ( 1999). Progress in studies on geographical environments of the Qinghai-Xizang Plateau. Scientia Geographica Sinica (地理科学), 9, 289-296. (in Chinese with English abstract)

[1]	赵艳超, 陈立同. 土壤养分对青藏高原高寒草地生物量响应增温的调节作用[J]. 植物生态学报, 2023, 47(8): 1071-1081.
[2]	师生波, 周党卫, 李天才, 德科加, 杲秀珍, 马家麟, 孙涛, 王方琳. 青藏高原高山嵩草光合功能对模拟夜间低温的响应[J]. 植物生态学报, 2023, 47(3): 361-373.
[3]	师生波, 师瑞, 周党卫, 张雯. 低温对高山嵩草叶片光化学和非光化学能量耗散特征的影响[J]. 植物生态学报, 2023, 47(10): 1441-1452.
[4]	林马震, 黄勇, 李洋, 孙建. 高寒草地植物生存策略地理分布特征及其影响因素[J]. 植物生态学报, 2023, 47(1): 41-50.
[5]	朱玉英, 张华敏, 丁明军, 余紫萍. 青藏高原植被绿度变化及其对干湿变化的响应[J]. 植物生态学报, 2023, 47(1): 51-64.
[6]	魏瑶, 马志远, 周佳颖, 张振华. 模拟增温改变青藏高原植物繁殖物候及植株高度[J]. 植物生态学报, 2022, 46(9): 995-1004.
[7]	金伊丽, 王皓言, 魏临风, 侯颖, 胡景, 吴铠, 夏昊钧, 夏洁, 周伯睿, 李凯, 倪健. 青藏高原植物群落样方数据集[J]. 植物生态学报, 2022, 46(7): 846-854.
[8]	卢晶, 马宗祺, 高鹏斐, 樊宝丽, 孙坤. 祁连山区演替先锋物种西藏沙棘的种群结构及动态对海拔梯度的响应[J]. 植物生态学报, 2022, 46(5): 569-579.
[9]	胡潇飞, 魏临风, 程琦, 吴星麒, 倪健. 青藏高原地区气候图解数据集[J]. 植物生态学报, 2022, 46(4): 484-492.
[10]	吴赞, 彭云峰, 杨贵彪, 李秦鲁, 刘洋, 马黎华, 杨元合, 蒋先军. 青藏高原高寒草地退化对土壤及微生物化学计量特征的影响[J]. 植物生态学报, 2022, 46(4): 461-472.
[11]	郑周涛, 张扬建. 1982-2018年青藏高原水分利用效率变化及归因分析[J]. 植物生态学报, 2022, 46(12): 1486-1496.
[12]	刘宁, 彭守璋, 陈云明. 气候因子对青藏高原植被生长的时间效应[J]. 植物生态学报, 2022, 46(1): 18-26.
[13]	聂秀青, 王冬, 周国英, 熊丰, 杜岩功. 三江源地区高寒湿地土壤微生物生物量碳氮磷及其化学计量特征[J]. 植物生态学报, 2021, 45(9): 996-1005.
[14]	陈哲, 汪浩, 王金洲, 石慧瑾, 刘慧颖, 贺金生. 基于物候相机归一化植被指数估算高寒草地植物地上生物量的季节动态[J]. 植物生态学报, 2021, 45(5): 487-495.
[15]	刘攀, 王文颖, 周华坤, 毛旭锋, 刘艳方. 青藏高原人工草地土壤可溶性氮组分与植被生产力动态变化过程[J]. 植物生态学报, 2021, 45(5): 562-572.