Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin

doi:10.17521/cjpe.2015.0253

Abstract

Abstract: AimsQuantifying the gross primary productivity (GPP) of vegetation is of primary interest in studies of global carbon cycle. This study aims to optimize the MODIS GPP model for specific environments of a fragile waterhead ecosystem, by performing simulations of long-term (from 2001 to 2012) GPP with optimized MOD_17 model, and to analyze the response of GPP to the local climatic variations.Methods The original MODIS GPP products that underestimate GPP were validated against two years (2010-2011) of eddy covariance (EC) data at two sites (i.e. an alpine pasture site and a forest site, respectively) in the upstream of Heihe River Basin. Three comparative experiments were then conducted to analyze the effects of input parameters derived from three sources (i.e. meteorological, biome-specific, and fraction of absorbed photosynthetically active radiation (fPAR) parameters) on the model behavior. After refining the model-driven parameters, long-term GPPs of the study area were estimated using the optimized MOD_17 model, and the Least Absolute Deviation method was applied to analyze the partial correlations between interannual GPPs and climatic variables (temperature, precipitation and vapor pressure deficit (VPD)). Important findings The uncertainties in the original MODIS GPP products are attributable to biome-specific parameters, input data (e.g. meteorological and radiometry data) and vegetation maps. At the pasture site, the light use efficiency had the strongest impact on the GPP simulations. The refined fPAR calculated from the leaf area index (LAI) products of Global Land Surface Satellite (GLASS) greatly improved the GPP estimates, especially at the forest site. The GPPs from the optimized MOD_17 model well matched the EC data (R² = 0.90, root mean squared error (RMSE) = 1.114 g C·m^-2·d^-1 at the alpine pasture site; R² = 0.91, RMSE = 0.649 g C·m^-2·d^-1 at the forest site). The time series of GPPs displayed an up trend at an average rate of 9.58 g C·m^-2·a^-1 from 2001 to 2012. Examination of the partial correlations between interannual GPPs and climatic variables showed that the annual mean temperature and VPD generally had significant positive impacts on GPP, and the annual precipitation had a negative impact on GPP.

http://jtp.cnki.net/bilingual/detail/html/ZWSB201601001

Key words: gross primary productivity, MOD_17 model, trend analysis, climatic factors, partial correlation analysis

YAN Min, LI Zeng-Yuan, TIAN Xin, CHEN Er-Xue, GU Cheng-Yan. Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin[J]. Chin J Plant Ecol, 2016, 40(1): 1-12.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2015.0253

https://www.plant-ecology.com/EN/Y2016/V40/I1/1

Figures/Tables 9

Fig. 1 The location and vegetation classification map of the upstream of Heihe River Basin.

Fig. 2 Seasonal variations of the 8-day minimum temperature (Tmin), photosynthetically active radiation (PAR), and vapor pressure deficit (VPD) at the Arou station.

Fig. 3 Seasonal variations of the 8-day minimum temperature (Tmin), photosynthetically active radiation (PAR), and vapor pressure deficit (VPD) at the Guantan Station.

Table 1 The lookup table of MOD_17 model

植被类型 Vegetation type	最大光能利用率 Maximum light use efficiency (g·(MJ·APAR)^-1)	最低温度最小值 Lowest minimum temperature, T_minmin (℃)	最低温度最大值 Highest minimum temperature, T_minmax (℃)	饱和水汽压差最大值 Maximum vapor pressure deficit (VPD_max) (Pa)	饱和水汽压差最小值 Minimum vapor pressure deficit (VPD_min) (Pa)
常绿针叶林 Evergreen needle-leaved forest	1.008	-8	8.31	2 500	650
常绿阔叶林 Evergreen broad-leaved forest	1.159	-8	9.09	3 900	1 100
落叶针叶林 Deciduous needle-leaved forest	1.103	-8	10.44	3 100	650
落叶阔叶林 Deciduous broad-leaved forest	1.044	-8	7.94	2 500	650
混交林 Mixed forest	1.116	-8	8.50	2 500	650
多树草原 Grassy woodland	0.800	-8	11.39	3 100	930
稀树草原 Savanna	0.768	-8	11.39	3 100	650
郁闭灌丛 Closed shrubland	0.888	-8	8.61	3 100	650
开放灌丛 Open shrubland	0.774	-8	8.80	3 600	650
草原 Grassland	0.680	-8	12.02	3 500	650
农田 Cropland	0.680	-8	12.02	4 100	650

Fig. 4 Comparisons between the moderate-resolution imaging spectroradiometer fraction of absorbed photosynthetically active radiation (MOD_fPAR) and the Global Land Surface Satellite fraction of absorbed photosynthetically active radiation (GLASS_ fPAR) at the Arou Station (A) and the Guantan Station (B).

Fig. 5 Comparisons of original and optimized gross primary productivity products at the Arou Station (A, C) and the Guantan Station (B, D). GPP_EC, eddy covariance measurements; GPP_Default, original MODIS GPP products; GPP_MOD1, GPP_MOD2, and GPP_MOD3 are the three comparative experiments described in the study.

Fig. 6 Maps of the spatial distribution of annual mean gross primary productivity (GPP, g C·m-2·a-1) (A) and the trend of changes (B) between 2001 and 2012.

Fig. 7 The trend of changes in temperature, precipita- tion and vapor pressure deficit between 2001 and 2012.

Fig. 8 The maps of partial correlations between gross primary productivity and climatic factors in the upstream of Heihe River Basin between 2001 and 2012.

References 34

1	Beer C, Reichstein M, Tomelleri E, Ciais P, Jung M, Carvalhais N, Rödenbeck C, Arain MA, Baldocchi D, Bonan GB, Bondeau A, Cescatti A, Lasslop G, Lindroth A, Lomas M, Luyssaert S, Margolis H, Oleson KW, Roupsard O, Veenendaal E, Viovy N, Williams C, Lan Woodward F, Papale D (2010). Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate.Science, 329, 834-838.
2	Birkes D, Dodge Y (1993). Alternative Methods of Regression. John Wiley & Sons, New York. 228.
3	Chen ZH, Ma QY, Wang J, Qi Y, Li J, Huang CL, Ma MG, Yang GJ (2008). Estimation of Heihe Basin net primary productivity using the CASA model.Journal of Natural Resources, 23, 263-273.
	(in Chinese with English abstract) [陈正华, 麻清源, 王建, 祁元, 李净, 黄春林, 马明国, 杨国靖 (2008). 利用CASA模型估算黑河流域净第一性生产力. 自然资源学报, 23, 263-273.]
4	Coops NC, Black TA, Jassal RS, Trofymow JA, Morgenstern K (2007). Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand.Remote Sensing of Environment, 107, 385-401.
5	Coops NC, Ferster CJ, Waring RH, Nightingale J (2009). Comparison of three models for predicting gross primary production across and within forested ecoregions in the contiguous United States.Remote Sensing of Environment, 113, 680-690.
6	Dai ZH, Birdsey RA, Johnson KD, Dupuy JM, Hernandez- Stefanoni JL, Richardson K (2014). Modeling carbon stocks in a secondary tropical dry forest in the Yucatan Peninsula, Mexico.Water, Air, & Soil Pollution, 225, 1925.
7	Desai AR, Richardson AD, Moffat AM, Kattge J, Hollinger DY, Barr A, Falge E, Noormets A, Papale D, Reichstein M, Stauch VJ (2008). Cross-site evaluation of eddy covariance GPP and RE decomposition techniques.Agricultural and Forest Meteorology, 148, 821-838.
8	Dury M, Hambuckers A, Warnant P, Henrot A, Favre E, Ouberdous M, François L (2011). Responses of European forest ecosystems to 21st century climate: Assessing changes in interannual variability and fire intensity.Forest-Biogeosciences and Forestry, 4, 82-99.
9	Guo Y, Li ZY, Chen EX, Tian X, Ling FL (2015). Estimating forest above-ground biomass in the upper reaches of Heihe River Basin using multi-spectral remote sensing.Scientia Silvae Sinicae, 51(1), 140-149.
	(in Chinese with English abstract) [郭云, 李增元, 陈尔学, 田昕, 凌飞龙 (2015). 甘肃黑河流域上游森林地上生物量的多光谱遥感估测. 林业科学, 51(1), 140-149.]
10	Heinsch FA, Reeves M, Votava P, Kang SY, Milesi C, Zhao MS, Glassy J, Jolly WM, Loehman R, Bowker CF, Kim- ball JS, Nemani RR, Running SW (.
11	Cited:2003-12-02.
12	Jarvis PG, Leverenz JW (1983). Productivity of temperate, deciduous and evergreen forests. In: Lange OL, Nobel PS, Osmond CB, Ziegler H eds. Physiological Plant Ecology IV. Springer-Verlag, New York. 233-280.
13	Jin BW (2007). Measurement and Study on Climatical and Hydrological Effect and Ecological Function of Water Conservation Forest in Qilian Mountains. PhD dissertation, Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Beijing. 41-48.
	(in Chinese with English abstract) [金博文 (2007). 祁连山水源涵养林的气候和水文效应及生态功能试验研究. 博士学位论文, 中国科学院寒区旱区环境与工程研究所, 北京. 41-48.]
14	Li X, Ma MG, Wang J, Liu Q, Che T, Hu ZY, Xiao Q, Liu QH, Su PX, Chu RZ, Jin R, Wang WZ, Ran YH (2008). Si- multaneous remote sensing and ground-based experiment in the Heihe River Basin: Scientific objectives and experiment design.Advances in Earth Science, 23, 897-914.
	(in Chinese with English abstract) [李新, 马明国, 王建, 刘强, 车涛, 胡泽勇, 肖青, 柳钦火, 苏培玺, 楚荣忠, 晋锐, 王维真, 冉有华 (2008). 黑河流域遥感—地面观测同步试验: 科学目标与试验方案. 地球科学进展, 23, 897-914.]
15	Li XP (2013). The Simulation of NPP Based on Remote Sensing and Its Temporal-Spatial Analysis Over Heihe River Basin. Master degree dissertation, Shaanxi Normal University, Xi’an. 46-48.
	(in Chinese with English abstract) [李旭谱 (2013). 黑河流域NPP遥感估算及其时空变化特征分析. 硕士学位论文, 陕西师范大学, 西安. 46-48.]
16	Long HL, Li XB, Huang LM, Wang H, Wei DD (2010). Net primary productivity in grassland ecosystem in Inner Mongolia and its relationship with climate.Chinese Journal of Plant Ecology, 34, 781-791.
	(in Chinese with English abstract) [龙慧灵, 李晓兵, 黄玲梅, 王宏, 魏丹丹 (2010). 内蒙古草原生态系统净初级生产力及其与气候的关系. 植物生态学报, 34, 781-791.]
17	Lu L, Li X, Veroustraete F (2005). Estimation of net primary productivity of Heihe River Basin using remote sensing.Journal of Desert Research, 25, 823-830.
	(in Chinese with English abstract) [卢玲, 李新, Veroustraete F (2005). 黑河流域植被净初级生产力的遥感估算. 中国沙漠, 25, 823-830.]
18	Lu L, Li X, Veroustraete F, Kang E, Wang J (2009). Analysing the forcing mechanisms for net primary productivity changes in the Heihe River Basin, northwest China.International Journal of Remote Sensing, 30, 793-816.
19	Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ, Myneni RB, Running SW (2003). Climate- driven increases in global terrestrial net primary production from 1982 to 1999.Science, 300, 1560-1563.
20	Pan XD (2012). Development of High Spatial and Temporal Resolution Meteorological Forcing Data in the Heihe River Basin: Model Simulation and Data Assimilation. PhD dissertation, Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou. 2-8.
	(in Chinese with English abstract) [潘小多 (2012). 黑河流域高分辨率大气驱动数据的制备: 模拟与数据同化. 博士学位论文, 中国科学院寒区旱区环境与工程研究所, 兰州. 2-8.]
21	Piao SL, Wang XH, Ciais P, Zhu B, Wang T, Liu J (2011). Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006.Global Change Biology, 17, 3228-3239.
22	Plummer S (2006). On validation of the MODIS gross primary production product.IEEE Transactions on Geoscience and Remote Sensing, 44, 1936-1938.
23	Ran YH, Li X, Lu L, Li ZY (2012). Large-scale land cover mapping with the integration of multi-source information based on the Dempster-Shafer theory.International Jour- nal of Geographical Information Science, 26, 169-191. doi: 10.1080/13658816.2011.577745.
24	Running SW, Nemani R, Glassy JM, Thornton PE (.
25	Cited:2015-07-03.
26	Running SW, Thornton PE, Nemani R, Glassy J (2000). Global terrestrial gross and net primary productivity from the earth observing system. In: Sala OE, Jackson RB, Mooney H eds. Methods in Ecosystem Science. Springer-Verlag, New York. 44-57.
27	Turner DP, Ritts WD, Cohen WB, Gower ST, Running SW, Zhao MS, Costa MH, Kirschbaum AA, Ham JM, Saleska SR, Ahl DE (2006b). Evaluation of MODIS NPP and GPP products across multiple biomes.Remote Sensing of Environment, 102, 282-292.
28	Wang XF (2012). Terrestrial Ecosystem Productivity Simulation over Heihe River Basin. PhD dissertation, Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Beijing. 2-8.
	(in Chinese with English abstract) [王旭峰 (2012). 黑河流域陆地生态系统生产力模拟研究. 博士学位论文, 中国科学院寒区旱区环境与工程研究所, 北京. 2-8.]
29	Wang XF, Ma MG, Li X, Song Y, Tan JL, Huang GH, Zhang ZH, Zhao TB, Feng JM, Ma ZG, Wei W, Bai YF (2013). Validation of MODIS-GPP product at 10 flux sites in northern China.International Journal of Remote Sensing, 34, 587-599.
30	Wang XF, Ma MG, Song Y, Tan JL, Wang HB (2014). Cou- pling of a biogeochemical model with a simultaneous heat and water model and its evaluation at an alpine meadow site.Environmental Earth Sciences, 72, 4085-4096.
31	Xiao ZQ, Liang SL, Wang JD, Chen P, Yin XJ, Zhang LQ, Song JL (2014). Use of general regression neural networks for generating the GLASS Leaf Area Index Product from time-series MODIS surface reflectance.IEEE Transactions on Geoscience and Remote Sensing, 52, 209-223.
32	Yang FH, Lchii K, White MA, Hashimoto H, Michaelis AR, Votava P, Zhu AX, Huete A, Running SW, Nemani RR (2007). Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through support vector machine approach.Remote Sensing of Environment, 110, 109-122.
33	Zhang YQ, Yu Q, Jiang J, Tang YH (2008). Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau.Global Change Biology, 14, 757-767.
34	Zhou GS, Wang YH, Jiang YL, Yang LM (2002). Conversion of terrestrial ecosystems and carbon cycling.Acta Phytoecologica Sinica, 26, 250-254.
	(in Chinese with English abstract) [周广胜, 王玉辉, 蒋延玲, 杨利民 (2002). 陆地生态系统类型转变与碳循环. 植物生态学报, 26, 250-254.]

[1]	Yu-Meng Yang Quan Lai Xin-Yi Liu. Quantitative analysis of climate change and human activities on vegetation GPP in Inner Mongolia [J]. Chin J Plant Ecol, 2024, 48(预发表): 0-0.
[2]	LIU Pei-Rong, TONG Xiao-Juan, MENG Ping, ZHANG Jin-Song, ZHANG Jing-Ru, YU Pei-Yang, ZHOU Yu. Effect of diffuse radiation on gross primary productivity of typical planted forests in eastern China [J]. Chin J Plant Ecol, 2022, 46(8): 904-918.
[3]	YUAN Yuan, MU Yan-Mei, DENG Yu-Jie, LI Xin-Hao, JIANG Xiao-Yan, GAO Sheng-Jie, ZHA Tian- Shan, JIA Xin. Effects of land cover and phenology changes on the gross primary productivity in an Artemisia ordosica shrubland [J]. Chin J Plant Ecol, 2022, 46(2): 162-175.
[4]	XUE Jin-Ru, LÜ Xiao-Liang. Assessment of vegetation productivity under the implementation of ecological programs in the Loess Plateau based on solar-induced chlorophyll fluorescence [J]. Chin J Plant Ecol, 2022, 46(10): 1289-1304.
[5]	XU Guang-Lai, LI Ai-Juan, XU Xiao-Hua, YANG Xian-Cheng, YANG Qiang-Qiang. NDVIdynamics and driving climatic factors in the Protected Zones for Ecological Functions in China [J]. Chin J Plant Ecol, 2021, 45(3): 213-223.
[6]	DING Jian-Xi, ZHOU Lei, WANG Yong-Lin, ZHUANG Jie, CHEN Ji-Jing, ZHOU Wen, ZHAO Ning, SONG Jun, CHI Yong-Gang. Application prospects for combining active and passive observations of chlorophyll fluorescence [J]. Chin J Plant Ecol, 2021, 45(2): 105-118.
[7]	Yuan-Feng SUN, Hong-Wei WAN, Yu-Jin ZHAO, Shi-Ping CHEN, Yong-Fei BAI. Spatial patterns and drivers of root turnover in grassland ecosystems in China [J]. Chin J Plan Ecolo, 2018, 42(3): 337-348.
[8]	ZHU Hong, ZHU Shu-Xia, LI Yong-Fu, YI Xian-Gui, DUAN Yi-Fan, WANG Xian-Rong. Leaf phenotypic variation in natural populations of Cerasus dielsiana [J]. Chin J Plant Ecol, 2018, 42(12): 1168-1178.
[9]	Ke-Qing WANG, He-Song WANG, Osbert Jianxin SUN. Application and comparison of remote sensing GPP models with multi-site data in China [J]. Chin J Plant Ecol, 2017, 41(3): 337-347.
[10]	SUN Xiao-Peng, WANG Tian-Ming, KOU Xiao-Jun, GE Jian-Ping. Normalized difference vegetation index dynamic change and its driving factor analysis with long time series in the Jinghe River watershed on the Loess Plateau of China [J]. Chin J Plant Ecol, 2012, 36(6): 511-521.
[11]	LI He, ZHANG Wei-Kang, WANG Guo-Hong. Relationship between climatic factors and geographical distribution of spruce forests in China [J]. Chin J Plant Ecol, 2012, 36(5): 372-381.
[12]	YU Zhen, SUN Peng-Sen, LIU Shi-Rong. Response of normalized difference vegetation index in main vegetation types to climate change and their variations in different time scales along a North-South Transect of Eastern China [J]. Chin J Plant Ecol, 2011, 35(11): 1117-1126.
[13]	HAO Yan-Bin, WANG Yan-Fen, CUI Xiao-Yong. Drought stress reduces the carbon accumulation of the Leymus chinensis steppe in Inner Mongolia, China [J]. Chin J Plant Ecol, 2010, 34(8): 898-906.
[14]	WU Fang, CHEN Yun-Ming, YU Zhan-Hui. Growing season sap-flow dynamics of Robinia pseudoacacia plantation in the semi-arid region of Loess Plateau, China [J]. Chin J Plant Ecol, 2010, 34(4): 469-476.
[15]	BAI T. Jay, LIANG Ying-Quan. VEGETATION MONITORING AND TREND ANALYSIS: DISCUSSIONS ON QUANTITATIVE VEGETATION ECOLOGY [J]. Chin J Plant Ecol, 2008, 32(4): 967-976.