Temporal and spatial variations of ecosystem photosynthetic parameters in arid and semi-arid areas of China and its influencing factors

doi:10.17521/cjpe.2021.0426

Abstract

Abstract:

Aims Ecosystem apparent quantum yield (α) and maximum photosynthetic rate (P_max) are important parameters reflecting the photosynthetic characteristics of ecosystem, and also important physiological parameters in ecosystem model simulation and remote sensing inversion. The objectives of this study were to: (1) analyze the characteristics and spatial-temporal variations of the light response parameters of ecosystems in arid and semi-arid areas; and (2) reveal the key factors affecting the photosynthetic parameters and its underlying mechanisms in arid and semi-arid areas, so as to provide a scientific basis for the study of ecosystem photosynthesis and response to climate change on a regional scale.

Methods The observational fluxes and synchronous meteorological data of 9 stations in arid and semi-arid area were integrated from ChinaFLUX. The non-rectangular hyperbolic equations were used to fit the light response parameters and which influencing factors were identified by linear regression, multiple stepwise regression and path analysis.

Important findings There were obvious spatial and temporal variations in ecosystem photosynthetic parameters in arid and semi-arid areas. The photosynthetic parameters increased gradually from desert, desert grassland, typical grassland to meadow grassland. Precipitation was the dominant environmental factor of the spatial variations of photosynthetic parameters, and it also affected the spatial variation of leaf area index, both of them jointly determine the spatial variation of photosynthetic parameters. α and P_max have an obvious increasing trend with the increase of precipitation, and there was a significant negative correlation between temperature and α, but the effect of radiation on the spatial variation of photosynthetic parameters was not significant. In the growing season, P_max and α increased first and then decreased, but the monthly variability and peak time of different vegetation types were different, the photosynthetic parameters of meadow grassland had the greatest monthly variability. The monthly dynamics of α was mainly controlled by temperature and radiation, while P_max was regulated by temperature and radiation in desert and desert grassland, and by soil water content in typical grassland and meadow grassland. Ecosystem α were 0.000 47-0.002 12 mg·μmol^-1, and P_max were 0.11-0.78 mg·m^-2·s^-1 in arid and semi-arid area, which were at a low level compared with other grassland ecosystems. High temperature and low soil water supply were likely the main factors restricting the photosynthetic parameters in arid and semi-arid areas.

Key words: apparent quantum yield, maximum photosynthetic rate, arid and semi-arid region, photosynthetic parameter, eddy-covariance (EC) technique

LIN Yong, CHEN Zhi, YANG Meng, CHEN Shi-Ping, GAO Yan-Hong, LIU Ran, HAO Yan-Bin, XIN Xiao-Ping, ZHOU Li, YU Gui-Rui. Temporal and spatial variations of ecosystem photosynthetic parameters in arid and semi-arid areas of China and its influencing factors[J]. Chin J Plant Ecol, 2022, 46(12): 1461-1472.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2021.0426

https://www.plant-ecology.com/EN/Y2022/V46/I12/1461

Figures/Tables 8

Fig. 1 Study area and flux observation stations in arid and semi-arid areas of China.

Table 1 Information of flux observation stations in arid and semi-arid areas

站点 Site	纬度 Latitude (N)	经度 Longitude (E)	海拔 Altitude (m)	年平均气温 Mean annual air temperature (℃)	年降水量 Mean annual precipitation (mm)	平均叶面积指数 Average leaf area index	植被类型 Vegetation type	通量观测时间 Flux observation time
沙坡头 SP	37.47°	105.00°	1 340	7.8	186	0.21	荒漠 Desert	2017, 2018
阜康 FK	44.71°	88.48°	590	8.8	140	0.21	荒漠 Desert	2017
达尔罕茂明安联合旗 DM	41.64°	110.33°	1 402	2.8	302	0.68	荒漠草原 Desert grassland	2012
四子王旗 SZ	41.78°	111.90°	1 442	3.2	280	0.66	荒漠草原 Desert grassland	2013
西乌珠穆沁旗 XW	44.36°	117.58°	1 135	2.3	330	1.06	典型草原 Typical grassland	2017, 2018
多伦 DL	42.05°	116.28°	1 322	3.4	385	1.19		2015, 2017
内蒙古 NM	43.55°	116.68°	1 250	2.5	350	0.80		2014
锡林浩特 XH	43.55°	116.67°	1 254	2.5	350	0.69		2014, 2019
呼伦贝尔 HL	49.35°	120.12°	667	-0.7	400	1.68	草甸草原 Meadow grassland	2019

Fig. 2 Spatial variation of ecosystem apparent quantum yield (α)(A) and maximum photosynthetic rate (Pmax)(B) in arid and semi-arid area (mean ± SE)(α = 0.000 47-0.002 12 mg·μmol-1, Pmax = 0.11-0.78 mg·m-2·s-1). The sites see Table 1.

Fig. 3 Correlation between ecosystem apparent quantum yield (α) and maximum photosynthetic rate (Pmax) of different sites in arid and semi-arid areas in growing seasons.

Fig. 4 Five-day (A, C) and monthly (B, D) average time dynamics of apparent quantum yield (α) and maximum photosynthetic rate (Pmax) of different vegetation types in arid and semi-arid areas of China.

Fig. 5 Correlation between ecosystem light response parameters and environmental factors in arid and semi-arid areas. α, apparent quantum yield; LAI, average leaf area index in the growing season; Pmax, maximum photosynthetic rate; PAR, average photosynthetic effective radiation in the growing season; Precipitation, cumulative precipitation in the growing season; Rn, average net radiation in the growing season; SWC, average soil water content in the growing season; Ta, average air temperature in the growing season; Ts, average soil temperature in the growing season.

Table 2 Influence factors of monthly dynamics of ecosystem photosynthetic parameters in arid and semi-arid areas

植被类型 Vegetation type	站点 Site	α主要影响因素 Main influencing factors of α	相关性 Correlation	P_max主要影响因素 Main influencing factors of P_max	相关性 Correlation
荒漠 Desert	FK	R_nPAR	+ -	R_n	+
荒漠 Desert	SP	R_n	+	T_sPAR	- -
荒漠草原 Desert grassland	DM	T_s	+	T_a	+
荒漠草原 Desert grassland	SZ	T_s	+	R_nPAR	+ -
典型草原 Typical grassland	XW	T_a	+	SWC	+
	DL	PAR	+	SWC	+
	NM	T_s	+	SWC	+
	XH	T_aT_s	+ +	SWC	+
草甸草原 Meadow grassland	HL	T_a	+	SWC	+

Fig. 6 Path analysis of influencing factors of ecosystem apparent quantum yield (α)(A) and maximum photosynthetic rate (Pmax)(B) in arid and semi-arid areas. The red arrow indicates that there is a positive correlation between factors, and the blue arrow indicates that there is a negative correlation between factors (*, p < 0.1; **, p < 0.01), the dotted arrow indicates that the correlation between factors is not significant; the number represents the standardized regression coefficient between influencing factors. The higher the absolute value of the coefficient, the greater the correlation between factors. LAI, leaf area index; Rn, average net radiation; SWC, average soil water content; Ta, average air temperature; Ts, average soil temperature. CFI, comparative fit index; RMSEA, root mean square error of approximation.

References 40

[1]	Anderson DE, Verma SB, Rosenberg NJ (1984). Eddy correlation measurements of CO₂, latent heat, and sensible heat fluxes over a crop surface. Boundary-Layer Meteorology, 29, 263-272. DOI URL
[2]	Baldocchi D (2014). Measuring fluxes of trace gases and energy between ecosystems and the atmosphere: the state and future of the eddy covariance method. Global Change Biology, 20, 3600-3609. DOI PMID
[3]	Baldocchi DD, Hincks BB, Meyers TP (1988). Measuring biosphere-atmosphere exchanges of biologically related gases with micrometeorological methods. Ecology, 69, 1331-1340. DOI URL
[4]	Barr JG, Engel V, Fuentes JD, Fuller DO, Kwon H (2013). Modeling light use efficiency in a subtropical mangrove forest equipped with CO₂ eddy covariance. Biogeosciences, 10, 2145-2158. DOI URL
[5]	Chen TX, van der Werf GR, Dolman AJ, Groenendijk M (2011). Evaluation of cropland maximum light use efficiency using eddy flux measurements in North America and Europe. Geophysical Research Letters, 38, L14707. DOI: 10.1029/2011GL047533. DOI
[6]	Dugas WA, Heuer ML, Mayeux HS (1999). Carbon dioxide fluxes over bermudagrass, native prairie and sorghum. Agricultural and Forest Meteorology, 93, 121-139. DOI URL
[7]	Ehleringer J, Pearcy RW (1983). Variation in quantum yield for CO₂uptake among C₃ and C₄. Plant Physiology, 73, 555-559. DOI PMID
[8]	Falge E, Baldocchi D, Olson R, Anthoni P, Aubinet M, Bernhofer C, Burba G, Ceulemans R, Clement R, Dolman H, Granier A, Gross P, Grünwald T, Hollinger D, Jensen NO, et al. (2001). Gap filling str for defensible annual sums of net ecosystem exchange. Agricultural and Forest Meteorology, 107, 43-69. DOI URL
[9]	Gilmanov TG, Aires L, Barcza Z, Baron VS, Belelli L, Beringer J, Billesbach D, Bonal D, Bradford J, Ceschia E, Cook D, Corradi C, Frank A, Gianelle D, Gimeno C, et al. (2010). Productivity, respiration, and light-response parameters of world grassland and agroecosystems derived from flux-tower measurements. Rangeland Ecology & Management, 63, 16-39. DOI URL
[10]	Hao YB (2006). Characteristics of Net Ecosystem Exchange of Carbon Dioxide and Their Driving Factors over a Fenced Leymus chinensis Steppe in Inner Mongolia. PhD dissertation, Graduate School of the Chinese Academy of Sciences, Beijing.
	[ 郝彦宾 (2006). 内蒙古羊草草原碳通量观测及其驱动机制分析. 博士学位论文, 中国科学院研究生院, 北京.]
[11]	Hunt JE, Kelliher FM, McSeveny TM, Byers JN (2002). Evaporation and carbon dioxide exchange between the atmosphere and a tussock grassland during a summer drought. Agricultural and Forest Meteorology, 111, 65-82. DOI URL
[12]	Ji JJ, Huang M, Liu Q (2005). Modeling studies of response mechanism of steppe productivity to climate change in middle latitude semiarid regions in China. Acta Meteorologica Sinica, 63, 257-266.
	[ 季劲钧, 黄玫, 刘青 (2005). 气候变化对中国中纬度半干旱草原生产力影响机理的模拟研究. 气象学报, 63, 257-266.]
[13]	Jones HJ (1983). Plant and Microclimate: a Quantitative Approach to Environmental Plant Physiology. Cambridge University Press, Cambridge, UK.
[14]	Kim J, Verma SB (1990). Carbon dioxide exchange in a temperate grassland ecosystem. Boundary-Layer Meteorology, 52, 135-149. DOI URL
[15]	Leuning R (2002). Temperature dependence of two parameters in a photosynthesis model. Plant, Cell & Environment, 25, 1205-1210.
[16]	Li M, Sun HQ, Su ZC (2021). Research progress in dry/wet climate variation in Northwest China. Geographical Research, 40, 1180-1194. DOI
	[ 李明, 孙洪泉, 苏志诚 (2021). 中国西北气候干湿变化研究进展. 地理研究, 40, 1180-1194.] DOI
[17]	Li Q, Wang YL, Hu ZH, Xue HX, Li J (2010). Research progress on carbon flux of grassland ecosystem based on the eddy covariance method in China. Pratacultural Science, 27(12), 38-44.
	[ 李琪, 王云龙, 胡正华, 薛红喜, 李洁 (2010). 基于涡度相关法的中国草地生态系统碳通量研究进展. 草业科学, 27(12), 38-44.]
[18]	Lloyd J, Taylor JA (1994). On the temperature dependence of soil respiration. Functional Ecology, 8, 315-323. DOI URL
[19]	Lü XM, Wang YH, Zhou GS, Xu ZZ, Chen J, Tan LP, Liu T (2015). Interactive effects of changing precipitation and elevated temperatures on plant biomass and its allocation of Stipa breviflora. Acta Ecologica Sinica, 35, 752-760.
	[ 吕晓敏, 王玉辉, 周广胜, 许振柱, 陈军, 谭丽萍, 刘涛 (2015). 温度与降水协同作用对短花针茅生物量及其分配的影响. 生态学报, 35, 752-760.]
[20]	Luo YQ, Hui DF, Cheng WX, Coleman JS, Johnson DW, Sims DA. (2000). Canopy quantum yield in a mesocosm study. Agricultural and Forest Meteorology, 100, 35-48. DOI URL
[21]	Ran JJ (2014). The Spatial and Temporal Characteristics of Temperature and Precipitation in Arid and Semi-arid Regions of China. Master degree dissertation, Lanzhou University, Lanzhou.
	[ 冉津江 (2014). 我国干旱半干旱区温度和降水的时空分布特征. 硕士学位论文, 兰州大学, 兰州.]
[22]	Ruimy A, Jarvis PG, Baldocchi DD, Saugier B (1995). CO₂ fluxes over plant canopies and solar radiation: a review. Advances in Ecological Research, 26, 1-68.
[23]	Schulze ED, Caldwell MM (1995). Ecophysiology of Photosynthesis. Springer, Berlin.
[24]	Shi YF, Shen YP, Li DL, Zhang GW, Ding YJ, Hu RJ, Kang ES (2003). Discussion on the present climate change from warm-dry to warm wet in northwest China. Quaternary Sciences, 23, 152-164.
	[ 施雅风, 沈永平, 李栋梁, 张国威, 丁永健, 胡汝骥, 康尔泗 (2003). 中国西北气候由暖干向暖湿转型的特征和趋势探讨. 第四纪研究, 23, 152-164.]
[25]	Verma SB, Baldocchi DD, Anderson DE, Matt DR, Clement RJ (1986). Eddy fluxes of CO₂, water vapor and sensible heat over a deciduous forest. Boundary-Layer Meteorology, 36, 71-91. DOI URL
[26]	Wang HS, Jia GS, Fu CB, Feng JM, Zhao TB, Ma ZG (2010). Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling. Remote Sensing of Environment, 114, 2248-2258. DOI URL
[27]	Wang HT, Zeng FJ, Zhang B, Li SJ, Gao HH, Lu JR (2015). Light response of Tamarix ramasissima Ledeb. physiological parameters under different cropping patterns. Arid Land Geography, 38, 753-762.
	[ 王会提, 曾凡江, 张波, 李尝君, 高欢欢, 鲁建荣 (2015). 不同种植方式下柽柳光合生理参数光响应特性研究. 干旱区地理, 38, 753-762.]
[28]	Wang HZ, Han L, Xu YL, Niu JL, Yu J (2017). Simulated photosynthetic responses of Populus euphratica during drought stress using light-response models. Acta Ecologica Sinica, 37, 2315-2324.
	[ 王海珍, 韩路, 徐雅丽, 牛建龙, 于军 (2017). 干旱胁迫下胡杨光合光响应过程模拟与模型比较. 生态学报, 37, 2315-2324.]
[29]	Wang XY, Li YL, Zhao XY, Mao W, Cui D, Qu H, Lian J, Luo YQ (2012). Responses of soil respiration to different environment factors in semi-arid and arid areas. Acta Ecologica Sinica, 32, 4890-4901. DOI URL
	[ 王新源, 李玉霖, 赵学勇, 毛伟, 崔夺, 曲浩, 连杰, 罗永清 (2012). 干旱半干旱区不同环境因素对土壤呼吸影响研究进展. 生态学报, 32, 4890-4901.]
[30]	Xi Y (2012). Study on Photosynthetic Physiological Characteristics of Dominant Plants in Typical Grassland of Inner Mongolia Under the Background of Climate Change. Master degree dissertation, Minzu University of China, Beijing.
	[ 席溢 (2012). 气候变化背景下内蒙古典型草原优势植物光合生理特征研究. 硕士学位论文, 中央民族大学, 北京.]
[31]	Xiao Z, Liang S, Jiang B (2017). Evaluation of four long time-series global leaf area index products. Agricultural and Forest Meteorology, 246, 218-230. DOI URL
[32]	Xu LL, Zhang XZ, Shi PL, Yu GR (2004). Determination of apparent quantum yield and apparent maximum photosynthetic rate of alpine meadow ecosystem in Qinghai Tibet Plateau. Science in China Series D: Earth Sciences, 34, 125-130.
	[ 徐玲玲, 张宪洲, 石培礼, 于贵瑞 (2004). 青藏高原高寒草甸生态系统表观量子产额和表观最大光合速率的确定. 中国科学(D辑: 地球科学), 34, 125-130.]
[33]	Yan YL, Zhang LX, Wan ZQ, Gu R, Su LD, Yang J, Gao QZ (2016). Effects of simulated warming and precipitation enhancement on photosynthesis of Stipa krylovii. Acta Prataculturae Sinica, 25, 240-250.
	[ 闫玉龙, 张立欣, 万志强, 谷蕊, 苏力德, 杨劼, 高清竹 (2016). 模拟增温与增雨对克氏针茅光合作用的影响. 草业学报, 25, 240-250.]
[34]	Yu GR, Wen XF, Sun XM, Tanner BD, Lee X, Chen JY (2006). Overview of ChinaFLUX and evaluation of its eddy covariance measurement. Agricultural and Forest Meteorology, 137, 125-137. DOI URL
[35]	Yu GR, Zhang LM, Sun XM, Fu YL, Wen XF, Wang QF, Li SG, Ren CY, Song X, Liu YF, Han SJ, Yan JH (2008). Environmental controls over carbon exchange of three forest ecosystems in eastern China. Global Change Biology, 14, 2555-2571. DOI URL
[36]	Zhang DQ, Zhang L, Yang J, Feng GL (2010). The impact of temperature and precipitation variation on drought in China in last 50 years. Acta Physica Sinica, 59, 655-663. DOI URL
	[ 章大全, 张璐, 杨杰, 封国林 (2010). 近50年中国降水及温度变化在干旱形成中的影响. 物理学报, 59, 655-663.]
[37]	Zhang FW, Li YN, Li HQ, Wang QX, Du MY, Zhao L, Wang SP (2007). The comparative study of the apparent quantum yield and maximum photosynthesis rates of 3 typical vegetation types on Qinghai-Tibetan Plateau. Acta Agrestia Sinica, 15, 442-448.
	[ 张法伟, 李英年, 李红琴, 王勤学, 杜明远, 赵亮, 汪诗平 (2007). 青藏高原3种主要植被类型的表观量子效率和最大光合速率的比较. 草地学报, 15, 442-448.] DOI
[38]	Zhang LM, Cao PY, Zhu YP, Li QK, Zhang JH, Wang XL, Dai GH, Li JG (2015). Dynamics and regulations of ecosystem light use efficiency in a broad-leaved Korean pine mixed forest, Changbai Mountain. Chinese Journal of Plant Ecology, 39, 1156-1165. DOI URL
	[ 张雷明, 曹沛雨, 朱亚平, 李庆康, 张军辉, 王晓凌, 戴冠华, 李金功 (2015). 长白山阔叶红松林生态系统光能利用率的动态变化及其主控因子. 植物生态学报, 39, 1156-1165.] DOI
[39]	Zhang LM, Yu GR, Sun XM, Wen XF, Ren CY, Fu YL, Li QK, Li ZQ, Liu YF, Guan DX, Yan JH (2006). Seasonal variations of ecosystem apparent quantum yield (α) and maximum photosynthesis rate (P_max) of different forest ecosystems in China. Agricultural and Forest Meteorology, 137, 176-187. DOI URL
[40]	Zhou LG, Song QH, Zhang YP, Fei XH, Deng Y, Wu CS, Zhou RW, Lin YX, Deng XB, Chen AG, Li PG (2017). Comparison of net ecosystem exchange light-response curve fitted parameters at four types of forest ecosystems. Chinese Journal of Ecology, 36, 1815-1824.
	[ 周立国, 宋清海, 张一平, 费学海, 邓云, 武传胜, 周瑞伍, 林友兴, 邓晓保, 陈爱国, 李培广 (2017). 4种森林生态系统光合作用光响应参数特征的比较. 生态学杂志, 36, 1815-1824.]