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Journal of Arid Land  2020, Vol. 12 Issue (2): 227-238    DOI: 10.1007/s40333-019-0020-y
Research article     
Relationship between ecological stoichiometry and plant community diversity in the upper reaches of Tarim River, northwestern China
ZHAO Jingjing1,2, GONG Lu1,2,*(), CHEN Xin1,2
1 College of Resources and Environment Science, Xinjiang University, Urumqi 830046, China
2 Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
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Abstract  

Changes in ecological stoichiometry reflect nitrogen (N), phosphorus (P) and both N and P limitations in a plant community, which in turn affect plant diversity of the community. However, the relationship between plant community diversity and ecological stoichiometry has not yet been fully researched in arid and semi-arid regions. Ecological stoichiometry and plant community diversity indices of eighteen communities in the upper reaches of Tarim River, northwestern China, were analyzed by multivariate analysis of variance in 2016. The correlation between ecological stoichiometry and plant community diversity was assessed by redundancy analysis (RDA). Results indicated that the Margalef index was significantly correlated with carbon (C) and P concentrations, the Simpson index and Shannon-Weaner index were significantly correlated with plant C concentration, and the Pielou index was significantly correlated with plant C and N concentrations. Moreover, C:N and C:P ratios had significant impacts on plant community diversity. Our results highlight the importance of ecological stoichiometry in driving plant community diversity in the upper reaches of Tarim River, northwestern China.



Key wordsMargalef index      Simpson index      Shannon-Weaner index      redundancy analysis      Tarim River     
Received: 25 December 2018      Published: 10 March 2020
Corresponding Authors:
About author: *Corresponding author: GONG Lu (E-mail: gonglu721@163.com)
Cite this article:

ZHAO Jingjing, GONG Lu, CHEN Xin. Relationship between ecological stoichiometry and plant community diversity in the upper reaches of Tarim River, northwestern China. Journal of Arid Land, 2020, 12(2): 227-238.

URL:

http://jal.xjegi.com/10.1007/s40333-019-0020-y     OR     http://jal.xjegi.com/Y2020/V12/I2/227

Fig. 1 Location of sampling zones in the upper reaches of Tarim River, northwestern China. T1, T2 and T3 are the sampling zones with six plant communities.
Community
code
Dominant species Total
number
Fre Cov Soil C
(g/kg)
Soil N
(g/kg)
Soil P
(g/kg)
Soil water
content (%)
T11 Populus euphratica,
Halostachys caspica
168 1.39 0.69 6.58 0.59 0.63 12.57
T12 P. euphratica, Tamarix chinensis 524 1.77 0.31 4.75 0.52 0.57 13.11
T13 P. euphratica, Lycium ruthenicum,
Glycyrrhiza uralensis
769 1.77 0.38 6.99 0.56 0.53 14.23
T14 T. chinensis 363 1.33 0.31 6.87 0.54 0.61 14.19
T15 P. euphratica, T. chinensis,
G. uralensis
109 1.33 0.38 1.19 0.22 0.58 12.86
T16 P. euphratica 110 0.67 0.23 0.89 0.20 0.65 12.08
T21 T. chinensis,
Phragmites communis

42
1.16 0.03 0.54 0.16 0.66 9.77
T22 T. chinensis,
Hexinia polydichotoma
36 1.00 0.03 1.04 0.20 0.52 11.76
T23 Alhagi sparsifolia,
Karelinia caspia
81 0.55 0.28 0.56 0.22 0.45 9.51
T24 T. chinensis, A sparsifolia 72 1.17 0.36 1.75 0.22 0.52 11.84
T25 P. euphratica, T. chinensis,
A. sparsifolia, K. caspia
219 1.72 0.28 2.04 0.19 0.52 11.66
T26 A. sparsifolia,
P. euphratica
43 0.56 0.04 1.82 0.22 0.50 9.70
T31 Halostachys caspica,
Kalidium foliatum
80 1.11 0.63 4.66 0.38 0.50 6.24
T32 H. caspica 8 1.05 0.25 7.39 0.59 0.56 8.38
T33 T. chinensis, H. polydichotoma 45 1.00 0.25 7.33 0.68 0.49 9.19
T34 H. caspica, A. sparsifolia,
K. caspia
336 1.61 0.28 4.28 0.62 0.51 5.05
T35 T. chinensis, A. sparsifolia,
K. caspia
30 1.39 0.07 3.27 0.19 0.54 8.61
T36 T. chinensis, K. caspia 10 1.17 0.12 2.66 0.26 0.53 8.19
Table 1 Vegetation composition and soil characteristics of different communities
Community
code
C
(mg/g)
N
(mg/g)
P
(mg/g)
C:N ratio C:P ratio N:P ratio
T11 428.33±1.04Bb 16.74±0.06Ad 1.32±0.07Aa 26.05±1.94Bbc 326.04±19.39Cc 12.53±0.34Bd
T12 447.70±11.76Aa 18.58±0.96Aab 1.10±0.04Ab 24.12±0.62Bbc 408.51±9.94Cb 16.94±0.58Bc
T13 453.39±3.43Aa 19.59±0.92Aa 1.09±0.02Ab 23.18±1.28Bc 414.34±5.02ABb 17.92±1.16Ac
T14 448.11±7.47Aa 10.42±0.85Bd 1.30±0.06Aa 43.18±2.86Aa 344.59±9.98Bbc 7.99±0.33Be
T15 434.91±2.33Ab 17.47±1.01Abc 0.67±0.09Bc 24.95±1.30Abc 653.89±89.28Aa 26.14±2.35ABa
T16 449.92±5.48Aa 16.85±1.23Abc 0.76±0.05Bc 26.78±1.71Bb 596.76±39.12Aa 22.39±2.59Ab
T21 451.39±1.00Aa 11.40±1.17Bb 0.95±0.01Bc 39.87±4.01Aa 474.62±4.67Bcd 11.99±1.30Bb
T22 420.51±1.05Bb 14.64±1.04Bb 0.59±0.01Ce 28.82±1.20ABbc 714.55±17.64Aa 24.89±2.26Aa
T23 441.61±10.29ABa 20.67±2.26Aa 0.92±0.10Bc 21.51±2.02Bd 486.68±59.06Ac 22.93±4.94Aa
T24 445.35±9.88Aa 13.13±1.64Ab 1.07±0.06Bb 34.24±4.07Bab 418.7±32.72Ad 12.34±1.65Ab
T25 435.52±13.37Aab 18.76±2.57Aa 0.69±0.02ABd 23.56±3.81Acd 629.96±34.95ABb 27.07±3.11Aa
T26 400.73±10.03Bc 14.51±1.92ABb 1.36±0.03Aa 27.97±4.21Bbcd 295.74±13.95Be 10.70±1.33Bb
T31 391.05±1.46Cc 11.35±0.84Bc 0.69±0.01Cc 34.58±2.66Aa 562.76±4.96Aa 16.07±0.73Abc
T32 405.37±5.95Bbc 11.62±2.00Cbc 0.71±0.02Bc 35.67±6.84Aa 567.44±16.64Ba 16.05±0.72Bbc
T33 432.19±11.33Ba 14.07±1.59Bbc 1.26±0.11Ab 35.22±4.88Aab 345.24±24.51Bc 11.31±2.23Bc
T34 433.15±22.08Aa 14.58±0.02Ab 1.46±0.10Aa 29.72±1.54Bab 297.79±6.26Cc 10.05±0.72Bc
T35 419.32±11.91Aab 17.93±2.81Aa 0.83±0.08Ac 23.80±3.93Ab 507.29±52.38Bb 21.50±2.34Ba
T36 443.39±18.88Aa 12.84±0.45Bbc 1.37±0.02Aab 34.53±0.52Aa 323.74±19.57Bc 9.37±0.49Bc
Table 2 Characteristics of C, N and P concentrations and their ratios in different communities
Fig. 2 Correlations among C, N and P concentrations and their ratios
Fig. 3 Simpson’s index (D; a), Shannon-Wiener index (H’; b), Margalef index (Ma; c) and Pielou index (E; d) in different plant communities. Different uppercase letters indicate significant differences among plant community diversity indices in T1, T2 and T3 zones at P<0.05 level. Bars indicate standard errors. T11-T16, T21-T26 and T31-T36 mean the six plant communities in T1, T2 and T3 zones, respectively.
Fig. 4 Biplot diagram of redundancy analysis (RDA) for ecological stoichiometry and plant community diversity indices. In this biplot diagram, longer lines indicate stronger associations, and shorter lines indicate weaker associations. When the angle is between 0° and 90°, there is a positive correlation between two variables; when the angle is between 90° and 180°, there is a negative correlation between two variables; when the angle is 90°, no correlation is observed between two variables. C, carbon; N, nitrogen; P, phosphorus; N, nitrogen; D, Simpson index; H’, Shannon-Wiener index; Ma, Margalef index; E, Pielou index.
Parameter Sequence Explanation F P
N 1 0.624 14.632 0.002
C:N ratio 2 0.571 13.302 0.002
C:P ratio 3 0.539 12.583 0.002
P 4 0.498 11.941 0.002
C 5 0.258 4.532 0.041
N:P ratio 6 0.103 1.524 0.235
Table 3 Sequence of importance and Duncan's test of carbon (C), nitrogen (N) and phosphorous (P) concentrations and their ratios
Fig. 5 t-value results from RDA for single stoichiometrical factor influencing plant community diversity indices. (a), N concentration; (b), P concentration; (c), C:N ratio; (d), C:P ratio. The solid circle indicates positive correlation and the dotted circle indicates negative correlation. Plant community diversity indices fall into the solid circle, indicating a positive correlation with the elemental concentration or ratio. Plant community diversity indices fall into the dotted circle indicating a negative correlation with the elemental concentration or ratio. C, carbon; N, nitrogen; P, phosphorus; N, nitrogen; D, Simpson index; H’, Shannon-Wiener index; Ma, Margalef index; E, Pielou index.
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[2] HE Bing, CHANG Jianxia, GUO Aijun, WANG Yimin, WANG Yan, LI Zhehao. Assessment of river basin habitat quality and its relationship with disturbance factors: A case study of the Tarim River Basin in Northwest China[J]. Journal of Arid Land, 2022, 14(2): 167-185.
[3] CHEN Limei, Abudureheman HALIKE, YAO Kaixuan, WEI Qianqian. Spatiotemporal variation in vegetation net primary productivity and its relationship with meteorological factors in the Tarim River Basin of China from 2001 to 2020 based on the Google Earth Engine[J]. Journal of Arid Land, 2022, 14(12): 1377-1394.
[4] BAI Jie, LI Junli, BAO Anmin, CHANG Cun. Spatial-temporal variations of ecological vulnerability in the Tarim River Basin, Northwest China[J]. Journal of Arid Land, 2021, 13(8): 814-834.
[5] WANG Shanshan, ZHOU Kefa, ZUO Qiting, WANG Jinlin, WANG Wei. Land use/land cover change responses to ecological water conveyance in the lower reaches of Tarim River, China[J]. Journal of Arid Land, 2021, 13(12): 1274-1286.
[6] ZHANG Pei, DENG Mingjiang, LONG Aihua, DENG Xiaoya, WANG Hao, HAI Yang, WANG Jie, LIU Yundong. Coupling analysis of social-economic water consumption and its effects on the arid environments in Xinjiang of China based on the water and ecological footprints[J]. Journal of Arid Land, 2020, 12(1): 73-89.
[7] Qinli XIONG, Yang XIAO, Waseem A HALMY Marwa, A DAKHIL Mohammed, Pinghan LIANG, Chenggang LIU, Lin ZHANG, PANDEY Bikram, Kaiwen PAN, B EL KAFRAWAY Sameh, Jun CHEN. Monitoring the impact of climate change andhuman activities on grassland vegetation dynamics in the northeastern Qinghai-Tibet Plateauof China during 2000-2015[J]. Journal of Arid Land, 2019, 11(5): 637-651.
[8] Chunlei ZHAO, Ming'an SHAO, Xiaoxu JIA, Laiming HUANG, Yuanjun ZHU. Spatial distribution of water-activesoil layer along the south-north transect in the Loess Plateau of China[J]. Journal of Arid Land, 2019, 11(2): 228-240.
[9] Lin WU, Yuanming ZHANG. Precipitation and soil particle size co-determine spatial distribution of biological soil crusts in the Gurbantunggut Desert, China[J]. Journal of Arid Land, 2018, 10(5): 701-711.
[10] Yang YU, Xi CHEN, HUTTNER Philipp, HINNENTHAL Marie, BRIEDEN Andreas, Lingxiao SUN, DISSE Markus. Model based decision support system for land use changes and socio-economic assessments[J]. Journal of Arid Land, 2018, 10(2): 169-182.
[11] AISHAN Tayierjiang, HALIK ümüt, Florian BETZ, TIYIP Tashpolat, DING Jianli, NUERMAIMAITI Yiliyasijiang. Stand structure and height-diameter relationship of a degraded Populus euphratica forest in the lower reaches of the Tarim River, Northwest China[J]. Journal of Arid Land, 2015, 7(4): 544-554.
[12] Yue HUANG, Xi CHEN, YongPing LI, AnMing BAO, YongGang MA. A simulation-based two-stage interval-stochastic programming model for water resources management in Kaidu-Konqi watershed, China[J]. Journal of Arid Land, 2012, 4(4): 390-398.
[13] Li ZHUANG, YaNing CHEN, WeiHong LI, ZhongKe WANG. Anatomical and morphological characteristics of Populus euphratica in the lower reaches of Tarim River under extreme drought environment[J]. Journal of Arid Land, 2011, 3(4): 261-267.
[14] YuTing FAN, YaNing CHEN, WeiHong LI, HuaiJun WANG, XinGong LI. Impacts of temperature and precipitation on runoff in the Tarim River during the past 50 years[J]. Journal of Arid Land, 2011, 3(3): 220-230.
[15] Chao LENG, YaNing CHEN, XinGong LI, YanXia SUN. Evaluation of oasis stability in the lower reaches of the Tarim River[J]. Journal of Arid Land, 2011, 3(2): 123-131.