Testing multiple hypotheses for the richness pattern of macrophyte in the Qaidam Basin of Northwest China

doi:10.17521/cjpe.2020.0364

Abstract

Abstract:

Aims Patterns of species richness are influenced by both ecological factors and processes. The formation mechanisms of macrophyte richness pattern have been mainly concentrated in a few aspects, such as geometric constraints, water-energy status, or random processes.
Methods In this study, using collected macrophyte species-level data in the Qaidam Basin, we examined macrophyte richness patterns along latitudinal and longitudinal gradients, and tested the mid-domain effect (MDE), area effect (AE), water-energy hypothesis, spatial autocorrelation, and habitat heterogeneity hypothesis for the geographical patterns.
Important findings Our study showed that the macrophyte richness in the Qaidam Basin showed a hump- shaped pattern along latitudinal and longitudinal gradients. Regression analyses indicated that MDE and AE, rather than water-energy hypothesis, spatial autocorrelation, or habitat heterogeneity hypothesis significantly influenced macrophyte richness in the Qaidam Basin. Variation partitioning showed that the explanatory power of MDE for longitudinal and latitudinal richness patterns of macrophyte was 68.41% and 66.91%, respectively. This result implies that macrophyte richness in the Qaidam Basin is mainly affected by geometric and dispersal restrictions. This study further confirms that geometric constraints and random processes may be important natural factors affecting the pattern of macrophyte richness in the arid area of Northwest China.

Key words: richness pattern, mid-domain effect, water-energy hypothesis, spatial autocorrelation, species-area effect, habitat heterogeneity hypothesis, macrophyte, Qaidam Basin

OU Wen-Hui, LIU Ya-Heng, LI Na, XU Zhi-Yan, PENG Qiu-Tong, YANG Yu-Jing, LI Zhong-Qiang. Testing multiple hypotheses for the richness pattern of macrophyte in the Qaidam Basin of Northwest China[J]. Chin J Plant Ecol, 2021, 45(11): 1213-1220.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2020.0364

https://www.plant-ecology.com/EN/Y2021/V45/I11/1213

Figures/Tables 6

Fig. 1 A map of macrophyte survey sites in the Qaidam Basin of northwest China.

Fig. 2 Longitudinal and latitudinal pattern of macrophyte richness at the Qaidam Basin. Solid lines represent predicted richness by Range Model based on mid-domain effect. Dashed lines represent the 95% confidence interval. ***, p < 0.001.

Fig. 3 Species-area relationship curve of macrophytes in the Qaidam Basin. The solid line represents predicted richness by species-area effect, and dashed lines the 95% confidence interval. ***, p < 0.001.

Table 1 Explanatory power of aquatic environmental factors on macrophyte species richness in the Qaidam Basin

水环境因子 Aquatic environment factor	解释度 Explain (%)	p
溶解性固体总量 TDS	2.0	0.046^*
盐度 Salinity	1.9	0.064
pH	1.5	0.154
电导率 Conductivity	1.3	0.250
水深 Water depth	1.0	0.460
温度 Temperature	0.9	0.478

Table 2 Regression equations of macrophyte richness in the Qaidam Basin under hypotheses of water-energy, spatial autocorrelation, and environmental heterogeneity

假说 Hypothesis	回归方程 Regression equation	p
水分-能量假说 Water-energy hypothesis	$\text{log}S=1.82-0.01\text{log}PAN-0.20\text{log}PET-0.02\text{log}PE{{T}^{2}}$	0.051
空间自相关 Spatial autocorrelation	-	0.250
栖息地异质性假说 Habitat heterogeneity hypothesis	$S=6.48-0.49TDS$	0.330

Fig. 4 Relative explanatory power of mid-domain effect and species-area effect on longitudinal and latitudinal patterns of macrophyte richness in the Qaidam Basin. A, B are the Venn diagram of the variance partitioning of mid-domain effect and species-area effect on longitude and latitude, respectively. The negative value is represented by 0, which means lack of explanatory power.

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