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Arid Land Geography ›› 2023, Vol. 46 ›› Issue (1): 86-93.doi: 10.12118/j.issn.1000-6060.2022.265

• Biology and Pedology • Previous Articles     Next Articles

Spatial distribution pattern of wetland plant species richness driven by water and heat conditions collectively in Xinjiang

HAN Dayong1(),NIU Zhongze2(),WU Yongming3,GAO Jian2   

  1. 1. College of Biological and Geographical Sciences, Yili Normal University, Yining 835000, Xinjiang, China
    2. Desert Engineering Survey and Design Institute, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    3. Forestry and Grassland Bureau of Xinjiang Uygur Autonomous Region, Urumqi 830099, Xinjiang, China
  • Received:2022-06-03 Revised:2022-08-20 Online:2023-01-25 Published:2023-02-21

Abstract:

On the geographic spatial scale, climate factors (such as environmental energy and precipitation) are the main driving factors of plant species diversity. However, it remains unclear whether climatic factors can explain the plant diversity in wetlands. This study discusses the influence of environmental factors, especially the effect of water and heat conditions on the distribution of wetland species. Specifically, it includes four categories and seven indicators, including spatial factors (longitude and latitude), terrain factors (altitude), water factors (annual average precipitation and evaporation), and heat factors (annual average air temperature and sunshine hours). The research objects involve 26 wetland parks in three secondary river basins in Xinjiang, China. The structural equation model is used to explore the relative importance of each indicator on wetland plant richness and their interaction. In addition, Moran’s I index is used to analyze the spatial correlation of the residuals of each variable to evaluate the impact of spatial correlation. The results show that (1) the structural equation model explains 41.8% of the variation in plant species richness. The total effect of annual average precipitation on species richness is the highest, which is 0.47, followed by the annual average sunshine hours, which is -0.42. Among them, the annual average precipitation has a positive effect, whereas the annual average sunshine hours have a negative effect. The effects of other indices on species richness are insignificant. (2) The influence of annual average precipitation on plant richness is primarily a direct effect, which is 0.39, accounting for 92.86% of the total effect. The influence of annual average sunshine hours on plant richness is primarily an indirect effect, which is -0.23, accounting for 54.76% of the total effect. (3) Spatial correlation analysis shows that there is no spatial correlation between the residuals of annual average precipitation and sunshine hours on different spatial scales, and the Moran’s I index fluctuates within the range of -0.15 to 0.10, which could be considered reliable prediction indices. (4) The direct effects of spatial factors such as longitude and latitude on plant richness are insignificant, whereas the indirect effects are significant. Longitude significantly affects the annual average precipitation, and latitude significantly affects the annual average sunshine hours and temperature, indicating that spatial factors indirectly affect the species richness by affecting the annual average precipitation and sunshine hours. In conclusion, the plant richness of the wetlands in Xinjiang is primarily driven by water and heat conditions. The role of heat depends on the water conditions. In future wetland plant diversity protection studies, the assessment and response measures of the impact of climate change on plant diversity should be strengthened.

Key words: water-energy dynamics hypothesis, structural equation model, spatial correlation, arid area, wetland protection