Biodiv Sci ›› 2022, Vol. 30 ›› Issue (3): 21392.  DOI: 10.17520/biods.2021392

• Original Papers: Plant Diversity • Previous Articles     Next Articles

Responses in spatial pattern of four dominant species to different water level environments in a freshwater marsh in the Sanjiang Plain

Yu Fu1, Kangxiang Huang1, Jinfeng Cai1, Huimin Chen1, Jiusheng Ren2,*(), Songze Wan1, Yang Zhang1, Heng Ren3, Rong Mao1, Fuxi Shi1,4,*()   

  1. 1 Key Laboratory of State Forestry and Grassland Administration on Forest Ecosystem Protection and Restoration of Poyang Lake Watershed, College of Forestry, Jiangxi Agricultural University, Nanchang 330045
    2 Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, School of Water Resources and Environmental Engineering, East China University of Technology, Nanchang 330013
    3 Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000
    4 Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102
  • Received:2021-09-27 Accepted:2021-12-27 Online:2022-03-20 Published:2022-02-08
  • Contact: Jiusheng Ren,Fuxi Shi


Aims: Instability of hydrological regimes is one of the most basic ecological processes in wetlands. Our objective is to determine how changing water level environments impacts the spatial patterns of marsh plants in the freshwater wetlands in the Sanjiang Plain, Northeast China.

Methods:We analyzed the spatial distribution patterns of populations for four dominant species (Carex lasiocarpa, C. pseudocuraica, Glyceria spiculosa, Deyeuxia angustifolia) in the seasonal inundated (SI) marsh and perennial inundated (PI) marsh in the Ecological Experiment Station of Mire Wetland in the Sanjiang Plain. We utilized a small-scale point pattern analysis based on three null models, including: complete spatial randomness process (CSR), Poisson cluster process (Neyman-Scott process, NS), and nested double-cluster process (DC). We then tested the population density and individual size characteristics of each species.

Results: Regardless of water level conditions, the four main dominant species were completely diverged from the CSR model, and the aggregation distance was primarily focused on 0-50 cm scale. These results indicate that there is a stronger aggregation in small scales for these marsh plants species, but the aggregated intensity was expressed in differences among water level environments. With the rising water level, the population density, individual aboveground biomass, plant height, and stem base diameter of C. lasiocarpa exhibited a significantly increasing trend, but its aggregated intensity became weaker. By contrast, these individual size parameters of D. angustifolia exhibited a dramatically decreasing trend, whereas its aggregated intensity increases. In addition, the changes in individual sizes and aggregated intensity of the other two species (i.e., C. pseudocuraica and G. spiculosa) were not significant. In seasonal inundated (SI) marsh, the four main dominant species were diverged from the NS model in small-scales, but their spatial distributions fit better with the DC model at 0-200 cm scale, indicating that there is a series of clustered patterns under slight flood stress. In the perennial inundated (PI) marsh, the spatial patterns of three species (i.e., C. lasiocarpa, C. pseudocuraica and G. spiculosa) also fit better with the DC model at 0-200 cm scale. However, the spatial patterns of D. angustifolia fit well with the NS model, implying the small-scale clustering disappeared with the intensification of flooding stress.

Conclusion: Hydrologic regimes may determine the patch patterns of marsh plants in the Sanjiang Plain, primarily via variations in reproductive allocation, intraspecific competitions, facilitation effect and individual sizes. The application of the various null models could help explain the formation mechanisms of the population spatial distribution patterns more efficiently.

Key words: point pattern, null models, individual sizes, marsh, Sanjiang Plain