Distribution patterns of plant communities and their associations with environmental soil factors on the eastern shore of Lake Taihu, China

Abstract

Introduction: Plant communities and soil factors might interact with each other in different temporal and spatial scales, which can influence the patterns and processes of the wetland ecosystem. To get a better understanding of the distribution of plants in wetlands and analyze their associations with environmental soil factors, the structure and types of plant communities in the eastern shore area of Lake Taihu were analyzed by two-way indicator species analysis and canonical correspondence analysis (CCA) ordination. The spatial distribution patterns of vegetation and the main factors affecting the distributions were investigated. Outcomes: Sixty-six sampling sites were selected to obtain vegetation species and soil environmental factor data. Results showed that 22 species from the 66 sites could be divided into seven communities: I: Arundo donax; II: A. donax + Phragmites australis; III: Zizania latifolia + Typha orientalis; IV: P. australis + Alternanthera philoxeroides + Polygonum hydropiper; V: P. australis; VI: P. australis + Humulus scandens; and VII: Erigeron acer + Ipomoea batatas + Rumex acetosa. Plant species and soil factors in the CCA analysis showed that I. batatas, E. acer, Chenopodium album, Polygonum lapathifolium, and Acalypha australis were mainly affected by pH, whereas Echinochloa crus-galli, Setaria viridis, and H. scandens were mainly affected by soil total phosphorus. Mentha canadensis and A. donax were mainly affected by soil conductivity, A. philoxeroides was mainly affected by soil organic matter and, Z. latifolia, Metaplexis japonica and P. hydropiper were mainly affected by available phosphorus. Conclusion:These results indicated that different plants adapted to different soil environmental factors and provided basic information on the diversity of Lake Taihu wetland vegetation.

Features of ecological differentiation of halophytic, steppe and petrophytic vegetation in the valley of the Liman Kuyalnik (Odesa Oblast)

“…The ordination analysis carried out by us provided assessment of ecological range and pattern of ecological differentiation of cenoses of halophytic, steppe and petrophytic vegetation in the Liman Kuyalnik valley. The analysis showed that distribution of plant communities most closely correlated with edaphic factors; microclimatic (light intensity) and climatic (thermal regime) factors have somewhat less effect on their differentiation, which is consistent with phytosociological studies of other authors (Tölgyesi et al, 2014;Li et al, 2017;Czortek et al, 2018). On halophytic vegetation, the greatest influence of importance of soil moisture and salinity was revealed.…”

Topography and soil content contribute to plant community composition and structure in subtropical evergreen-deciduous broadleaved mixed forests

“…The quadrats were used as the unit to calculate the importance value (IV) of the species in the quadrats using the formula: importance value (IV) = (relative abundance + relative significance + relative frequency)/3 ( Zhang et al., 2018 ). The two-way indicator species analysis (TWINSPAN) in the VEAPAN software package was used for systematic quantitative classification of the quadrats ( Li et al., 2017 ). Detrended correspondence analysis (DCA) in the CANOCO 4.5 software was used to explain and verify mountain plant community types obtained by TWINSPAN systematic quantitative classification ( Kersti et al., 2020 ), which are all based on a matrix of the importance values of species and quadrats.…”

“…The spatial heterogeneity of plant communities is controlled by several factors, both biotic and abiotic, including topography and soil nutrients ( Li et al., 2017 ; Liang and Chan, 2017 ). These factors also influence spatiotemporal distributions of vegetation ( Iturrate-Garcia et al., 2016 ; Peringer et al., 2017 ; Phillips et al., 2017 ; Yang et al., 2019 ).…”

Analysis of the contributions of human factors and natural factors affecting the vegetation pattern in coastal wetlands

“…Canonical correlation analysis (CCA) is a sorting method based on a single-peak model that combines correspondence analysis and multivariate regression analysis in the sorting process (Ter Braak 1986;Li et al 2017) and is thus capable of presenting the quadrats, the study object and the sorting results for the environmental factors on the same plot (Bu et al 2016). In this paper, because the study object is a type variable, we added three virtual variables and converted the four vegetation types to quantitative variables.…”