2015
DOI: 10.1111/jvs.12270
|View full text |Cite
|
Sign up to set email alerts
|

Long‐term changes in marsh vegetation in Sanjiang Plain, northeast China

Abstract: Questions Is there a consistent change in species composition and species richness across the communities along the wetness zonation? Which species are sensitive to environmental changes? Has species richness increased or decreased? What are the relative effects of climate, geographical position and local environmental factors on the inland marsh community? Location Sanjiang Plain, northeast China (130–133° E, 45–48° N). Methods A total of 94 plots were re‐surveyed in 2012 and compared with data from 1973. Det… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

1
15
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
7
1

Relationship

2
6

Authors

Journals

citations
Cited by 27 publications
(16 citation statements)
references
References 29 publications
1
15
0
Order By: Relevance
“…In addition, the negative correlation between species richness and water depth in two Carex communities indicated that species number per plot would show increasing trends with the habitat drying, similar to the result of Dwire et al [ 38 ], and confirmed by a long-term study by Lou et al [ 39 ]. Furthermore, this also demonstrated that the water table depth of the growing season is a significant predictor of species diversity for marsh vegetation.…”
Section: Discussionsupporting
confidence: 82%
See 1 more Smart Citation
“…In addition, the negative correlation between species richness and water depth in two Carex communities indicated that species number per plot would show increasing trends with the habitat drying, similar to the result of Dwire et al [ 38 ], and confirmed by a long-term study by Lou et al [ 39 ]. Furthermore, this also demonstrated that the water table depth of the growing season is a significant predictor of species diversity for marsh vegetation.…”
Section: Discussionsupporting
confidence: 82%
“…Significantly, this is a pseudo-correlation statistically, and resulted from the fact that aboveground biomass increased as flooding depth decreased along the vegetation zone. So with the habitat drying resulted from human activity and climate warming in this region marshes [ 39 ], vegetation productivity and carbon sequestration in this temperate freshwater marshes would increase by species replace and community succession.…”
Section: Discussionmentioning
confidence: 99%
“…A water level decrease was the factor most clearly related to the changes along the marsh zonation. The temperature showed an increasing trend, while precipitation fluctuated without a trend; this would result in a decline in humidity [44]. These findings indicate that if the drying of wetlands in this region continues, then Carex lasiocarpa and Carex pseudocuraica marshes will gradually be replaced by Calamagrostis angustifolia wet meadows in the near future.…”
Section: Modeling the Spatial Distribution Of Wetland Vegetation Species' Response To The Hydrological Gradientmentioning
confidence: 82%
“…Hydrological conditions have been demonstrated to be the main factor controlling changes in vegetation community composition in the Sanjiang Plain [11,34,44]. How the probability of occurrence varies between different plant species in response to an increasing hydrological gradient may play an important role in the distribution of vegetation zones in these freshwater marshes.…”
Section: Modeling the Spatial Distribution Of Wetland Vegetation Species' Response To The Hydrological Gradientmentioning
confidence: 99%
“…Variations of community characteristics, including community structure, species composition and plant diversity, are common ecological phenomenon in wetland ecosystem (Lou et al 2015(Lou et al , 2018. Previous studies have highlighted that plant diversity and community composition can change in responses to environmental fluctuations, especially with a variation of soil physiochemical properties (Ma et al 2017;Wang et al 2018a).…”
Section: Introductionmentioning
confidence: 99%