The Ecological Response of Carex lasiocarpa Community in the Riparian Wetlands to the Environmental Gradient of Water Depth in Sanjiang Plain, Northeast China

Abstract

The response of Carex lasiocarpa in riparian wetlands in Sanjiang Plain to the environmental gradient of water depth was analyzed by using the Gaussian Model based on the biomass and average height data, and the ecological water-depth amplitude of Carex lasiocarpa was derived. The results indicated that the optimum ecological water-depth amplitude of Carex lasiocarpa based on biomass was [13.45 cm, 29.78 cm], while the optimum ecological water-depth amplitude of Carex lasiocarpa based on average height was [2.31 cm, 40.11 cm]. The intersection of the ecological water-depth amplitudes based on biomass and height confirmed that the optimum ecological water-depth amplitude of Carex lasiocarpa was [13.45 cm, 29.78 cm] and the optimist growing water-depth of Carex lasiocarpa was 21.4 cm. The TWINSPAN, a polythetic and divisive classification tool, was used to classify the wetland ecological series into 6 associations. Result of TWINSPAN matrix classification reflected an obvious environmental gradient in these associations: water-depth gradient. The relation of biodiversity of Carex lasiocarpa community and water depth was determined by calculating the diversity index of each association.

Modeling the Spatial Distribution of Three Typical Dominant Wetland Vegetation Species’ Response to the Hydrological Gradient in a Ramsar Wetland, Honghe National Nature Reserve, Northeast China

“…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. At present, most research in this study area is still mostly focused on distribution responses of individual species to the water depth in the Sanjiang Plain [26,27], while little attention has been paid to research on the vegetation zonation pattern distribution along hydrological gradients in wetlands, especially the ecological spatial distribution pattern and the process of quantitative research across a larger landscape.It is highly relevant to combine large numbers of observations with species response models to predict future vegetation changes dependent on water level changes. Therefore, based on the GIS and results of the probability of occurrence model, the distribution probability of wetland vegetation under the hydrological gradient was predicted, and further, the dominant species under the hydrological gradient were predicted.…”

“…In the past, spatial wetland models were developed in a geographic information system (GIS) to simulate the wetland vegetation response to water level fluctuations to improve species distribution models [24][25][26]. To date, related studies have mainly focused on studying the spatial distribution of wetland plant species based only on intensive fieldwork [27][28][29] or have modeled the spatial distribution of wetland vegetation responses to environmental gradients only using remote sensing data [25,26,30]. However, few studies in the literature have developed a model to simulate the distribution of plants across a larger landscape and to predict future plant distributions in the case that the hydrological conditions become drier or wetter over the next decade or two.…”

Effects of Different Vegetation Zones on CH4and N2O Emissions in Coastal Wetlands: A Model Case Study

“…Comparisons of CH 4 and N 2 O flux in different locations were complex. Multiple factors could cause the regional difference, such as temperature, rainfall, water level, and soil pH (e.g., [ 34 , 35 ]).…”

Vegetation development and water level changes in Shenjiadian peatland in Sanjiang Plain, Northeast China

“…However, the impact of each environmental factor on the plant community is different. Some researchers have carried out studies of the relationship between the plant community and environment factors in the Sanjiang Plain (Ji et al, 2006;Zhou et al, 2006;Luan et al, 2013). The results of these studies suggest that water level is the main factor controlling the components of the vegetation community (Zhou et al, 2012;Lou et al, 2013).…”