scholarly journals UPLAND AND WETLAND VEGETATION DYNAMICS IN THE TOLVOJARVI NATURE RESERVE SINCE THE ALLERØD

Author(s):  
Людмила Владимировна Филимонова ◽  
Lyudmila Filimonova
Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2041
Author(s):  
Dandan Yan ◽  
Zhaoqing Luan ◽  
Dandan Xu ◽  
Yuanyuan Xue ◽  
Dan Shi

Water level fluctuations resulting from natural and anthropogenic factors have been projected to affect the functions and structures of wetland vegetation communities. Therefore, it is important to assess the impact of the hydrological gradient on wetland vegetation. This paper presents a case study on the Honghe National Nature Reserve (HNNR) in the Sanjiang Plain, located in Northeast China. In this study, 210 plots from 18 sampling line transects were sampled in 2011, 2012, and 2014 along the hydrological gradient. Using a Gaussian logistic regression model, we determined a relationship between three wetland plant species and a hydrologic indicator—a combination of the water level and soil moisture—and then applied that relationship to simulate the distribution of plants across a larger landscape by the geographic information system (GIS). The results show that the optimum ecological amplitude of Calamagrostis angustifolia to the hydrological gradient based on the probability of occurrence model was [0.09, 0.41], that of Carex lasiocarpa was [0.35, 0.57], and that of Carex pseudocuraica was [0.49, 0.77]. The optimum of Calamagrostis angustifolia was 0.25, Carex lasiocarpa was 0.46, and Carex pseudocuraica was 0.63. Spatial distribution probability maps were generated, as were maps detailing the distribution of the most suitable habitats for wetland vegetation species. Finally, the model simulation results were verified, showing that this approach can be employed to provide an accurate simulation of the spatial distribution pattern of wetland vegetation communities. Importantly, this study suggests that it may be possible to predict the spatial distribution of different species from the hydrological gradient.


2020 ◽  
Vol 10 (12) ◽  
pp. 4209
Author(s):  
Yaotong Cai ◽  
Shutong Liu ◽  
Hui Lin

The dynamic monitoring and analysis of wetland vegetation play important roles in revealing the change, restoration and reconstruction of the ecosystem environment. The increasing availability of high spatial-temporal resolution remote sensing data provides an unprecedented opportunity for wetland dynamic monitoring and change detection. Using the reconstructed dense monthly Landsat time series, this study focuses on the continuous monitoring of vegetation dynamics in Dongting Lake wetland, south China, in the last two decades (2000–2019) by using the Bayesian estimator of abrupt change, seasonal change, and trend (BEAST) method. Firstly, the flexible spatiotemporal data fusion (FSDAF) model is applied to blend Landsat and moderate-resolution imaging spectroradiometer (MODIS) images on the basis of the input image pair selection strategy named “cross-fusion” to generate the monthly time-series normalized difference vegetation index (NDVI) with the spatial resolution of 30 m. Then, the abrupt changes, trend, and seasonality of the vegetation in the study area as well as the uncertainties of change detection are estimated by the BEAST method. Results show that there is a close relationship between the ground true data and the estimated changepoints. A high overall accuracy (OA) of 87.37% and Kappa coefficient of 0.85 were achieved by the proposed framework. Additionally, the temporal validation got the interval intersection of 86.57% and the absolute difference of mean interval length of 6.8 days. All of the results demonstrate that the vegetation changes in the Dongting Lake wetland varied spatially and temporally in the last two decades, because of extreme weathers and anthropogenic factors. The presented approach can accurately identify the vegetation changes and time of disturbance in both the spatial and temporal domains, and also can retrieve the evolution process of wetland vegetation under the influence of climate changes and human activities. Therefore, it can be used to reveal potential causes of the degradation and recovery of wetland vegetation in subtropical areas.


2014 ◽  
Vol 26 (2) ◽  
pp. 253-259 ◽  
Author(s):  
YE Chun ◽  
◽  
WU Guiping ◽  
ZHAO Xiaosong ◽  
WANG Xiaolong ◽  
...  

2013 ◽  
pp. 76-88
Author(s):  
E. A. Starodubtseva ◽  
L. G. Khanina ◽  
V. E. Smirnov

We studied 80-years vegetation dynamics of the Voronezh Nature Reserve. Dynamics of vegetation was evaluated by analyzing 1051 phytosociological relevés collected at temporal plots that were located in different landscape units. We found out that meadow — pine forest vegetation was widely distributed in the Reserve in 1930s except the floodplains. It was caused by the intensive human impact before the preservation of this territory. We defined the landscape units, where autogenic succession or allogenic succession has been prevailing since 1930s. It is shown that autogenic succession leads to the increase of the nemoral species abundance in all vegetation layers of plant communities; soil fertility increased and light decreased during the succession. Periodic fires, mass tree-falls, and mowing are the main factors caused the allogenic succession in the Reserve. It is proved that high vegetation diversity of the Reserve is currently maintained by exogenous factors.


1986 ◽  
Vol 13 (6) ◽  
pp. 561 ◽  
Author(s):  
J. R. Dodson ◽  
P. W. Greenwood ◽  
R. L. Jones

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