| Bayinbuluke grassland wetland is a transitional ecosystem that between land and water body. It has unique hydrological, soil, vegetation and biological characteristics and it is the source of many important rivers in this basin. As an important part of watershed ecosystem, Bayinbuluke grassland wetland is crucial for watershed ecosystem health because of its unique position of geography and ecology. The Eco-environmental in Bayinbuluke grassland wetland is very fragile because of its high altitude. Climate change and human activities have more severe effects in this basin than other general regions. Recent years, the landscape pattern in Bayinbuluke grassland wetland changed dramatically because of Global Climate Change and human activities.This study selects Bayinbuluke grassland wetland as the research object and establishes a classification system referring to its landscape pattern. Based on ENVI 4.8, do a series of preprocessing work and use the Maximum Likelihood Method to classify the remote sensing images which are taken in 1998,2006 and 2014. Calculate the transition matrix by the spatial overlay analysis function of ArcGIS 10.0, then calculate the landscape pattern indexes at both class level and landscape level with the support of FRAGSTATS 4.0. Summarize variation laws of the landscape pattern in Bayinbuluke grassland wetland by analyzing the transition matrix and the landscape pattern indexes. Reveal the root cause of the variation with the support of a theoretical framework that combining hydrological processes and the responses of wetland landscape pattern. The results will provide theoretical foundations for utilization of wetland resources and protection of wetland ecological environment in this region, thereby providing a reference for regional ecological security.The main conclusions in this paper are shown as below:(1)In the period from 1998 to 2014, wetland area showed an increasing trend and this is mainly due to the climate in this basin is becoming warm and humid. Sandy area is expanding with an increasing speed, this is duo to overgraze and rain erosion in some areas. The landscape on the overall was fragmented to a larger extent. The shape of the patches became more complex and their dominance was somewhat decreased. Spatial heterogeneity of the landscape was enhanced, patch types were distributed in equilibrium and the scale of landscape is getting more and more dispersed.(2)There was a significant negative correlation between the water level and the vegetation species richness in the study area with a correlation value of-0.82 at the 0.01 level, indicating that plant species are affected by water level. Within a certain range, vegetation species richness decreased with the increasing water level.(3)There was a significant correlation between the water level and the biomass in the study area. With the increase of water level, vegetation biomass showed a trend of first increasing and then decreasing, R2=0.764. The possible reason is that the increasing water level improved the access conditions of water and nutrient which determines primary productivity, but when the underground water level continued to rise until in submerged conditions, lower species richness resulted in lower vegetation biomass.(4)Hydrological processes are recognized as the significant driving forces of the changes of wetland landscape pattern. Hydrological processes have not only direct effects but also indirect effects on wetland landscape pattern by making changes on physical, chemical and biological processes. Cray connection analysis showed that there was a significant relationship between the indexes of landscape pattern and hydrological factors. The indices of LSI, ED, SHDI and SHEI have large relevance degrees with precipitation and runoff. |
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