| The wetlands of Liaohe estuary are located in the intersection of land and sea.Due to the constraints of land and sea environment and the interference of human activities,its ecosystem is facing the problems of shrinking area and environmental deterioration.In recent years,the landscape pattern of Liaohe estuary wetlands has been changed under the influence of multiple factors,and the original hydrological connectivity of the wetlands has been cut off.This paper takes Liaohe estuary wetland as the research object and extracts nine types of landscapes,including reed field,rice field,winged alkali canopy,farm,building,river,mudflat,reservoir and others,by visual interpretation in 1985,2000,2014 and 2020,and analyzes the dynamic changes of landscape area and landscape type shifts in Liaohe estuary wetland in 35 years.The hydrological connectivity of Liaohe estuarine wetlands in the four periods was compared and analyzed;the landscape pattern evolution of Liaohe estuarine wetlands was analyzed by the landscape index method;finally,the influence of landscape pattern evolution on hydrological connectivity was analyzed based on the correlation between landscape pattern index and hydrological connectivity index;with a view to providing reference for ecological restoration of Liaohe estuarine wetlands.This paper divides the years 1985-2000,2000-2014,2014-2020 and 1985-2020 into four stages Ⅰ,Ⅱ,Ⅲ and Ⅳ in turn,and the conclusions are as follows.(1)The area of natural wetlands in Liaohe estuary decreases,the area of artificial wetlands increases,and the area of non-wetland landscape fluctuates,but tends to be stable in general.The natural wetlands in Liaohe estuary have a tendency to change to artificial wetlands.The landscapes with the largest amount of area change in the four periods are mudflats,farms,mudflats and mudflats in order;the ones with the smallest amount of area change are winged alkali ponds,reservoirs,farms and winged alkali ponds;the landscapes with the largest dynamic attitude are reservoirs,farms,mudflats and farms;the ones with the smallest dynamic attitude are rivers,reed fields,rice fields and reed fields.(2)The main landscape types that turned out in the four periods are mudflats and reed fields;mudflats are mainly transformed into farms,rice fields and reed fields,and reed fields are mainly transformed into built landscapes;in stages II and III,rivers are severely shrinking in area and evolving mainly to mudflats;in stage IV,there are more transformations from mudflats to farms and rivers to mudflats.The principal component analysis shows that socio-economic and demographic factors are the main driving factors for the shift of wetland landscape in Liaohe estuary.(3)Based on Fragstats software and remote sensing interpretation data,the landscape pattern index was calculated from the type and landscape scales.At the type scale,the landscape patches of reed fields,rice fields and farms tend to be fragmented,irregularly shaped and with dispersed landscape patterns;the landscape of winged alkali ponds and rivers tends to be fragmented;the landscape of mudflats is complex in shape and shows aggregated and compact landscape patterns;the landscape of buildings is regular in shape but more discrete.At the landscape level,the landscape of Liaohe estuary wetland tends to be simple,with regular shape,increasing diversity and deepening fragmentation.(4)The hydrological connectivity of Liaohe estuary wetlands was initially evaluated by fuzzy comprehensive evaluation method,meanwhile,the hydrological connectivity indices IIC and PC were calculated based on Conefor Sensinode software,and the results both indicated that the hydrological connectivity of Liaohe estuary wetlands changed from better to worse.The results of Pearson correlation analysis between landscape pattern index and hydrological connectivity index based on RStudio software show that PLAND index of river landscape has a significant positive correlation with PC;IJI of beach landscape has a highly significant positive correlation with PC;NP index of landscape scale has a significant negative correlation with both IIC and PC. |
