| The giant panda is a national treasure of China and a world-class endangered species.Sichuan is the main habitat for giant pandas in China.The interference of global climate change and human factors will inevitably affect the ecological environment quality of giant panda habitats,thereby affecting the survival and development of giant pandas.The study reveals the spatiotemporal changes in the ecological environment quality of giant panda habitats,which is of great significance for the protection of giant pandas.At present,there is still a lack of research on the long-term spatiotemporal changes in the ecological environment quality of giant panda habitats.Therefore,this article selects the Wanglang Giant Panda Nature Reserve,the earliest established giant panda reserve in China,as the research area.Three remote sensing images from 2001,2011,and 2020 were selected,and GIS and RS technologies were used to study the vegetation types,landscape patterns,and spatiotemporal changes in ecological environment quality in the research area over the past20 years,The main conclusions are as follows:(1)In 2001,shrub and coniferous forest were relatively more distributed in the study area,accounting for 29.67% and 27.87% respectively,followed by meadow and mixed coniferous and broad-leaved forest,accounting for 17.97% and 15.31% respectively,and evergreen broad-leaved forest was relatively less,accounting for only 9.16%.The coniferous forest,mixed coniferous and broad-leaved forest and evergreen broad-leaved forest are mainly distributed in the middle and east of the study area with relatively low altitude,and the meadow and shrub are mainly distributed in the west and southwest with relatively high altitude.From 2001 to 2020,the area of coniferous and broad-leaved mixed forests,shrubs and meadows has increased.Among them,the coniferous and broad-leaved mixed forests suitable for the concentrated distribution of giant pandas have the largest increase,increasing by 12.66%,and the coniferous forest has the largest decrease,decreasing by 16.28%.The increase source of mixed coniferous and broad-leaved forest is mainly coniferous forest and evergreen broad-leaved forest,the increase source of shrub is mainly coniferous forest,the increase source of meadow is mainly shrub,and the decrease direction of coniferous forest and evergreen broad-leaved forest is mainly transformed into mixed coniferous and broad-leaved forest and shrub.(2)The research area is mainly composed of forest and grass landscape types,and the overall landscape pattern shows good uniformity,low fragmentation,and high focus.Over the past 20 years,the landscape pattern in the study area has shown a trend of decreasing fragmentation,decreasing diversity and uniformity,and increasing aggregation.The Shannon Diversity Index(SHDI)and Shannon Uniformity Index(SHEI)have decreased from 1.54 and 0.96 in 2001 to 1.49 and 0.83 in 2020,respectively.The Scattering and Parallel Index(IJI)and Spread Index(CONTAG)have increased from 59.59 and 47.73 to70.03 and 53.46,respectively.From the perspective of landscape types,the fragmentation degree of coniferous and broad-leaved mixed forests,shrubs,and meadows decreased,while the aggregation degree increased.The dispersion and juxtaposition index(IJI)increased from 48.60,53.97,and 32.22 to 70.86,73.25,and 37.61,and the maximum patch index(LPI)increased from 2.46,8.47,and 4.48 to 10.93,9.58,and 5.10;The fragmentation degree of evergreen broad-leaved forest and coniferous forest increased,the aggregation degree decreased,the IJI decreased from 56.81 and 73.74 to 22.78 and 55.19,and the LPI decreased from 4.64 and 19.41 to 0.44 and 1.71.(3)The average remote sensing greenness index(NDVI)and humidity index(WET)of the study area in 2001 were 0.5608 and 0.5154,while the average heat index(LST)and dryness index(NDBSI)were 0.2900 and 0.3091,indicating that the overall vegetation coverage of the study area was good.The eastern region has relatively low altitude,relatively high NDVI and WET values,and relatively low LST and NDBSI values;The western and southwestern regions have relatively high altitudes,relatively low NDVI and WET values,and relatively high LST and NDBSI values.Over the past 20 years,the NDVI value in the research area has shown an overall upward trend,with an average increase of 0.0335;The WET value showed a downward trend,with an average decrease of 0.0629;The changes in LST and NDBSI values in the study area were relatively small,with increases of 0.0161 and 0.0107,respectively.(4)The overall ecological environment quality of the research area is good.In 2001,the average of the Remote Sensing Ecological Environment Index(RSEI)reached 0.5719.The areas with excellent and relatively good ecological environment quality levels accounted for 28.91% and 24.94%,respectively.The areas with poor and poor ecological environment quality levels were relatively small,accounting for 17.24% and 12.32%,respectively.The high value areas of the Ecological Remote Sensing Index(RSEI)are mainly distributed in the central and eastern regions with relatively low elevations,Low value areas are mainly distributed in the western and southwestern regions with relatively high elevations.In the past 20 years,the ecological environment quality of the research area has further improved,and the overall RSEI has shown an upward trend.Compared to2001,it increased by 0.0246 in 2020,and the total area of the superior and superior levels increased by 2.15%,while the difference and poor levels decreased by 5.73%.The significantly improved areas are located in the central and southeastern regions of the study area,accounting for 4.58%.The research results indicate that in recent years,the protection effect of the study area has been significant,and the overall ecological environment quality of the study area has tended to improve.(5)Over the past 20 years,the average annual precipitation and average annual temperature in the research area have shown a fluctuating upward trend,with an increase of 28.18 mm and 0.01℃,respectively.The correlation analysis results show that the NDVI,LST,WET,and RSEI indices are significantly and extremely positively correlated with annual average precipitation and temperature,while the NDBSI is significantly negatively correlated with precipitation and positively correlated with temperature.This indicates that the study area is far from human activity centers,and most of the sub areas have relatively high altitudes and low temperatures.The increase in precipitation and temperature promotes the growth of vegetation in the study area,this is the main reason for the improvement of ecological environment quality. |
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