Factors Driving Changes in Vegetation in Mt. Qomolangma (Everest): Implications for the Management of Protected Areas

Remote Sensing

卷:13

Shicheng Li¹  Mingjun Ding²  Linshan Liu³  Huamin Zhang³  Binghua Zhang³  Qionghuan Liu³  Zhaofeng Wang³  Basanta Paudel³  Yili Zhang³  Lanhui Li⁴ 

[1] Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China;

[2] Key Lab of Poyang Lake Wetland and Watershed Research of Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330028, China;

[3] Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

[4] School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China;

关键词: time effect;    BFAST;    protected area;    human activity;    central Himalaya;   

DOI  :  10.3390/rs13224725

来源: DOAJ

【 摘 要 】

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.

【 授权许可】

Unknown