Abstract
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.
Highlights
Protected areas are designed to represent or sample regional biodiversity and are vital for safeguarding the biodiversity and maintaining crucial ecosystem services [1,2]
The annual mean normalized difference vegetation index (NDVI) in the Qomolangma (Everest) National Nature Preserve (QNNP) generally showed a tendency of growth (0.0008 per year, p < 0.05) during 2000–2018
To analyze the factors that might have affected the vegetation in the QNNP, we examined the response of the vegetation to the changing climate by considering the effects of time lag and time accumulation
Summary
Protected areas are designed to represent or sample regional biodiversity and are vital for safeguarding the biodiversity and maintaining crucial ecosystem services [1,2]. Remote sensing provides non-invasive change detection in protected areas It is less money and labor consuming than the field methods, and provides large-scale, periodic, and near-real-time images that can help study the causes and consequences of changes in vegetation. It facilitates the extrapolation of point measurements across landscapes [8]. It allows for the spatial and temporal comparisons of terrestrial photosynthetic activity and structural variations in canopies [14] and has been widely used to detect the vegetation dynamics of protected areas [15,16], to evaluate the effectiveness and representativeness of protection measures [17,18], and to identify the impact of the relevant policies on the environment [19,20]
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