Institute of Loess Plateau, Shanxi University, Taiyuan, Shanxi 030006, China.
College of environmental &Resource Science, Shanxi University, Taiyuan, Shanxi 030006, China.
Sci Rep. 2017 Jan 9;7:40092. doi: 10.1038/srep40092.
Variability in satellite measurements of terrestrial greenness in drylands is widely observed in land surface processes and global change studies. Yet the underlying causes differ and are not fully understood. Here, we used the GeogDetector model, a new spatial statistical approach, to examine the individual and combined influences of physiographic factors on dryland vegetation greenness changes, and to identify the most suitable characteristics of each principal factor for stimulating vegetation growth. Our results indicated that dryland greenness was predominantly affected by precipitation, soil type, vegetation type, and temperature, either separately or in concert. The interaction between pairs of physiographic factors enhanced the influence of any single factor and displayed significantly non-linear influences on vegetation greenness. Our results also implied that vegetation greenness could be promoted by adopting favorable ranges or types of major physiographical factors, thus beneficial for ecological conservation and restoration that aimed at mitigating environmental degradation.
在陆地表面过程和全球变化研究中，广泛观察到卫星对干旱地区陆地绿色度测量的变化。然而，其根本原因不同，并且尚未完全理解。在这里，我们使用地理探测器模型（一种新的空间统计方法）来检查地形因素对干旱地区植被绿色度变化的单独和综合影响，并确定每个主要因素最适合促进植被生长的特征。我们的结果表明，干旱地区的绿色度主要受到降水、土壤类型、植被类型和温度的影响，无论是单独作用还是共同作用。地形因素对植被绿色度的影响呈现出显著的非线性，并且地形因素之间的相互作用增强了任何单一因素的影响。我们的结果还表明，通过采用有利的主要地形因素范围或类型，可以促进植被的绿色化，从而有利于生态保护和恢复，以减轻环境退化。
