Wang Guangjie, Peng Wenfu
The Institute of Geography and Resources Science, Sichuan Normal University, Chengdu, 610068, People's Republic of China.
Key Lab of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Sichuan Normal University, Chengdu, 610068, People's Republic of China.
Environ Sci Pollut Res Int. 2022 May;29(21):32016-32031. doi: 10.1007/s11356-021-17544-w. Epub 2022 Jan 11.
The influence of factors on vegetation changes in different regions is still largely unknown. We applied the geographic detector, a new spatial statistical method, to study the interactive effects of factors on the spatial patterns of normalised vegetation index (NDVI) changes and determine the optimal characteristics of key impact factors beneficial to vegetation growth. Our results show that from 2000 to 2015, the vegetation cover for the upper reaches of the Minjiang River, western China was in good condition. Furthermore, more than 80% of the areas had NDVI values ranging from 0.6 to 0.8 and NDVI > 0.8, and the spatial-temporal changes of vegetation cover were significant. The vegetation cover changes showed a significant transformation in the regions with NDVI > 0.6. Our study uniquely illustrated that elevation, annual average temperature and soil type can explain vegetation changes quite well. We propose that interactive effects exist among impact factors on vegetation NDVI, and the synergistic effects of the impact factors show mutual and nonlinear enhancements. The interactions among impact factors significantly enhance the impact of a single factor on vegetation changes. The most suitable characteristics of the main impact factors that promote vegetation growth were revealed by this study and will help improve our understanding of factors that impact NDVI and its driving mechanisms. Our findings suggest that the established favourable value range or the most suitable characteristics of impact factors will help management plans to intervene and promote vegetation change for vegetation restoration and alleviate environmental degradation.
不同区域中各因素对植被变化的影响在很大程度上仍不为人知。我们应用地理探测器这一新型空间统计方法，研究各因素对归一化植被指数（NDVI）变化空间格局的交互作用，并确定有利于植被生长的关键影响因素的最佳特征。我们的结果表明，2000年至2015年期间，中国西部岷江上游的植被覆盖状况良好。此外，超过80%的区域NDVI值在0.6至0.8之间以及NDVI > 0.8，植被覆盖的时空变化显著。在NDVI > 0.6的区域，植被覆盖变化呈现出显著转变。我们的研究独特地表明，海拔、年平均温度和土壤类型能够很好地解释植被变化。我们提出，影响植被NDVI的各因素之间存在交互作用，且这些影响因素的协同效应呈现出相互且非线性的增强。各影响因素之间的相互作用显著增强了单一因素对植被变化的影响。本研究揭示了促进植被生长的主要影响因素的最合适特征，这将有助于增进我们对影响NDVI及其驱动机制的因素的理解。我们的研究结果表明，所确定的有利值范围或影响因素的最合适特征将有助于管理计划进行干预，并促进植被变化以实现植被恢复并缓解环境退化。
