Xue Cong, Zan Mei, Zhou Yanlian, Chen Zhizhong, Kong Jingjing, Yang Shunfa, Zhai Lili, Zhou Jia
School of Geographical Science and Tourism, Xinjiang Normal University, Urumqi, China.
Xinjiang Laboratory of Lake Environment and Resources in the Arid Zone, Urumqi, China.
Front Plant Sci. 2024 Aug 9;15:1418396. doi: 10.3389/fpls.2024.1418396. eCollection 2024.
Climate change and human activities have increased droughts, especially overgrazing and deforestation, which seriously threaten the balance of terrestrial ecosystems. The ecological carrying capacity and vegetation cover in the arid zone of Xinjiang, China, are generally low, necessitating research on vegetation response to drought in such arid regions. In this study, we analyzed the spatial and temporal characteristics of drought in Xinjiang from 2001 to 2020 and revealed the response mechanism of SIF to multi-timescale drought in different vegetation types using standardized precipitation evapotranspiration index (SPEI), solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) data. We employed trend analysis, standardized anomaly index (SAI), Pearson correlation, and trend prediction techniques. Our investigation focused on the correlations between GOSIF (a new SIF product based on the Global Orbital Carbon Observatory-2), NDVI, and EVI with SPEI12 for different vegetation types over the past two decades. Additionally, we examined the sensitivities of vegetation GOSIF to various scales of SPEI in a typical drought year and predicted future drought trends in Xinjiang. The results revealed that the spatial distribution characteristics of GOSIF, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) were consistent, with mean correlations with SPEI at 0.197, 0.156, and 0.128, respectively. GOSIF exhibited the strongest correlation with SPEI, reflecting the impact of drought stress on vegetation photosynthesis. Therefore, GOSIF proves advantageous for drought monitoring purposes. Most vegetation types showed a robust response of GOSIF to SPEI at a 9-month scale during a typical drought year, with grassland GOSIF being particularly sensitive to drought. Our trend predictions indicate a decreasing trend in GOSIF vegetation in Xinjiang, coupled with an increasing trend in drought. This study found that compared with that of the traditional greenness vegetation index, GOSIF has obvious advantages in monitoring drought in the arid zone of Xinjiang. Furthermore, it makes up for the lack of research on the mechanism of vegetation GOSIF response to drought on multiple timescales in the arid zone. These results provide strong theoretical support for investigating the monitoring, assessment, and prediction of vegetation response to drought in Xinjiang, which is vital for comprehending the mechanisms of carbon and water cycles in terrestrial ecosystems.
气候变化和人类活动加剧了干旱,特别是过度放牧和森林砍伐,这严重威胁着陆地生态系统的平衡。中国新疆干旱区的生态承载能力和植被覆盖度普遍较低,因此有必要对干旱地区植被对干旱的响应进行研究。在本研究中,我们分析了2001年至2020年新疆干旱的时空特征,并利用标准化降水蒸散指数(SPEI)、太阳诱导叶绿素荧光(SIF)、归一化植被指数(NDVI)和增强植被指数(EVI)数据,揭示了不同植被类型中SIF对多时间尺度干旱的响应机制。我们采用了趋势分析、标准化异常指数(SAI)、Pearson相关性和趋势预测技术。我们的调查重点是过去二十年中不同植被类型的全球轨道碳观测卫星2(GOSIF,一种基于全球轨道碳观测站-2的新型SIF产品)、NDVI和EVI与SPEI12之间的相关性。此外,我们研究了典型干旱年份植被GOSIF对不同尺度SPEI的敏感性,并预测了新疆未来的干旱趋势。结果表明,GOSIF、归一化植被指数(NDVI)和增强植被指数(EVI)的空间分布特征一致,与SPEI的平均相关性分别为0.197、0.156和0.128。GOSIF与SPEI的相关性最强,反映了干旱胁迫对植被光合作用的影响。因此,GOSIF在干旱监测方面具有优势。在典型干旱年份,大多数植被类型在9个月尺度上GOSIF对SPEI表现出强烈响应,其中草地GOSIF对干旱尤为敏感。我们的趋势预测表明,新疆GOSIF植被呈下降趋势,同时干旱呈上升趋势。本研究发现,与传统的绿度植被指数相比,GOSIF在监测新疆干旱区干旱方面具有明显优势。此外,它弥补了干旱区植被GOSIF对多时间尺度干旱响应机制研究的不足。这些结果为研究新疆植被对干旱的监测、评估和预测提供了有力的理论支持,这对于理解陆地生态系统中的碳和水循环机制至关重要。