气候变化和人类活动加剧了干旱,尤其是过度放牧和砍伐森林,严重威胁陆地生态系统的平衡。新疆干旱区生态承载力与植被覆盖,中国,通常很低,有必要研究此类干旱地区的植被对干旱的响应。在这项研究中,利用标准化降水蒸散指数(SPEI)分析了2001-2020年新疆干旱的时空特征,揭示了SIF对不同植被类型多时间尺度干旱的响应机制,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。我们采用了趋势分析,标准化异常指数(SAI),皮尔逊相关性,和趋势预测技术。我们的调查重点是GOSIF(基于全球轨道碳观测站-2的新SIF产品)之间的相关性,NDVI,在过去的二十年里,不同植被类型的EVI和SPEI12。此外,我们研究了典型干旱年份植被GOSIF对各种尺度SPEI的敏感性,并预测了新疆未来的干旱趋势。结果表明,GOSIF的空间分布特征,归一化植被指数(NDVI),和增强植被指数(EVI)是一致的,与SPEI的平均相关性分别为0.197、0.156和0.128。GOSIF与SPEI表现出最强的相关性,反映了干旱胁迫对植被光合作用的影响。因此,GOSIF证明有利于干旱监测目的。在典型的干旱年份中,大多数植被类型在9个月的尺度上显示出GOSIF对SPEI的强劲响应,草原GOSIF对干旱特别敏感。我们的趋势预测表明,新疆GOSIF植被呈下降趋势,再加上干旱的增加趋势。本研究发现,与传统绿度植被指数相比,GOSIF在新疆干旱区干旱监测中具有明显优势。此外,弥补了干旱区植被GOSIF对干旱多时间尺度响应机制研究的不足。这些结果为调查监测提供了有力的理论支持,评估,新疆植被对干旱的响应预测,这对于理解陆地生态系统中碳和水循环的机制至关重要。
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.