复合干热胁迫下黄土高原夏季植被脆弱性评估

随着气候变化的加剧，高温干旱事件频发，对植被健康生长造成了严重影响。针对相关性方法难以准确刻画复合干热胁迫下植被脆弱性的问题，利用1982—2015年去趋势和标准化的归一化植被指数（detrended and standardized normalized difference vegetation index，SNDVI）、标准化降水蒸散发指数（standardized precipitation and evapotranspiration index，SPEI）和标准化气温指数（standardized temperature index，STI），构建基于Vine Copula的复合干热胁迫下植被脆弱性评估模型，量化黄土高原不同土地利用类型和气候区植被对高温干旱的响应关系。结果表明：1）黄土高原大部分区域SNDVI与SPEI呈正相关关系，与STI呈负相关关系，草地SNDVI与SPEI、STI的相关性最高，其次为耕地，林地最低；2）相对于单一干旱或高温事件，复合干热事件进一步加剧了植被脆弱性，复合干热胁迫下黄土高原6、7、8月植被损失概率分别为0.51、0.57和0.55，较高的区域集中在陕西北部、宁夏、甘肃东部和内蒙古等地区；3）黄土高原地区不同植被类型对复合干热的脆弱性各异，脆弱性从大到小依次为草地、耕地、灌木、林地。研究结果有助于深入了解植被对气候极端事件的响应，支持应对气候变化的陆地生态系统风险管理。

Assessing the vegetation vulnerability of Loess Plateau under compounddry and hot climates

Vegetation is one of the key components in terrestrial ecosystems, particularly in climate, carbon balance, and water cycling. The healthy growth of vegetation can depend mainly on the context of climate change, such as more frequent occurrences of droughts and heat waves. Moreover, the degradation of vegetation can cause irreversible damage to the structure and functionality of terrestrial ecosystems. Compound hot and dry events can further exacerbate their impact on the vegetation, due to the positive feedback between droughts and heatwaves. Therefore, it is very necessary to evaluate the response relationship between vegetation and compound hot and dry events, in order to clarify the ecosystem response to climate change for effective mitigation and adaptation strategies. The correlation between vegetation and drought or hot indices has been commonly used to determine their relationship in recent years. However, the overall correlation coefficient is often insufficient to capture the tail dependence between extreme events and vegetation conditions. In this study, a Vine Copula-based model was constructed to assess the vulnerability of vegetation using the detrended and standardized normalized vegetation index (SNDVI), standardized precipitation and evapotranspiration index (SPEI), and standardized temperature index (STI). The probability of vegetation loss was determined for the different land use and climatic regions in the Loess Plateau from 1982 to 2015. The results show: 1) There was a positive correlation between SNDVI and SPEI in most areas of the Loess Plateau, whereas, a negative correlation was found between SNDVI and STI. Grasslands shared the highest correlation between SNDVI and SPEI, followed by cropland, and the forests with the lowest correlation. There was no significant difference in the correlation distribution between grassland and cropland SNDVI with SPEI from June to August. However, there was a gradual decrease in the correlation between forest and shrub SNDVI with SPEI. The correlation distribution between grassland and cropland SNDVI with STI remained relatively unchanged, while the correlation between forest and shrub SNDVI with STI gradually increased. 2) The vulnerability values of vegetation to extreme compound dry and hot conditions were 0.51, 0.57, and 0.55 respectively, in June, July, and August, which was significantly higher than those to single drought or high-temperature events. Regions with higher vulnerability were concentrated in the northern part of Shaanxi, Ningxia, eastern Gansu, and Inner Mongolia. 3) The vegetation exhibited a significantly higher vulnerability to extreme compound dry and hot conditions in arid and semi-arid regions, compared with the single extreme drought or high-temperature events. In humid and semi-humid regions, vegetation vulnerability to extreme compound dry and hot conditions was generally comparable or slightly lower than that to single drought or high-temperature events. 4) There was a great variation in the vulnerability of different vegetation types. The vulnerability was ranked in the descending order of grassland, cropland, shrub, forest. The vulnerability of grassland to extreme compound dry and hot conditions increased by 26% to 56% during summer, compared with single drought or high-temperature events, while the cropland vulnerability increased by 11% to 24% and 19% to 48%, respectively. Since the SNDVI can only represent the vegetation cover, more vegetation indices (such as gross primary productivity (GPP) and net primary productivity (NPP)) can be expected to assess the vegetation dynamics and their response to extreme events, in order to reduce some uncertainties in the future research.