全球增温背景下，复合干热事件的频率和强度呈现上升趋势，对社会经济发展造成严重威胁，受到了社会和学术界的广泛关注。作为陆地生态系统的重要组成部分，植被在调节水分和温度方面具有关键作用，高温与干旱并发的极端气候事件通过改变水热条件影响植被生态系统碳水循环过程，从而影响其碳水耦合程度。然而，目前研究对高温、干旱事件的复合特征关注较少，且全球植被碳水耦合对复合干热事件的响应机制尚不清楚。长江中下游作为典型季风气候区，近年来复合干热事件表现出持续时间长、影响范围广、极端性强等特点，对生态系统造成严重影响。探讨该地区复合干热事件特征及其对植被碳水利用效率的影响，对应对气候变化和促进区域发展至关重要。因此，本文基于标准化降水指数（SPI）和标准化温度指数（STI）识别复合干热年份，并利用Copula模型联合构建复合干热指数（CDHI），表征复合干热年份中复合事件的强度。同时基于总初级生产力（GPP）、净初级生产力（NPP）和蒸散数据（ET）估算植被水分利用效率（WUE）和碳利用效率（CUE），并分析其时空变化特征，利用联合生态弹性指数方法评估植被生态系统弹性状态。最后，采用一阶差分法和结构方程模型等方法分析长江中下游植被碳水利用效率对气候变化的响应，进一步探究其与气候因子的路径关系。主要结论如下：

（1）长江中下游干旱与高温呈现显著协同增强趋势，复合干热事件发生频率、强度及影响范围持续扩大。2001-2019年长江中下游高温热浪程度增强、范围扩大，2008年、2013年、2019年气温偏高且极端性强。2011年后，长江中下游干旱强度和频率增加，春季干旱化、秋季极端干旱趋势明显。发生复合高温干旱且影响范围较大的年份有2005年、2007年、2008年、2009年、2013年、2014年、2017年和2019年，大部分复合高温干旱事件集中在4-9月。时间尺度上，长江中下游年均CDHI呈波动上升趋势，流域内高强度和中高强度等级面积占比增加，表明干热状况有加剧趋势。空间尺度上，长江中下游复合干热状况逐步重发，强度大、范围广，热点区域从北向南转移，南部尤其是干流沿线及以南部地区高温干旱复合风险增加趋势显著。

（2）长江中下游WUE与CUE呈现显著地形-植被耦合分异。时间尺度上，WUE多年均值为1.81 gC×mm^-1×m^-2，CUE在19年间平均值为0.41，整体呈波动上升。空间尺度上，WUE随海拔升高而升高，呈“南高北低，西高东低”分布，流域CUE呈“西北高，东南低”分布，整体波动上升。各类植被WUE和CUE均呈波动增长，耕地WUE水平较低，林地WUE水平较高，草地CUE值整体较高且增长值较大。WUE和CUE同增同减区域占67.9%，WUE和CUE变化趋势相反的区域占28.6%，分布在长江干流和人口密集区。联合生态弹性指数方法可将生态系统分为有弹性、轻微非弹性和中等非弹性三个等级。有弹性区域（占10.67%）在研究区东北部秦岭和南阳盆地；中等非弹性区域（占11.32%）在长江干流及洞庭湖周边，受人类活动影响大；轻微非弹性区域面积占比最大，位于研究区南部，以林地为主。

（3）降水和气温对植被碳水利用效率表现出差异化驱动机制。降水对CDHI为正贡献率的区域面积与负贡献率基本持平，气温对CDHI贡献率高的区域占33.6%，植被类型为耕地（水田）。60.3%的区域降水对WUE呈正贡献率，植被类型为林地，负贡献率的地区多为耕地；气温对WUE正向贡献的区域主要植被类型为有林地，负向贡献的区域约为12.3%，主要植被类型为水田。降水对CUE正向贡献率的区域约占17.4%，植被覆盖类型为水田，负向贡献率的区域约占21.3%，植被类型为林地。影响因子对WUE的直接效应绝对值大小为：气温＞降水＞CDHI，降水通过抑制CDHI间接增强WUE，气温通过增强CDHI间接抑制WUE，但效应微弱。CUE的驱动机制中，降水（-0.172）与气温（-0.141）均呈现负向相关关系，CDHI呈现微弱正向关系。对于不同植被类型，气温对草地WUE和CUE抑制作用最强；降水对耕地WUE促进作用最强，对耕地CUE抑制作用最强；CDHI对林地WUE和CUE正向效应较明显。

In the context of global warming, the frequency and intensity of compound dry and hot events show an upward trend, posing a serious threat to socio-economic development and attracting extensive attention from society and academia. As an important component of terrestrial ecosystems, vegetation plays a key role in regulating water and temperature, and extreme climatic events with high temperature and drought concurrently impact the carbon and water cycling process of vegetation ecosystems by altering the hydrothermal conditions, thus affecting their coupling. However, the current research pays less attention to the composite characteristics of hot-dry events, and the response mechanism of global vegetation carbon and water coupling to the composite dry and hot events is still unclear. As a typical monsoon climate area, the middle and lower reaches of the Yangtze River Basin, in recent years, have been characterized by long duration, widespread impact, and high intensity, severely damaging ecosystems. It is important to explore the characteristics of compound dry heat events and their impacts on vegetation water and carbon use efficiency to address climate change and promote efficient regional development. Therefore, this paper identifies composite dry and hot years based on Standardized Precipitation Index (SPI) and Standardized Temperature Index (STI), and constructs the Compound Drought and Heat Index (CDHI) using the Copula model to characterize the intensity of compound events in these years. The temporal and spatial changes of Water Use Efficiency (WUE) and Carbon Use Efficiency (CUE) of the vegetation in the middle and lower reaches of the Yangtze River are also investigated based on the Gross Primary Productivity (GPP), Net Primary Productivity (NPP), and Evapotranspiration (ET) data, and the joint ecological resilience index is used to assess the resilience of the vegetation ecosystem. Finally, the first-order difference method and structural equation modeling (SEM) are used to analyze the response of vegetation WUE and CUE to climate change in the middle and lower reaches of the Yangtze River Basin, and to further explore the path relationships with climate factors. The main conclusions are as follows:

(1) Drought and high temperature in the middle and lower reaches of the Yangtze River showed a significant synergistic trend, and the frequency, intensity and impact range of the compound dry and hot events continued to expand. The degree of high-temperature heat waves in the middle and lower reaches of the Yangtze River enhanced and expanded in scope from 2001 to 2019, with high temperatures and high extremes in 2008, 2013, and 2019.Since 2011, the intensity and frequency of droughts increased, and the trend of droughtization in the spring and extreme drought in the fall was obvious. The years in which compound high-temperature droughts with a large impact range occurred were 2005, 2007, 2008, 2009, 2013, 2014, 2017, and 2019, and most of the compound dry and hot events were concentrated in April-September. On the time scale, the annual average CDHI in the middle and lower reaches of the Yangtze River Basin showed a fluctuating upward trend, and the proportion of the area with high and medium-high intensity classes increased in the basin, indicating an intensifying trend of dry and hot conditions. On the spatial scale, the compound dry and hot conditions in the region gradually recur with high intensity and wide range, and the hotspot area is shifted from the north to the south, with a significant increase in the compound risk of high temperature and drought in the southern part of the basin, especially along the main streams and the areas to the south.

(2) WUE and CUE in the middle and lower reaches of the Yangtze River show significant topography-vegetation coupling divergence. On the time scale, the multi-year average value of WUE was 1.81 gC×mm^-1×m^-2, and the average value of CUE was 0.41 during the 19 years, with an overall fluctuating increase. On the spatial scale, WUE increased with elevation, showing a distribution of “high in the south and low in the north, high in the west and low in the east”, and CUE in the watershed showed a distribution of “high in the northwest and low in the southeast”, with an overall fluctuating increase. The WUE and CUE of all vegetation types in the study area showed fluctuating growth, the WUE level of cultivated land was low, the WUE level of forested land was high, and the CUE value of grassland was high and had a large growth value. 67.9% of the areas with the same increase and decrease of WUE and CUE, and 28.6% of the areas with the opposite trend of change of WUE and CUE were located in the main streams of the Yangtze River and the densely populated areas. The ecosystems were categorized into resilient, slightly inelastic and moderately inelastic by the joint ecological resilience index method. The resilient areas (10.67%) are in the Qinling and Nanyang basins in the northeast of the study area; the moderately inelastic areas (11.32%) are around the Yangtze River and Dongting Lake, which are highly affected by human activities; and the slightly inelastic areas account for the largest proportion of the area, which are in the south of the study area and are dominated by forested land.

(3) Precipitation and temperature exhibit differential driving mechanisms for vegetation water and carbon use efficiencies. The area of areas with a positive contribution of precipitation to CDHI is almost the same as the negative contribution, the area with a high contribution of temperature to CDHI is 33.6%, and the type of vegetation is cultivated land (paddy field). 60.3% of the regions with positive contribution of precipitation to WUE have vegetation type of forested land, and most of the regions with negative contribution are cultivated land; the main vegetation type of the regions with positive contribution of temperature to WUE is forested land, and the regions with negative contribution are about 12.3%, and the main vegetation type is paddy field. The area with positive contribution of precipitation to CUE is about 17.4%, and the type of vegetation cover is paddy field, and the area with negative contribution is about 21.3%, and the type of vegetation is forested land. The absolute magnitude of the direct effect of the influencing factors on WUE was: temperature>precipitation>CDHI, precipitation indirectly enhanced WUE by suppressing CDHI, and temperature indirectly suppressed WUE by enhancing CDHI, but the effect was weak. Among the driving mechanisms of CUE, both precipitation (-0.172) and temperature (-0.141) showed negative correlations, and CDHI showed a weak positive relationship. For different vegetation types, air temperature had the strongest inhibitory effect on grassland WUE and CUE; precipitation had the strongest promotional effect on cropland WUE and the strongest inhibitory effect on cultivated land CUE; and CDHI had a more pronounced positive effect on woodland WUE and CUE.

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