西南高山亚高山区植被水分利用效率时空特征及其与气候因子的关系

水分利用效率(WUE)是深入理解生态系统水碳循环及其耦合关系的重要指标。为了揭示气候变化背景下区域尺度不同植被类型的响应和适应特征, 对中国西南高山亚高山地区2000-2014年的9种植被类型的WUE时空特征及其影响因素进行探究。该研究基于MODIS总初级生产力(GPP)、蒸散发(ET)数据和气象数据, 估算西南高山亚高山区植被WUE, 采用趋势分析及相关分析等方法, 分析了研究区植被WUE与气温、降水及海拔的关系。主要结果: (1)西南高山亚高山区2000-2014年植被WUE多年均值为0.95 g·m^-2·mm^-1, 整体呈显著增加趋势, 增速为0.011 g·m^-2·mm^-1·a^-1; 空间上WUE呈东南高西北低的分布, 85.84%区域的WUE呈增加趋势。(2)西南高山亚高山区各植被类型WUE多年均值表现为常绿针叶林>稀树草原>常绿阔叶林>有林草原>农田>落叶阔叶林>混交林>郁闭灌丛>草地; 时间上, 各植被类型WUE均呈上升趋势。(3)西南高山亚高山区89.56%区域的WUE与气温正相关, 92.54%区域的WUE与降水量负相关; 各植被类型中, 草地WUE与气温的相关性最高, 有林草原WUE与降水量的相关性最高。(4)西南高山亚高山区典型的地带性顶极植被常绿针叶林的WUE具有较强的海拔适应性及应对气候变化的能力。

Spatio-temporal characteristics of vegetation water use efficiency and their relationships with climatic factors in alpine and subalpine area of southwestern China

Aims Water use efficiency (WUE) is an important indicator for understanding the coupling and trade-off relationships between ecosystem water and carbon cycles. In order to reveal the response and adaptation characteristics of different vegetation types to climate change regionally, we examined the trends, altitudinal distributions, and spatial variations of WUE in nine vegetation types in the alpine and subalpine area of southwestern China during the period of 2000-2014. Methods We estimated the vegetation WUE using Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) and evapotranspiration (ET) products, and the gridded climate data interpolated from Aunsplin. Trend analysis and correlation analysis were conducted to examine the relationships between vegetation WUE and other factors, including air temperature, precipitation, and elevation. Important findings The results showed that: (1) The average annual WUE in the study region was 0.95 g·m^-2·mm^-1 with a significantly increasing trend at 0.011 g·m^-2·mm^-1·a^-1 from 2000 to 2014. The average WUE showed a pattern of higher in the southeast region but lower in the northwest region, and the WUE was found increased in 85.84% of study area. (2) The average WUEs were increasing in all vegetation types, and the WUEs showed a gradient of evergreen needleleaf forest > savannas > evergreen broadleaf forest > woody savannas > cropland > deciduous broadleaf forest > mixed forest > closed shrublands > grassland. (3) The WUE was positively correlated with air temperature in 89.56% of the study area, but it was negatively correlated with precipitation in 92.54% of the study area. The highest correlation between WUE and air temperature was found in grassland, while the highest correlation between WUE and precipitation was identified in woody savannas. (4) As the regional climax vegetation type in southwestern China, the evergreen needleleaf forest’s WUE has high adaptation abilities to both altitudinal change and climate change.