Synthesis Research Center of Chinese Ecosystem Research Network, and Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
Sci Rep. 2019 Dec 20;9(1):19516. doi: 10.1038/s41598-019-56115-5.
Carbon use efficiency (CUE), one of the most important eco-physiological parameters, represents the capacity of plants to transform carbon into new biomass. Understanding the variations and controls of CUE is crucial for regional carbon assessment. Here, we used 15-years of continuous remote sensing data to examine the variations of CUE across broad geographic and climatic gradients in China. The results showed that the vegetation CUE was averaged to 0.54 ± 0.11 with minor interannual variation. However, the CUE greatly varied with geographic gradients and ecosystem types. Forests have a lower CUE than grasslands and croplands. Evergreen needleleaf forests have a higher CUE than other forest types. Climate factors (mean annual temperature (MAT), precipitation (MAP) and the index of water availability (IWA)) dominantly regulated the spatial variations of CUE. The CUE exhibited a linear decrease with enhanced MAT and MAP and a parabolic response to the IWA. Furthermore, the responses of CUE to environmental change varied with individual ecosystem type. In contrast, precipitation exerted strong control on CUE in grassland, while in forest and cropland, the CUE was mainly controlled by the available water. This study identifies the variations and response of CUE to environmental drivers in China, which will be valuable for the regional assessment of carbon cycling dynamics under future climate change.
碳利用效率（CUE）是最重要的生态生理参数之一，代表植物将碳转化为新生物量的能力。了解 CUE 的变化及其控制因素对于区域碳评估至关重要。在这里，我们使用了 15 年的连续遥感数据，研究了中国广泛地理和气候梯度上 CUE 的变化。结果表明，植被 CUE 的平均值为 0.54±0.11，年际变化较小。然而，CUE 随地理梯度和生态系统类型有很大的变化。森林的 CUE 低于草地和农田。常绿针叶林比其他森林类型具有更高的 CUE。气候因素（年平均温度（MAT）、降水（MAP）和水分可用性指数（IWA））主导着 CUE 的空间变化。CUE 随 MAT 和 MAP 的增加呈线性下降，随 IWA 的增加呈抛物线响应。此外，CUE 对环境变化的响应因个别生态系统类型而异。相比之下，降水对草地 CUE 的控制作用较强，而在森林和农田中，CUE 主要受可用水的控制。本研究确定了中国 CUE 对环境驱动因素的变化和响应，这对于未来气候变化下区域碳循环动态的评估将具有重要价值。
