Decadal change and inter-annual variability of net primary productivity on the Tibetan Plateau

初级生产 环境科学 降水 中分辨率成像光谱仪 气候学 气候变化 大气科学 云量 空间变异性 生态系统 卫星 气象学 云计算 地质学 地理 生态学 海洋学 航空航天工程 工程类 操作系统 数学 统计 生物 计算机科学
作者
Lan Cuo,Yongxin Zhang,Xu-Ri Xu-Ri,Bingrong Zhou
出处
期刊:Climate Dynamics [Springer Science+Business Media]
卷期号:56 (5-6): 1837-1857 被引量:16
标识
DOI:10.1007/s00382-020-05563-1
摘要

Abstract Net primary productivity (NPP) is an important indicator of plant dynamics and the net carbon exchange between the terrestrial ecosystem and atmosphere. Both the long-term shifts in climate mean (climate change) and short-term variations around the climate mean (climate variability) have impacts on NPP but studies examining both aspects of climate variations are rare especially in the data-scarce regions such as the Tibetan Plateau (TP). Here, we used a dynamic vegetation model to investigate the impacts of the changes and variabilities in temperature, precipitation, cloud cover and CO 2 on NPP on the TP. The simulated NPP was evaluated using field and Moderate-Resolution Imaging Spectroradiometer NPP and was found to be reasonable. At monthly time scale, NPP significantly correlated concurrently and at 1-month lag with temperature, precipitation and cloud cover (coefficient of determination, R 2 , in 0.52–0.77). Annual NPP variability was high (low) where mean annual NPP was low (high). The effects of annual precipitation, cloud cover and temperature variability on annual NPP variability were spatially heterogeneous, and temperature variability appeared to be the dominant factor (R 2 of 0.74). Whereas, NPP changes were very similar to CO 2 increases across the TP (spatial correlation of 0.60), indicating that long-term changes in NPP were dominated by CO 2 increases. For both variability and long-term changes in NPP, temperature was the major factor of influence (highest spatial correlation of 0.67). These findings could assist in making informed mitigation policies on the impacts of climate change and variability on ecosystem and local nomadic communities.
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