Daytime and nighttime temperatures exert different effects on vegetation net primary productivity of marshes in the western Songnen Plain

第一作者：	Wang, Yanji
英文第一作者：	Wang, Yanji
联系作者：	Shen, Xiangjin
英文联系作者：	Shen, Xiangjin
发表年度：	2022
卷：	137
摘要：	The western Songnen Plain has a large area of marshes that are able to modulate the regional carbon cycle. Net primary productivity (NPP) is an important ecological indicator of carbon storage within the marsh ecosystems. Although climate change could have significantly changed marsh vegetation NPP during the past decades, the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh vegetation NPP remain unclear in the western Songnen Plain. In this paper, we assessed the spatiotemporal variation in the NPP of marshes at the western Songnen Plain and evaluated its response to climate change from 2000 to 2020. The NPP of marshes over the western Songnen Plain increased significantly at a rate of 5.69 g C/m(2)/a during 2000 to 2020, with an average value of about 273.62 g C/m(2)/a. The largest increase of the NPP of marshes was mainly distributed in the northwest part of the Songnen Plain. Correlation analysis results showed that the increased precipitation in summer and autumn could enhance the NPP of marsh vegetation. By contrast, the increase of mean temperature in summer reduced the NPP of marshes. In addition, we first found the asymmetric impacts of summer minimum temperature (T-min) and maximum temperature (T-max) on marsh vegetation NPP. Notably, the increase in summer T-max could significantly reduce NPP, while the increase in T-min could increase NPP. Under the background of global asymmetric warming of daytime and nighttime temperatures, more attention should be paid to the different effects of T-max and T-min on marsh NPP in the western Sonegnen Plain. The findings of this study can provide theoretical guidance for ecological protection and the adaptive management of marsh vegetation at the western Songnen Plain.
刊物名称：	Ecological Indicators
参与作者：	Y. J. Wang, X. J. Shen, M. Jiang, S. Z. Tong and X. G. Lu