Assessment of Carbon Dynamics of Forest Ecosystems in the Poyang Lake Basin Responding to Afforestation and Future Climate Change

2013 ◽  
Vol 4 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Zhou Lei ◽  
Wang Shaoqiang ◽  
Ju Weimin ◽  
Xiong Zhe ◽  
Georg Kindermann ◽  
...  
2012 ◽  
Vol 16 (7) ◽  
pp. 2005-2020 ◽  
Author(s):  
S. L. Sun ◽  
H. S. Chen ◽  
W. M. Ju ◽  
J. Song ◽  
J. J. Li ◽  
...  

Abstract. To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan) within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m3 s−1 yr−1 and 1.29 m3 s−1 yr−1 at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m3 s−1 yr−1), Gaosha (1.12 m3 s−1 yr−1), and Xiashan (1.34 m3 s−1 yr−1), while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m3 s−1 yr−1). In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds. For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3) under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1) for the period of 2061–2100. When the future changes in the soil water storage changes are assumed ignorable, the streamflow shows an uptrend with the projected increases in both precipitation and evapotranspiration (except for the SRESB1 scenario in Xiashan watershed) relative to the observed mean during 1961–2000. Furthermore, the largest increase in the streamflow is found at Meigang (+4.31%) and Xiashan (+3.84%) under the SRESA1B scenario, while the increases will occur at Saitang (+6.87%) and Gaosha (+5.15%) under the SRESB1 scenario.


2012 ◽  
Vol 112 (1-2) ◽  
pp. 169-183 ◽  
Author(s):  
Shanlei Sun ◽  
Haishan Chen ◽  
Weimin Ju ◽  
Jie Song ◽  
Hao Zhang ◽  
...  

The Holocene ◽  
2021 ◽  
pp. 095968362110477
Author(s):  
Maofeng He ◽  
Fengxian Bu ◽  
Claudio O Delang ◽  
Jialin Xie ◽  
Quan Ye ◽  
...  

Climate change and human activities have been an important part of studies regarding historical environmental changes in China over the past 2000 years. In this study, we focused on environmental changes, that is, natural disasters and human activities, in the Poyang Lake Basin over the past 2000 years, to analyze interactions between land use cover changes and human activities from the perspective of regional sustainable development. We collected historical records of climate and hydrology, floods and droughts, and rivers and lakes in the Poyang Lake area, and established time sequences for the floods and droughts, lake water level and lake area, amount of farming land, and population, in order to discuss interactions between changes in the environment and the climate, with emphasis on the impacts of extreme events on lake and river basin environment changes. The following results were obtained. First, climate changes in historical periods had wide-ranging and far-reaching impacts on agricultural production, especially disasters caused by climate change. Among the changes in the Poyang Lake basin environment, including river network systems, lake water levels, etc., changes in lake water volume are direct evidence of climate change, adaptation to climate change, and obvious phased characteristics. Second, in the process of changes to the lake and river network in the Poyang Lake Basin, social and economic development is accompanied by evolution of the lake. Increases and decreases in population, the scale of agricultural production, and lake environment changes have direct and significant interactions. Third, the Poyang Lake basin’s environmental changes during the historical period are mainly reflected in the pressure feedback mode of “population–agriculture” in the lake environment.


2021 ◽  
Vol 123 ◽  
pp. 103019
Author(s):  
Xiangyong Lei ◽  
Lu Gao ◽  
Jianhui Wei ◽  
Miaomiao Ma ◽  
Ligang Xu ◽  
...  

2020 ◽  
Author(s):  
Hongfei Xie ◽  
JUNFANG ZHAO ◽  
Jianyong Ma ◽  
Weixiong Yan

Abstract Background At present, global warming is an indisputable fact, and more and more attention has been paid to the impacts of climate warming on global ecological environments. Forests play increasing significant roles in regulating global carbon balance and mitigating climate change. Therefore, to understand the response mechanisms of the carbon budget of global forest ecosystems to future climate change, an improved version of the FORest ecosystem Carbon budget model for CHiNa (FORCCHN) and future Representative Concentration Pathway (RCP) scenario RCP4.5 and RCP8.5 were applied in this study.Results The global forest ecosystems will play a major role in the carbon sink under the future two climate change scenarios. In particular, the average carbon budget (namely the Net Ecosystem Productivity, NEP) of global forest ecosystems under RCP4.5 scenario was estimated to be 0.017 kg(C)·m− 2·yr− 1 from 2006 to 2100. The future carbon sink areas of global forest ecosystems will increase significantly. Under RCP4.5 and RCP8.5 climate scenarios, the carbon sink areas of global forest ecosystems during 2026–2100 would be significantly higher than those in 2006–2025, with increases of 83.16–87.26% and 23.53–29.70%, respectively. The impacts of future climate change on NEP of global forest ecosystems will significantly vary between different regions. The NEP of forests will be enhanced in the northern hemisphere and significantly weakened in the southern hemisphere under the future two climate change scenarios. The carbon sink regions of global forests will be mainly distributed in the middle and high latitudes of the northern hemisphere. In particular, the forests'NEP in northeastern and central Asia, northern Europe and western North America will increase by 40%~80%. However, the NEP of forests will decrease by 20%~40% in the most regions of the southern hemisphere. In northern South America and central Africa, the forests' NEP will be reduced by more than 40%.Conclusions The global forest ecosystems will play a major role in the carbon sink under the future two climate change scenarios. However, the NEP of forests will be enhanced in the northern hemisphere and significantly weakened in the southern hemisphere. In the future, in some areas of southern hemisphere, where the forests' NEP was predicted to be reduced, some measures for improving forest carbon sink, such as strengthening forest tending, enforcing prohibiting deforestation laws and scientific forest management, and so on, should be implemented to ensure immediate mitigation and adaptation to climate change.


2014 ◽  
Vol 644-650 ◽  
pp. 5471-5474
Author(s):  
Jian Bo He ◽  
Zhen Wang

The climate change is an important part of global change which can change the present situation of regional and even global human and animal’s survival. This article is mainly discussing the impact of climate change of the Poyang Lake Basin on regional tourism. On the basis of finding the relevant data of the climate change impact on regional tourism at home and broad, it analyses the influences that the regional tourism destination and tourists and tourism places have, as well as puts forward corresponding countermeasures.


Author(s):  
Jie Wen ◽  
Yilin Wang ◽  
Guangru Sun ◽  
Shujing Liu ◽  
Weihua Zhang

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