Reconstruction and Future Prediction of the Distribution of Wetlands in China

Reconstruction and Future Prediction of the Distribution of Wetlands in China
复制标题

中国湿地分布重建及未来预测

DOI:
10.1029/2017ef000807
复制
发表时间:
2018-11
期刊:
影响因子:
8.2
通讯作者:
Tong Shouzheng
Tong Shouzheng
中科院分区:
地球科学1区
文献类型:
--
作者:
Xue Zhenshan;Zou Yuanchun;Zhang Zhongsheng;Lyu Xianguo;Jiang Ming;Wu Haitao;Liu Xiaohui;Tong Shouzheng

文献摘要

参考文献

被引文献

相似文献

由于缺乏历史和准确的数据,人们对中国湿地在过去几千年中如何受到人类干扰和气候变化的影响以及气候变暖是否会影响中国现存的湿地知之甚少。利用基于生态位的分布模型和过去和未来的降尺度气候数据,我们预测了中国湿地的潜在分布。我们的研究结果表明,在过去的几千年里,中国一半以上的湿地已经被破坏。此外,未来的变暖将对剩余的湿地产生负面影响。淡水沼泽和季节性盐沼在未来的情景下预计将大大减少。高山区和内陆干旱区的湿地正面临退化和水盐碱化的威胁。本研究可为中国湿地保护和管理提供有价值的信息。
Due to lack of historical and accurate data, less well known is how the wetlands of China were changed and affected by human disturbance and climate change during past millennia and also, whether climate warming could impact the surviving wetlands in China. Using niche‐based distribution models and downscaled climate data of the past and future, we projected the potential distribution of wetlands in China. Our results show that more than half of the wetlands in China have been destroyed over the past few millennia. Also, future warming will have a negative effect on remaining wetlands. Freshwater swamp and seasonal salt marsh are predicted to dramatically reduce under future scenarios. Wetlands in high mountain regions and inland arid regions are under threat of degeneration and water salinization. This research could provide valuable information for the future conservation and management of wetlands in China.
DOI: 10.1198/tas.2003.s212
发表时间: 2003-02
期刊: The American Statistician
影响因子: --
作者:
R. D. Cook;S. Weisberg
通讯作者: R. D. Cook;S. Weisberg
DOI: 10.1198/004017002320256422
发表时间: 2002-08
期刊: Technometrics
影响因子: 2.5
作者:
E. Ziegel
通讯作者: E. Ziegel
DOI: 10.1002/wics.175
发表时间: 2011-08
期刊: Wiley Interdisciplinary Reviews: Computational Statistics
影响因子: --
作者:
John Neuhaus;Charles McCulloch
通讯作者: John Neuhaus;Charles McCulloch
DOI: 10.1002/9781118445112.stat07551
发表时间: 2019-11
期刊: Hands-On Machine Learning with R
影响因子: --
作者:
Bradley C. Boehmke;Brandon M. Greenwell
通讯作者: Bradley C. Boehmke;Brandon M. Greenwell
DOI: 10.1016/j.gnr.2010.03.004
发表时间: 2010-03
影响因子: 0.3
作者:
S. S. Ganzeĭ-S.;V. Yermoshin;N. Mishina
通讯作者: S. S. Ganzeĭ-S.;V. Yermoshin;N. Mishina