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浏览/检索结果: 共307条，第1-10条 帮助 限定条件 专题：地理科学与资源研究所    第一署名单位    第一作者单位    通讯作者单位     条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Soil Mineral-Associated Organic Carbon and Its Relationship to Clay Minerals across Grassland Transects in China 期刊论文  OAI收割 APPLIED SCIENCES-BASEL, 2024, 卷号: 14, 期号: 5, 页码: 2061 作者:  Zhao, Minshuang;  Zhang, Zhidan;  Li, Meijia;  Gao, Chunyang;  Zhang, Jinjing   |  收藏  |  浏览/下载：14/0  |  提交时间：2024/04/08 climate  mineral-associated organic carbon  clay mineralogy  spatial variation  grassland transects   Widespread reduction in gross primary productivity caused by the compound heat and drought in Yangtze River Basin in 2022 期刊论文  OAI收割 ENVIRONMENTAL RESEARCH LETTERS, 2024, 卷号: 19, 期号: 3, 页码: 34048 作者:  Li, Tingyu;  Wang, Shaoqiang;  Chen, Bin;  Wang, Yingping;  Chen, Shiliang   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/04/08 gross primary productivity  compound heat and drought  extreme climate event  Yangtze River Basin   A new scheme of climate-vegetation regionalization in the Hengduan Mountains Region 期刊论文  OAI收割 SCIENCE CHINA-EARTH SCIENCES, 2024, 页码: 18 作者:  Zhang, Xueqin;  Xu, Xiaoming;  Li, Xiang;  Cui, Peng;  Zheng, Du   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/03/04 Climate-vegetation regionalization  Thin plate smoothing spline (TPSS)  GeoDetector  Stepwise downscaling pane division method  Hengduan Mountains Region   Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland 期刊论文  OAI收割 GLOBAL CHANGE BIOLOGY, 2024, 卷号: 30, 期号: 1, 页码: 17 作者:  Liu, Yijing;  Wang, Peiyan;  Elberling, Bo;  Westergaard-Nielsen, Andreas   |  收藏  |  浏览/下载：10/0  |  提交时间：2024/01/22 Arctic tundra ecosystem  climate change  projection  seasonal transition dates  snow cover   Relative humidity and solar radiation exacerbate snow drought risk in the headstreams of the Tarim River 期刊论文  OAI收割 ATMOSPHERIC RESEARCH, 2024, 卷号: 297, 页码: 18 作者:  Wang, Zhixia;  Huang, Shengzhi;  Mu, Zhenxia;  Leng, Guoyong;  Duan, Weili   |  收藏  |  浏览/下载：7/0  |  提交时间：2024/01/02 Snow drought risk  Copula function  Equitable threat score  Multivariable return period  Dynamic drought risk   Simulation of urban thermal anisotropy at remote sensing pixel scales: Evaluating three schemes using GUTA-T over Toulouse city 期刊论文  OAI收割 REMOTE SENSING OF ENVIRONMENT, 2024, 卷号: 300, 页码: 15 作者:  Wang, Dandan;  Hu, Leiqiu;  Voogt, James A.   |  收藏  |  浏览/下载：9/0  |  提交时间：2024/01/02 Thermal infrared remote sensing  Thermal anisotropy  Land surface temperature  Urban areas  Parametric model  GUTA-T   Future variation of land surface temperature in the Yangtze River Basin based on CMIP6 model 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 卷号: 16, 期号: 1, 页码: 2776-2796 作者:  Liu, Jinlian;  Tang, Hanya;  Yan, Fengqin;  Liu, Shiwei;  Tang, Xuguang   |  收藏  |  浏览/下载：16/0  |  提交时间：2023/09/07 Temporal and spatial changes  Delta downscaling  Random forest  Global warming  >   Conversion of biochar into sulfonate-bearing solid acids used for the hydrolysis of tylosin: the effect of aromaticity and degree of condensation 期刊论文  OAI收割 BIOCHAR, 2023, 卷号: 5, 期号: 1, 页码: 88 作者:  Xie, Qianqian;  Yang, Xiao;  Sarkar, Binoy;  Dou, Xiaomin;  Withana, Piumi Amasha   |  收藏  |  浏览/下载：4/0  |  提交时间：2024/01/04 Biochar upgrading  Sulfonation  Hydrolytic mitigation  Tylosin removal  Biochar-based solid acids   Spring wood phenology responds more strongly to chilling temperatures than bud phenology in European conifers 期刊论文  OAI收割 TREE PHYSIOLOGY, 2023, 页码: 14 作者:  Lin, Shaozhi;  Wang, Huanjiong;  Dai, Junhu;  Ge, Quansheng   |  收藏  |  浏览/下载：1/0  |  提交时间：2024/03/01 budburst  climate change  wood formation   Prediction of monthly average and extreme atmospheric temperatures in Zhengzhou based on artificial neural network and deep learning models 期刊论文  OAI收割 FRONTIERS IN FORESTS AND GLOBAL CHANGE, 2023, 卷号: 6, 页码: 1249300 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/01/04 extreme atmospheric temperature  artificial neural network  deep learning  CNN-GRU  CNN-LSTM  prediction  training algorithm  forest