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中国黄(渤)海候鸟栖息地系列遗产地和提名地突出普遍价值的全球对比分析 被引量:3
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作者 闻丞 顾燚芸 黄越 《自然与文化遗产研究》 2020年第4期1-12,共12页
中国黄(渤)海候鸟栖息地系列遗产地和提名地位于黄海生态区中国一侧沿岸,对东亚-澳大利西亚候鸟迁飞路线上的、超过20种受胁鸟种的生存具有关键作用。按照世界遗产价值全球对比分析框架,通过检索联合国教科文组织世界遗产中心数据库和... 中国黄(渤)海候鸟栖息地系列遗产地和提名地位于黄海生态区中国一侧沿岸,对东亚-澳大利西亚候鸟迁飞路线上的、超过20种受胁鸟种的生存具有关键作用。按照世界遗产价值全球对比分析框架,通过检索联合国教科文组织世界遗产中心数据库和相关发表文献,我们对以标准(ix)或标准(x)列入或提名的遗产地和提名地,从生物地理区划、保护对象和在东亚-澳大利西亚迁飞区(EAAF)范围内对受胁鸟类保护发挥的作用等方面,对中国黄(渤)海候鸟栖息地系列遗产地和提名地与EAAF范围内的其他属于沿海类型的候鸟栖息地进行比较研究(尤其从生境类型、地形地貌成因等方面将其与韩国西南海岸潮间带提名地进行比较)。此外,还将其与世界上仅有的3个位于EAAF范围之外,属于沿海滩涂、三角洲类型的遗产地或提名地,从生物地理区划、鸟种数量、滩涂成因等方面进行了比较研究。结果显示,中国黄(渤)海沿岸的多样地貌和丰富栖息地类型形成于数条世界级大河持续输入沉积物堆积和大陆架沉降交互的复杂过程,这一全球独特过程造就了广袤多样的栖息地和丰富的物种。EAAF范围内已有15处与候鸟保护相关的自然遗产地,中国黄(渤)海候鸟栖息地系列遗产地和提名地是全球受胁迁徙鸟类种数最多的遗产地和提名地,其整体申报成功将对在EAAF范围内实现完整保护将发挥极大的积极促进作用。 展开更多
关键词 中国()候鸟栖息地系列遗产地和提名地 突出普遍价值 全球对比分析
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“中国黄(渤)海候鸟栖息地(第二期)”申报中的重要候鸟栖息地保护状况——基于以半蹼鹬为主的候鸟重要迁徙中停地江苏省连云港市的调查
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作者 杨子悠 韩永祥 +6 位作者 李静 蔡上逍 郭瑾 项乐 章麟 蔡志扬 闻丞 《自然与文化遗产研究》 2021年第2期14-21,共8页
连云港市位于中国江苏省北部,该地滨海湿地位于东亚-澳大利西亚迁飞路线(East Asia-Australasian F lyway,EAAF)的中心。连云港是候鸟在迁飞途中的重要停歇点之一,也是一个人口密集且正在快速发展的滨海城市。2003—2018年间,27%的连云... 连云港市位于中国江苏省北部,该地滨海湿地位于东亚-澳大利西亚迁飞路线(East Asia-Australasian F lyway,EAAF)的中心。连云港是候鸟在迁飞途中的重要停歇点之一,也是一个人口密集且正在快速发展的滨海城市。2003—2018年间,27%的连云港潮间带被围垦,并逐步转化为工业园区和水产养殖塘。然而,这些区域目前仍有重要的保护价值。在2008—2018年的调查期间,连云港共记录到鹬类43种,其中有20种超过了1%的EAAF种群总数。此前的调查仅由一名当地调查员执行展开,这意味着调查结果在时间和空间的维度上都十分局限。为了对这片区域的水鸟,尤其是鹬类有更深入的了解,2019年5月9—13日,笔者团队在连云港市的临洪河口、青口河口和兴庄河口开展了水鸟同步调查,以期推动更有效的水鸟及其栖息地的保育工作。 展开更多
关键词 连云港 半蹼鹬 中国() 候鸟栖息地
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遗产综合体构建研究--以盐城世界自然遗产为例
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作者 陈耀华 魏天星 《中国园林》 CSCD 北大核心 2024年第2期11-16,共6页
世界遗产管理已经进入可持续、高质量发展的新阶段,亟须探索保护与发展联动的管理模式。借鉴“旅游综合体”这一功能复合、高效互动、以点带面的旅游开发模式,在遗产地构建“遗产综合体”,即以遗产保护为核心,由与遗产相关的监测、研究... 世界遗产管理已经进入可持续、高质量发展的新阶段,亟须探索保护与发展联动的管理模式。借鉴“旅游综合体”这一功能复合、高效互动、以点带面的旅游开发模式,在遗产地构建“遗产综合体”,即以遗产保护为核心,由与遗产相关的监测、研究、展示、服务、产业等多种设施或机构以及管理体制、利益相关者协调机制等制度环境共同构成的功能复合体。它遵循多元综合、保护与发展联动、区域促进等原则,旨在实现遗产保护与地区可持续发展的双重目标。以中国黄(渤)海候鸟栖息地(I期)为例,探讨盐城遗产综合体的现状、问题和优化对策。 展开更多
关键词 风景园林 世界遗产 遗产综合体 可持续发展 盐城 中国()候鸟栖息地
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The Suspended Sediment Concentration Distribution in the Bohai Sea,Yellow Sea and East China Sea 被引量:11
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作者 BIAN Changwei JIANG Wensheng +1 位作者 Richard J.Greatbatch DING Hui 《Journal of Ocean University of China》 SCIE CAS 2013年第3期345-354,共10页
The distribution of the suspended sediment concentration (SSC) in the Bohai Sea, Yellow Sea and East China Sea (BYECS) is studied based on the observed turbidity data and model simulation results. The observed tur... The distribution of the suspended sediment concentration (SSC) in the Bohai Sea, Yellow Sea and East China Sea (BYECS) is studied based on the observed turbidity data and model simulation results. The observed turbidity results show that (i) the highest SSC is found in the coastal areas while in the outer shelf sea areas turbid water is much more difficult to observe, (ii) the surface layer SSC is much lower than the bottom layer SSC and (iii) the winter SSC is higher than the summer SSC. The Regional Ocean Modeling System (ROMS) is used to simulate the SSC distribution in the BYECS. A comparison between the modeled SSC and the observed SSC in the BYECS shows that the modeled SSC can reproduce the principal features of tlte SSC distribution in the BYECS. The dynamic mechanisms of the sediment erosion and transport processes are studied based on the modeled results. The horizontal distribution of the SSC in the BYECS is mainly determined by the current-wave induced bottom stress and the fine-grain sediment distribution. The current-induced bottom stress is much higher than the wave-induced bottom stress, which means the tidal currents play a more significant role in the sediment resuspension than the wind waves. The vertical mixing strength is studied based on the mixed layer depth and the turbulent kinetic energy distribution in the BYECS. The strong winter time vertical mixing, which is mainly caused by the strong wind stress and surface cooling, leads to high surface layer SSC in winter. High surface layer SSC in summer is restricted in the coastal areas. 展开更多
关键词 ROMS model turbidity observation seasonal variation bottom stress vertical mixing
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Evaluation and fusion of SST data from MTSAT and TMI in East China Sea, Yellow Sea and Bohai Sea in 2008 被引量:1
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作者 伍玉梅 申辉 +2 位作者 崔雪森 杨胜龙 樊伟 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2012年第4期697-702,共6页
Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea... Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%-75%) is more constant than that of MTSAT (9%-93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K). 展开更多
关键词 satellite SST AVAILABILITY FUSION root mean square BIAS
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Vertical displacement loading tides and self-attraction and loading tides in the Bohai, Yellow, and East China Seas 被引量:7
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作者 FANG GuoHong XU XiaoQing +2 位作者 WEI ZeXun WANG YongGang WANG XinYi 《Science China Earth Sciences》 SCIE EI CAS 2013年第1期63-70,共8页
The loading tides are calculated by means of the Green's function method based on a high-resolution regional ocean tide model, the TOPO7.0 global ocean tide model, and the Gutenberg-Bullen A Earth model. The resul... The loading tides are calculated by means of the Green's function method based on a high-resolution regional ocean tide model, the TOPO7.0 global ocean tide model, and the Gutenberg-Bullen A Earth model. The results show that the maximal amplitude of M2 vertical displacement loading (VDL) tide in the Bohai, Yellow, and East China Seas exceeding 28mm appears 150km off the Zhejiang coast; the second maximum exceeding 20mm appears in Inchon Bay; and the third maximum exceeding 14mm is located in the northeast of the North Yellow Sea. The maximal amplitudes of S2 VDL tide at the above three locations exceed 10, 8, and 4mm, respectively. The maximal amplitudes of the K1 and O1 VDL tides, exceeding 13 and 10 mm respectively, appear near the central and north Ryukyu Islands; the amplitudes tend to decease toward the inward areas. The phases of semidiurnal VDL tides are basically opposite to those of corresponding ocean tides. The phases of diurnal VDL tides are basically opposite to those of corresponding ocean tides in the most part of the East China Sea and the eastern part of the South Yellow Sea. This anti-phase relationship generally does not hold in the rest parts of the Bohai and Yellow Seas. The distribution patterns of self-attraction and loading (SAL) tides are very similar to those of VDL tides. The SAL tides have amplitudes about 1.2-1.7 times of the corresponding VDL tides and their phases are basically opposite to the corresponding VDL tides. The maximal amplitude of M2 SAL tide also appears off the Zhejiang coast, with a magnitude exceeding 42mm. 展开更多
关键词 Bohai Sea Yellow Sea East China Sea ocean tides loading tides self-attraction and loading tides
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