Based on the simulation with the Ocean-Atmosphere Coupled Model CCSM and Ocean Model POP under the green- house gas emission scenario of the IPCC SRES A2 （IPCC, 2001）, and on the earth crust subsidence and glacier m...Based on the simulation with the Ocean-Atmosphere Coupled Model CCSM and Ocean Model POP under the green- house gas emission scenario of the IPCC SRES A2 （IPCC, 2001）, and on the earth crust subsidence and glacier melting data, the relative sea level change is obtained along the coast of China in the 21 st century. Using the SRTM elevation data the submergence of coastal low land is calculated under the extreme water level with a 100-year retum period. The total flooding areas are 98.3× 10^3 and 104.9× 10^3 km2 for 2050 and 2080, respectively. For the three regions most vulnerable to extreme sea level rise, i.e., the coast of Bohai Bay, the Yangtze River Delta together with neighboring Jiangsu Province and northern Zhejiang Province, and the Pearl River Delta, the flooded areas are 5.0× 10^3, 64.1×10^3 and 15.3 × 10^3 km2 in 2050 and 5.2 × 10^3, 67.8×10^3 and 17.2 × 10^3 km2 in 2080, respectively.展开更多
The CVI （coastal vulnerability index） was developed and used to assess the vulnerability of the coastline of the Kingdom of Bahrain main islands to future SLR （sea level rise）. A total of 717 km of the coastline w...The CVI （coastal vulnerability index） was developed and used to assess the vulnerability of the coastline of the Kingdom of Bahrain main islands to future SLR （sea level rise）. A total of 717 km of the coastline was evaluated. Six spatial factors acting on the coastal area： erosion/accretion patterns （shoreline change）, topography （elevation above mean sea level）, geology, geomorphology, slope, and mean sea level rise were incorporated and ranked to develop the CVI. This index was classified into four levels of vulnerability： low, moderate, high, and very high. Vulnerable hotspots are located along the central portions of the western and eastern coastlines. The vulnerability of these areas is mostly driven by their characteristically shallow coastal slopes, low elevations, and erosion-prone nature of the sandy soils presents, comprising about 54 km of the studied shoreline. Another 33 km of coastline were classified as highly vulnerable and located along the eastern coast. In addition, the western coast of the southern tip of the main island （Bahrain） was also classified as a highly vulnerable shoreline. Twenty-two km was classified as the moderate vulnerable. The remaining coastal areas were classified as low to moderately vulnerable comprising about 608 km of the total length of the coastline. Identifying those hotspots susceptible to SLR is essential for more effective coastal zone management and to help in reducing the impacts of SLR on both infrastructure and human beings.展开更多
Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-...Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-made objects. Knowing where these avian migration ＂hot-spots＂ occur in time and space is vital to improve flight safety and inform the spatial planning process （e.g. environmental assessments for offshore windfarms）. We developed a simple spatial model to identify avian migration hot- spots in coastal areas based on prevailing migration orientation and coastline features known, from visual and radar observations, to concentrate migrating landbirds around land masses. Regional scale model validation was achieved by combining nocturnal passerine movement data gathered from two tier radar coverage （long-range dual-polarization Doppler weather radar and short- range marine surveillance radar） and standardised bird ringing. Applied on a national scale, the model correctly identified the ten most important Danish coastal hot-spots for spring migrants and predicted the relative numbers of birds that concentrated at each site. These bird numbers corresponded well with historical observational data. Here, we provide a potential framework for the es- tablishment of the first three-dimensional avian airspace sanctuaries, which could contribute to more effective conservation of long-distance migratory birds [Current Zoology 60 （5）： 680-691, 2014].展开更多
基金supported by the National Key Technology R&D Program(No.2007BAC03A06)the National Natural Science Foundation of China(NSFC)project(No.40976006)+2 种基金the National Marine Public Welfare Research Project of China(No.201005019)Key Laboratory Project(Key Laboratory of Coastal Disasters and Defence,Ministry of Education,No.200808)Laboratory of Coastal Disasters and Defence,Ministry of Education)(No.200802)
文摘Based on the simulation with the Ocean-Atmosphere Coupled Model CCSM and Ocean Model POP under the green- house gas emission scenario of the IPCC SRES A2 （IPCC, 2001）, and on the earth crust subsidence and glacier melting data, the relative sea level change is obtained along the coast of China in the 21 st century. Using the SRTM elevation data the submergence of coastal low land is calculated under the extreme water level with a 100-year retum period. The total flooding areas are 98.3× 10^3 and 104.9× 10^3 km2 for 2050 and 2080, respectively. For the three regions most vulnerable to extreme sea level rise, i.e., the coast of Bohai Bay, the Yangtze River Delta together with neighboring Jiangsu Province and northern Zhejiang Province, and the Pearl River Delta, the flooded areas are 5.0× 10^3, 64.1×10^3 and 15.3 × 10^3 km2 in 2050 and 5.2 × 10^3, 67.8×10^3 and 17.2 × 10^3 km2 in 2080, respectively.
文摘The CVI （coastal vulnerability index） was developed and used to assess the vulnerability of the coastline of the Kingdom of Bahrain main islands to future SLR （sea level rise）. A total of 717 km of the coastline was evaluated. Six spatial factors acting on the coastal area： erosion/accretion patterns （shoreline change）, topography （elevation above mean sea level）, geology, geomorphology, slope, and mean sea level rise were incorporated and ranked to develop the CVI. This index was classified into four levels of vulnerability： low, moderate, high, and very high. Vulnerable hotspots are located along the central portions of the western and eastern coastlines. The vulnerability of these areas is mostly driven by their characteristically shallow coastal slopes, low elevations, and erosion-prone nature of the sandy soils presents, comprising about 54 km of the studied shoreline. Another 33 km of coastline were classified as highly vulnerable and located along the eastern coast. In addition, the western coast of the southern tip of the main island （Bahrain） was also classified as a highly vulnerable shoreline. Twenty-two km was classified as the moderate vulnerable. The remaining coastal areas were classified as low to moderately vulnerable comprising about 608 km of the total length of the coastline. Identifying those hotspots susceptible to SLR is essential for more effective coastal zone management and to help in reducing the impacts of SLR on both infrastructure and human beings.
文摘Migrating landbirds are known to follow coast lines and concentrate on peninsulas prior to crossing water bodies, es- pecially during daylight but also at night, creating enhanced potential collision hazards with man-made objects. Knowing where these avian migration ＂hot-spots＂ occur in time and space is vital to improve flight safety and inform the spatial planning process （e.g. environmental assessments for offshore windfarms）. We developed a simple spatial model to identify avian migration hot- spots in coastal areas based on prevailing migration orientation and coastline features known, from visual and radar observations, to concentrate migrating landbirds around land masses. Regional scale model validation was achieved by combining nocturnal passerine movement data gathered from two tier radar coverage （long-range dual-polarization Doppler weather radar and short- range marine surveillance radar） and standardised bird ringing. Applied on a national scale, the model correctly identified the ten most important Danish coastal hot-spots for spring migrants and predicted the relative numbers of birds that concentrated at each site. These bird numbers corresponded well with historical observational data. Here, we provide a potential framework for the es- tablishment of the first three-dimensional avian airspace sanctuaries, which could contribute to more effective conservation of long-distance migratory birds [Current Zoology 60 （5）： 680-691, 2014].
