研究采用7个微卫星标记分析在青海省西大滩区域,位于青藏公路两侧的4个高原鼠兔(Ochotona curzoniae)种群的遗传变异情况。分别采用软件TFPGA和GENE POP 3.4计算各种群间的Nei’s标准遗传距离,基因分化系数(Fst)等参数,并对遗传距离进行...研究采用7个微卫星标记分析在青海省西大滩区域,位于青藏公路两侧的4个高原鼠兔(Ochotona curzoniae)种群的遗传变异情况。分别采用软件TFPGA和GENE POP 3.4计算各种群间的Nei’s标准遗传距离,基因分化系数(Fst)等参数,并对遗传距离进行UPGMA聚类分析。研究结果表明,公路同侧种群间平均遗传距离和基因分化系数分别为0.0808和0.0541;异侧种群间平均遗传距离和基因分化系数分别为0.1037和0.0705,公路东侧和西侧的两个种群分别聚为一类。青藏公路对分布于公路两侧的高原鼠兔种群间的基因交流产生了一定的阻隔效应,并导致种群间出现了一定程度的遗传分化。展开更多
Based on the NOAA AVHRR-NDVI monthly data from 1981 to 2001, the spatial distribution and dynamic change of land cover along the Qinghai-Tibet Highway and Railway were studied. The results of the analytical data indic...Based on the NOAA AVHRR-NDVI monthly data from 1981 to 2001, the spatial distribution and dynamic change of land cover along the Qinghai-Tibet Highway and Railway were studied. The results of the analytical data indicate that the NDVI values in July, August and September are rather high during a year, and a linear trend by calculating NDVI of each pixel computed based on the average values of NDVI in July, August and September were obtained. The results are as follows： 1） Land cover of the study area by NDVI displays high at two sides of the area and low in the center, and agriculture area 〉 alpine meadow 〉 alpine grassland 〉 desert grassland. 2） In the study area, the amount ofpixels with high increase, slight increase, no change, slight decrease and high decrease account for 0.29%, 14.86%, 67.61%, 16.7% and 0.57% of the whole area, respectively. The increase of land cover pixels is mainly in the agriculture and alpine meadow and the decrease pixels mainly in the alpine grassland, desert grassland and hungriness. Grassland and hungriness contribute to the decrease mostly and artificial land and meadow contribute to the increase mostly. 3） In the area where human beings live, the changing trend is obvious, such as the valleys of Lhasa River and Huangshui River and area along the Yellow River; in the high altitude area with fewer people living, the changing trend is relatively low, like the area of Hoh Xil. 4） Human being＇s behaviors are a key factor followed by the climate changes affecting land cover.展开更多
文摘研究采用7个微卫星标记分析在青海省西大滩区域,位于青藏公路两侧的4个高原鼠兔(Ochotona curzoniae)种群的遗传变异情况。分别采用软件TFPGA和GENE POP 3.4计算各种群间的Nei’s标准遗传距离,基因分化系数(Fst)等参数,并对遗传距离进行UPGMA聚类分析。研究结果表明,公路同侧种群间平均遗传距离和基因分化系数分别为0.0808和0.0541;异侧种群间平均遗传距离和基因分化系数分别为0.1037和0.0705,公路东侧和西侧的两个种群分别聚为一类。青藏公路对分布于公路两侧的高原鼠兔种群间的基因交流产生了一定的阻隔效应,并导致种群间出现了一定程度的遗传分化。
基金National Natural Science Foundation of China No.90202012+1 种基金 National Basic Research Program of China, No.2005CB422006 No. 2002CB412507
文摘Based on the NOAA AVHRR-NDVI monthly data from 1981 to 2001, the spatial distribution and dynamic change of land cover along the Qinghai-Tibet Highway and Railway were studied. The results of the analytical data indicate that the NDVI values in July, August and September are rather high during a year, and a linear trend by calculating NDVI of each pixel computed based on the average values of NDVI in July, August and September were obtained. The results are as follows： 1） Land cover of the study area by NDVI displays high at two sides of the area and low in the center, and agriculture area 〉 alpine meadow 〉 alpine grassland 〉 desert grassland. 2） In the study area, the amount ofpixels with high increase, slight increase, no change, slight decrease and high decrease account for 0.29%, 14.86%, 67.61%, 16.7% and 0.57% of the whole area, respectively. The increase of land cover pixels is mainly in the agriculture and alpine meadow and the decrease pixels mainly in the alpine grassland, desert grassland and hungriness. Grassland and hungriness contribute to the decrease mostly and artificial land and meadow contribute to the increase mostly. 3） In the area where human beings live, the changing trend is obvious, such as the valleys of Lhasa River and Huangshui River and area along the Yellow River; in the high altitude area with fewer people living, the changing trend is relatively low, like the area of Hoh Xil. 4） Human being＇s behaviors are a key factor followed by the climate changes affecting land cover.
