Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010....Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions(GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority(UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.展开更多
Some animals have the capacity to produce different alarm calls for terrestrial and aerial predators. However, it is not clear what cognitive processes are involved in generating these calls. One possibility is the po...Some animals have the capacity to produce different alarm calls for terrestrial and aerial predators. However, it is not clear what cognitive processes are involved in generating these calls. One possibility is the position of the predator： Anything on the ground receives a terrestrial predator call, and anything in the air receives an aerial predator call. Another possibility is that animals are able to recognize the physical features of predators and incorporate those into their calls. As a way of elucidating which of these mechanisms plays a primary role in generating the structure of different calls, we performed two field experiments with Gunnison＇s prairie dogs. First, we presented the prairie dogs with a circle, a triangle, and a square, each moving across the colony at the same height and speed. Second, we presented the prairie dogs with two squares of differing sizes. DFA statistics showed that 82.6 percent of calls for the circle and 79.2 percent of the calls for the triangle were correctly classified, and 73.3 percent of the calls for the square were classified as either square or circle. Also, 100 percent of the calls for the larger square and 90 percent of the calls for the smaller square were correctly classified. Because both squares and circles are features of terrestrial predators and triangles are features of aerial predators, our results suggest that prairie dogs might have a cognitive mechanism that labels the abstract shape and size of different predators, rather than the position of the predator [Current Zoology 58 （5）： 741-748, 2012].展开更多
文摘Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions(GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority(UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.
文摘Some animals have the capacity to produce different alarm calls for terrestrial and aerial predators. However, it is not clear what cognitive processes are involved in generating these calls. One possibility is the position of the predator： Anything on the ground receives a terrestrial predator call, and anything in the air receives an aerial predator call. Another possibility is that animals are able to recognize the physical features of predators and incorporate those into their calls. As a way of elucidating which of these mechanisms plays a primary role in generating the structure of different calls, we performed two field experiments with Gunnison＇s prairie dogs. First, we presented the prairie dogs with a circle, a triangle, and a square, each moving across the colony at the same height and speed. Second, we presented the prairie dogs with two squares of differing sizes. DFA statistics showed that 82.6 percent of calls for the circle and 79.2 percent of the calls for the triangle were correctly classified, and 73.3 percent of the calls for the square were classified as either square or circle. Also, 100 percent of the calls for the larger square and 90 percent of the calls for the smaller square were correctly classified. Because both squares and circles are features of terrestrial predators and triangles are features of aerial predators, our results suggest that prairie dogs might have a cognitive mechanism that labels the abstract shape and size of different predators, rather than the position of the predator [Current Zoology 58 （5）： 741-748, 2012].
