2 resultados para Vegetation of China

em Bucknell University Digital Commons - Pensilvania - USA


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This thesis assesses relationships between vegetation and topography and the impact of human tree-cutting on the vegetation of Union County during the early historical era (1755-1855). I use early warrant maps and forestry maps from the Pennsylvania historical archives and a warrantee map from the Union County courthouse depicting the distribution of witness trees and non-tree surveyed markers (posts and stones) in early European settlement land surveys to reconstruct the vegetation and compare vegetation by broad scale (mountains and valleys) and local scale (topographic classes with mountains and valleys) topography. I calculated marker density based on 2 km x 2 km grid cells to assess tree-cutting impacts. Valleys were mostly forests dominated by white oak (Quercus alba) with abundant hickory (Carya spp.), pine (Pinus spp.), and black oak (Quercus velutina), while pine dominated what were mostly pine-oak forests in the mountains. Within the valleys, pine was strongly associated with hilltops, eastern hemlock (Tsuga canadensis) was abundant on north slopes, hickory was associated with south slopes, and riparian zones had high frequencies of ash (Fraxinus spp.) and hickory. In the mountains, white oak was infrequent on south slopes, chestnut (Castanea dentata) was more abundant on south slopes and ridgetops than north slopes and mountain coves, and white oak and maple (Acer spp.) were common in riparian zones. Marker density analysis suggests that trees were still common over most of the landscape by 1855. The findings suggest there were large differences in vegetation between valleys and mountains due in part to differences in elevation, and vegetation differed more by topographic classes in the valleys than in the mountains. Possible areas of tree-cutting were evenly distributed by topographic classes, suggesting Europeans settlers were clearing land and harvesting timber in most areas of Union County.

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There is a consensus in China that industrialization, urbanization, globalization and information technology will enhance China's urban competitiveness. We have developed a methodology for the analysis of urban competitiveness that we have applied to China's 25 principal cities during three periods from 1990 through 2009. Our model uses data for 12 variables, to which we apply appropriate statistical techniques. We are able to examine the competitiveness of inland cities and those on the coast, how this has changed during the two decades of the study, the competitiveness of Mega Cities and of administrative centres, and the importance of each variable in explaining urban competitiveness and its development over time. This analysis will be of benefit to Chinese planners as they seek to enhance the competitiveness of China and its major cities in the future.