972 resultados para Vegetation of China


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A study was conducted in the forest-steppe region of the Loess Plateau to provide insight into the factors affecting the process of vegetation establishment, and to provide recommendations for the selection of indigenous species in order to speed up the succession process and to allow the establishment of vegetation more resistant to soil erosion. Four distinctive vegetation types were identified, and their distribution was affected not only by the time since abandonment but also by other environmental factors, mainly soil water and total P in the upper soil layers. One of the vegetation types, dominated by Artemisia scoparia, formed the early successional stage after abandonment while the other three types formed later successional stages with their distribution determined by the soil water content and total P. It can be concluded that the selection of appropriate species for introduction to accelerate succession should be determined by the local conditions and especially the total P concentration and soil water content.

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Successions of lake ecosystems from clear-water, macrophyte-rich conditions into turbid states with abundant phytoplankton have taken place in many shallow lakes in China. However, little is know about the change of carbon fluxes in lakes during such processes. We conducted a case study in Lake Biandantang to investigate the change of carbon fluxes during such a regime shift. Dissolved aquatic carbon and gaseous carbon (methane (CH4) and carbon dioxide (CO2)) across air-water interface in three sites with different vegetation covers and compositions were studied and compared. CH4 emissions from three sites were 0.62 +/- 0.36, 0.70 +/- 0.36, and 1.31 +/- 0.57 mg m(-2) h(-1), respectively. Correlation analysis showed that macrophytes, rather than phytoplankton, directly positively affected CH4 emission. CO2 fluxes of three sites in Lake Biandantang were significantly different, and the average values were 77.8 +/- 20.4, 52.2 +/- 14.1 and 3.6 +/- 26.8 mg m(-2) h(-1), respectively. There were an evident trend that the larger macrophyte biomass, the lower CO2 emissions. Correlation analysis showed that in different sites, dominant plant controlled CO2 flux across air-water interface. In a year cycle, the percents of gaseous carbon release from lake accounting for net primary production were significantly different (from 39.3% to 2.8%), indicating that with the decline of macrophytes and regime shift, the lake will be a larger carbon source to the atmosphere. (c) 2006 Elsevier Ltd. All rights reserved.

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Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA, GEOPRO). Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process mechanism models of CASA, GLOPEM and CEVSA, the following conclusions could be made: (1) during the last 20 years, NPP change in China followed closely the seasonal change of climate affected by monsoon with an overall trend of increasing; (2) simulated average seasonal NPP was: 0.571 +/- 0.2 GtC in spring, 1.573 +/- 0.4 GtC in summer, 0.6 +/- 0.2 GtC in autumn, and 0.12 +/- 0.1 GtC in winter. Average annual NPP in China was 2.864 +/- 1 GtC. All the five models were able to simulate seasonal and spatial features of biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases.

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Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

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The characteristics of the modern monsoon climate of China may be used as clues for recognizing the records of paleomonsoon climate. The present paper deals primarily with the various paleomonsoon records of the last 130,000 years in the southeast monsoon area. These records mainly come from the following three fields: (i) the historical, (ii) the geological, including loess-paleosol sequence, deserts, lakes, snowlines, timberlines, the phenomena of continental desertization and so on, and (iii) the biological, presented by vegetation a.d mammals. Among these records, the loess-paleosol sequence in the Loess Plateau reflects a climatic history characterized by alternation of two different climatic periods when the Asian winter monsoon and summer monsoon showed pronounced effects on environment, respectively.