5 resultados para Distribution management

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Gymnocypris przewalskii (Kessler 1876) is an endangered and state-protected rare fish species in Qinghai Lake, China. To further understand the life history and distribution of this fish, five surveys were carried out in Qinghai Lake between 2002-2006. Results of these surveys indicate that fishes were predominantly distributed about 2 m under the surface. In July, significant differences in fish density were found between surface and bottom layers (P = 0.001), and/or between middle and bottom layers (P = 0.025). Fish density was the greatest in the surface layer. In August and October, no significant differences were found between the different layers, but the bottom layer had a greater fish density. Furthermore, there were very large differences among different zones in fish distribution density. Differences in horizontal distribution were not significantly correlated to factors such as water depth and inshore distance, possibly because of very low and uniform fish density. Feeding, changes in water temperature, over-wintering and spawning appeared to influence fish distribution. Hydroacoustic estimates of G. przewalskii biomass in Qinghai Lake increased significantly between 2002 and 2006. We attribute this increase to the management measures put in place to protect this species.

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Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.