Maintaining genetic diversity is a major issue in conservation biology. In this study, we demonstrate the differences of genetic diversity levels between wild and captive individuals of Elliot’s Pheasant Syrmaticus e...Maintaining genetic diversity is a major issue in conservation biology. In this study, we demonstrate the differences of genetic diversity levels between wild and captive individuals of Elliot’s Pheasant Syrmaticus ellioti. Wild individuals showed a higher genetic diversity level than that of the captive individuals. Nucleotide diversity and haplotype diversity of wild individuals were 0.00628 and 0.993, while those of captive individuals were 0.00150 and 0.584 respectively. Only 3 haplotypes of mtDNA control region sequence were identified among 36 captive individuals, while 16 unique haplotypes were identified among the 17 wild individuals in this study. One captive haplotype was shared by a wild individual from Anhui Province. It is concluded that a low number of founders was the likely reason for the lower level genetic diversity of the captive group. Careful genetic man- agement is suggested for captive populations, particularly of such an endangered species, to maintain genetic variability levels.展开更多
Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong K...Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods （decision tree analysis and linear discriminant analysis） were used, and their applications were compared. Much more effort was put on selecting soil covariates for modeling. First, analysis of variance （ANOVA） was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.展开更多
基金Project (No. 30170144) supported by the National Nature ScienceFoundation of China
文摘Maintaining genetic diversity is a major issue in conservation biology. In this study, we demonstrate the differences of genetic diversity levels between wild and captive individuals of Elliot’s Pheasant Syrmaticus ellioti. Wild individuals showed a higher genetic diversity level than that of the captive individuals. Nucleotide diversity and haplotype diversity of wild individuals were 0.00628 and 0.993, while those of captive individuals were 0.00150 and 0.584 respectively. Only 3 haplotypes of mtDNA control region sequence were identified among 36 captive individuals, while 16 unique haplotypes were identified among the 17 wild individuals in this study. One captive haplotype was shared by a wild individual from Anhui Province. It is concluded that a low number of founders was the likely reason for the lower level genetic diversity of the captive group. Careful genetic man- agement is suggested for captive populations, particularly of such an endangered species, to maintain genetic variability levels.
基金Supported by the Public Policy Research of the Research Grants Council of Hong Kong, China (No.2002-PPR-3)the Knowledge Innovation Program of the Chinese Academy of Sciences (No.KZCX2-YW-409)+1 种基金the National Natural ScienceFoundation of China (Nos.40625001 and 40771092)the Mini-AOE (Area of Excellence) Fund from the Hong Kong Baptist University,China (No.RC/AOE/08-09/01)
文摘Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods （decision tree analysis and linear discriminant analysis） were used, and their applications were compared. Much more effort was put on selecting soil covariates for modeling. First, analysis of variance （ANOVA） was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.
