One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model a...One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model approach was employed to unbiasedly predict genotypic values of 20 traits for eliminating the environmental effect. Six commonly used genetic distances(Euclidean,standardized Euclidean,Mahalanobis,city block,cosine and correlation distances) combining four commonly used hierarchical cluster methods(single distance,complete distance,unweighted pair-group average and Ward's methods) were used in the least distance stepwise sampling(LDSS) method for constructing different core subsets. The analyses of variance(ANOVA) of different evaluating parameters showed that the validities of cosine and correlation distances were inferior to those of Euclidean,standardized Euclidean,Mahalanobis and city block distances. Standardized Euclidean distance was slightly more effective than Euclidean,Mahalanobis and city block distances. The principal analysis validated standardized Euclidean distance in the course of constructing practical core subsets. The covariance matrix of accessions might be ill-conditioned when Mahalanobis distance was used to calculate genetic distance at low sampling percentages,which led to bias in small-sized core subset construction. The standardized Euclidean distance is recommended in core subset construction with LDSS method.展开更多
A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to auto...A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to automatically identify the water-flooded status of oil-saturated stratum is described. The experiments show that this algorithm can improve the performances for the identification and the generalization in the case of a limited set of samples.展开更多
Combining ecological niche modeling with phylogeography has become a popular approach to understand how historical climate changes have created and maintained population structure. However, methodological choices in g...Combining ecological niche modeling with phylogeography has become a popular approach to understand how historical climate changes have created and maintained population structure. However, methodological choices in geographic extents and environmental layer sets employed in modeling may affect results and interpretations profoundly. Here, we infer range-wide phylogeographic structure and model ecological niches of Cyanoderrna ruficeps, and compare results to previous studies that examined this species across China's Mainland and Taiwan only. Use of dense taxon sampling of closely related species as outgroups question C. ruficeps monophyly. Furthermore, previously unsampled C. ruficeps populations from central Vietnam were closely related to disjunct western populations （Nepal, Tibet, Myanmar, Yunnan）, rather than to geographically proximate populations in northern Vietnam and eastern China. Phylogeographic structure is more complex than previously appreciated; niche model projections to Last Glacial Maximum climate scenarios identified larger areas of suitable conditions than previous studies, but potential distributional limits differed markedly between climate models employed and were dependent upon interpretation of non-analogous historical climate scenarios. Previously identified population expansion across central China may result from colonization from refugial distributions during the Last Interglacial, rather than the Last Glacial Maximum, as previously understood [Current Zoology 61 （5）： 901-909, 2015].展开更多
基金Project supported by the National Natural Science Foundation of China (No. 30270759)the Cooperation Project in Science and Technology between China and Poland Governments (No. 32-38)the Scientific Research Foundation for Doctors in Shandong Academy of Agricultural Sciences (No. [2007]20), China
文摘One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model approach was employed to unbiasedly predict genotypic values of 20 traits for eliminating the environmental effect. Six commonly used genetic distances(Euclidean,standardized Euclidean,Mahalanobis,city block,cosine and correlation distances) combining four commonly used hierarchical cluster methods(single distance,complete distance,unweighted pair-group average and Ward's methods) were used in the least distance stepwise sampling(LDSS) method for constructing different core subsets. The analyses of variance(ANOVA) of different evaluating parameters showed that the validities of cosine and correlation distances were inferior to those of Euclidean,standardized Euclidean,Mahalanobis and city block distances. Standardized Euclidean distance was slightly more effective than Euclidean,Mahalanobis and city block distances. The principal analysis validated standardized Euclidean distance in the course of constructing practical core subsets. The covariance matrix of accessions might be ill-conditioned when Mahalanobis distance was used to calculate genetic distance at low sampling percentages,which led to bias in small-sized core subset construction. The standardized Euclidean distance is recommended in core subset construction with LDSS method.
基金Supported by the Natural Science Foundation of Heilong- jiang Province (No.F01-20).
文摘A method of B-spline transform for signal feature extraction is developed. With the B-spline, the log-signal space is mapped into the vector space. An efficient algorithm based on Support Vector Machine (SVM ) to automatically identify the water-flooded status of oil-saturated stratum is described. The experiments show that this algorithm can improve the performances for the identification and the generalization in the case of a limited set of samples.
基金We thank Nikki Boggess, who assisted in labwork. Fieldwork in Vietnam was facilitated by Dr. Le Mahn Hung, and supported by the National Geographic Committee for Research and Exploration. Fieldwork in China was supported by the National Science Foundation （DEB-0344430 to ATP）. The laboratory portions of this work were supported by the National Science Foundation （DEB-0743576 to RGM）. We thank recordists who shared their Stachyris/Cyanoderma recordings on Xeno-canto.
文摘Combining ecological niche modeling with phylogeography has become a popular approach to understand how historical climate changes have created and maintained population structure. However, methodological choices in geographic extents and environmental layer sets employed in modeling may affect results and interpretations profoundly. Here, we infer range-wide phylogeographic structure and model ecological niches of Cyanoderrna ruficeps, and compare results to previous studies that examined this species across China's Mainland and Taiwan only. Use of dense taxon sampling of closely related species as outgroups question C. ruficeps monophyly. Furthermore, previously unsampled C. ruficeps populations from central Vietnam were closely related to disjunct western populations （Nepal, Tibet, Myanmar, Yunnan）, rather than to geographically proximate populations in northern Vietnam and eastern China. Phylogeographic structure is more complex than previously appreciated; niche model projections to Last Glacial Maximum climate scenarios identified larger areas of suitable conditions than previous studies, but potential distributional limits differed markedly between climate models employed and were dependent upon interpretation of non-analogous historical climate scenarios. Previously identified population expansion across central China may result from colonization from refugial distributions during the Last Interglacial, rather than the Last Glacial Maximum, as previously understood [Current Zoology 61 （5）： 901-909, 2015].
