Phylogeography of the Qinghai-Tibetan Plateau endemic Juniperus przewalskii (Cupressaceae) inferred from chloroplast DNA sequence variation

The vegetation of the northeast Qinghai-Tibetan Plateau is dominated by alpine meadow and desert-steppe with sparse forests scattered within it. To obtain a better understanding of the phylogeography of one constituent species of the forests in this region, we examined chloroplast trnT-trnF and trnS-trnG sequence variation within Juniperus przewalskii, a key endemic tree species. Sequence data were obtained from 392 trees in 20 populations covering the entire distribution range of the species. Six cpDNA haplotypes were identified. Significant population subdivision was detected (G(ST) = 0.772, N-ST = 0.834), suggesting low levels of recurrent gene flow among populations and significant phylogeographic structure (N-ST > G(ST), P < 0.05). Eight of the nine disjunct populations surveyed on the high-elevation northeast plateau were fixed for a single haplotype (A), while the remaining, more westerly population, contained the same haplotype at high frequency together with two low frequency haplotypes (C and F). In contrast, most populations that occurred at lower altitudes at the plateau edge were fixed or nearly fixed for one of two haplotypes, A or E. However, two plateau edge populations had haplotype compositions different from the rest. In one, four haplotypes (A, B, D and E) were present at approximately equivalent frequencies, which might reflect a larger refugium in the area of this population during the last glacial period. Phylogenetic analysis indicated that the most widely distributed haplotype A is not ancestral to other haplotypes. The contrasting phylogeographic structures of the haplotype-rich plateau edge area and the almost haplotype-uniform plateau platform region indicate that the plateau platform was recolonized by J. przewalskii during the most recent postglacial period. This is supported by the findings of a nested clade analysis, which inferred that postglacial range expansion from the plateau edge followed by recent fragmentation is largely responsible for the present-day spatial distribution of cpDNA haplotypes within the species.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.

Comparative molecular cytogenetic studies in the order Carnivora: mapping chromosomal rearrangements onto the phylogenetic tree

We have made a set of chromosome-specific painting probes for the American mink by degenerate oligonucleotide primed-PCR (DOP-PCR) amplification of flow-sorted chromosomes. The painting probes were used to delimit homologous chromosomal segments among human, red fox, dog, cat and eight species of the family Mustelidae, including the European mink, steppe and forest polecats, least weasel, mountain weasel, Japanese sable, striped polecat, and badger. Based on the results of chromosome painting and G-banding, comparative maps between these species have been established. The integrated map demonstrates a high level of karyotype conservation among mustelid species. Comparative analysis of the conserved chromosomal segments among mustelids and outgroup species revealed 18 putative ancestral autosomal segments that probably represent the ancestral chromosomes, or chromosome arms, in the karyotype of the most recent ancestor of the family Mustelidae. The proposed 2n = 38 ancestral Mustelidae karyotype appears to have been retained in some modern mustelids, e.g., Martes, Lutra, ktonyx, and Vormela. The derivation of the mustelid karyotypes from the putative ancestral state resulted from centric fusions, fissions, the addition of heterochromatic arms, and occasional pericentric inversions. Our results confirm many of the evolutionary conclusions suggested by other data and strengthen the topology of the carnivore phylogenetic tree through the inclusion of genome-wide chromosome rearrangements. Copyright (C) 2002 S. KargerAG, Basel.

The evolution of intermediate castration virulence and ant coexistence in a spatially structured environment

Theory suggests that spatial structuring should select for intermediate levels of virulence in parasites, but empirical tests are rare and have never been conducted with castration (sterilizing) parasites. To test this theory in a natural landscape, we co

Uncovering the rules for protein-protein interactions from yeast genomic data

Identifying protein-protein interactions is crucial for understanding cellular functions. Genomic data provides opportunities and challenges in identifying these interactions. We uncover the rules for predicting protein-protein interactions using a frequent pattern tree (FPT) approach modified to generate a minimum set of rules (mFPT), with rule attributes constructed from the interaction features of the yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regressions under various statistical measures. Our study indicates that mFPT outranks other methods in predicting the protein-protein interactions for the database used. We predict a new protein-protein interaction complex whose biological function is related to premRNA splicing and new protein-protein interactions within existing complexes based on the rules generated.