Correlation between stand structure and ground vegetation: an analytical approach

The effect of stand structure on the diversity of the forest's ground vegetation was examined based on data on permanent sample plots collected in the northern parts of North-Carelia, eastern Finland. Different ordination methods (DCA, GNMDS, LNMDS, and HMDS) were used together with the TWINSPAN classification method. The aim was to construct a basis for classifying forests with respect to the biodiversity of the forest vegetation. Fertility and stand age showed the strongest correlation with the variation in ground vegetation. Other important factors were basal area, tree species composition, and crown cover. These variables were important in the division of the sample plots into different classes. According to the diversity indices, species diversity was at its highest in young stands on fertile forest sites. As a result, twenty-one different classes were formed based on the relative abundance of understorey species. The variables with the highest correlation were used to describe the stand structure in these classes.     

Comments on the Systematics and Classification of the Beavers (Rodentia, Castoridae)

The systematics of the beavers (Castoridae) are reviewed and definitions are presented for each subfamilial group. Four subfamilies are recognized: primitive Agnotocastorinae (divided into two tribes, Agnotocastorini and Anchitheriomyini); burrowing beavers, Palaeocastorinae; giant beavers, Castoroidinae (containing two tribes, Castoroidini and Trogontheriini); and the Castorinae. The agnotocastorines are viewed as the ancestral group for all later subfamilies. The Palaeocastorinae is viewed as a side-branch, not ancestral or closely related to any of the later subfamilies. The Castorinae and Castoroidinae may represent a distinct clade united by dental features.     

MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification

Background

Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially expressed genes. However, for classification, we must consider multiple genes and their interactions.

Results

Thus, we introduce a hierarchical multivariate Poisson model (MP) and the associated optimal Bayesian classifier (OBC) for classifying samples using sequencing data. Lacking closed-form solutions, we employ a Monte Carlo Markov Chain (MCMC) approach to perform classification. We demonstrate superior or equivalent classification performance compared to typical classifiers for two synthetic datasets and over a range of classification problem difficulties. We also introduce the Bayesian minimum mean squared error (MMSE) conditional error estimator and demonstrate its computation over the feature space. In addition, we demonstrate superior or leading class performance over an RNA-Seq dataset containing two lung cancer tumor types from The Cancer Genome Atlas (TCGA).

Conclusions

Through model-based, optimal Bayesian classification, we demonstrate superior classification performance for both synthetic and real RNA-Seq datasets. A tutorial video and Python source code is available under an open source license at http://bit.ly/1gimnss.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0401-3) contains supplementary material, which is available to authorized users.     

On the variability of “flexion creases” in the distal plantar areas of newborns

The plantae of 83 male and 95 female healthy, full-term Caucasian newborns from Austria (gestational age 235–301 days) were photographed and the flexion creases in the distal part were examined. Analysis of the creases was done under four different aspects, the main evaluation based on a scheme of nine creases introduced by Schenk and Patzer (1959). Two transversal (No. 1 and No. 9) and three longitudinal (Nos. 3, 6, and 7) creases are always or predominantly present, a finding corresponding with the data of Schenk on 52 male and 48 female newborns from Germany. In addition, the nine plantar creases were evaluated according to six degrees of expression, and some typical crease combinations are shown. Bilateral and bisexual similarity prevails. The results of this study might serve investigations of different populations and of medical disorders.     

Structural root architecture of 5-year-old Pinus pinaster measured by 3D digitising and analysed with AMAPmod

Pinus pinaster (Ait.) is a high yielding forest tree, producing nearly a fourth of French marketed timber essentially from intensively managed stands located in southwestern France, in the Landes Forest. This species has generally a poor stem straightness, especially when it grows in poor sandy podzol of the Landes Forest, affected by summer droughts and winter floods. Above- and below-ground architecture and biomass as well as stem straightness were measured on twenty-nine 5-year-old planted trees uprooted by pulling with a lumbering crane. A very precise numeric representation of the geometry and topology of structural root architecture was gained using a low-magnetic-field digitising device (Danjon et al., 1998; Sinoquet and Rivet, 1997). Data were analysed with AMAPmod, a database software designed to analyse plant topological structures (Godin et al., 1997). Several characteristics of root architecture were extracted by queries including root number, length, diameter, volume, spatial position, ramification order, branching angle and inter-laterals length. Differences between root systems originated from their dimensions, but also from the proportion of deep roots and the taproot size, which represented 8% of the total root volume. The proportion of root volume in the zone of rapid taper was negatively correlated with the proportion of root volume in the taproot indicating a compensation between taproot and main lateral root volume. Among all studied root characteristics the maximal rooting depth, the proportion of deep roots and the root partitioning coefficient were correlated with stem straightness. This revised version was published online in June 2006 with corrections to the Cover Date.