Litter production and decomposition in a terra-firme forest of Central Amazonia

Summary Chemical and biological aspects of litter production and decomposition were studied in three distinct areas of the Central Amazon. Litter production was measured during three years, employing the litter trap technique, with adapted conical collectors. Leaf litter decomposition was studied in experiments, over five-month-periods with repetitions for the dry and wet seasons, using the nylon-mesh bag technique. The greatest litter production took place during the drier period of the year, mainly from June to October, while decomposition processes were more accentuated in the wet season: in the plateau site, one-half, of the litter disappears, according to a mathematical model, in about, 218 days under dry season conditions as against 32 days in the wet season. In the rainy season, weight reduction and mineral losses from decomposing leaves occurred more rapidly, owing to the intense biological activity on the material during this period. Particularly noticeable was the intense activity of termites in organic matter breakdown and mineral removal, and the extensive root penetration in the decomposing leaves, which removed some minerals but increased the amounts of other. Leaching effects were also quite noticeable in this period. During the rainy season, in the latosol sites, termites were responsible for more than 40% of the removal of decomposing leaves. While intense biological activity appears to be the major factor responsible for weight reduction and loss of many minerals, as well as for the accumulation of some other minerals (mainly zinc iron and aluminium) in the decomposing material, leaching seems to be the major factor responsible for the loss of certain minerals such as potassium, boron and copper.     

Microbiological reduction of steroidal ketones using the thermophilic bacteriumCaldariella acidophila

Summary Twelve steroidal ketones have been subjected to reduction withC. acidophila resting cells, regio- and stereospecific reduction of the 3-keto groups being observed, as well as reduction of the ⁴-double bond. The presence of oxo groups at C-11 or C-12 and the presence of hydrophobic side chains on the steroidal molecules inhibit the reduction.     

Transformation of progesterone byCaldariella acidophila,an extreme thermophilic bacterium

Summary Caldariella Acidophila, a thermophilic bacterium, converts porgesterone (1) to pregn-4-en-3,6,20-trione (2), 5a-pregnan-3, 6, 20-trione (3), pregn-4-en-20a-ol-3-one (4), pregn-4-6-ol-3, 20-dione (5) and pregn-4-en-6a-ol-3, 20-dione (6). Different patterns of these metabolites were obtained by modifying the incubation conditions and using differently treated biocatalysis.     

Recuperation of nitrogen cycling in Amazonian forests following agricultural abandonment

Phosphorus (P) is generally considered the most common limiting nutrient for productivity of mature tropical lowland forests growing on highly weathered soils. It is often assumed that P limitation also applies to young tropical forests, but nitrogen (N) losses during land-use change may alter the stoichiometric balance of nutrient cycling processes. In the Amazon basin, about 16% of the original forest area has been cleared, and about 30-50% of cleared land is estimated now to be in some stage of secondary forest succession following agricultural abandonment. Here we use forest age chronosequences to demonstrate that young successional forests growing after agricultural abandonment on highly weathered lowland tropical soils exhibit conservative N-cycling properties much like those of N-limited forests on younger soils in temperate latitudes. As secondary succession progresses, N-cycling properties recover and the dominance of a conservative P cycle typical of mature lowland tropical forests re-emerges. These successional shifts in N:P cycling ratios with forest age provide a mechanistic explanation for initially lower and then gradually increasing soil emissions of the greenhouse gas nitrous oxide (N(2)O). The patterns of N and P cycling during secondary forest succession, demonstrated here over decadal timescales, are similar to N- and P-cycling patterns during primary succession as soils age over thousands and millions of years, thus revealing that N availability in terrestrial ecosystems is ephemeral and can be disrupted by either natural or anthropogenic disturbances at several timescales.     

Hox genes in brachiopods and priapulids and protostome evolution.

Understanding the early evolution of animal body plans requires knowledge both of metazoan phylogeny and of the genetic and developmental changes involved in the emergence of particular forms. Recent 18S ribosomal RNA phylogenies suggest a three-branched tree for the Bilateria comprising the deuterostomes and two great protostome clades, the lophotrochozoans and ecdysozoans. Here, we show that the complement of Hox genes in critical protostome phyla reflects these phylogenetic relationships and reveals the early evolution of developmental regulatory potential in bilaterians. We have identified Hox genes that are shared by subsets of protostome phyla. These include a diverged pair of posterior (Abdominal-B-like) genes in both a brachiopod and a polychaete annelid, which supports the lophotrochozoan assemblage, and a distinct posterior Hox gene shared by a priapulid, a nematode and the arthropods, which supports the ecdysozoan clade. The ancestors of each of these two major protostome lineages had a minimum of eight to ten Hox genes. The major period of Hox gene expansion and diversification thus occurred before the radiation of each of the three great bilaterian clades.     

Predicting phenotypic variation in yeast from individual genome sequences

A central challenge in genetics is to predict phenotypic variation from individual genome sequences. Here we construct and evaluate phenotypic predictions for 19 strains of Saccharomyces cerevisiae. We use conservation-based methods to predict the impact of protein-coding variation within genes on protein function. We then rank strains using a prediction score that measures the total sum of function-altering changes in different sets of genes reported to influence over 100 phenotypes in genome-wide loss-of-function screens. We evaluate our predictions by comparing them with the observed growth rate and efficiency of 15 strains tested across 20 conditions in quantitative experiments. The median predictive performance, as measured by ROC AUC, was 0.76, and predictions were more accurate when the genes reported to influence a trait were highly connected in a functional gene network.     

Study on mechanism of mercury oxidation by fly ash from coal combustion

To understand the interaction of fly ash and mercury, systematic experiments on mercury oxidation in single flue gas composition are conducted on a fixed bed reactor system, the desorption rate and speciation of mercury are valuated. The results indicate that fly ash itself can significantly promote elemental mercury oxidation. A classification of fly ash activated sites is developed according to the speciation of mercury during adsorption-desorption tests, the reaction mechanism of mercury oxidation by fly...     

Forecasting the Term Structure of Interest Rates Using Integrated Nested Laplace Approximations

This article discusses the use of Bayesian methods for inference and forecasting in dynamic term structure models through integrated nested Laplace approximations (INLA). This method of analytical approximation allows accurate inferences for latent factors, parameters and forecasts in dynamic models with reduced computational cost. In the estimation of dynamic term structure models it also avoids some simplifications in the inference procedures, such as the inefficient two‐step ordinary least squares (OLS) estimation. The results obtained in the estimation of the dynamic Nelson–Siegel model indicate that this method performs more accurate out‐of‐sample forecasts compared to the methods of two‐stage estimation by OLS and also Bayesian estimation methods using Markov chain Monte Carlo (MCMC). These analytical approaches also allow efficient calculation of measures of model selection such as generalized cross‐validation and marginal likelihood, which may be computationally prohibitive in MCMC estimations. Copyright © 2014 John Wiley & Sons, Ltd.