Soil organic matter dynamics in density and particle-size fractions following destruction of tropical rainforest and the subsequent establishment of Imperata grassland in Indonesian Borneo using stable carbon isotopes

Background and aims

Large portions of the deforested areas in Southeast Asia have been ultimately replaced by the invasive grass Imperata cylindrica, but the dynamics of soil organic matter (SOM) during such land transitions are poorly understood. This study presents SOM dynamics in density and particle-size fractions following rainforest destruction and the subsequent establishment and persistence of Imperata grassland.

Methods

We examined soil C stock and natural ¹³C abundance in these fractions to depths of 100 cm. We predicted future soil C storage and evaluated C turnover rates in these fractions using a simple exponential model. Because soil texture strongly affects soil C storage, two chronosequences of soils differing in soil texture were compared (n?=?1 in each chronosequence).

Results

The clay-associated SOM increased in all soil layers (0–100 cm) along the forest-to-grassland chronosequence, whereas light-fraction SOM in the surface soil layer (0–5 cm) decreased.

Conclusions

In the surface layer, all SOM fractions exhibited rapid replacement of forest-derived C to grassland-derived C, indicating fast turnover. Meanwhile, δ¹³C values of the light fraction in the surface layer indicated that forest-derived charcoal and/or occluded low-density organic matter constituted unexpectedly large proportions of the light fraction. Mathematical modelling (0–50 cm) showed that grassland-derived C in the clay and silt fractions in all soil layers increased almost linearly for at least 50 years after grassland establishment. In the meantime, the forest-derived C stock in the clay fraction constituted 82 % of the total stable C pool at 0–50-cm depths even under steady-state conditions (t = ∞), indicating that residue of forest-derived SOM associated with clay largely contributed to preserving the soil C pool. Comparing soils with different soil textures, clay and silt particles in coarse-textured soil exhibited a substantially higher degree of organo-mineral interactions per unit volume of clay or silt compared to fine-textured soils.     

Badnaviruses and banana genomes: a long association sheds light on Musa phylogeny and origin

Badnaviruses are double-stranded DNA pararetroviruses of the family Caulimoviridae. Badnaviral sequences found in banana are distributed over three main clades of the genus Badnavirus and exhibit wide genetic diversity. Interestingly, the nuclear genome of many plants, including banana, is invaded by numerous badnaviral sequences although badnaviruses do not require an integration step to replicate, unlike animal retroviruses. Here, we confirm that banana streak viruses (BSVs) are restricted to clades 1 and 3. We also show that only BSVs from clade 3 encompassing East African viral species are not integrated into Musa genomes, unlike BSVs from clade 1. Finally, we demonstrate that sequences from clade 2 are definitively integrated into Musa genomes with no evidence of episomal counterparts; all are phylogenetically distant from BSVs known to date. Using different molecular approaches, we dissected the coevolution between badnaviral sequences of clade 2 and banana by comparing badnavirus integration patterns across a banana sampling representing major Musa speciation events. Our data suggest that primary viral integrations occurred millions of years ago in banana genomes under different possible scenarios. Endogenous badnaviral sequences can be used as powerful markers to better characterize the Musa phylogeny, narrowing down the likely geographical origin of the Musa ancestor.     

A Consistency-Based Feature Selection Method Allied with Linear SVMs for HIV-1 Protease Cleavage Site Prediction

Background

Predicting type-1 Human Immunodeficiency Virus (HIV-1) protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors) against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space) turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy.

Results

We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs). We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations.

Conclusion

Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper.

Software availability

The software is available at http://ozyer.etu.edu.tr/c-fs-svm.rar.The software can be downloaded at esnag.etu.edu.tr/software/hiv_cleavage_site_prediction.rar; you will find a readme file which explains how to set the software in order to work.     

Changes in soil carbon stock after deforestation and subsequent establishment of “Imperata” grassland in the Asian humid tropics

Globally, tropical deforestation is often followed by the establishment of fire-prone grassland. In Southeast Asia, Imperata cylindrica grassland is the dominant land cover after deforestation. No quantitative data are available on the changes in soil carbon (C) stock upon such land conversion. We aimed to elucidate changes in soil C stock after deforestation followed by the occurrence and persistence of I. cylindrica grassland in the Asian humid tropics. We compared soil C stock between primary forests (n?=?20) and grasslands (n?=?14) with a wide range of soil textures in East Kalimantan (Indonesian Borneo). We also assessed the temporal change in soil C stock in the grassland sites between 1992 and 2004 by comparing identical soil pits (n?=?7). Soil C stock (0–100 cm deep) increased by 23% following transition from primary forest to grassland during about 10 years. Over 12 years at the grassland sites, however, soil C stock did not change in the 0–100 cm depth, but we observed increased blackness of soil, especially coarse-textured soils. The increase in C stock following the transition was largely attributed to the organic matter supply by grass roots, rhizomes, and charred materials from wildfires to the subsurface soils and subsoils (5–100 cm). The unchanged soil C stock (0–100 cm) over 12 years at the grassland sites suggests that the soil C stock level there has nearly reached a new equilibrium state. However, the increased blackness of the soil suggests changes in the quality of soil organic matter by higher subsoil root input and deeper bioturbation by earthworms.     

Coat Polymorphism in Eurasian Lynx: Adaptation to Environment or Phylogeographic Legacy?

Journal of Mammalian Evolution - We studied the relationship between the variability and contemporary distribution of pelage phenotypes in one of most widely distributed felid species and an array...     

Dynamics of soil carbon following destruction of tropical rainforest and the subsequent establishment of Imperata grassland in Indonesian Borneo using stable carbon isotopes

Southeast Asia has the highest rate of tropical rainforest deforestation worldwide, and large deforested areas have been replaced ultimately by the highly invasive grass Imperata cylindrica. However, information on the carbon (C) budget with such land transition is very scarce. This study presents the dynamics of soil C following rainforest destruction and the subsequent establishment of Imperata grassland in the lowland humid tropics of Indonesian Borneo using stable C isotopes. To evaluate the relative contribution of organic matter originating from primary forest (C₃) and grasslands (C₄), we compared soil C stock and natural ¹³C abundance from six sites to a depth of 100 cm using samples with a wide range of soil textures. Twelve years after the first soil sampling in the grasslands, we re‐sampled to examine temporal changes in soil organic matter. The grassland topsoil (0–5 cm) is an active layer with rapid decomposition and incorporation of fresh C (mean residence time: 7.5 year) and a substantial proportion of the stable C pool (37%). The decline in forest‐derived C was slight, even at 5–10 cm depths, and subsoil (20–100 cm depth) forest‐derived C did not change along the forest‐to‐grassland chronosequence. Grassland‐derived C stock increased significantly in the subsurface and subsoils (5–100 cm). Simulation indicated that total soil C stock (0–100 cm) increased by 18.6 Mg ha^?1 from initial primary forest (58.0 Mg ha^?1) to a new equilibrium state of the grassland (76.6 Mg ha^?1) after 30–50 years of grassland establishment. This research indicates that the soil did not function as a CO₂ source when the deforested area was replaced by Imperata grassland on the Ultisols of the Asian humid tropics. Instead, increased soil C stocks offset CO₂ emissions, with the C offset accounting for 6.6–7.4% of the loss of biomass C stock.