Deforestation and Reforestation of Latin America and the Caribbean (2001–2010)

Forest cover change directly affects biodiversity, the global carbon budget, and ecosystem function. Within Latin American and the Caribbean region (LAC), many studies have documented extensive deforestation, but there are also many local studies reporting forest recovery. These contrasting dynamics have been largely attributed to demographic and socio‐economic change. For example, local population change due to migration can stimulate forest recovery, while the increasing global demand for food can drive agriculture expansion. However, as no analysis has simultaneously evaluated deforestation and reforestation from the municipal to continental scale, we lack a comprehensive assessment of the spatial distribution of these processes. We overcame this limitation by producing wall‐to‐wall, annual maps of change in woody vegetation and other land‐cover classes between 2001 and 2010 for each of the 16,050 municipalities in LAC, and we used nonparametric Random Forest regression analyses to determine which environmental or population variables best explained the variation in woody vegetation change. Woody vegetation change was dominated by deforestation (?541,835 km²), particularly in the moist forest, dry forest, and savannas/shrublands biomes in South America. Extensive areas also recovered woody vegetation (+362,430 km²), particularly in regions too dry or too steep for modern agriculture. Deforestation in moist forests tended to occur in lowland areas with low population density, but woody cover change was not related to municipality‐scale population change. These results emphasize the importance of quantitating deforestation and reforestation at multiple spatial scales and linking these changes with global drivers such as the global demand for food.     

Gloverins of the silkworm Bombyx mori: Structural and binding properties and activities

Gloverins are basic, glycine-rich and heat-stable antibacterial proteins (～14- kDa) in lepidopteran insects with activity against Escherichia coli, Gram-positive bacteria, fungi and a virus. Hyalophora gloveri gloverin adopts a random coil structure in aqueous solution but has α-helical structure in membrane-like environment, and it may interact with the lipid A moiety of lipopolysaccharide (LPS). Manduca sexta gloverin binds to the O-specific antigen and outer core carbohydrate of LPS. In the silkworm Bombyx mori, there are four gloverins with slightly acidic to neutral isoelectric points. In this study, we investigate structural and binding properties and activities of B. mori gloverins (BmGlvs), as well as correlations between structure, binding property and activity. Recombinant BmGlv1-4 were expressed in bacteria and purified. Circular dichroism (CD) spectra showed that all four BmGlvs mainly adopted random coli structure (>50%) in aqueous solution in regardless of pH, but contained α-helical structure in the presence of 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), smooth and rough mutants (Ra, Rc and Re) of LPS and lipid A. Plate ELISA assay showed that BmGlvs at pH 5.0 bound to rough mutants of LPS and lipid A but not to smooth LPS. Antibacterial activity assay showed that positively charged BmGlvs (at pH 5.0) were active against E. coli mutant strains containing rough LPS but inactive against E. coli with smooth LPS. Our results suggest that binding to rough LPS is the prerequisite for the activity of BmGlvs against E. coli.     

Identification of Penicillin-binding proteins employing support vector machines and random forest

Penicillin-Binding Proteins are peptidases that play an important role in cell-wall biogenesis in bacteria and thus maintaining bacterial infections. A wide class of β-lactam drugs are known to act on these proteins and inhibit bacterial infections by disrupting the cell-wall biogenesis pathway. Penicillin-Binding proteins have recently gained importance with the increase in the number of multi-drug resistant bacteria. In this work, we have collected a dataset of over 700 Penicillin-Binding and non-Penicillin Binding Proteins and extracted various sequence-related features. We then created models to classify the proteins into Penicillin-Binding and non-binding using supervised machine learning algorithms such as Support Vector Machines and Random Forest. We obtain a good classification performance for both the models using both the methods.     

不同类群水生昆虫群落间的一致性以及空间和环境因子的相对作用

生物多样性监测和保护过程中通常用到指示类群,然而对于这些指示类群有效性的测度仍然十分欠缺.为探讨不同类群水生昆虫群落的一致性及空间因子、环境变量的相对影响,作者于2010年4月对东苕溪流域源头溪流21个采样点进行了调查.共记录水生昆虫7目44科92属130种.我们将水生昆虫群落划分成鞘翅目(C)、蜉蝣目+襀翅目+毛翅目(EPT)和双翅目+广翅目+蜻蜒目(DMO)3个类群.一致性分析结果表明:3个类群的群落一致性(r)较高,分别为C对EPTr=0.65 (P＜0.001)、C对DMO r=0.67 (P＜0.001)、EPT对DMO r=0.82 (P＜0.001).方差分解表明环境变量是影响不同类群水生昆虫群落结构的主要因素,空间因子的影响相对较小.环境因子中影响不同类群水生昆虫群落的关键变量大体相似,其中海拔、pH、平均流速和化学需氧量是最主要的驱动因子.我们的结果表明该研究区域不同类群的水生昆虫群落一致性很高,且对环境变量的响应也相似;因此,在水生昆虫生物多样性保护中可考虑利用其中的某一类群,如蜉蝣目+襀翅目+毛翅目(EPT)类群,作为有效的指示类群.     

Unveiling the Pathways of Dioxygen Through the C2 Component of the Environmentally Relevant Monooxygenase p‐Hydroxyphenylacetate Hydroxylase from Acinetobacter baumannii: A Molecular Dynamics Investigation

In this work, models of the homotetrameric C2 component of the monooxygenase p‐hydroxyphenylacetate hydroxylase from Acinetobacter baumannii, in complex with dioxygen (O₂) and, or not, the substrate p‐hydroxyphenylacetate (HPA) were built. Both models proved to be amenable to random‐acceleration molecular dynamics (RAMD) simulations, whereby a tiny randomly oriented external force, acting on O₂ at the active site in front of flavin mononucleotide (FMNH^?), accelerated displacement of O₂ toward the bulk solvent. This allowed us to carry out a sufficiently large number of RAMD simulations to be of statistical significance. The two systems behaved very similarly under RAMD, except for O₂ leaving the active site more easily in the absence of HPA, but then finding similar obstacles in getting to the gate as when the active site was sheltered by HPA. This challenges previous conclusions that HPA can only reach the active center after that the C4aOOH derivative of FMNH^? is formed, requiring uptake of O₂ at the active site before HPA. According to these RAMD simulations, O₂ could well get to FMNH^? also in the presence of the substrate at the active site.     

Comparison of boosted regression tree and random forest models for mapping topsoil organic carbon concentration in an alpine ecosystem

Soil organic carbon (SOC) plays an important role in soil fertility and carbon sequestration, and a better understanding of the spatial patterns of SOC is essential for soil resource management. In this study, we used boosted regression tree (BRT) and random forest (RF) models to map the distribution of topsoil organic carbon content at the northeastern edge of the Tibetan Plateau in China. A set of 105 soil samples and 12 environmental variables (including topography, climate and vegetation) were analyzed. The performance of the models was evaluated using a 10-fold cross-validation procedure. Maps of the mean values and standard deviations of SOC were generated to illustrate model variability and uncertainty. The results indicate that the BRT and RF models exhibited very similar performance and yielded similar predicted distributions of SOC. The two models explained approximately 70% of the total SOC variability. The BRT and RF models robustly predicted the SOC at low observed SOC values, whereas they underestimated high observed SOC values. This underestimation may have been caused by biased distributions of soil samples in the SOC space. Vegetation-related variables were assigned the highest importance in both models, followed by climate and topography. Both models produced spatial distribution maps of SOC that were closely related to vegetation cover. The SOC content predicted by the BRT model was clearly higher than that of the RF model in areas with greater vegetation cover because the contributions of vegetation-related variables in the two models (65% and 43%, respectively) differed significantly. The predicted SOC content increased from the northwestern to the southeastern part of the study area, average values produced by the BRT and RF models were 27.3 g kg⁻¹ and 26.6 g kg⁻¹, respectively. We conclude that the BRT and RF methods should be calibrated and compared to obtain the best prediction of SOC spatial distribution in similar regions. In addition, vegetation variables, including those obtained from remote sensing imagery, should be taken as the main environmental indicators and explicitly included when generating SOC maps in Alpine environments.     

Climatic effects on the distribution of ant- and bat fly-associated fungal ectoparasites (Ascomycota,Laboulbeniales)

Laboulbeniales (Ascomycota: Laboulbeniomycetes) are obligate ectoparasitic fungi of arthropods with a worldwide distribution. Their effects on host physiology and behaviour as well as their ecology have recently gained wider attention. One aspect that is virtually unknown regarding Laboulbeniales and arthropod-associated fungi in general, is how abiotic factors shape the distribution of these parasites. We used ant- and bat fly-associated Laboulbeniales to study whether climatic elements play a role in the distribution of fungal species. We collected uninfected and Laboulbeniales-infected insects belonging to three species: bat flies Nycteribia schmidlii and Penicillidia conspicua (Diptera: Nycteribiidae) and the ant Myrmica scabrinodis (Hymenoptera: Formicidae). We used climatic variables and performed statistical analyses to explain the distribution of Laboulbeniales infection. Our results show a higher likelihood of Laboulbeniales presence in habitats with low annual mean temperature and humidity, suggesting that climatic elements can considerably shape the distribution of Laboulbeniales species.