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Several bimetallic PtSn catalysts supported on multiwalled carbon nanotubes for ethanol electro‐oxidation were prepared by conventional impregnation‐reduction method. The Pt loading was kept at 20 wt.% and Pt:Sn atomic ratios of 5:1, 3:1, and 1:1 were selected. The catalysts were structurally characterized by temperature programmed reduction, X‐ray diffraction, X‐ray photoelectron spectroscopy, H2 chemisorption, cyclohexane dehydrogenation reaction, and transmission electron microscopy. The electrochemical characterization of the electrocatalytic materials was carried out in acid medium by cyclic voltammetry, linear sweep voltammetry, chronoamperometry, and CO stripping techniques. Among the different stoichiometries tested, the Pt(20)Sn(12.17)/CNT catalyst exhibited the highest electrocatalytic activity for ethanol oxidation reaction, with mass current density of 189.5 mA mgPt−1 at 796 mV (vs. Ag/AgCl). [ABSTRACT FROM AUTHOR]

In recent years fires of greater magnitude have been documented throughout northwest Europe, and with several climate projections indicating future increases in fire activity in this temperate area, it is imperative to identify the status of fire in this region. This study unravels important unknowns about the state of the fire regime in northwest Europe by characterizing one of the key aspects of fire behavior, the rate of spread (ROS). Using an innovative approach to cluster VIIRS hotspots into fire perimeter isochrones to derive ROS, we identify the effects of land cover and season on fire rate of spread of 254 landscape fires that occurred between 2012 and 2020. Results reveal no significant differences between land cover types and there is a clear peak of ROS and burned area in the months of April and May. During this late spring period, 67 % of the burned area occurs and median fire runs are approximately 0.16 km/hr during a 12 hour overpass. Heightened ROS and burned area values persist in the bordering months of March and June suggesting that may present the extent of the fire season in northwestern Europe. Accurate data on ROS among the represented land cover types as well as periods of peak activity are essential for determining periods of elevated fire risk, the effectiveness of available suppression techniques as well as appropriate mitigation strategies (land and fuel management). [ABSTRACT FROM AUTHOR]

Summary: In forests, ectomycorrhizal mycelium is pivotal for driving soil carbon and nutrient cycles, but how ectomycorrhizal mycelial dynamics vary in ecosystems with drought periods is unknown. We quantified the production and turnover of mycorrhizal mycelium in Mediterranean Pinus pinaster, Pinus sylvestris and Quercus ilex forests and related the estimates to standardised precipitation index (SPI), to study how mycelial dynamics relates to tree species and drought‐moisture conditions.Production and turnover of mycelium was estimated between July and February, by quantifying the fungal biomass (ergosterol) in ingrowth mesh bags and using statistical modelling. SPI for time scales of 1–3 months was calculated from precipitation records and precipitation data over the study period.Forests dominated by Pinus trees displayed higher biomass but were seasonally more variable, as opposed to Q. ilex forests where the mycelial biomass remained lower and stable over the season. Production and turnover, respectively, varied between 1.4–5.9 kg ha−1 d−1 and 7.2–9.9 times yr−1 over the different forest types and were positively correlated with 2‐month and 3‐month SPI over the study period.Our results demonstrated that mycorrhizal mycelial biomass varied with season and tree species and we speculate that production and turnover are related to physiology and plant host performance during drought. See also the Commentary on this article by Fernandez, 230: 1296–1299. [ABSTRACT FROM AUTHOR]

Background: The prediction of biogeographical patterns from a large number of driving factors with complex interactions, correlations and non-linear dependences require advanced analytical methods and modeling tools. This study compares different statistical and machine learning-based models for predicting fungal productivity biogeographical patterns as a case study for the thorough assessment of the performance of alternative modeling approaches to provide accurate and ecologically-consistent predictions. Methods: We evaluated and compared the performance of two statistical modeling techniques, namely, generalized linear mixed models and geographically weighted regression, and four techniques based on different machine learning algorithms, namely, random forest, extreme gradient boosting, support vector machine and artificial neural network to predict fungal productivity. Model evaluation was conducted using a systematic methodology combining random, spatial and environmental blocking together with the assessment of the ecological consistency of spatially-explicit model predictions according to scientific knowledge. Results: Fungal productivity predictions were sensitive to the modeling approach and the number of predictors used. Moreover, the importance assigned to different predictors varied between machine learning modeling approaches. Decision tree-based models increased prediction accuracy by more than 10% compared to other machine learning approaches, and by more than 20% compared to statistical models, and resulted in higher ecological consistence of the predicted biogeographical patterns of fungal productivity. Conclusions: Decision tree-based models were the best approach for prediction both in sampling-like environments as well as in extrapolation beyond the spatial and climatic range of the modeling data. In this study, we show that proper variable selection is crucial to create robust models for extrapolation in biophysically differentiated areas. This allows for reducing the dimensions of the ecosystem space described by the predictors of the models, resulting in higher similarity between the modeling data and the environmental conditions over the whole study area. When dealing with spatial-temporal data in the analysis of biogeographical patterns, environmental blocking is postulated as a highly informative technique to be used in cross-validation to assess the prediction error over larger scales. [ABSTRACT FROM AUTHOR]

Background: Robinia pseudoacacia is a widely planted pioneer tree species in reforestations on barren mountains in northern China. Because of its nitrogen-fixing ability, it can play a positive role in soil and forest restoration. After clear-cutting of planted stands, R. pseudoacacia stands become coppice plantations. The impacts of shifting from seedling to coppice stands on soil bacterial community and soil properties have not been well described. This study aims to quantify how soil properties and bacterial community composition vary between planted seedling versus coppice stands. Methods: Nine 20 m × 20 m plots were randomly selected in seedling and coppice stands. The bulk soil and rhizosphere soil were sampled in summer 2017. Bulk soil was sampled at 10 cm from the soil surface using a soil auger. Rhizosphere soil samples were collected using a brush. The soil samples were transported to the laboratory for chemical analysis, and bacterial community composition and diversity was obtained through DNA extraction, 16S rRNA gene amplification and high-throughput sequencing. Results: The results showed that, compared to seedling plantations, soil quality decreased significantly in coppice stands, but without affecting soil exchangeable Mg2+ and K+. Total carbon (C) and nitrogen (N) were lower in the rhizosphere than in bulk soil, whereas nutrient availability showed an opposite trend. The conversion from seedling to coppice plantations was also related to significant differences in soil bacterial community structure and to the reduction of soil bacterial α-diversity. Principal component analysis (PCA) showed that bacterial community composition was similar in both bulk and rhizosphere soils in second-generation coppice plantations. Specially, the conversion from seedling to coppice stands increased the relative abundance of Proteobacteria and Rhizobium, but reduced that of Actinobacteria, which may result in a decline of soil nutrient availability. Mantel tests revealed that C, N, soil organic matter (SOM), nitrate nitrogen (NO3−-N) and available phosphorus positively correlated with bacterial community composition, while a variation partition analysis (VPA) showed that NO3−-N explained a relatively greater proportion of bacterial distribution (15.12%), compared with C and SOM. Surprisingly, N showed no relationship with bacterial community composition, which may be related to nitrogen transportation. Conclusions: The conversion from seedling to coppice stands reduced soil quality and led to spatial-temporal homogenization of the soil bacterial community structure in both the rhizosphere and bulk soils. Such imbalance in microbial structure can accelerate the decline of R. pseudoacacia. This may affect the role of R. pseudoacacia coppice stands in soil and forest restoration of barren lands in mountain areas. [ABSTRACT FROM AUTHOR]

Key Message: Earlywood and latewood widths differently respond to the climate in boreal and Mediterranean Scots pine forests. The response is constrained by allometric relationships. Measurements of earlywood (EW) and latewood (LW) width can be used to assess how tree growth responds to the climate in different biomes. Through tree-ring analyses, we quantified and analysed EW and LW width in six Scots pine (Pinus sylvestris) forests situated in the boreal and Mediterranean biomes. We aimed to answer: (i) how coupled are EW and LW width in Scots pine boreal and Mediterranean European forests, and (ii) how do they respond to climate and atmospheric patterns. Using allometric approaches to assess the EW‒LW coupling and correlations with climate variables and indices we found that EW and LW width in Scots pine responds to different climate variables depending on biome and site. We identified two groups of sites with slow-growing trees producing dense wood with more LW in boreal sites vs. fast-growing trees producing more conductive wood with a higher EW proportion in Mediterranean sites. In these sites, spring-to-summer drought was the main constraint of EW and LW production. In boreal sites, wet springs and warm summers improved EW and LW width, respectively. We also found a high coupling between EW and LW width in cold, dry Mediterranean sites. LW width was very responsive to climate and atmospheric patterns in warm, dry Mediterranean sites. The most consistent response to atmospheric patterns was a negative correlation between EW and the January North Atlantic Oscillation index in Mediterranean sites. Mediterranean Scots pine forests where LW width is not very dependent on EW width are potential sites for using LW variables as proxies of drought during the growing season. [ABSTRACT FROM AUTHOR]