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Mesoporous carbon was synthesized to be employed as support in PtRe anodic electrocatalysts. The catalysts were prepared by the polyol method with the following Re loadings: 1, 3, 5, and 10 wt.%. The N 2 adsorption-desorption isotherms, thermogravimetric measurements, temperature programmed desorption and temperature programmed reduction of the support were performed and the catalysts were structurally characterized by temperature programmed reduction, H 2 chemisorption, X-ray diffraction, X-ray photoelectron spectroscopy, benzene hydrogenation reaction, and transmission electron microscopy. Furthermore, the electrochemical characterization of the catalysts was carried out by cyclic voltammetry, chronoamperometry, and CO stripping techniques. The addition of Re leads to a decrease in the CO oxidation onset potential value. The PtRe(3)/MC catalyst exhibited the best electrocatalytic activity, showing an electrochemical active surface area value of 82.5 m2 gPt−1. Moreover, the potential and anodic current values for ethanol oxidation reaction were 889 mV vs Ag/AgCl and 648 mA mgPt−1, respectively. This result is consistent with electronic effects and the smallest particle size found for this catalyst. [ABSTRACT FROM AUTHOR]

Urban forests are becoming increasingly important for human well-being as they provide ecosystem services that contribute to improving well-being of city dwellers and to addressing climate change. However, despite their importance, there is an information gap in most of the world's urban forests due to the high cost and complexity of conducting standard forest inventories in urban environments. New technologies based on artificial intelligence can represent a smart and efficient alternative to costly traditional inventories. In this paper, we present an approach based on deep learning algorithms for the detection, counting, and geopositioning of trees using a combination of ground-level and aerial/satellite imagery. We tested several convolutional networks, exploring different combinations of hyperparameters and adjusting the query distance between ground-level images, detection radius, and various resolutions of satellite and aerial images. Our methodology is able to detect and accurately locate 79% of the urban street tree with a positional accuracy of 60 cm to the center of the canopy. Additionally, this approach allows us to determine the availability of photographs of urban trees, indicating from which Google Street View image each tree is visible. Our research provides a scalable and replicable solution to the scarcity of urban tree data and information worldwide, demonstrating the potential of artificial intelligence to revolutionize the way in which we inventory and monitor urban forests. • There is an information gap in most urban forests due to the high cost of conducting standard forest inventories. • New technologies based on artificial intelligence can be a smart and efficient alternative to traditional inventories. • Artificial intelligence has the potential to change the way in which we inventory and monitor urban forest and street tree. • The methodology can detect and locate urban street trees with a great positional accuracy. [ABSTRACT FROM AUTHOR]

We present a browser-based App for smartphones that is freely available to end-users for collecting geotagged and oriented photos depicting vegetation biomass and fuel characteristics. Our solution builds on advantages of smartphones, allowing their use as easy sensors to collect data by imaging forest ecosystems. The strength and innovation of the proposed solution is based on the following points: (i) using a low memory footprint App, streaming images and data with as little data-volume and memory as needed; (ii) using JavaScript APIs that can be launched from both a browser or as an installed App, as it applies features such as service workers and Progressive Web App; (iii) storing both image and survey data (geolocation and sensor orientation) internally to the device on an indexed database, and synchronizing the data to a cloud-based server when the smartphone is online and when all other safety tests have been successfully passed. The goal is to achieve properly positioned and oriented photos that can be used as training and testing data for future estimation of the surface fuel types based on automatic segmentation and classification via Machine Learning and Deep Learning. [ABSTRACT FROM AUTHOR]

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions. [ABSTRACT FROM AUTHOR]

Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner. [ABSTRACT FROM AUTHOR]

Ruthenium (1 wt%) catalysts supported on alumina doped with alkaline (Na and K) and alkaline earth metals (Ba, Ca, and Mg) of different concentrations (1, 5, and 10 wt%) were tested in the dry reforming of methane. All catalysts were prepared by the successive impregnation method. Supports were characterized by X-ray diffraction, BET surface area, temperature-programmed desorption of CO2, and 2-propanol dehydration. Additionally, catalysts were characterized by temperature-programmed reduction (TPR), temperature-programmed oxidation (TPO), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). Stability tests to study coke deposition were performed using long-time dry reforming reactions. All the catalysts showed good catalytic activity, and activity falls were never detected. Ru metallic phase seemed to be resistant to coke formation even though its particles are sintered during a long-term reaction. [ABSTRACT FROM AUTHOR]

Variables of soil chemistry (orange bars) are represented by nutrient availability, pH and soil organic matter content and variables of climatic conditions (blue bars) are represented by relative humidity, soil moisture content, air and soil temperature, as well as precipitation Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 2 Partial least squares (PLS) correlation loading plots for models explaining relationships between biomass of different fungal guilds in relation to a all environmental variables, b soil properties and c variables related to climatic conditions. [Extracted from the article]

Soil fungi are vital for regulating ecosystem carbon balance and productivity, by driving processes related to soil carbon and nutrient cycling. The rate and capacity of fungi-mediated processes are linked to fungal biomass dynamics and identifying the drivers of fungal biomass is important for predicting ecosystem responses to environmental changes. Here, ergosterol-based fungal biomass estimates and ITS2-based fungal community composition profiles were used to assess biomass of fungal guilds. Effects of forest management (thinning), environmental factors (soil chemical properties, microclimate, weather and forest stand composition) and season were related to the fungal biomass dynamics to identify the guild-specific drivers of biomass. Biomass of most fungal guilds increased with nutrient availability (nitrogen and potassium in particular) and decreased with forest thinning, and variation in total biomass was mainly driven by variation in mycorrhizal biomass. Most fungal guilds reached a minimum in biomass during summer except for mycorrhizal and root-associated ascomycetes, which instead reached a minimum during winter. Mycorrhizal fungi and root-associated ascomycetes displayed similar spatiotemporal variability in biomass. Yeasts and moulds were the only fungi displaying strong linkages with microclimate, whereas pathogenic and moss-associated fungi largely diverged in their responses to the environmental factors. The results of our study highlight that environmental factors related to the availability of soil nutrients may have an overall stronger effect on variation in biomass of fungal guilds in Mediterranean Pinus pinaster forests than direct influences of microclimate, weather and forest management. [ABSTRACT FROM AUTHOR]

Highlights: [•] Pb acts as a promoter or a poison of Pt supported catalysts in butane dehydrogenation. [•] There is an improvement of catalytic behavior in dehydrogenation at low Pb contents. [•] There is a marked fall of initial catalytic activity in dehydrogenation at high Pb contents. [•] The PtInPb/MgAl2O4 catalyst showed the best yield to butenes. [ABSTRACT FROM AUTHOR]

Abstract: The influence of the preparation methods of Al2O3–SnO2 on the catalytic behaviour of Pt supported on the above supports in the n-butane dehydrogenation reaction was studied. Two methods were used for the preparation of the support with different Sn loadings: (i) incipient impregnation and (ii) impregnation with an excess of solution. It was determined that the second preparation method would lead to more homogeneous catalysts than the incipient impregnation with SnCl2. Different characterization techniques (XPS, TPR, SEM, test reactions of the acidic and metallic functions, H2 chemisorption) showed that geometric effects and also possible electronic effects between Pt and Sn with probable alloys formation could take place in Pt/Al2O3–SnO2 catalysts. In all cases it was found an excellent behaviour in the n-butane dehydrogenation even when higher Sn contents in the support were used. [Copyright &y& Elsevier]

Abstract: The Sn(0.3 or 0.5wt.%) addition to Pt(0.3wt.%)/ZnAl2O4 and Pt(0.3wt.%)/MgAl2O4 catalysts leads to an increase of the activity and selectivity to olefins in the n-butane dehydrogenation reaction. Slight differences in the catalytic behaviour were found between 0.3 and 0.5wt.% of Sn added to Pt in both catalyst series. Besides, the bimetallic catalysts also show a good stability through the five successive reaction-regeneration cycles, mainly the PtSn/MgAl2O4 one. The mono- and bimetallic catalysts were characterized by using different techniques: tests reactions of the metallic phase (cyclohexane dehydrogenation and cyclopentane hydrogenolysis), temperature programmed reduction, X-ray photoelectron spectroscopy, H2 chemisorption, microcalorimetric measurements of the propylene adsorption and XRD. Results show that the nature of the metallic phase in monometallic samples appears to be different for the two supports. Thus, metallic particles with a very low concentration of hydrogenolytic sites (steps, corners and edges) would exist in the Pt/ZnAl2O4 catalyst in contrast with the structure of the metallic phase of the Pt/MgAl2O4 one, where the existence of an important concentration of hydrogenolytic sites is clearly observed (according to the cyclopentane hydrogenolysis results). The modification of Pt by the Sn addition clearly improves the catalytic behaviour in n-butane dehydrogenation due to important changes in the structure of the metallic phase. Thus, when Sn is added to Pt/ZnAl2O4 and Pt/MgAl2O4 catalysts the metallic surface structure seems to be more complex. In fact, results would indicate not only a partial formation of PtSn alloys or intermetallic compounds between Pt0 and a fraction of Sn(0), but also a surface enrichment in Sn, dilution effects as well as the presence of tin stabilized on the support, probably as Sn(II/IV) oxides and SnCl2 species. [Copyright &y& Elsevier]

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year-1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year-1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink. [ABSTRACT FROM AUTHOR]

Late-spring frosts (LSFs) affect the performance of plants and animals across the world’s temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees’ adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species’ innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy. [ABSTRACT FROM AUTHOR]

Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM. • Latin America (LATAM) is a major contributor to the global supply of forest carbon credits. • Forest carbon market projects continue to expand to support the rainforest carbon sequestration. • Substantial challenges undermine the quality and integrity of forest carbon market projects. • Recommendations are provided to improve existing governance structures of forest carbon markets. • Remote sensing can reduce technical barriers to measurement, reporting and verification (MRV). [ABSTRACT FROM AUTHOR]

Wild mushrooms contribute to a variety of ecosystem services. The expected warmer and drier conditions for the Mediterranean region as a consequence of climate change, are raising concerns about future mushroom productivity due to potential reduction of soil water availability for fungi. The aim of this study was to increase our understanding of the interaction between climate and soil moisture in relation to their impact on mushroom productivity in Mediterranean forests. Mushroom yield data were obtained from 28 permanent mushroom inventory plots intensively monitored in Maritime pine ( Pinus pinaster Ait.) stands of northeastern Iberian Peninsula. Annual productivity of total, edible and marketed mushrooms was obtained from measurements conducted every week during the autumn fruiting season for years 2008–2015. Historical weather conditions were obtained through data interpolation from meteorological stations. Soil moisture data were obtained from continuous plot-level measurements. A process-based soil water balance model was used to predict soil moisture under two climate change scenarios, using the predictions of two different regional climate models. Mixed-effects models using either precipitation or soil moisture as predictors, in combination with other weather variables, were fitted to annual mushroom occurrence and yield data. Mushroom yield was primarily dependent on weather and soil moisture conditions during the same month, with the exception of precipitation, whose effects exhibited a one-month delay. High temperatures limited mushroom yield at the beginning of the fruiting season, but tended to enhance it towards the end. The analysis revealed no apparent negative effect of climate change on long-term mushroom productivity, but rather the opposite (i.e., predicted median productivity of marketed mushrooms for 2016–2100 was 23–93% higher compared to the current yield), mainly due to an elongation of the fruiting season arising from the combined effect of increased precipitation at the beginning of the season and warmer temperatures at the end. [ABSTRACT FROM AUTHOR]

The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide.The value of biodiversity in maintaining commercial forest productivity alone—US$166 billion to 490 billion per year according to our estimation—is more than twice what it would cost to implement effective global conservation.This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities. [ABSTRACT FROM AUTHOR]

[Display omitted] • Different materials were used as catalytic supports for n-butane dehydrogenation. • Nanotubes and graphitic carbons are original and promising for the reaction. • The Pt catalysts supported on CN and CV carbons showed the best catalytic behaviors. • High metallic dispersion and good reactant accessibility are due to carbon structure. • Suitable metallic phase favours dehydrogenation reaction and inhibits collateral ones. New carbon-supported Pt catalysts were characterized and evaluated in the direct non-oxidative dehydrogenation of n-butane to butenes. After a comparison with catalysts supported on oxidic materials, Pt catalysts supported on carbon nanotubes and Vulcan carbon showed the best activity and selectivity to olefins, and a low deactivation throughout the reaction time. This fact is attributed to the chemical properties of such carbonaceous materials, which lead to a good metal-support interaction and metallic dispersion, excellent accessibility to reactants and to the formation of a suitable metallic phase, thus favoring the dehydrogenation reaction and inhibiting collateral ones. Pt catalysts supported on Vulcan carbon and carbon nanotubes become very promising candidates for the large-scale development of catalysts applied in the direct light paraffin dehydrogenation process. [ABSTRACT FROM AUTHOR]

• A unique fungal productivity database and random forest models are used. • Total productivity is predicted to decline, mainly in subalpine and montane forests. • Changes occur heterogeneously driven by spatial differences in climate change impacts. • Productivity changes will be greater under RCP 8.5 than RCP 4.5. • Contrary to mycorrhizal fungi, saprobes may increase their productivity under RCP 8.5. Fungi are responsible for many of the processes that occur in natural ecosystems and largely determine forest ecosystem dynamics, such as the ability of trees to access limiting nutrients and sequester carbon. Understanding and predicting climate change impacts on fungal dynamics over large scales is key in order to gain further insights into the effects of global change on natural ecosystem functioning and related ecosystem services. In this study, we use predictive models based on machine learning algorithms to estimate, in a spatially explicit way, the historical and future (1976–2100) evolution of mycorrhizal and saprotrophic macrofungal productivity in Mediterranean forest areas under climate change scenarios. The greatest changes in total productivity, as well as mycorrhizal fungi, are predicted to occur in subalpine and montane pine forests, where fungal productivity is estimated to decrease, and will be more pronounced under climate change scenarios with higher expected increase in temperature. In contrast to mycorrhizal species, saprotrophic fungi could benefit from pronounced changes in climate and increase their productivity in supra- and mesomediterranean regions at mid-range elevations. Moreover, we estimated that fungal productivity has also changed historically in some scattered areas where changes in climate over the years may have led to a decrease in productivity. This study contributes to raising awareness on the need for anticipating potential global change impacts on this key element of ecosystem functioning, and for deploying possible management policies oriented toward maintaining the important role of fungal productivity in both climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

Abstract: The liquid phase citral hydrogenation, using Pt and PtSn catalysts supported on MgAl2O4 and γ-Al2O3, was studied in a stirred reactor at 70°C and atmospheric pressure. It was found that the addition of Sn to the Pt catalysts increases the selectivity to double unsaturated alcohols for both catalyst series. Besides, monometallic catalysts hydrogenate the α,β-unsaturation with a high selectivity in absence of cyclization secondary products. The performance of these catalysts in the citral hydrogenation was related with the characteristics of the metallic phase. Results from test reactions – cyclohexane dehydrogenation (CHD) and cyclopentane hydrogenolysis (CPH) – H2 chemisorption, 2-propanol dehydration, temperature programmed reduction (TPR) and X-ray photoelectron spectroscopy (XPS), were used to explain the influence of the support and the Sn loading and postulate the models of the catalytic metallic surface. Results indicated that, a fraction of ionic Sn would be deposited near Pt, thus increasing the polarization of the carbonyl group, and a fraction of metallic Sn could form Pt–Sn alloy phases that would hinder the hydrogenation of the olefinic bonds and would be active to the hydrogenation of the carbonyl group. Both effects contribute to a higher selectivity to unsaturated alcohols in bimetallic PtSn/Al2O3 catalysts than PtSn/MgAl2O4 ones, which display a low alloy formation. [ABSTRACT FROM AUTHOR]

Abstract: In this paper the catalytic performance of Pt, PtSn and PtGe catalysts supported on γ-Al2O3 (γ-A) prepared by washcoating of spheres of α-Al2O3 (α-A) is studied in the n-butane dehydrogenation. For this purpose, the effect of the addition of Sn (0.3 and 0.5wt.%) and Ge (0.18 and 0.3wt.%) to Pt (0.3wt.%) on the activity, selectivity and the catalytic stability was analyzed. The catalyst characterization was carried out by using cyclohexane dehydrogenation (CHD) and cyclopentane hydrogenolysis (CPH) reactions, and also temperature programmed reduction (TPR), H2 chemisorption, X-ray photoelectron spectroscopy (XPS) and scanning electronic microscopy (SEM). Results show that important advances in the development of these catalysts were obtained. In this sense the PtSn(0.5)/γ-A/α-A catalyst showed the best catalytic performance (activity, selectivity to all butenes and high stability) in n-butane dehydrogenation reaction. Results showed a different composition of the metallic phase according to the nature of the second metal (Sn or Ge). In fact, PtSn catalysts show a low electronic interaction between the two metals, with a surface segregation of Sn and oxidized Sn stabilized on the support. On the other hand, PtGe catalysts present strong PtGe interactions with probable alloys formation. [Copyright &y& Elsevier]

Abstract: Trimetallic PtSnIn and PtSnGa catalysts supported on coprecipitated MgAl2O4 display better behaviors in n-butane conversion, selectivity to butenes and deactivation due to coke formation, than bimetallic PtSn/MgAl2O4 catalysts, and much better than the mometallic catalyst. The addition of Sn and In to Pt produces mainly an important decrease of the metallic particle sizes and geometric modifications of the metallic phase, these facts being the cause for the excellent performance. For PtSnGa/MgAl2O4, not only geometric but also electronic effects on the metallic phase would be present. [Copyright &y& Elsevier]

Poisoning tolerance of Pt-based catalyst is an important parameter for the designing of direct electrochemical fuel cells (EFCs) based on electrooxidation of alcohols (i.e. methanol, ethanol). Applicability of direct ethanol EFCs is still challenging taking into account the lack of effective electrocatalysts which are able to produce high faradic current densities and high stability towards strong adsorption of C1 and C2 oxidation products. As we present here, mono- and bimetallic Pt-based electrocatalysts have been synthesized on a carbon black support for the elecotrooxidation of ethanol in acidic media. Depending of the molar ratio between poly- n -vinylpyrrolidone (PVP, acting as protecting agent) and Pt, nanoparticle size distribution has been controlled, obtaining an optimal condition of Pt loading and electroactive surface area (ECSA) for the PVP/Pt ratio = 1. The electrochemical behavior of electrocatalyst Pt/Re/CB-1 shows a negligible variation in the ECSA (98.3 m2 g−1) in comparison with the monometallic electrodes (90.2 m2 g−1). In contrast, addition of Ir tends to reduce the ECSA by agglomeration of some nanoparticles and decreasing its electrochemical performance. Incorporation of Re in the alloy promotes bond breaking of the intermediates adsorbed on surface, specifically adsorbed C2 molecules, releasing great number of the active sites from the Pt surface, minimizing the deactivation with cycling and providing remarkable stable catalyst with high specific current densities with the addition of small amounts of Re. [Display omitted] • Mono- and bimetallic electrocatalyst for ethanol oxidation reaction. • Controlled amount and electrochemical active surface area of Pt in mono- and bimetallic by the synthesis of electrocatalyst. • High CO-tolerance of electrocatalyst with small addition of Re. [ABSTRACT FROM AUTHOR]

Abstract: In order to synthesize MgAl2O4, three methods were used: (a) a solid phase reaction of MgO and γ-Al2O3 oxides at 900°C for 24h (ceramic method), (b) wet milling during 24h of the mixture of oxides followed by the reaction at 900°C for 12h (mechanochemical synthesis), and (c) coprecipitation of Mg(NO3)2·6H2O and Al(NO3)3·9H2O with ammonia solution followed by a calcination in a flow of air at 800°C during 4h (coprecipitation method). The synthesized materials were characterized by XRD, BET isotherm, isopropanol dehydration reaction, TGA/DTA and SEM. The results indicate that in all the cases the MgAl2O4 spinel was formed. Besides, a residue of MgO in the samples obtained by the ceramic method and mechanochemical synthesis was found, which was eliminated by purification. The surface area of MgAl2O4 obtained by mechanochemical synthesis and coprecipitation method are much higher than that of the spinel synthesized by the ceramic method. Pt (0.3%) catalysts were prepared by impregnating the three supports with H2PtCl6. The metallic dispersion of Pt/MgAl2O4 obtained by mechanochemical synthesis was higher than that of Pt catalysts supported on the other spinels, in agreement with the catalytic behavior observed in n-butane dehydrogenation reaction and test reactions of the metallic phase. [Copyright &y& Elsevier]

In this work, supported Pt monometallic catalysts were prepared using oxide and carbon supports by conventional impregnation methods. Similar Pt metallic nanoparticle sizes (mean sizes about 1.8-2 nm) have been obtained using different Pt precursor loadings (0.3 to 5 wt%). For comparison, catalysts with larger nanoparticle sizes were prepared using the liquid phase reduction method. Characterization results indicate different electronic and structural characteristics for the Pt nanoparticles, comparing nanoparticles with similar and different sizes, implying that both the Pt loading and the preparation method affect the formation of different metallic phases. We used the direct dehydrogenation of n -butane to n -butenes reaction as a test reaction to study the catalytic behavior of the Pt nanoparticles obtained at different Pt atomic concentrations. Surprisingly, Pt catalysts with the lowest metallic loading show the highest selectivities to olefins. Besides, Pt catalysts supported on carbon materials showed higher selectivity to butenes than those supported on oxide materials, this was attributed to a higher electron density in the Pt active sites. Likewise, at low Pt loadings, the CNP-supported Pt nanoparticles could be confined at the defect in the nanotube structure as crystalline agglomerates of atoms with few layers or monolayers with very few surface adatom or stepped adatom nanostructures or simply as a group of atoms, thus creating active Pt sites that favor the dehydrogenation reaction over secondary reactions.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems., (© 2024. The Author(s).)

The scarcity of long-term observational data has limited the use of statistical or machine-learning techniques for predicting intraannual ecological variation. However, time-stamped citizen-science observation records, supported by media data such as photographs, are increasingly available. In the present article, we present a novel framework based on the concept of relative phenological niche, using machine-learning algorithms to model observation records as a temporal sample of environmental conditions in which the represented ecological phenomenon occurs. Our approach accurately predicts the temporal dynamics of ecological events across large geographical scales and is robust to temporal bias in recording effort. These results highlight the vast potential of citizen-science observation data to predict ecological phenomena across space, including in near real time. The framework is also easily applicable for ecologists and practitioners already using machine-learning and statistics-based predictive approaches., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Institute of Biological Sciences.)

Freshwater ecosystems host disproportionately high biodiversity and provide unique ecosystem services, yet they are being degraded at an alarming rate. Fires, which are becoming increasingly frequent and intense due to global change, can affect these ecosystems in many ways, but this relationship is not fully understood. We conducted a systematic review to characterize the literature on the effects of fires on stream ecosystems and found that (1) abiotic indicators were more commonly investigated than biotic ones, (2) most previous research was conducted in North America and in the temperate evergreen forest biome, (3) following a control-impact (CI) or before-after (BA) design, (4) predominantly assessing wildfires as opposed to prescribed fires, (5) in small headwater streams, and (6) with a focus on structural and not functional biological indicators. After quantitatively analyzing previous research, we detected great variability in responses, with increases, decreases, and no changes being reported for most indicators (e.g., macroinvertebrate richness, fish density, algal biomass, and leaf decomposition). We shed light on these seemingly contradicting results by showing that the presence of extreme hydrological post-fire events, the time lag between fire and sampling, and whether the riparian forest burned or not influenced the outcome of previous research. Results suggest that although wildfires and the following hydrological events can have dramatic impacts in the short term, most biological endpoints recover within 5-10 years, and that detrimental effects are minimal in the case of prescribed fires. We also detected that no effects were more often reported by BACI studies than by CI or BA studies, raising the question of whether this research field may be biased by the inherent limitations of CI and BA designs. Finally, we make recommendations to help advance this field of research and guide future integrated fire management that includes the protection of freshwater ecosystems., (Global Change Biology© 2024 The Author(s). Global Change Biology published by John Wiley & Sons Ltd.)

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4-43% higher growth rates, 14-17% higher survival rates and 4-7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks., (© 2024. The Author(s).)

Clear-cutting is a common silvicultural practice. Although temporal changes in the soil fungal community after clear-cutting have been widely investigated, little is known about stand-level variations in the spatial distribution of soil fungi, particularly at the clear-cut edge. We performed spatial soil sampling in three clear-cuts (0.5 ha), edge habitats, and surrounding forests 8 years after clear-cutting to examine the impact of clear-cutting on the soil fungal community (diversity, composition, guilds, and biomass) and soil properties in a managed Pinus sylvestris forest in northern Spain. Our analyses showed small differences in the composition of the soil fungal community between edge, forest, and clear-cut zones, with <4 % of the species strictly associated with one or two zones. The richness, diversity, and evenness of the fungal community in the edge zone was not significantly different to that in the forest or clear-cut zones, although the clear-cut core had approximately a third fewer ectomycorrhizal species than the edge or the forest. Saprotrophic fungi were widespread across the clear-cut-forest gradient. Soil fungal biomass varied significantly between zones, ranging from 4 to 5 mg g -1 dry soil in the forest and at the forest edge to 1.7 mg g -1 dry soil in the clear-cut area. Soil organic matter, pH, nitrogen, and phosphorus did not differ significantly between edge, forest, and clear-cutting zones and were not significantly related to the fungal community composition. Overall, our study showed that small-scale clear-cut treatments are optimal to guarantee, in the medium-term, soil fungal communities within harvested areas and at the forest edge that are comparable to soil fungal communities in the forest, even though the amount of fungal biomass in the clear-cut zone is lower than at the forest edge or in the forest., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Giada Centenaro reports a relationship with University of Lleida that includes: employment. Sergio de Miguel Manana reports a relationship with University of Lleida that includes: employment. Svetlana Dashevskaya reports a relationship with University of Lleida that includes: employment. Jose Antonio Bonet reports a relationship with Cataluna Forest Technology Centre that includes: employment. Fernando Martinez Pena reports a relationship with Centro de Investigación y Tecnología Agroalimentaria de Aragón that includes: employment. Angel Ponce reports a relationship with University of Lleida that includes: employment. Josu G. Alday reports a relationship with University of Lleida that includes: employment., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1 . Remote-sensing estimates to quantify carbon losses from global forests 2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets., (© 2023. The Author(s).)

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling., (© 2023. The Author(s).)

Litter decomposition is a key step in global biogeochemical cycling. In forest ecosystems, litter from different tree spec1ies often decompose together. Although species diversity is widely acknowledged to accelerate decomposition through the regulation of nutrient transfer between litter and decomposer communities, the underlying mechanism remains unclear. To explore the association between the bacterial community and mixed-litter chemical transformation, we conducted a one-year litter mixing decomposition experiment using leaf litter from four dominant tree species in Mount Tai (Eastern China), Robinia pseudoacacia , Quercus acutissima , Pinus tabulaeformis , and Pinus densiflora . Our results showed that: 1) Mass loss of leaf litter mixtures was significantly faster than that of leaf litter monocultures, except for R. pseudoacacia . Litter mixtures without R. pseudoacacia showed non-additive synergistic effects, whereas litter mixtures with R. pseudoacacia exerted additive effects; 2) Litter species in the absence of R. pseudoacacia significantly decreased the nutrient retention rates of litter mixtures compared to those of monocultures; 3) Litter mixtures with or without R. pseudoacacia showing additive and non-additive effects in monocultures had a distinct bacterial community structure; 4) Bacterial community structure was also modified by initial litter traits; carbon (C), nitrogen (N), and phosphorus (P) concentrations in monocultures; N/P and C/N ratios of mixtures with R. pseudoacacia ; and the lignin/N ratio of mixtures without R. pseudoacacia . Overall, these findings indicate that tree species diversity controls decomposition and nutrient cycling, implying that an appropriate species community composition is beneficial to maintaining forest ecosystems., Competing Interests: TThe authors declare that they have no conflict of interest.

Urban forests provide direct and indirect benefits to human well-being that are increasingly captured in residential property values. Remote Sensing (RS) can be used to measure a wide range of forest and vegetation parameters that allows for a more detailed and better understanding of their specific influences on housing prices. Herein, through a systematic literature review approach, we reviewed 89 papers (from 2010 to 2022) from 21 different countries that used RS data to quantify vegetation indices, forest and tree parameters of urban forests and estimated their influence on residential property values. The main aim of this study was to understand and provide insights into how urban forests influence residential property values based on RS studies. Although more studies were conducted in developed (n = 55, 61.7%) than developing countries (n = 34, 38.3%), the results indicated for the most part that increasing tree canopy cover on property and neighborhood level, forest size, type, greenness, and proximity to urban forests increased housing prices. RS studies benefited from spatially explicit repetitive data that offer superior efficiency to quantify vegetation, forest, and tree parameters of urban forests over large areas and longer periods compared to studies that used field inventory data. Through this work, we identify and underscore that urban forest benefits outweigh management costs and have a mostly positive influence on housing prices. Thus, we encourage further discussions about prioritizing reforestation and conservation of urban forests during the urban planning of cities and suburbs, which could support UN Sustainable Development Goals (SDGs) and urban policy reforms., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Ltd.)