Long-Term Effect of Charcoal Accumulation in Hearth Soils on Tree Growth and Nutrient Cycling

There is a lack of long-term field approach investigating biochar impact on soil properties and vegetation, particularly in forest ecosystems. Relic charcoal hearths (RCHs), the result of the historical charcoal production in the forests, preserve a charcoal-enriched topsoil horizon, thus representing a suitable proxy for studying the long-term effect of biochar addition to soil. In this study, we analyzed the chemical properties of a soil as impacted by charcoal accumulation in three RCH plots in southern Wallonia (Belgium) compared to the soil outside RCHs. We further evaluated the effects of RCHs soil properties on the growth performances of silver birch and European beech as well as the leaves' nutrient concentration of the latter. RCHs soil stored much more carbon and nitrogen than the reference ones. Most of the C in RCHs derived from charcoal (70–94% of total organic carbon), which would correspond to a total input of 342 tons of biochar per hectare in these soils. Such an accumulation of charcoal still affects nutrient status of soil even after 150 years since charcoal hearths abandonment: CEC and K, Ca, Mg, Na, Mn, and Zn concentration remained higher in RCHs soil compared to the reference one. In spite of a seemingly higher fertility of RCHs soil, elemental concentrations of European beech leaves grown in RCHs did not show any significant difference compared to the reference plots, except for C and Mn concentration, higher and lower, respectively, in the leaves of European beech trees grown inside than outside RCHs. Overall, RCHs soil chemical properties were not a decisive factor in significantly improving tree growth. On the contrary, tree ring width average values of both tree species was slightly lower in RCH plots, suggesting to better investigate the potential long-term detrimental effect of a large biochar addition to soil on forest trees

Downscaling CMIP6 climate projections to classify the future offshore wind energy resource in the Spanish territorial waters

The Spanish government has established a Maritime Spatial Planning including areas for wind farms, with the aim of contributing up to 40% of European floating offshore wind power by 2030. Thus, it is crucial to assess the current and future offshore wind energy resource in these areas, and classify the near future resource by considering wind power density and other relevant factors like resource stability, environmental risks, and installation costs. To attain the necessary high spatial resolution, a dynamic downscaling of a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project was conducted using the Weather Research and Forecasting model in Spanish territorial waters, including the Iberian Peninsula, Balearic Islands, and Canary Islands. Future projections were considered under the Shared Socioeconomic Pathways 2–4.5 and 5–8.5 scenarios. According to the results, Spain’s offshore wind energy potential is projected to grow in the upcoming years, particularly in the Atlantic Ocean and surrounding the Canary Islands. Wind resource classification in the potential offshore wind farm areas reveals noteworthy diversity, with ratings ranging from “fair” (3/7) to “outstanding” (6/7). The most promising areas for offshore wind farm development in the near future are located in the northwest of the Iberian Peninsula and the Canary Islands.Xunta de Galicia | Ref. ED431C 2021/44Agencia Estatal de Investigación | Ref. TED2021-129479A-I00Agencia Estatal de Investigación | Ref. PID2021-128510OB-I00Agencia Estatal de Investigación | Ref. IJC2020-043745-

Exploring environmental variables based on ecotopes derived by remote sensing

LifewatchWB contributes to the European Research Infrastructure Consortium for biodiversity and ecosystem research (Lifewatch) by providing online tools for the visualization of environmental variables. It consists in two Web portals (www.uclouvain.be/lifewatch) providing data about i) weekly anomalies of the dynamic land cover properties (snow cover and vegetation greenness) and ii) high resolution characterization of ecotopes. The topic of this abstract is the ecotope visualization interface. Ecotopes are the smallest ecologically functional units. They can be mapped by intersecting a large number of thematic layers (soil type, land cover, topographic types). However, this creates a lot of polygons with an exponentially increasing number of categorical values combinations. The visualization and analysis of those polygons is therefore difficult. On the other hand, the LifewatchWB ecotopes consist in irregular polygons derived from geographic object-based image analysis (grouping adjacent pixels of similar properties to create a partition of irregular polygons). Each polygon is then characterized using a set of continuous fields: quantitative variables (climate, elevation, slope, artificial light, contextual variables…) are either interpolated or averaged at the level of the ecotopes depending on the resolution of the input layers; categorical variables (soil types, land cover types…) are provided as proportions inside the ecotopes. The ecotope database is an open data layer currently available for the Walloon Region (Belgium). It consists in 1.2 million polygons with more than 80 quantitative fields. Those fields cannot be visualized together, therefore several visualization tools are provided on the interface: 1) each variable can be visualized individually in grey level, 2) any set of three variables can be visualized as a color composite and 3) queries based on potentially all variables can provide binary outputs. In addition, an online tool is available to extract the values of the ecotope characteristics in a set of point locations for further analysis in other softwares. With its polygon-based structure that is homogeneous with respect to the land cover and the topography, ecotopes provides meaningful landscape units with a large set of precomputed variables. Those variables are easy to visualize in a WebGIS and have been combined with species observations to run habitat and biotope models

Achievable agricultural soil carbon sequestration across Europe from country-specific estimates

Publication history: Accepted - 9 September 2021; Published online - 20 September 2021.The role of soils in the global carbon cycle and in reducing GHG emissions from agriculture has been increasingly acknowledged. The ‘4 per 1000’ (4p1000) initiative has become a prominent action plan for climate change mitigation and achieve food security through an annual increase in soil organic carbon (SOC) stocks by 0.4%, (i.e. 4‰ per year). However, the feasibility of the 4p1000 scenario and, more generally, the capacity of individual countries to implement soil carbon sequestration (SCS) measures remain highly uncertain. Here, we evaluated country-specific SCS potentials of agricultural land for 24 countries in Europe. Based on a detailed survey of available literature, we estimate that between 0.1% and 27% of the agricultural greenhouse gas (GHG) emissions can potentially be compensated by SCS annually within the next decades. Measures varied widely across countries, indicating differences in country-specific environmental conditions and agricultural practices. None of the countries' SCS potential reached the aspirational goal of the 4p1000 initiative, suggesting that in order to achieve this goal, a wider range of measures and implementation pathways need to be explored. Yet, SCS potentials exceeded those from previous pan-European modelling scenarios, underpinning the general need to include national/regional knowledge and expertise to improve estimates of SCS potentials. The complexity of the chosen SCS measurement approaches between countries ranked from tier 1 to tier 3 and included the effect of different controlling factors, suggesting that methodological improvements and standardization of SCS accounting are urgently required. Standardization should include the assessment of key controlling factors such as realistic areas, technical and practical feasibility, trade-offs with other GHG and climate change. Our analysis suggests that country-specific knowledge and SCS estimates together with improved data sharing and harmonization are crucial to better quantify the role of soils in offsetting anthropogenic GHG emissions at global level.This study has been funded and supported by the Horizon 2020 European Joint Programme SOIL (EJP-SOIL), grant agreement: 862695; Funding source: H2020-SFS-2018-2020/H2020-SFS-2019-1

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\mathrm{t}\overline{\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV)

Particle-flow reconstruction and global event description with the CMS detector

The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic tau decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8 TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions

Search for heavy resonances decaying to a top quark and a bottom quark in the lepton+jets final state in proton–proton collisions at 13 TeV

info:eu-repo/semantics/publishe

Evidence for the Higgs boson decay to a bottom quark–antiquark pair

info:eu-repo/semantics/publishe

Measurement of differential cross sections for top quark pair production using the lepton plus jets final state in proton-proton collisions at 13 TeV

National Science Foundation (U.S.

Pseudorapidity and transverse momentum dependence of flow harmonics in pPb and PbPb collisions

info:eu-repo/semantics/publishe