Tree species effects on soil microbial community composition and greenhouse gases emissions in a Mediterranean ecotone forest

Resumen de una presentación realizada en: I Simposio sobre Interacciones Planta-Suelo (ICA-CSIC, Madrid, 25-26 Febrero 2016)Over recent decades in the Iberian Peninsula, altitudinal shifts from Pinus sylvestris L. to Quercus pyrenaica Willd species has been observed as a consequence of Global Change, meaning changes in temperature, precipitation, land use and forestry. The forest conversion from pine to oak can alter the litter quality and quantity provided to the soil and thereby the soil microbial community composition and functioning. Since soil microbiota plays an important role in organic matter decomposition, and this in turn is key in biogeochemical cycles and forest ecosystems productivity, the rate in which forests produce and consume greenhouse gases can be also affected by changes in forest composition. In other words, changes in litter decomposition will ultimately affect downstream carbon and nitrogen dynamics although this impact is uncertain. In order to predict changes in carbon and nitrogen stocks in Global Change scenarios, it is necessary to deepen the impact of vegetation changes on soil microbial communities, litter decomposition dynamics (priming effect) and the underlying interactions between these factors. To test this, we conducted a full-factorial transplant microcosms experiment mixing both fresh soils and litter from Pyrenean oak, Scots pine and mixed stands collected inside their transitional area in Central Spain. The microcosms consisted in soil cylinders inside Kilner jars used as chambers inside an incubator. In this experiment, we investigated how and to what extent the addition of litter with different quality (needles, oak leaves and mixed needlesleaves) to soil inoculums with contrasting soil microbiota impact on soil (i) CO2, NO, N2O and CH4 efflux rates, (ii) total organic carbon and nitrogen and (iii) dissolved organic carbon and nitrogen. Furthermore, we assessed if these responses were controlled by changes in the microbial community structure using the PLFA analyses prior and after the incubation period of 54 days.Peer reviewe

Multi-Objective Big Data Optimization with jMetal and Spark

Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each evaluation step of a metaheuristic and to provide a software tool to solve these kinds of problems. This tool combines the jMetal multi-objective optimization framework with Apache Spark. We have carried out experiments to measure the performance of the proposed parallel infrastructure in an environment based on virtual machines in a local cluster comprising up to 100 cores. We obtained interesting results for computational e ort and propose guidelines to face multi-objective Big Data Optimization problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

N 2 O emissions and NO 3 − leaching from two contrasting regions in Austria and influence of soil, crops and climate: a modelling approach

National emission inventories for UN FCCC reporting estimate regional soil nitrous oxide (N 2 O) fluxes by considering the amount of N input as the only influencing factor for N 2 O emissions. Our aim was to deepen the understanding of N 2 O fluxes from agricultural soils, including region specific soil and climate properties into the estimation of emission to find targeted mitigation measures for the reduction of nitrogen losses and GHG emissions. Within this project, N 2 O emissions and nitrate (NO 3 − ) leaching were modelled under spatially distinct environmental conditions in two agricultural regions in Austria taking into account region specific soil and climatic properties, management practices and crop rotations. The LandscapeDNDC ecosystem model was used to calculate N 2 O emissions and NO 3 − leaching reflecting different types of vegetation, management operations and crop rotations. In addition, N input and N fluxes were assessed and N 2 O emissions were calculated. This approach allowed identifying hot spots of N 2 O emissions. Results show that certain combinations of soil type, weather conditions, crop and management can lead to high emissions. Mean values ranged from 0.15 to 1.29 kg N 2 O–N ha −1  year −1 (Marchfeld) and 0.26 to 0.52 kg N 2 O–N ha −1  year −1 (Grieskirchen). Nitrate leaching, which strongly dominated N-losses, often reacted opposite to N 2 O emissions. Larger quantities of NO 3 − were lost during years of higher precipitation, especially if winter barley was cultivated on sandy soils. Taking into account the detected hot spots of N 2 O emissions and NO 3 − leaching most efficient measures can be addressed to mitigate environmental impacts while maximising crop production. © 2018, The Author(s)

Fungal and bacterial utilization of organic substrates depends on substrate complexity and N availability

There is growing evidence of a direct relationship between microbial community composition and function, which implies that distinct microbial communities vary in their functional properties. The aim of this study was to determine whether differences in initial substrate utilization between distinct microbial communities are due to the activities of certain microbial groups. We performed a short-term experiment with beech forest soils characterized by three different microbial communities (winter and summer community, and a community from a tree-girdling plot). We incubated these soils with different 13C-labelled substrates with or without inorganic N addition and analyzed microbial substrate utilization by 13C-phospholipid fatty acid (PLFA) analysis. Our results revealed that the fate of labile C (glucose) was similar in the three microbial communities, despite differences in absolute substrate incorporation between the summer and winter community. The active microbial community involved in degradation of complex C substrates (cellulose, plant cell walls), however, differed between girdling and control plots and was strongly affected by inorganic N addition. Enhanced N availability strongly increased fungal degradation of cellulose and plant cell walls. Our results indicate that fungi, at least in the presence of a high N supply, are the main decomposers of polymeric C substrates

Enhanced ionization of acetylene in intense laser pulses is due to energy upshift and field coupling of multiple orbitals

Synopsis We describe a new enhanced ionization mechanism for polyatomic molecules. It works via a significant energy up-shift of valence orbitals for stretched bonds and a strong concomitant increase in the coupling between multiple molecular orbitals

N2_{2}O emissions and NO3_{3}−^{-} leaching from two contrasting regions in Austria and influence of soil, crops and climate: a modelling approach

National emission inventories for UN FCCC reporting estimate regional soil nitrous oxide (N$_{2}$O) fluxes by considering the amount of N input as the only influencing factor for N$_{2}$O emissions. Our aim was to deepen the understanding of N$_{2}$O fluxes from agricultural soils, including region specific soil and climate properties into the estimation of emission to find targeted mitigation measures for the reduction of nitrogen losses and GHG emissions. Within this project, N$_{2}$O emissions and nitrate (NO$_{3}$$^{-}$) leaching were modelled under spatially distinct environmental conditions in two agricultural regions in Austria taking into account region specific soil and climatic properties, management practices and crop rotations. The LandscapeDNDC ecosystem model was used to calculate N$_{2}$O emissions and NO$_{3}$$^{-}$ leaching reflecting different types of vegetation, management operations and crop rotations. In addition, N input and N fluxes were assessed and N$_{2}$O emissions were calculated. This approach allowed identifying hot spots of N$_{2}$O emissions. Results show that certain combinations of soil type, weather conditions, crop and management can lead to high emissions. Mean values ranged from 0.15 to 1.29 kg N$_{2}$O–N ha$^{-1}$ year$^{-1}$ (Marchfeld) and 0.26 to 0.52 kg N$_{2}$O–N ha$^{-1}$ year$^{-1}$ (Grieskirchen). Nitrate leaching, which strongly dominated N-losses, often reacted opposite to N$_{2}$O emissions. Larger quantities of NO$_{3}$$^{-}$ were lost during years of higher precipitation, especially if winter barley was cultivated on sandy soils. Taking into account the detected hot spots of N$_{2}$O emissions and NO$_{3}$$^{-}$ leaching most efficient measures can be addressed to mitigate environmental impacts while maximising crop production

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 2: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials

The effects of atmospheric nitrogen deposition (N$_{dep}$) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of N$_{dep}$ across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry+wet) reactive nitrogen (N$_{r}$) deposition.We propose a methodology for untangling the effects of N$_{dep}$ from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO$_{2}$ exchange fluxes from a Europe-wide network of 22 forest flux towers. Total N$_{r}$ deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP= dN$_{dep}$) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP/dN$_{dep}$ value. This model-enhanced analysis of the C and N$_{dep}$ flux observations at the scale of the European network suggests a mean overall dNEP/dN$_{dep}$ response of forest lifetime C sequestration to N$_{dep}$ of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus N$_{dep}$ were non-linear, with no further growth responses at high N$_{dep}$ levels (N$_{dep}$ >2.5–3 gNm$^{-2}$ yr$^{-1}$) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high N$_{dep}$ levels implies that the forecast increased N$_{r}$ emissions and increased Ndep levels in large areas of Asia may not positively impact the continent’s forest CO$_{2}$ sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC/dN response

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord