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Methane emissions from aquatic and terrestrial ecosystems play a crucial role in global warming, which is particularly affecting high-latitude ecosystems. As major contributors to methane emissions in natural environments, the microbial communities involved in methane production and oxidation deserve a special attention. Microbial diversity and activity are expected to be strongly affected by the already observed (and further predicted) temperature increase in high-latitude ecosystems, eventually resulting in disrupted feedback methane emissions. The METHANOBASE project has been designed to investigate the intricate relations between microbial diversity and methane emissions in Arctic, Subarctic and Subantarctic ecosystems, under natural (baseline) conditions and in response to simulated temperature increments. We report here a small subunit ribosomal RNA (16S rRNA) analysis of lake, peatland and mineral soil ecosystems.

Many species are too slow to track their poleward moving climate niche under global warming. Pesticide exposure may contribute to this by reducing population growth and impairing flight ability. Moreover, edge populations at the moving range front may be more vulnerable to pesticides because of the rapid evolution of traits to enhance their rate of spread that shunt energy away from detoxification and repair. We exposed replicated edge and core populations of the poleward moving damselfly Coenagrion scitulum to the pesticide esfenvalerate at low and high densities. Exposure to esfenvalerate had strong negative effects on survival, growth rate and development time in the larval stage and negatively affected flight-related adult traits (mass at emergence, flight muscle mass and fat content) across metamorphosis. Pesticide effects did not differ between edge and core populations, except that at the high concentration the pesticide-induced mortality was 17% stronger in edge populations. Pesticide exposure may therefore slow down the range expansion by lowering population growth rates, especially because edge populations suffered a higher mortality, and by negatively affecting dispersal ability by impairing flight-related traits. These results emphasize the need for direct conservation efforts toward leading-edge populations for facilitating future range shifts under global warming. MAIN DATAEVA-2015-167-OA DATA.xlsSUPPLEMENTARY DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS)EVA-2015-167-OA DATA FOR APPENDICES (BIOTIC AND ABIOTIC PARAMETERS).xls

Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.

Abstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.

To reduce plastic waste generation from failed product batches during industrial injection molding, the sustainable production of representative prototypes is essential. Interesting is the more recent hybrid injection molding (HM) technique, in which a polymeric mold core and cavity are produced via additive manufacturing (AM) and are both placed in an overall metal housing for the final polymeric part production. HM requires less material waste and energy compared to conventional subtractive injection molding, at least if its process parameters are properly tuned. In the present work, several options of AM insert production are compared with full metal/steel mold inserts, selecting isotactic polypropylene as the injected polymer. These options are defined by both the AM method and the material considered and are evaluated with respect to the insert mechanical and conductive properties, also considering Moldex3D simulations. These simulations are conducted with inputted measured temperature-dependent AM material properties to identify in silico indicators for wear and to perform cooling cycle time minimization. It is shown that PolyJetted Digital acrylonitrile-butadiene-styrene (ABS) polymer and Multi jet fusioned (MJF) polyamide 11 (PA11) are the most promising. The former option has the best durability for thinner injection molded parts, and the latter option the best cooling cycle times at any thickness, highlighting the need to further develop AM options.

Digital Transformations (DT) play an increasingly important role in academia and business, yet their significant Environmental Footprint (EF) is often overlooked, sidelining their potential for Environmental Sustainability (ES). This paper bridges this gap by integrating ES into the discourse of DT, proposing Green Enterprise Architecture (GREAN) as a method for sustainable transformation. Utilizing a Design Science Research approach, we developed an artefact outlining a comprehensive strategy for embedding ES in DT across various layers of an organization. The tool’s need was validated via a systematic literature review (SLR), highlighting the significant research gap in Green Enterprise Architecture. The artefact provides concrete Courses of Action (CoAs) for incorporating ES into the organizational strategy, business, data, application, and technology layers and proposes relevant capabilities to address this. The paper further presents an ES-aware business capability modelling, an innovative business modelling approach that integrates environmental sustainability principles by using (in a novel way) the presentation and analysis methods that capability mapping offers. The proposed artefact serves as a starting point for environmentally sustainable DTs. Future research directions include in-depth exploration of each enterprise layer for ES, real-world validation of our proposed tools and concepts, and the expansion of these into a full framework.

Analyses of ancient food webs reveal important paleoecological processes and responses to a range of perturbations throughout Earth’s history, such as climate change. These responses can inform our forecasts of future biotic responses to similar perturbations. However, previous analyses of ancient food webs rarely accounted for key differences between modern and ancient community data, particularly selective loss of soft-bodied taxa during fossilization. To consider how fossilization impacts inferences of ancient community structure we (1) analyzed node-level attributes to identify correlations between ecological roles and fossilization potential and (2) applied selective information loss procedures to food web data for extant systems. We found that selective loss of soft-bodied organisms has predictable effects on the trophic structure of “artificially fossilized” food webs, because these organisms occupy unique, consistent food web positions. Fossilized food webs misleadingly appear less stable (i.e., more prone to trophic cascades), with less predation and an overrepresentation of generalist consumers. We also found that ecological differences between soft- and hard-bodied taxa—indicated by distinct positions in modern food webs—are recorded in an Early Eocene web, but not in Cambrian webs. This suggests that ecological differences between the groups have existed for ≥ 48 million years. Our results indicate that accounting for soft-bodied taxa is vital for accurate depictions of ancient food webs. However, the consistency of information loss trends across the analyzed food webs means it is possible to predict how the selective loss of soft-bodied taxa affects food web metrics, which can permit better modeling of ancient communities. Repository Contents: Supplementary Information: Containing Supplementary Text, Figures, Tables, and Data descriptions. Supplementary Data 1: Food web data (adjacency matrices and metadata; see publication; see Related Works). Supplementary Data 2: Additional references consulted for preservation group assignments. Supplementary Data 3: Data and R scripts to recreate analyses from this study. S3_AllWebTaxonomy_updated_200903.csv: Taxonomy data for all food web nodes. S3_AnalysisOfTaxonomicRanks.csv: Lowest taxonomic rank for each node. S3_MainFigures_CaimanComparison.R: Compare the three food webs contained in (Roopnarine and Hertog 2013). S3_MainFigures_ComparisonFunctions.R: Functions for calculating metrics and generating trophic species webs. S3_MainFigures_FossilizationFunctions.R: Functions for artificially fossilizing networks. S3_MainFigures_Setup_200826.R: Setup to import food webs. S3_MainFigures_Code.R: Code to apply functions. S3_pbdb_data_200504.csv: Data from the Paleobiology Database, excluding Lagerstätten (see publication). S3_PresGrAssignments_updated_200902.csv: Preservation group assignments for all nodes. Fossil faunal lists were downloaded from the PBDB on 17th January 2020. Any data processing steps are shown in R Scripts and described in publication. Paleobiology Database is licensed under a CC BY 4.0 International License. https://creativecommons.org/licenses/by/4.0/. We analyzed food webs for four modern marine systems, one modern freshwater system, two ancient marine systems, and one ancient lake system from previous publications. All webs have similar, broad higher-rank taxonomic compositions and contain at least 85 nodes (the size of the smallest ancient network considered). For comparisons with ancient diversity, we downloaded fossil occurrences from the Paleobiology Database (PBDB) on 17th January 2020. 

The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.