Strategic Green Infrastructure and Ecosystem Restoration

This report draws on a range of European-wide datasets, geospatial methods, and tools available for green infrastructure (GI) mapping. It shows how two complementary mapping approaches (physical and ecosystem based) and the three key GI principles of connectivity, multifunctionality and spatial planning are used in case studies selected in urban and rural landscapes; it provides guidance for the strategic design of a well-connected, multi-functional, and cross-border GI, and identifies knowledge gaps. GI mapping has been demonstrated to enhance nature protection and biodiversity beyond protected areas, to deliver ecosystem services such as climate change mitigation and recreation, to prioritise measures for defragmentation and restoration in the agri-environment and regional development context, and to find land allocation trade-offs and possible scenarios involving all sectors.JRC.D.6-Knowledge for Sustainable Development and Food Securit

Influence of the culture conditions on the production of NGPs by Aspergillus tubingensis

The filamentous fungus Aspergillus tubingensis that belongs to the black Aspergillus section has the capacity to produce high-value metabolites, for instance, Naphtho-Gamma-Pyrones (NGPs). For these fungal secondary metabolites, numerous biological properties of industrial interest have been demonstrated, such as antimicrobial, antioxidant and anti-cancer capacities. It has been observed that these secondary metabolites production is linked with the fungal sporulation. The aim of this research was to apply environmental stresses to trigger the production of NGPs in liquid cultures with CYB (Czapek Dox Broth): osmotic and oxidative stresses. In addition, numerous parameters were tested during the experiments, such as pH value, incubation time, container geometry, and static and agitation conditions. Results demonstrate that the produced amount of NGPs can be enhanced by decreasing the water activity (aw) or by adding an oxidative stress factor. In conclusion, this study can contribute to our knowledge regarding A. tubingensis to present an effective method to increase NGPs's production, which may support the development of current industrial processes

Effects of input data aggregation on simulated crop yields in temperate and Mediterranean climates

The modelling exercise for this study was highly supported by partner universities and research institutes in the framework of the MACSUR project and financially supported by the German Federal Ministry of Education and Research BMBF (FKZ 2815ERA01J) in the framework of the funding measure “Soil as a Sustainable Resource for the Bioeconomy – BonaRes”, project “BonaRes (Module B): BonaRes Centre for Soil Research (FKZ BOMA03037514, 031B0026A and 031A608A) and by the Ministry of Agriculture and Food (BMEL) in the framework of the MACSUR project (FKZ 2815ERA01J). In addition, the relevant co-authors from the partner institutes are separately financed by their respective projects. AV, EC, and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences). JC thank the INRA ACCAF metaprogramm for funding. KCK, CN, XS and TS were supported by MACSUR2 (FKZ 031B0039C). MK thanks for the funding by the UK BBSRC (BB/N004922/1) and the MAXWELL HPC team of the University of Aberdeen for providing equipment and support for the DailyDayCent simulations. FE acknowledges support by the German Science Foundation (project EW 119/5-1). GRM, TG, and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The authors also would like to acknowledge the support provided by the BMBF and the valuable comments of the scientists of the Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), University of Bonn, Germany.Peer reviewedPostprin

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), (2851ERA01J). FT and RPR were supported by FACCE MACSUR (3200009600) through the Finnish Ministry of Agriculture and Forestry (MMM). EC, HE and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences) and thank professor P-E Jansson (Royal Institute of Technology, Stockholm) for support. JC, HR and DW thank the INRA ACCAF metaprogramm for funding and Eric Casellas from UR MIAT INRA for support. CB was funded by the Helmholtz project “REKLIM—Regional Climate Change”. CK was funded by the HGF Alliance “Remote Sensing and Earth System Dynamics” (EDA). FH was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) under the Grant FOR1695. FE and SS acknowledge support by the German Science Foundation (project EW 119/5-1). HH, GZ, SS, TG and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Uncovering the Prevalence and Diversity of Integrating Conjugative Elements in Actinobacteria

Horizontal gene transfer greatly facilitates rapid genetic adaptation of bacteria to shifts in environmental conditions and colonization of new niches by allowing one-step acquisition of novel functions. Conjugation is a major mechanism of horizontal gene transfer mediated by conjugative plasmids and integrating conjugative elements (ICEs). While in most bacterial conjugative systems DNA translocation requires the assembly of a complex type IV secretion system (T4SS), in Actinobacteria a single DNA FtsK/SpoIIIE-like translocation protein is required. To date, the role and diversity of ICEs in Actinobacteria have received little attention. Putative ICEs were searched for in 275 genomes of Actinobacteria using HMM-profiles of proteins involved in ICE maintenance and transfer. These exhaustive analyses revealed 144 putative FtsK/SpoIIIE-type ICEs and 17 putative T4SS-type ICEs. Grouping of the ICEs based on the phylogenetic analyses of maintenance and transfer proteins revealed extensive exchanges between different sub-families of ICEs. 17 ICEs were found in Actinobacteria from the genus Frankia, globally important nitrogen-fixing microorganisms that establish root nodule symbioses with actinorhizal plants. Structural analysis of ICEs from Frankia revealed their unexpected diversity and a vast array of predicted adaptive functions. Frankia ICEs were found to excise by site-specific recombination from their host's chromosome in vitro and in planta suggesting that they are functional mobile elements whether Frankiae live as soil saprophytes or plant endosymbionts. Phylogenetic analyses of proteins involved in ICEs maintenance and transfer suggests that active exchange between ICEs cargo-borne and chromosomal genes took place within the Actinomycetales order. Functionality of Frankia ICEs in vitro as well as in planta lets us anticipate that conjugation and ICEs could allow the development of genetic manipulation tools for this challenging microorganism and for many other Actinobacteria

Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km2), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m−2 d−1 and 2.7–6.1 g C m−2 d−1 for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data aggregation. However, the scale of climate data is more relevant for impacts on annual averages of NPP or if the period is strongly affected or dominated by drought stress. There should be an awareness of the greater uncertainty for the NPP values in these situations if data are not available at high resolution. On the other hand, the results suggest that there is no need to simulate at high resolution for long term regional NPP averages based on the simplified assumptions (soil and management constant in time and space) used in this study

Effects of climate input data aggregation on modelling regional crop yields

Crop models can be sensitive to climate input data aggregation and this response may differ among models. This should be considered when applying field-scale models for assessment of climate change impacts on larger spatial scales or when coupling models across scales. In order to evaluate these effects systematically, an ensemble of ten crop models was run with climate input data on different spatial aggregations ranging from 1, 10, 25, 50 and 100 km horizontal resolution for the state of North Rhine-Westphalia, Germany. Models were minimally calibrated to typical sowing and harvest dates, and crop yields observed in the region, subsequently simulating potential, water-limited and nitrogen-limited production of winter wheat and silage maize for 1982-2011. Outputs were analysed for 19 variables (yield, evapotranspiration, soil organic carbon, etc.). In this study the sensitivity of the individual models and the model ensemble in response to input data aggregation is assessed for crop yield. Results show that the mean yield of the region calculated from climate time series of 1 km horizontal resolution changes only little when using climate input data of higher aggregation levels for most models. However, yield frequency distributions change with aggregation, resembling observed data better with increasing resolution. With few exceptions, these results apply to the two crops and three production situations (potential, water-, nitrogen-limited) and across models including the model ensemble, regardless of differences among models in simulated yield levels and spatial yield patterns. Results of this study improve the confidence of using crop models at varying scales

Mise en œuvre de simulations grande échelle de stics sur la plate-forme record. Application aux projets AGMIP (Pilote C3MP) et Macsur (Scaling Pilot)

Session 1: PostersMise en œuvre de simulations grande échelle de stics sur la plate-forme record. Application aux projets AGMIP (Pilote C3MP) et Macsur (Scaling Pilot). 10. Colloque Modèle de culture STIC

Translating the Sendai Framework into action: the EU approach to ecosystem-based disaster risk reduction

© 2018 Elsevier Ltd The strong linkages between disaster risk reduction and the environment are well-acknowledged, and are magnified by the impacts of climate change on the severity and frequency of environmental disasters (landslides, floods, storm surges, forest fires, etc). Most of the time, ecosystems themselves can offer sustainable solutions for the reduction of disaster risks and the severity of their impacts, while adapting to global changes. Nature-Based Solutions, Ecosystem-based Adaptation, Green Infrastructure and Natural Water Retention Measures are examples of ecosystem-based initiatives that have been promoted by the European Commission to address a variety of policy goals. In this context, ecosystem-based approaches for Disaster Risk Reduction aim at improving the condition and resilience of ecosystems in urban, rural and wilderness areas and as such, contribute to implementing the new Sendai Framework for Disaster Risk Reduction 2015–2030, while also contributing to achieving other policy objectives - from biodiversity conservation to climate change adaptation. The European Commission has also been actively engaging the research community to better address disaster risk management knowledge and technology gaps through its Research and Innovation strategy and Framework Programmes, notably Horizon 2020. Research has shown that ecosystem-based approaches are often cost-effective and provide a wide range of co-benefits for local and regional economies, social cohesion and the broader environment. Fostering green growth through promoting risk-proofed investments and building the capacity of local, regional and national authorities and communities is a priority of the EU Action Plan for Disaster Risk Reduction, which sets the basis for a disaster-risk-informed approach to policy making at EU level.status: publishe