Methodological Guide to Co-design Climate-smart Options with Family Farmers

Climate-smart agriculture (CSA) seeks to improve productivity for the achievement of food security (pillar 1: Productivity), to develop a better ability to adapt (pillar 2: Adaptation), and to limit greenhouse gas emissions (pillar 3: Mitigation). Technical and organizational innovations are needed to find synergies among those three pillars. Innovation (its creation and its operation) is a social phenomenon. Many studies worldwide have shown that promoting a sustainable change and innovation within organizations has to be analyzed and implemented with stakeholders. Thus, the ability of local actors to tackle climate change and mitigate its effects will depend on their ability to innovate and mobilize material and non-material resources, to articulate links among national policies, not only between themselves, but also undertaking actions at the local level. To support stakeholders in the development of responses to this challenge, we propose the development of open innovation platforms, in which all local actors may participate. These platforms are virtual, physical, or physico-virtual spaces to learn, jointly conceive, and transform different situations; they are generated by individuals with different origins, different backgrounds and interests (Pali and Swaans, 2013).The purpose of this manual is to provide a seven-step methodology to allow family farmers to co-build and adopt CSA options to tackle climate change in an open innovation platfor

Functionalization of synthetic talc-like phyllosilicates by alkoxyorganosilane grafting

A range of talc-like phyllosilicates were prepared via a hydrothermal synthesis performed at five different temperatures from 160 to 350 °C. The organization of the lattice and the degree of crystallinity of the new materials were evaluated by different techniques such as XRD, FTIR, solid-state 29Si NMR, TEM, FEG-SEM and TG-DTA. When synthesized at low temperature the material presents high degree of hydration, low crystallinity and flawed structure. This was attributed to stevensite-talc interstratified product present in the samples. The stevensite/talc ratio and the hydration decrease in the talc-like phyllosilicate samples when the hydrothermal synthesis temperature increases and so the crystallinity becomes higher. A thermal treatment at 500 °C allowed a significant flaw reduction in talc-like phyllosilicate structure; the synthesized sample at 350 °C and heat treated presents a structure close to that of talc. The different talc-like phyllosilicates were grafted covalently by two organoalkoxysilane reagents, N-(3-triethoxysilylpropyl)-4,5-dihydroimidazole (IM2H) and 2-hydroxy-4-(3-triethoxysilylpropoxy)-diphenylketone (HTDK). The grafted amounts of the hybrids, determined by elemental analysis and confirmed by thermogravimetric data, are dependent on the hydrothermal synthesis temperature and organoalkoxysilanes; they become smaller when the synthesis temperature increases and when HTDK is used. FTIR and solid-state 13C CP MAS NMR were applied to characterize the grafted organic groups. So, in this work it is shown that by choosing the hydrothermal synthesis temperature or by performing an additional annealing it is possible to adjust the amount of defects in the structure of talc-like phyllosilicates which seems to be strongly correlated to the grafting performance

The EGIM, modular though generic addresses the requirements of the EMSO platforms

The EGIM (EMSO Generic Instrument Module ) is designed to consistently and continuously measure parameters of interest for most major science areas covered by EMSO. This research infrastructure provides accurate records on marine environmental changes from distributed regional nodes around Europe. The system can deliver data that can support the Global Ocean Observing System –Essential Ocean Variables concept, as well as the Marine Strategy Framework Directive towards evaluating environmentalstatus. The EGIM is flexible for adaptation according to site and disciplinespecific requirements. Inter - operability and capacity of future evolution of the system are key aspects of the modularity. The EGIM is able to operate on any EMSO node type: mooring line, sea bed station, cabled or non - cabled and surface buoy to monitor environmental parameters over a wide depth range. Operating modes, power requirements, mechanical design can adapt to the various EMSO node configurations. In addition to sensors already included in the EGIM prototype (temperature, conductivity, pressure, dissolved Oxygen, Turbidity, currents and passive acoustics) the EGIMcan host up to five additional sensors such as chl -a, pCO 2, pH, seismic and photographic/video images ornew sensors. The EGIM provides all the sensor hosting services required ,for instance power distribution, positioning , and protection against bio -fouling . Within EMSO , the EGIM aimsto have a number of ocean locations where the same set of core variables are measured homogeneously: using the same hardware, same sensor references, same qualification methods, same calibration methods, same data format and access and the same maintenance procedures. It’s compact and modular nature allows for flexible deploymentscenarios that include being able to accommodate new instruments such for Essential Ocean Variables and other needs as theirtechnology readiness levels improve.Peer ReviewedPostprint (published version

Capture of Xe and Ar atoms by quantized vortices in4He nanodroplets

We present a computational study, based on time-dependent Density Functional theory, of the real-time interaction and trapping of Ar and Xe atoms in superfluid4He nanodroplets either pure or hosting quantized vortex lines

SPECTRAL CLUSTERING BASED PARCELLATION OF FETAL BRAIN MRI

Many neuroimaging studies are based on the idea that there are distinct brain regions that are functionally or micro-anatomically homogeneous. Obtaining such regions in an au-tomatic way is a challenging task for fetal data due to the lack of strong and consistent anatomical features at the early stages of brain development. In this paper we propose the use of an automatic approach for parcellating fetal cerebral hemi-spheric surfaces into K regions via spectral clustering. Unlike previous methods, our technique has the crucial advantage of only relying on intrinsic geometrical properties of the corti-cal surface and thus being unsupervised. Results on a data-set of fetal brain MRI acquired in utero demonstrated a convinc-ing parcellation reproducibility of the cortical surfaces across fetuses with varying gestational ages and folding magnitude

Effect of mixed-phase cloud on the chemical budget of trace gases: A modeling approach

International audienceA multiphase cloud chemistry model coupling a detailed chemical reactivity mechanism in gas phase and aqueous phase to a cloud parcel model with a two-moment microphysical scheme has been extended to include ice phase processes. This newly developed model is used to study the influence of the ice phase on HCOOH, HNO3, H2O2 and CH2O in a mixed-phase cloud. Microphysical processes are describing the interactions between the water vapor phase, the liquid phase (cloud and rain water) and the ice phase (pristine ice, snow and graupel) in the cloud and for soluble chemical species, their transfer by mixed-phase microphysical processes has been included. In addition to microphysical transfer between iced hydrometeors, the probable two main processes incorporating soluble chemical species in iced hydrometeors are the retention in ice phase as riming or freezing occurs and the burial in the ice crystal as the crystal grows by vapor diffusion. The model is applied to a cloud event describing a moderate precipitating mixed-phase cloud forming in a continental air mass in winter. The main features of the cloud are described and the evolution of key chemical species as function of time and temperature is discussed. Sensitivity tests are performed: a run without ice to highlight the influence of ice phase on the chemical gas phase composition of the cloud, a run without burial showing that it is a negligible process, a run assuming full retention in ice for all species and a run varying the ice crystal shapes. A detailed analysis of the microphysical rates and chemical rates linked to retention and burial effects show that for this cloud event, the effect of the ice phase on gas phase composition is driven by riming of cloud droplets onto graupels, which leads to retention or not of soluble chemical species in the ice phase. Finally, the impact of crystal geometry on the efficiency of collection is studied together with its impact on the riming of cloud droplets on graupels and also on the retention of chemical species in ice phase

Co-designing climate-smart farming systems with local stakeholders: A methodological framework for achieving large-scale change

The literature is increasing on how to prioritize climate-smart options with stakeholders but relatively few examples exist on how to co-design climate-smart farming systems with them, in particular with smallholder farmers. This article presents a methodological framework to co-design climate-smart farming systems with local stakeholders (farmers, scientists, NGOs) so that large-scale change can be achieved. This framework is based on the lessons learned during a research project conducted in Honduras and Colombia from 2015 to 2017. Seven phases are suggested to engage a process of co-conception of climate-smart farming systems that might enable implementation at scale: (1) “exploration of the initial situation,” which identifies local stakeholders potentially interested in being involved in the process, existing farming systems, and specific constraints to the implementation of climate-smart agriculture (CSA); (2) “co-definition of an innovation platform,” which defines the structure and the rules of functioning for a platform favoring the involvement of local stakeholders in the process; (3) “shared diagnosis,” which defines the main challenges to be solved by the innovation platform; (4) “identification and ex ante assessment of new farming systems,” which assess the potential performances of solutions prioritized by the members of the innovation platform under CSA pillars; (5) “experimentation,” which tests the prioritized solutions on-farm; (6) “assessment of the co-design process of climate-smart farming systems,” which validates the ability of the process to reach its initial objectives, particularly in terms of new farming systems but also in terms of capacity building; and (7) “definition of strategies for scaling up/out,” which addresses the scaling of the co-design process. For each phase, specific tools or methodologies are used: focus groups, social network analysis, theory of change, life-cycle assessment, and on-farm experiments. Each phase is illustrated with results obtained in Colombia or Honduras

A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers

Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared three different approaches in order to better understand assessments of aquatic macroinvertebrate diversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species richness model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species richness model, that is, a generalized linear model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the kicknet and eDNA approaches, particularly at a local scale. We found the EPT-specific primer set fwhF2/EPTDr2n, detected a greater number of targeted EPT species compared to the more general primer set mlCOIintF/HCO2198. Moreover, we found that the species richness measured by eDNA from either primer set was poorly correlated to the richness measured by kicknet sampling (Pearson correlation = 0.27) and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the species richness model (Pearson correlation = 0.30 and 0.44, respectively). The weak relationships between the traditional kicknet sampling and eDNA with this model indicates inherent limitations in upscaling species richness estimates, and possibly a limited ability of the model to meet real world expectations. It is also possible that the number of replicates was not sufficient to detect ambiguous correlations. Future challenges include improving the accuracy and sensitivity of each approach individually, yet also acknowledging their respective limitations, in order to best meet stakeholder demands and address the biodiversity crisis we are facing