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Data steward, le jeu - Livret pédagogique
Get PDFData steward est un jeu sérieux qui permet de découvrir le cycle de vie des données et de comprendre l'intérêt d'un plan de gestion des données. Les joueurs ou joueuses doivent construire le cycle de vie des données et associer à chaque étape les bonnes pratiques. En parallèle, chacun.e doit contribuer au plan de gestion des données (PGD). Mais attention, des embuches viennent compliquer la tâche des "data stewards" ! Le livret pédagogique alimente les discussions autour de la gestion des données de recherche
Digital transition in agriculture and public policies. Insights from Latin America
No full textThe digital transition in Latin America's agricultural sector has developed rapidly since the COVID crisis. It has the potential to revolutionize many aspects of agriculture and food systems, such as production practices, access to and management of means of production, access to natural resources, rural extension and product marketing. The digital transition also offers the potential to revolutionize policy tools for agriculture. While this transition brings multiple benefits for meeting the challenges facing agriculture in Latin America, it also entails risks, especially in terms of widening the gap between family farmers and agribusiness. With its 13 chapters presenting studies at the regional level and at the national or territorial level in 6 Latin American countries (Argentina, Brazil, Chile, Costa Rica, Uruguay and Mexico), this book, an initiative of the PP-AL network – Public Policies and Rural Development in Latin America – provides an overview of the dynamics of the digital transition in the agricultural sector in Latin American countries, territories and chains. It analyzes the current advances and limitations of digitalization, as well as the policies related to the digital transition in various countries of the region
Rapid response to hemorrhagic fever emergence in Guinea: Community-based systems can enhance engagement and sustainability
Get PDFSince the 2013–2014 Ebola virus disease outbreak, Guinea has faced recurrent epidemics of viral hemorrhagic fevers. Although the country has learned from these epidemics by improving its disease surveillance and investigation capacities, local authorities and stakeholders, including community actors, are not sufficiently involved in the disease-emergence response. As a result, measures are not fully understood and have failed to engage local stakeholders. However, recent research has shown community-based response measures to be effective. For this study, we used a qualitative participatory research approach to (i) describe and analyze the health signals that alert local stakeholders to a problem, (ii) describe the outbreak response measures implemented in Guinée Forestière from local to national levels, and (iii) identify obstacles and levers for implementing responses adapted to the local sociocultural context. Local stakeholders receive a variety of health, environmental, and sociopolitical signals. When dealing with health signals, their next step should be to follow a flowchart developed using a top-down approach and disseminated by national stakeholders. However, our interviews revealed that local stakeholders found this official flowchart difficult to understand. To address this issue, we used a bottom-up approach to co-construct with local stakeholders a response flowchart based on their perceptions and experiences. The resulting diagram opens the door to the development of a community-based response. We then identified six main obstacle categories from the interviews, including insufficient logistical and financial resources, lack of legitimacy of community workers, and inadequate coordination. Based on these obstacles, we suggest ways to develop a response to emerging zoonotic diseases that would enable local stakeholders to better understand their roles and responsibilities and improve their commitment to the outbreak response. Ultimately, this study should help to build an integrated, community-based early warning and response system in Guinée Forestière
Nested PCR to optimize rpoB metabarcoding for low-concentration and host-associated bacterial DNA
Get PDFHousekeeping genes have proven to be effective taxonomic markers for characterizing bacterial microbiota in short-read amplicon metabarcoding studies. A region of the rpoB gene has been shown to minimize Operational Taxonomic Unit (OTU) overestimation bias with a high degree of accuracy, providing better species-level taxonomic resolution (J.-C. Ogier, S. Pagès, M. Galan, M. Barret, and S. Gaudriault, S., BMC Microbiol. 19:171, https://doi.org/10.1186/s12866-019-1546-z). However, the primers for rpoB are highly degenerate, leading to potential problems in the amplification of bacterial DNA present at low concentration in the sample or embedded within eukaryotic matrices, as for the host-associated microbiota. We addressed these limitations by using a two-step PCR approach to optimize the rpoB procedure. The first PCR amplifies a region of the rpoB gene with the outer primers, and the second PCR then uses primers incorporating Illumina adapters, the inner primers, to amplify the taxonomic marker for metabarcoding. We first used in silico approaches to evaluate the universality of the outer and inner rpoB primers. We then tested the nested rpoB PCR method on commercial mock samples. The nested PCR approach increased amplification efficiency for dilute samples without biasing the bacterial composition of the mock sample revealed by metabarcoding relative to single-step PCR. We also tested the nested rpoB PCR method on field-collected samples of insects. The nested PCR outperformed single-step PCR, increasing amplification efficiency for bacterial DNA present at low concentrations (insect oral secretions) or embedded in eukaryotic DNA matrices (insect larvae). This method provides a promising new strategy for characterizing host-associated microbiota
Remote sensing and field data show complementary functions when predicting forage productivity in heterogeneous native forests
Get PDFNative forests around the world are widely used for livestock grazing as they offer different sources of forage. Nevertheless, in heterogeneous forested landscapes, forage productivity drivers are still unclear, hindering precise predictions of field receptivity. Our aim is to relate landscape variables with forage productivity in forested landscapes using satellite and ground-based data. To accomplish this, we harvested 36 enclosures in two Patagonian valleys during a three-year period. The location of the enclosures encompassed a gradient of altitude and mean annual rainfall, across three vegetation types commonly used for cattle raising. We estimated five generalized linear models to predict forage productivity using different remote sensing and ground (field) data as predictors. The most important variables for predicting forage productivity were five of remote sensing type and two of field type. The highest goodness of fit was obtained when all variables were included (D2 = 0.71). When ground-based information was combined with remote sensing data, the goodness of fit was higher (D2 = 0.65) compared with models that only used remote data as predictors (D2 = 0.49). Models obtained based on remote data serve to support situations where field information is not available. High forage productivity levels can be obtained in high forests or scrubs with varying values of canopy openness, without removing the forest. The models generated in this work improve livestock stocking rates adjustment in NW Patagonia forests, and may be also re-estimated with new data in other regions used for cattle raising worldwide, contributing to the sustainable use of native forests
From external shocks to internal propagation within agri-food systems: A socio-metabolic perspective of the animal sector on an isolated tropical island
No full textInsular agri-food systems face significant challenges due to their exposure to external shocks via trade dependencies, geographic isolation, and constrained land and natural resources. This study proposes a novel socio-metabolic analytical framework and applies it to investigate how external shocks propagate within the animal product supply systems (APSS) of La Reunion Island, a French overseas department. By conceptualizing APSS as a metabolic network, we analyze characteristics that influence three vulnerability factors: exposure, sensitivity, and incapacity to cope. To analyze shock propagation dynamics, this paper introduces the distinction between cascading and domino effects: cascading effects trace the sectors and stages impacted, while domino effects highlight how the nature of disruptions evolves as they spread. Using a mixed-methods approach, we map flow dynamics and identify critical interaction nodes susceptible to convey shock propagation clusters. Drawing on stakeholder insights, our empirical findings from disruptions during the COVID-19 pandemic, the Russo-Ukrainian war, and other events reveal the interplay of different cascading and domino effects influencing the availability, accessibility and stability of animal-based products. Our findings underscore a paradox: while import-dependent local APSS are highly exposed and present vulnerabilities to external shocks, they also buffer impacts on the food supply by ensuring some degree of autonomy. The results offer insights into the systemic vulnerabilities of insular agri-food systems and provide a framework for analyzing shock propagation in complex food supply networks
