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Dynamique de la filière du lait de chamelle au Niger : opportunités et défis pour un développement durable
Get PDFCette étude explore la dynamique en pleine mutation de la filière du lait de chamelle dans le bassin d'approvisionnement de la ville de Tahoua. Un total de 137 acteurs clés dont 88 éleveurs, 28 collecteurs du lait et 21 points de vente ont été enquêtés. Entre 2011 et 2024, le nombre de collecteurs est passé de 1 à 56 et celui des points de vente de 1 à 32 au cours de la même période, traduisant une structuration progressive de la filière. Cette évolution a contribué à faire passer les volumes journaliers de lait livrés à la ville de 85 litres à 793 litres. Pourtant, cette croissance de l'offre reste en deçà d'une demande urbaine toujours croissante, sans incidence sur le prix de vente au consommateur, resté fixe à 1000 FCFA/litre (1,5 Euros) depuis 2013. La fluctuation des prix est observée prin- cipalement entre les producteurs et les collecteurs. La chaîne repose largement sur des contrats oraux et des relations de confiance ancrées dans les liens familiaux et ethniques. Face aux multiples contraintes techniques, organisationnelles et logistiques, les acteurs déploient des stratégies d'adaptation qui assurent une certaine résilience du système et permettent de maintenir l'approvisionnement de la ville en lait de chamelle
Utiliser la SPIR sur des échantillons d'herbiers pour l'identification taxonomique ?
Get PDFLes collections d'herbiers constituent des sources inestimables de matériel et de données sur la biodiversité végétale. Mais ce matériel à la fois scientifique et patrimonial reste fragile. La SPIR est une méthode déjà largement employée pour effectuer des mesures rapides et non destructives sur des échantillons végétaux. Cet outil semble donc particulièrement adapté pour obtenir de nouveaux types de données à partir d'échantillons d'herbiers. Les applications de la SPIR sur les herbiers sont encore récentes et exploratoires. La spectrométrie peut apporter des éléments intéressants sur différents aspects : chimie, écologie, physiologie, taxonomie, etc. L'une des possibilités qui semble particulièrement intéressante est de distinguer des espèces voisines sur le plan taxonomique. Pour évaluer le potentiel de la SPIR dans cette perspective, nous avons mené deux projets parallèles sur des taxons très différents. Le premier se concentre sur le genre Pistacia et plus particulièrement sur cinq espèces méditerranéennes (P. lentiscus, P. terebinthus, P. vera, P. atlantica, P. saportae). C'est un modèle d'étude intéressant pour travailler sur des espèces proches qui peuvent même s'hybrider. Facile à trouver et à identifier à partir des feuilles, il nous a permis de travailler à la fois sur un grand nombre d'herbiers anciens et sur des collectes récentes réalisées pour notre étude. Les premiers résultats montrent de très bonnes performances en matière de prédictions, à tel point que certaines erreurs d'identification sur des herbiers historiques ont pu être détectées. Les 4 principales espèces de Pistacia sont discriminée avec un taux de réussite de 98%. Entre les 2 espèces les plus proches et leur hybride, la discrimination est aussi très bonne et les erreurs sont toujours entre l'hybride et une espèce. Enfin la prédiction sur les nouveaux échantillons à partir d'une calibration faites sur les herbiers historiques donne un taux de succès de 87%
Young apple tree development under agroforestry radiative conditions: A multi-scale morphological and architectural dataset
Get PDFAgroforestry is a major adaptation and mitigation strategy facing climate warming, but its agronomic viability depends on actual plant responses to shade conditions. Growing fruit trees under dominant trees may reduce the risks related to extreme climatic events, such as frost or heat waves. Nonetheless, except for some sciaphilous plants, such as coffee or cacao, their physiological and architectural responses to agroforestry conditions are little known, especially in temperate climate. We present a dataset describing the architecture and morphology of 45 young apple trees, acquired in two consecutive years, along a radiative gradient, as in three growing conditions of an agroforestry plot: (i) the open field, (ii) between, and (iii) along rows of dominant walnut trees. The data are stored as standard multi-scale tree graphs that allow to store the topology, geometry, and attributes of the plant at different scales. It includes plant traits at three topological scales: whole tree, growth unit, and the internode. The traits include organ fate (latent, vegetative, floral bud, and bud extinction sites); length and an estimate of the leaf area of growth units; diameter, zenith, and azimuth angles of second-order branches. The number of leaves, flowers, fruits, and fruit drops is also counted on a sample of 10, possibly apical, flower buds per tree. The dataset includes ancillary measurements on sampled shoots, used to derive allometric relationships between shoot length and leaf area; and an estimate of the radiation reaching each apple tree during the vegetative season. The multi-scale description and the different light growing conditions characterizing the digitized trees allow to investigate relationships between the shade-related agroforestry environment and the apple tree morphological and architectural plasticity, during the early tree development, from the internode to the whole tree
Recovery of tree species functional composition in eucalypt plantations with natural regeneration differs among canopy strata
No full textTree monocultures have been promoted globally to supply timber; yet, a high diversity of native trees can establish in less intensively managed plantations, allowing to both harvest timber and transition towards a more natural forest. However, little is known about the functional recovery of native trees under plantations, which is critical for biodiversity conservation and ecosystem services. Here, we evaluate how functional composition of tree strata differs between two restoration methods (eucalypt plantations with natural regeneration and naturally regenerating forests) and how this is affected by stand age, climatic water deficit, and soil characteristics. We established 129 plots in two restoration methods and mature forest as reference, in São Paulo state, Brazil. We divided tree stratum in each plot into different canopy strata using perfect plasticity approximation. We measured five key traits that are important for fire resistance (bark thickness), drought tolerance (wood density), productivity (specific leaf area and leaf thickness), and nutrient cycling (nitrogen-fixing ability) for 393 species and calculated for each stratum community-weighted mean trait values. Community traits were mostly affected by canopy strata, the interaction between canopy strata and restoration method, and water availability. Eucalypt trees dominated the upper strata of plantations, presenting higher wood density, tougher leaves, and thicker bark, reflecting the drought and fire adaptation of eucalypts. The lower strata of eucalypt plantations and naturally regenerating forests had similar functional composition. Our results suggest that eucalypt plantations can be used as a tool to facilitate natural regeneration and restore ecosystem functioning in degraded areas
Adapting a global plant identification model to detect invasive alien plant species in high-resolution road side images
Get PDFEarly detection of invasive alien plant species is crucial for addressing their environmental impact. Recent advancements in vehicle-mounted equipment enable automatic analysis of high-resolution images to detect invasive plants along roadsides, a primary vector for their spread. Deep learning technologies show promise for processing this data efficiently, but the choice of approach significantly affects both computational and human resource costs. Object detection and segmentation methods require costly annotations, making them impractical for scaling to the thousands of invasive species worldwide. In contrast, multi-label classification, i.e. to predict all species present in the image, is less demanding but still challenging to implement without many annotated images for numerous species. However, large datasets from citizen science platforms such as Pl@ntNet or iNaturalist offer rich visual data for classifying individual plant species. In this article, we assess whether large plant identification models trained on such data can be leveraged for species detection in high-resolution images. Specifically, we explore two approaches: a multi-label classification model and a tiling-based model, using a vision transformer from the Pl@ntNet platform. We evaluate these models on high-resolution roadside images, both using a pre-trained model without fine-tuning and after applying fine-tuning. Our findings indicate that the tiling approach significantly outperforms other methods without fine-tuning and shows a slight advantage when fine-tuning is applied, demonstrating significant potential for detecting thousands of species without task-specific adaptation
Introduction - A worldwide perspective of geographical indications in a time of changes:crossed views between researchers, policy makers and practitioners
Get PDFGeographical indications (GIs) are signs used to designate products having a specific geographical origin and possessing qualities or a reputation that are due to that origin. Actually, the world's food and artisanal heritage encompasses a multitude of products linked to their origin that rely on the knowledge, skills, practices and traditions developed collectively by local producers over time and transmitted across generations. GIs are an intellectual property right granting exclusive right to use the name that can particularly benefit local producers, and particularly smallholders, and be therefore a tool to preserve and promote origin
Analyse in itinere des conditions de mise en place d'une IG : Le cas du Gassirè-Wagashi au Bénin
No full textOil palm smallholder's management practices and yield: A case study in Krabi, Southern Thailand
Get PDFIn recent years, Southern Thailand has witnessed an increase in surface planted with oil palm, driven primarily by smallholders who contribute over 90% of Thailand's oil palm output. Despite their significant contribution, oil palm smallholders have consistently achieved lower yields compared to agro-industries, and limited research has been conducted to understand the limiting factors, such as management practices. Structured interviews were conducted to gather information about management practices and estimate the fresh fruit bunch yield in a network of 18 plantations in Krabi province, Thailand. A clustering approach, combining principal component analysis and hierarchical cluster analysis, was used to characterise the diversity of smallholder management practices. Four clusters of management practices were highlighted, characterised by varying intensities of fertiliser application (nitrogen, phosphorus, and potassium), mechanical versus chemical weeding, and harvest intervals. Notably, the farmers in our study applied less fertiliser, on average, than the recommendations of Thai Good Agricultural Practices. A significant portion of plots in the area (12 out of 18 plots) achieved good yields compared to attainable yields. A clear relationship between management practices and yield could however not be established. The large diversity of oil palm smallholders' management practices and their performances highlighted in this study need to be better taken into account and understood in order to improve sustainability and foster certification schemes such as Roundtable on Sustainable Palm Oil (RSPO)
Host-feeding preferences of Culex pipiens and its potential significance for flavivirus transmission in the Camargue, France
Get PDFThe spread of the West Nile (WNV) and Usutu (USUV) flaviviruses in Europe in recent decades highlights the urgent need to understand the transmission networks of these pathogens as a basis for effective decision-making. These viruses are part of a complex disease cycle that involves birds as principal hosts and humans and horses as dead-end hosts. Our study aims to uncover the intricate relationships between the main mosquito vector of these viruses, Culex pipiens L. (Diptera: Culicidae) and its feeding preferences based on the forage ratio among several host species, primarily birds in a land-use gradient. We estimated the bird host potential to act as a host for flavivirus, the reservoir capacity index, based on forage ratios and potential host competence based on molecular prevalence. We sampled mosquitoes and, at the same time, conducted bird censuses in the Camargue region in southern France, where co-circulation of these viruses has been reported. Several localities were sampled along a land-use gradient in peri-urban, agricultural and natural areas from May to November 2021. We identified 55 vertebrate species in 110 engorged Cx. pipiens by PCR amplification and sequencing of mitochondrial 12S and 16S Ribosomal DNA genes. Culex pipiens feeds primarily on 51 bird species and secondarily on two mammals, one amphibian and one reptile. Based on forage ratios, we found a preference of Cx. pipiens in the Camargue for the order Passeriformes and, more specifically, for Columba livia domestica L. (Columbiformes: Columbidae) in agricultural areas, and for Passer domesticus/montanus L. (Passeriformes: Passeridae), in agricultural and peri-urban areas. The natural habitats had significantly higher forage ratio values than agricultural and peri-urban areas. We suggest that certain key species, such as Passer sp., Columba livia and Turdus sp., might be potentially considered locally relevant hosts for transmission in this area, as they are important for mosquito feeding and also potentially important hosts for flavivirus amplification. These data will be beneficial in understanding host–vector interactions and the relationships between bird communities, mosquito feeding preferences and emerging mosquito-borne diseases