The domestic yak, a type of cattle native to the Himalayan region and Siberia, is known for its ability to withstand harsh climatic conditions at high altitudes and is primarily domesticated for its milk, wool, and meat. Most of the research on yaks has been conducted in China, where approximately 94% of the total estimated yak population can be found. In this study, the authors conducted an ethology study on the social behaviour of yaks in the Annapurna Valley of Nepal, where they are raised for their milk, wool, and meat and are also used for transportation. The authors used ethnographic inquiries to gather data on the social behaviour of yaks and the coping strategies used by herders to manage them. They also equipped cattle with one Actigraph wgt3x-BT to measure activity using an accelerometer and spatial associations using a proximity recorder. They found that yaks in both herds exhibited cohesive and synchronized behaviour, with similar activity patterns during the day and a peak of activity at night. They also observed that yaks in the first herd were more reactive to the presence of humans, while those in the second herd were more reactive to the presence of other yaks. The authors suggest that these differences in behaviour may be due to the different herding management practices used in each herd.

L’analyse de la répartition spatiale des plantes cultivées est souvent a-chronique : elle repose sur des inventaires datés et analysés en fonction de facteurs contemporains de l’époque d’observation. Des comparaisons entre deux dates donnent une idée de l’évolution de cette répartition, mais les corpus de données permettant une analyse diachronique de ce genre sont rares. L’histoire pourtant permet de comprendre la distribution des plantes cultivées dans l’espace : leur ancienneté locale, les...

La répartition spatiale des plantes cultivées répond à des facteurs multiples qui différent selon qu’on considère les niveaux de la combinaison des espèces, du cortège variétal ou de la structuration génétique. Les espèces domestiquées sont tout à la fois des objets biologiques façonnés par les contraintes de l’environnement ; elles sont aussi l’objet de nombreuses manipulations humaines qui influencent leur évolution. Les semences peuvent être sélectionnées au champ ou dans les greniers par les paysans qui les cultivent, échangées dans le cadre de réseaux non monétaires et chargées de valeur culturelle, mais elles sont aussi, et depuis longtemps sans doute, transférées de manière marchande dans le cadre de systèmes commerciaux à longue distance. Elles sont enfin transformées et transférées dans le cadre de programmes internationaux d’amélioration et de développement ou de programmes de diffusion mis en place par des compagnies multinationales. Tous ces phénomènes ont, à des degrés divers, une influence sur la biologie autant que sur les dynamiques sociales et spatiales qui affectent la répartition des plantes cultivées et des ressources génétiques. L’étude de cette dynamique doit à l’évidence être conduite de façon multi-scalaire et en croisant les approches de différentes disciplines de l’ethnologie, de la génétique… et de la géographie.

Trois hypothèses principales peuvent être posées pour expliquer les facteurs qui organisent dans l’espace la diversité des plantes cultivées. Elles sous-tendent les textes présentés dans ce premier volume. La biologie de la plante commande sa répartition selon un gradient physique et climatique. Cette première hypothèse se révèle assez efficace lorsqu’elle porte sur de grandes étendues avec une précision grossière : ainsi, on définit aisément l’aire de distribution de la culture du sorgho ent...

This paper presents an agent-based spatial simulation of shifting cultivation applied to savannah landscape in North-Cameroon (Duupa ethnic community). The model is based on empirical rules and was developed by a team who seek to create interdisciplinary dynamics by combining domain specific approaches to the same subject. The manner in which the model is described in this paper reflects the interdisciplinary processes that guided its development. It is made up of four domain-specific modules - demography, agriculture, savannah regrowth and social rules - which converge to form a fifth one, i.e., the evolution of the mosaic of cultivated fields. The focus is on how the spatial organization of landscapes results of environmental and social interactions. Two scenarios are presented in this paper. The first simulates the transformation of savannah woodland into a shifting cultivation savannah landscape. The second simulates changes in the landscape and socio-demographic structure of a Duupa village over a 60-year period. The simulation results are used to identify some of the key aspects of the socio-environmental interactions and help to explain why at large spatial scales and over a long period of time, the composition and structure of a landscape appear rather stable. For instance, it is well known that demography plays a key role in both social and environmental dynamics of shifting cultivation systems. Yet, in the case of the Duupa system, we show that social resilience can be acquired through interactions between demographic cycles of rising and falling population levels and a socioeconomic redistribution system. Finally, we compare the model developed with other shifting cultivation models and provide some insights on future developments

The circulation of seed among farmers is central to agrobiodiversity conservation and dynamics. Agrobiodiversity, the diversity of agricultural systems from genes to varieties and crop species, from farming methods to landscape composition, is part of humanity’s cultural heritage. Whereas agrobiodiver-sity conservation has received much attention from researchers and policymakers over the last decades, the methods available to study the role of seed exchange networks in preserving crop biodiversity have only recently begun to be considered. In this overview,we present key concepts,methods, and challenges to better understand seed exchange networks so as to improve the chances that traditional crop varieties (landraces) will be pre- served and used sustainably around the world. The available literature suggests that there is insufficient knowledge about the social, cultural, and methodological dimensions of environmental change, including how seed exchange networks will cope with changes in climates, socio-economic factors, and family structures that have supported seed exchange systems to date. Methods available to study the role of seed exchange networks in the preservation and adaptation of crop specific and genetic diversity range from meta-analysis to modelling, from participatory approaches to the development of bio-indicators, from genetic to biogeographical studies, from anthropological and ethnographic research to the use of network theory. We advocate a diversity of approaches, so as to foster the creation of robust and policy-relevant knowledge. Open challenges in the study of the role of seed exchange networks in biodiversity conservation include the development of methods to (i) enhance farmers’ participation to decision-making in agroecosystems, (ii) integrate ex situ and in situ approaches, (iii) achieve interdisciplinary research collaboration between social and natural scientists, and (iv) use network analysis as a conceptual framework to bridge boundaries among researchers, farmers and policy makers, as well as other stakeholders.

In this chapter, we develop new indicators and statistical tests to characterize patterns of crop diversity at local scales to better understand interactions between ecological and socio-cultural functions of agroecosystems. Farms, where a large number of crops (species or landraces) is grown, are known to contribute a large part of the locally available diversity of both rare and common crops but the role of farms with low diversity remains little understood: do they grow only common varieties—following a nestedness pattern typical of mutualistic networks in ecology—or do ‘crop–poor’ farmers also grow rare varieties? This question is pivotal in ongoing efforts to assess the local-scale contribution of small farms to global agrobiodiversity. We develop new network-based approaches to characterize the distribution of local crop diversity (species and infra-species) at the village level and to validate these approaches using meta-datasets from 10 countries. Our results highlight the sources of heterogeneity in crop diversity at the village level. We often identify two or more groups of farms based on their different levels of diversity. In some datasets, ‘crop–poor’ farms significantly contribute to the local crop diversity. Generally, we find that the distribution of crop diversity is more heterogeneous at the species than at the infra-species level. This analysis reveals the absence of a general pattern of crop diversity distribution, suggesting strong dependence on local agro-ecological and socio-cultural contexts. These different patterns of crop diversity distribution reflect an heterogeneity in farmers’ self-organized action in cultivating and maintaining local crop diversity, which ensures the adaptability of agroecosystems to global change.

capitolul 6. Traducere de Margareta Gyurcsik

chapitre 6 d'un ouvrage d'introduction à l'ethnologie

L'agrobiodiversité désigne l'ensemble des composantes de la diversité biologique liées à l'alimentation, à l'agriculture et au fonctionnement des écosystèmes agricoles. Elle rassemble les plantes et les animaux domestiqués, mais aussi tous les parents sauvages, les prédateurs et les organismes vivants aidant à la production agricole (auxiliaires de cultures), et les espèces fourragères et autres plantes non semées dans les champs (adventices) avec qui ils interagissent. Comme pour le concept de biodiversité dont il est dérivé, l'agrobiodiversité se décline à plusieurs niveaux (gènes, variétés ou races, espèces et agroécosystèmes) et englobe la diversité des végétaux et des animaux ainsi que, selon les définitions, les savoirs et pratiques associés, au travers notamment des processus de sélection.