Articles

Supporting the agroecological transition of mountain dairy systems: which evaluation tools account for on-farm diversity?

Abstract

In the frame of an agroecological transition of livestock systems, an evaluation of their diversity and multiperformance is needed. Here, we develop the case of mountain dairy systems. Five multicriteria evaluation tools are described, which are more or less specific for these systems. We analyse their ability to characterize system diversity and the ecological processes on which farm operation is based, along with the ecosystem services they provide. Several types of evaluation are described, from a global diagnosis (DIAG and BOT) to deeper analysis of specific aspects, such as environmental impact (CAP), durability of Cantal AOP farms (LAU) and diagnosis of the forage system (DIAM). Even though they share the common objective of evaluating farm multiperformance and sustainability, these five tools are different in their structure and investigation type. Overall, tools specifically developed for mountain dairy systems lead to a good evaluation of grassland management and diversity. However, they do not consider other aspects, such as animal health and the implication of farmer in the agroecological transition, which are only taken into account by less specific tools. Eventually, the more general tools seem more likely to sustain an agroecological transition and identify sustainable practices. All tools lack the ability to identify and assess animal diversity (intra-herd variability and mixed farming), which should be improved in forthcoming evaluation tools.

Authors


Madeline KOCZURA

madeline.koczura@inrae.fr

Affiliation : Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France

Country : France


Bertrand DUMONT

Affiliation : Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France

Country : France

Attachments

No supporting information for this article

##plugins.generic.statArticle.title##

Views: 2525