Certifying the sustainability of herding practices in Mongolia

Abstract

Certification schemes for agriculture aim to incentivize sustainable land management. To be credible, they need robust metrics to assess the practices of producers. We demonstrate an approach for evaluating practice, which is repeatable and explicitly representative of stakeholders. We apply it to nomadic pastoralism in Mongolia, where livestock overgrazing is of concern. Our approach uses judgements from stakeholders about the sustainability of hypothetical but realistic herding scenarios. From these, we create models to predict sustainability scores. These can be applied as tools to assess the actual practices of herders. We use two judgement datasets: one representing producers’ judgements, another a subset that also conforms to the environmental expectations of the certifier. The differences must be negotiated when we choose evaluation methods. The approach could be used for any production system, provided variables are devised that summarize practice and appropriate stakeholders are available to judge the sustainability of different practices. Credible sustainability certifications require robust evaluation to ensure trustworthiness; however, judgements of sustainable practices may differ between the practitioners and the certifiers. Stakeholder engagement can help bridge this gap to provide robust certification evaluation.