Published online by Cambridge University Press: 17 November 2017
In response to the current needs of humanity with regard to food production, environmental disasters and climate change, it is important to define (livestock) production systems and management practices that are both productive and ecologically sustainable. We qualitatively assessed advanced silvopastoral experiences in five ecologically and culturally distinct regions in Chiapas, Mexico, given their ability to provide key services: internal (productivity and productive resiliency) and external (climate change mitigation and biodiversity conservation). We propose 20 indicators that reflect management, resources, use of external inputs, availability of food, commercial products and animal feed and trees in grazing and forest areas. Sets of some indicators form criteria for dependence on external inputs, productive diversification with emphasis on food security, soil conservation, tree cover and landscape connectivity, among others. Indicators and thresholds were adjusted to critical (traffic light) levels, based on field data. Comparing the levels reached by the studied experiences, we found that most of the resulting services go hand in hand; so ‘win–win’ situations are possible to be achieved. The elements and practices that affect both internal and external services were explored. The red light critical points in each production unit were identified so that they could be attended. Experiences that presented higher levels in assessment criteria could serve as examples to enable the improvement of livestock systems under similar conditions. We propose this assessment as a tool for rapid intervention that can be widely applied to livestock systems, from conventional to organic or diversified, because of the criteria used. However, it can be more flexible, as new criteria can be added and thresholds can be adjusted for other types of production systems, always reflecting local and desired conditions. The proposed indicators can be also used as a basis for a quantitative agroecosystem assessment.