Transdisciplinary research for systemic change: who to learn with, what to learn about and how to learn

摘要: A key aim of transdisciplinary research is for actors from science, policy and practice to co-evolve their understanding a social–ecological issue, reconcile diverse perspectives co-produce appropriate knowledge serve common purpose. With its concurrent grounding in represents significant departure conventional research. We focus on mutual learning within highlight three aspects that could guide other researchers designing facilitating such learning. These are: “who learn with”, “what about” “how learn”. For each these questions, we present heuristics are supported by comparative analysis two case studies addressed contemporary conservation issues South Africa but varied scale duration. were five-year national-scale project focusing the prioritisation freshwater ecosystems three-year local-scale used ecological infrastructure as theme advancing sustainability dialogues. Regarding proposed heuristics, with” dependent needs be informed relevant disciplines sectors with establishing network representing empirical, pragmatic, normative purposive functions. This emergent should enriched involving experts, novices bridging agents, where possible. It important networks about respective histories, system processes drivers, values exist interest. Moreover, together concepts can help develop shared vocabulary, which turn contribute understanding, vision an agreed way responding it. New ways group promoted enhanced co-developing outputs (boundary objects) application across domains creating spaces (third places) facilitate exchange co-production. conclude five generic lessons enhance success: (a) duration, timing continuation potential influences prospects achieving systemic sustainable change; (b) especially if embedded implementing agency, play critical role outcomes; (c) need participate co-learners rather than masters domains; (d) purposeful mixed-paradigm designs mend fragmentation science; (e) must vigilant pitfalls initiatives, namely biases participant self-selection, perceived superiority scientific attraction simple solutions wicked problems retain status quo.