Séminaire des doctorants

The bio-based economy, 2030 Agenda, and strong sustainability – A regional-scale assessment of sustainability goal interactions

Co-auteurs : Salim Belyazid, Ingrid Stjernquist, Arnaud Diemer, Samaneh Seifollahi-Aghmiuni et Zahra Kalantari

Discutants : Jean-Denis Mathias, Manuel E. Morales

Résumé

Policy-makers face the challenge of assessing and implementing sustainability measures, while also dealing with parallel and sometimes conflicting policy agendas, long-term policy impacts, and contested interpretations of sustainability. To support evidence-based decision-making in this context, this paper presents the results from an integrated assessment of sustainability goal interactions. Links between the bio-based economy, the 2030 Agenda, and the so-called strong sustainability paradigm were explored in a regional-scale case. The analysis focused primarily on developments in the forestry and energy sectors. Direct trade-offs and synergies as well as broader systemic impacts were identified. The results show how goals from the bio-based economy, 2030 Agenda and strong sustainability paradigm are mutually interacting. Positive interactions were found within two clusters of goals, offering coherent and synergetic transition pathways within these. The first cluster encompasses developments toward intensified forestry, renewable energy, and closed-loop production systems. The second pathway supports diversified forestry and protection of critical natural capital. However, while internally coherent, trade-offs were identified between these goal clusters, demonstrating the difficulty in simultaneously making progress on goals belonging to different sustainability agendas. The results also stress the need for disaggregation and long-term assessments to identify trade-offs and synergies. Finally, the analysis highlights the theoretical potential but practical challenges of implementing the bio-based economy and 2030 Agenda in a way that adheres to strong sustainability. The analytical framework used in the present study may be adapted and applied to other decision-making contexts. It is particularly useful in settings characterized by uncertainty and unstructured problem spaces.

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