The Multiple Evidence Base Approach

A framework for connecting indigenous, local and scientific knowledge systems

M. Tengö, P. Malmer, T. Elmqvist, Stockholm Resilience Centre; E. Brondizio, Indiana University; M. Spierenburg, VU University Amsterdam

In spite of the recognition of indigenous and local knowledge systems, their potential has often not informed decision making beyond the local level. Furthermore, the actors and knowledge systems that generate and underpin knowledge and insights are often not part of decision-making processes. Thus, there is a great need to develop functioning mechanisms to engage and legitimate, in a transparent and constructive way, synergies between knowledge systems (Reid et al. 2006, Turnhout et al. 2012).

Whereas indigenous, local and scientific knowledge systems are viewed to generate equally valid, complementarily and useful evidence for interpreting conditions, change, trajectories, and in some cases causal relationships relevant to the sustainable governance of ecosystems and biodiversity (Tengö et al. 2013) -- the Multiple Evidence Base (MEB) is an approach that proposes parallels. The approach draws on literature and existing practice emphasizing the complementary nature of various knowledge systems, as well as the need to move away from translating knowledge into one currency, or “integrating” indigenous and local knowledge into science through unidirectional validation processes (Berkes 2007, Nadasdy 1999). It also draws on the outcomes of a dialogue process in collaboration with a network of indigenous peoples and local communities, in particular the International Indigenous Forum for Biodiversity (IIFB) (see

The MEB approach highlights the importance of indigenous and local knowledge systems on their own terms. It also recognizes differences among scientific knowledge, such as social science and natural science disciplines and forms of evidence. To realize the potential of each knowledge system, we argue that different criteria of validation should be applied to data and information originating from different systems. A MEB approach on an issue or assessment topic, such as Arctic sea ice dynamics related to climate change, will create an enriched picture of understanding in an assessment process, as is illustrated in the middle pane in figure 1. We propose the MEB as a ‘nested approach’ that considers different types of knowledge (from very specific and localized to more general) and different types of overlap between knowledge systems that may appear at different levels (and for different goals). A MEB approach should be tailored in relation to different goals, regions, and kinds of assessment and scales of investigation, but also needs to recognize cross-scale interactions.

Parallel approaches to addressing complementarities, potential synergies as well as contradictions across knowledge systems have been applied across the globe and for various issues: sea ice dynamic and climate change (Laider 2006); population dynamics of fish and other wildlife (Mackinson 2001, Moller et al. 2004); and land use change and farming practices (Chalmers and Fabricius 2007, Brondizio 2008). Many of the case studies find that the approach creates an opportunity for “a culturally informed” appraisal of scientific knowledge and practice (IPBES, 2012). Combining scientific and traditional methods for monitoring wildlife has, for example, provided customary users an opportunity to scrutinize science and for scientists to learn relationships and processes previously unknown (Moller et al. 2004). Thus, in addition to broadening and enhancing the available sources of relevant knowledge as a base for decision making, a MEB approach aims at enhancing trust and avoiding the arrogance of a single ex ante “right approach,” which frequently overrides the contribution of indigenous peoples, local communities, and practitioners in the context of assessment programs and development projects.

To realize a MEB approach and build credibility and legitimacy among all involved, there is a need for true dialogue at the outset, as well as co-production of problem definitions, an assessment process, and an evaluation and synthesis of the findings. MEB is an approach used to mobilize existing knowledge for not only assessments but also for improving policy such as within IPBES. It is a way to support and enhance existing mechanisms for learning and decision-making in response to the dynamics of social-ecological systems at all scales. The complementary perspective proposed by such an approach will contribute to building resilience and capacity for transformation that includes empowerment of indigenous peoples and local communities.

Figure 1. Outlining three phases of a Multiple Evidence Base approach, emphasizing the need for co-production of problem definitions as well as joint analysis and evaluation of the enriched picture created in the assessment process. Phase 1 Concerns defining stakeholders, problems and goals in a collaborative manner. Phase 2 entails bringing together knowledge on an equal platform, using parallel systems of valuing and assessing knowledge, and Phase 3 is the joint analysis and evaluation of knowledge and insights to generate multi-level synthesis and identify and catalyze processes for generating new knowledge.

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