How can local and traditional knowledge be effectively incorporated into international assessments?

Abstract

There have been persistent calls for greater use oflocal and traditional or indigenous knowledge alongsideconventional scientific knowledge in making decisionsabout biodiversity and natural resources (Fazey et al., 2006;Raymond et al., 2010). Yet such calls are rarely reflectedin practice. Different types of knowledge have not been wellintegrated into national and international assessment ex-ercises, including the Intergovernmental Panel on ClimateChange, Millennium Ecosystem Assessment and The Eco-nomics of Ecosystems and Biodiversity (Turnhout, 2012),allofwhichfocusalmostexclusivelyonconventionalscientificknowledge. The newly formed Intergovernmental Platformon Biodiversity and Ecosystem Services (IPBES), chargedwith strengthening the knowledge base for decision-makersconcernedwithbiodiversityconservationandtheimportanceof the environment for human well-being, aspires to dobetter. Its operating principle is to ‘Recognize and respectthe contribution of indigenous and local knowledge to theconservation and sustainable use of biodiversity and ecosys-tems’.Thereisanurgentneedtoestablishprocessestoachievethis if such aspirations areto be translated into good practice(Tengo et al., 2013; Sutherland, 2013; Thaman et al., 2013).Hereweoutlinewhywebelieveanexplicitsetofprocessesisneeded,includingwithinIPBES,torecognizeandintegrateinformation from conventional science and local andtraditional knowledge systems. We identify key features ofsuch processes and propose a specific mechanism that couldhelpintegrateinformationfromdifferent,parallelknowledgesystems into international knowledge assessments.There are clear benefits of incorporating local andtraditional knowledge alongside conventional scientificknowledge when assessing current understanding to guidedecision-making (Tengo et al., 2013). Local and traditionalknowledge can provide complementary perspectives, bornefromlongperiodsofsharedobservationandexperimentationthat are often lacking in conventional scientific knowledge.The latter commonly depends on sets of observations orexperiments conducted over relatively short time-scales bygroups of people disconnected from the environmentalcontext. Local knowledge, for example, has been repeatedlyshown to extend our understanding of the spatial andtemporal dynamics of biodiversity, including for individualspecies (e.g. the Arctic fox Alopex lagopus; Gagnon B van Oudenhoven & Haider, 2012).Limiting the collation of information to conventionalscience could also mean that science conducted in moredeveloped countries (with larger scientific budgets) maydictate decision-making elsewhere. This situation is unlikelytobeeitherpoliticallyacceptableorappropriate.Thereisoftena mismatch between the needs of decision-makers and theconventional scientific knowledge available (Amano &Sutherland, 2013). This mismatch is important, as illustratedby considering pollinators, a topic of considerable currentinterest and favoured for the first IPBES assessment. In aglobalreviewofconventionalscientificevidencefortheeffectsof interventions to maintain or restore wild bee populations(Dicksetal.,2010)30ofthe163studiesidentifiedwereoutsideEurope and North America. With evidence for effectivenessbasedlargelyintemperateregions,interventionsonlyrelevantto the tropics are poorly understood and may even beoverlooked.Insuchcontexts,localandtraditionalknowledgeare particularly necessary to enable assessments that aretailored to local understanding and needs.So how can information from traditional and conven-tional scientific knowledge be effectively combined in thecontext of national and international assessments? Wesuggest there are at least three parts to the addressing ofthis problem. The first step is to recognize that there arefundamentally different types of knowledge, each associatedwith different needs for different stakeholder groups (Fazeyet al., 2006). Here, it is important to distinguish information(whether drawn from observations or experiment, or from ascientific study or experience, information can be tested insome way) from values (i.e. preferences relating to prioritiesfor action or particular outcomes) and associated mentalmodels (i.e. the cognitive frameworks that people use tointerpret and understand the world). Values and mentalmodels must be made explicit to ensure that collaborationamongst stakeholders involved in an assessment is