
doi: 10.1111/csp2.396
Abstract The concept of social–ecological knowledge diversity (SEKD) provides a novel way of examining coupled human–environment interactions—it acknowledges differences in knowledge, values, and beliefs of stakeholder groups within social–ecological systems (SES). Thus, understanding and measuring SEKD is an essential component of sustainable management with implications for conflict resolution, collective action and policymaking. However, methods to efficiently define and model knowledge diversity are still underdeveloped. Using a semiquantitative cognitive mapping approach, we collected and analyzed stakeholder‐specific knowledge and perceptions of the Western Baltic cod fishery to model SEKD. Results demonstrate substantial variation in perceptions across different individuals and social groups. SEKD was evident in (a) distinctive meanings attached to social factors relative to ecological factors, (b) causal relationships underlying the understanding of SES dynamics, and (c) social impacts of ecological changes on ecosystems (and vice versa). By identifying and representing knowledge‐specific disparities in SES frameworks, our model explicitly improves the understanding of human–environment interactions with implications that could help reduce conflicts and legitimize management plans.
Baltic Sea, fuzzy cognitive mapping, Ecology, knowledge diversity, General. Including nature conservation, geographical distribution, cod, QH1-199.5, mental models, natural resource management, QH540-549.5
Baltic Sea, fuzzy cognitive mapping, Ecology, knowledge diversity, General. Including nature conservation, geographical distribution, cod, QH1-199.5, mental models, natural resource management, QH540-549.5
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
