Linking a conceptual framework on systems thinking with experiential knowledge

Abstract

This paper addresses a systemic approach for the study of fishers’ ecological knowledge in order to describe fishers’ ways of knowing and dealing with complexity in ecosystems, and discusses how knowledge is generated through, e.g. apprenticeship, experiential knowledge, and testing of hypotheses. The description and analysis of fishers’ ecological knowledge has been done using the Structure–Dynamics–Functions conceptual framework. Fishers identify 5–50 feeding interactions (Structure), recognize populations’ dynamics over time, and, the impact of external factors (climate change, water quality and overfishing) (Dynamics) and finally, acknowledge different values or services (Functions) of the ecosystem (drinking water and fishing). Knowing about these three main aspects seems to be core knowledge embedded in fishers’ ecological knowledge, which comprises systems thinking. Systems thinking is arguably part of fishers’ professional skills and significant for sustainable natural resource management yet understanding ecosystem complexity is also a cognitive challenge.

Keywords:

• fishers
• ecological knowledge
• systems thinking
• cognition
• knowing complexity
• sustainable natural resource management

Acknowledgements

We would like to acknowledge all the 14 fishers that participated voluntarily in this study for opening the doors to their homes, answered our questions, let us accompany them when fishing – for their endless contributions. We thank as well the County Administrative Board in Jönköping for all the information and assistance provided. This study was made possible thanks to funding by the Swedish Research Council. Thanks also to the Wallenberg Foundation for travel funding in 2011. Finally, we would like to thank the Santa Fe Institute, Santa Fe, NM and the Pacific Ecoinformatics and Computational Ecology Lab ‘PEaCE’, Berkeley, CA, especially to our colleagues Jennifer Dunne, Neo Martinez and Eric Berlow for their academic support and collaboration regarding issues on complexity in ecosystems.