| Summary: | Human knowledge is not a static entity, but is a dynamic and cumulative learning process, which transforms and evolves through experience and communication. Human beings, and therefore human societies, are guided and governed based on the acquired and inherited knowledge. When we face complex environmental problems, the available knowledge is our best tool to overcome them and find solutions, and each individual, community or society applies the knowledge at hand, or at least, considered as useful. This PhD research discusses that under complex environmental issues -in which there are varying degrees of uncertainty and urgency, such as the impacts of climate change, invasive agricultural species, or overfishing- techno-scientific data is not providing all the answers that humans and environment require. Therefore, an urgent need to mobilise other kinds of knowing in order to co-create knowledge and elaborate more efficient policies is proposed. It is explored how relevant sources of situated environmental knowledge exist within communities that have subsisted and evolved under conditions of insularity and relative isolation, that is, in islands and remote territories. These types of spaces share a series of characteristics that allow their study under a unique perspective: insularity; in addition, they are suggested as “environmental-knowledge hot spots”. Under a Post-Normal Science paradigm, and in order to validate the value and usefulness of the knowledge these types of communities hold, this thesis applies an integrated approach consisting on institutional analysis and participatory processes to three different case studies. The studied cases range from the invasion of an agricultural pest that severely affects the cultivation of potatoes on the island of Tenerife (Canary Islands); the artisanal fishing as a response to overfishing in Tenerife; and finally, the impacts of climate change on small Arctic communities. This research tries to illustrate the need to overcome scientific, social, cultural and ...
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