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  • 2020-2022  (1)
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    Publication Date: 2020-09-11
    Description: Context Most protected areas are managed based on objectives related to scientific ecological knowledge of species and ecosystems. However, a core principle of sustainability science is that understanding and including local ecological knowledge, perceptions of ecosystem service provision and landscape vulnerability will improve sustainability and resilience of social-ecological systems. Here, we take up these assumptions in the context of protected areas to provide insight on the effectiveness of nature protection goals, particularly in highly human-influenced landscapes. Objectives We examined how residents’ ecological knowledge systems, comprised of both local and scientific, mediated the relationship between their characteristics and a set of variables that represented perceptions of ecosystem services, landscape change, human-nature relationships, and impacts. Methods We administered a face-to-face survey to local residents in the Sierra de Guadarrama protected areas, Spain. We used bi- and multi-variate analysis, including partial least squares path modeling to test our hypotheses. Results Ecological knowledge systems were highly correlated and were instrumental in predicting perceptions of water-related ecosystem services, landscape change, increasing outdoors activities, and human-nature relationships. Engagement with nature, socio-demographics, trip characteristics, and a rural–urban gradient explained a high degree of variation in ecological knowledge. Bundles of perceived ecosystem services and impacts, in relation to ecological knowledge, emerged as social representation on how residents relate to, understand, and perceive landscapes. Conclusions Our findings provide insight into the interactions between ecological knowledge systems and their role in shaping perceptions of local communities about protected areas. These results are expected to inform protected area management and landscape sustainability.
    Print ISSN: 0921-2973
    Electronic ISSN: 1572-9761
    Topics: Biology
    Published by Springer
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