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An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts
Author(s) -
Steven J. Lade,
Susa Niiranen,
Jonas HentatiSundberg,
Thorsten Blenckner,
Wiebren J. Boonstra,
Kirill Orach,
Martin F. Quaas,
Henrik Österblom,
Maja Schlüter‬
Publication year - 2015
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1504954112
Subject(s) - ecological systems theory , ecology , boom , social ecological model , sustainability , ecosystem , baltic sea , social dynamics , environmental change , agent based model , system dynamics , environmental resource management , climate change , environmental science , computer science , biology , oceanography , environmental engineering , geology , artificial intelligence
Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social-ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social-ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social-ecological models.

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