Micro-level explanations for emergent patterns of self-governance arrangements in small-scale fisheries-A modeling approach.

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2017-01

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Abstract

Small-scale fisheries (SSFs) in developing countries are expected to play a significant role in poverty alleviation and enhancing food security in the decades to come. To realize this expectation, a better understanding of their informal self-governance arrangements is critical for developing policies that can improve fishers' livelihoods and lead to sustainable ecosystem stewardship. The goal of this paper is to develop a more nuanced understanding of micro-level factors-such as fishers' characteristics and behavior-to explain observed differences in self-governance arrangements in Northwest Mexico. We focus on two ubiquitous forms of self-governance: hierarchical non-cooperative arrangements between fishers and fishbuyers, such as patron-client relationships (PCs), versus more cooperative arrangements amongst fishers, such as fishing cooperatives (co-ops). We developed an agent-based model of an archetypical SSF that captures key hypotheses from in-depth fieldwork in Northwest Mexico of fishers' day-to-day fishing and trading. Results from our model indicate that high diversity in fishers' reliability, and low initial trust between co-op members, makes co-ops' establishment difficult. PCs cope better with this kind of diversity because, in contrast to co-ops, they have more flexibility in choosing whom to work with. However, once co-ops establish, they cope better with seasonal variability in fish abundance and provide long-term security for the fishers. We argue that existing levels of trust and diversity among fishers matter for different self-governance arrangements to establish and persist, and should therefore be taken into account when developing better, targeted policies for improved SSFs governance.

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10.1371/journal.pone.0175532

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Lindkvist, Emilie, Xavier Basurto and Maja Schlüter (2017). Micro-level explanations for emergent patterns of self-governance arrangements in small-scale fisheries-A modeling approach. PloS one, 12(4). p. e0175532. 10.1371/journal.pone.0175532 Retrieved from https://hdl.handle.net/10161/18611.

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Scholars@Duke

Basurto

Xavier Basurto

Professor of Sustainability Science in the Division of Marine Science and Conservation

I am interested in the fundamental question of how groups (human and non-human) can find ways to self-organize, cooperate, and engage in successful collective action for the benefit of the common good. To do this I strive to understand how the institutions (formal and informal rules and norms) that govern social behavior, interplay with biophysical variables to shape social-ecological systems. What kind of institutions are better able to govern complex-adaptive systems? and how can societies (large and small) develop robust institutions that provide enough flexibility for collective learning and adaptation over the long-term?

My academic and professional training is based on a deep conviction that it is through integrating different disciplinary perspectives and methods that we will be able to find solutions to challenging dilemmas in natural resources management, conservation, and environmental policy. Trained as a marine biologist, I completed a M.S in natural resources studying small-scale fisheries in the Gulf of California, Mexico. Realizing the need to bring social science theories into my work on common-pool resources sustainability, I earned an MPA and a Ph.D. in Management (with a minor in cultural anthropology) from the University of Arizona and under the supervision of Edella Schlager. Following I spent two years working with Elinor Ostrom, 2009 co-winner of the Nobel Prize in Economics, at the Workshop for Political Theory and Policy Analysis of Indiana University. Methodologically, I am familiar with a variety of quantitative and qualitative approaches and formally trained to conduct Qualitative Comparative Analysis (QCA or more recently fsQCA), that allows among other things, systematic comparisons of middle range N sample sizes and address issues of multiple-causality.


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