Maja Schlüter

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Maja Schlüter

Institution

Stockholm Resilience Centre, Stockholm University

Personal homepage

www.seslink.org

Professional homepage

http://stockholmresilience.org/contact-us/staff/2012-11-27-schluter.html

ORCID more info

No associated orcid account.

GitHub more info

No associated github account.

No bio entered.

Research Interests

Co-evolutionary dynamics of social-ecological systems
social-ecological systems modeling

AgentEx aims to advance understanding of group processes for sustainable management of a common pool resource (CPR). By supporting the development and test explanations of cooperation and sustainable exploitation.

AgentEx aims to advance understanding of group processes for sustainable management of a common pool resource (CPR). By supporting the development and test explanations of cooperation and sustainable exploitation.

The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.

This model examines how financial and social top-down interventions interplay with the internal self-organizing dynamics of a fishing community. The aim is to transform from hierarchical fishbuyer-fisher relationship into fishing cooperatives.

PoliSEA represents a continuous policy process cycle, integrated with the dynamics of a fishery social-ecological system. The policy process in the model is represented by interactions between policymakers and interest groups and subsequent voting during which policymaker decide to increase or decrease the fishing quota for the next season. Policymakers’ positions can be influenced by lobbying of interest groups or interest group coalitions. The quota adopted through the policy process determines the amount of fish that can be harvested from the fish population during the season.

FIBE represents a simple fishery model. Fish that reproduce and fisher with different fishing styles that fish as their main source of income. The aim of the model is to reflect the different fishing behaviours as described and observed in the (Swedish) Baltic Sea fishery and explore the consequences of different approximations of human/fisher behaviour in under different environmental and managerial scenarios.

The overarching aim is to advance the incorporation and understanding of human behaviour (diversity) in fisheries research and management. In particular focusing on insights from social (fishery) science of fisher behaviour.

SSFxity is an agent-based model of an ‘archetypical’ small scale fishery in which development interventions may take place. The purpose of the model is to enable taking a complexity lens, i.e. to enable understanding and gradually unravelling complexities in small scale fisheries. Complexity is not one thing, it depends on the context, insights and relevance related to particular fisheries. SSFxity guides one in deciding or considering which complexities are relevant for your case, but also supporting to think and consider the consequences of each of them.

The purpose of this model is to understand the role of trade networks and their interaction with different fish resources, for fish provision. The model is developed based on a multi-methods approach, combining agent-based modeling, network analysis and qualitative data based on a small-scale fisheries study case. The model can be used to investigate both how trade network structures are embedded in a social-ecological context and the trade processes that occur within them, to analyze how they lead to emergent outcomes related to the resilience of fish provision. The model processes are informed by qualitative data analysis, and the social network analysis of an empirical fish trade network. The network analysis can be used to investigate diverse network structures to perform model experiments, and their influence on model outcomes.

The main outcomes we study are 1) the overexploitation of fish resources and 2) the availability and variability of fish provision to satisfy different market demands, and 3) individual traders’ fish supply at the micro-level. The model has two types of trader agents, seller and dealer. The model reveals that the characteristics of the trade networks, linked to different trader types (that have different roles in those networks), can affect the resilience of fish provision.

Under development.

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