Strategies for Sustainable Renewable Resource Management During Environmental Change
(English)Article in journal (Refereed) Submitted
As a consequence of global environmental change, enhanced management strategies for sustainable use of renewable resources must be developed. Here we undertake a novel approach to solving resource growth problems using a computational form of learning-by-doing to support optimal strategies for prevalent natural resource management dilemmas. We investigate discount rates, exploration versus exploitation, and updating versus retaining knowledge, to inform decision-making with respect to optimal actions (harvest efforts) for sustainable resource management. To operationalize these issues we use an artificially intelligent agent-based model and analyze how different trends and fluctuations in resource growth rates affect different management strategies. We find that resources with decreasing trends in growth rate demand higher adaptation rates and more exploration compared to increasing trends, for optimal efficiency. However, sustainable management strategies with both high efficiency and robustness to endogenous and exogenous disturbances can be obtained by striving for: higher update rates of new knowledge, high valuation of future outcomes, and modest exploration around what is perceived as the optimal management strategy.
Learning By Doing, Natural Resource Management, Growth, Reinforcement Learning, Neural Networks, Global Environmental Change, Mental Model
Social Sciences Interdisciplinary Ecology Other Natural Sciences
Research subject Sustainability Science
IdentifiersURN: urn:nbn:se:su:diva-128599OAI: oai:DiVA.org:su-128599DiVA: diva2:915867
FunderMistra - The Swedish Foundation for Strategic Environmental Research