Greed is good: Heuristic adaptations for resilience in renewable resource management

Decision problems may be subject to objectives or constraints that make the formal model intractable. We propose an adaptive and pragmatic approach to address such nonstandard objectives or constraints, where these are first circumvented for feasibility, then accounted for through heuristics. One ex...

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Bibliographic Details
Published in:Natural resource modeling 2023-05, Vol.36 (2), p.n/a
Main Authors: Ni, Yuanming, Sandal, Leif K., Kvamsdal, Sturla F.
Format: Article
Language:English
Subjects:
Constraint modelling
Dynamic programming
Economic impact
ecosystem‐based management
Fisheries
Fishing
Heuristic
heuristics
Predator-prey simulation
Predators
Prey
Problem solving
Recovery plans
Renewable resources
Resilience
Resource management
Risk management
risk of collapse
Risk reduction
uncertainty
viability
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Summary:Decision problems may be subject to objectives or constraints that make the formal model intractable. We propose an adaptive and pragmatic approach to address such nonstandard objectives or constraints, where these are first circumvented for feasibility, then accounted for through heuristics. One example is managing risk and resilience in a natural system facing uncertainty. Our procedure is exemplified in a predator‐prey fisheries system where a reference policy that maximizes expected profits implies a risk of prey stock collapse. The reference policy includes a no‐fishing section for the prey and harvest beyond myopic catch for the predator in parts of state space. We construct heuristic recovery plans, based on the reference policy, to reduce the risk of collapse by partly backing in the auxiliary objective. Under the heuristic policies, system resilience is enhanced with limited economic losses. Via Monte Carlo simulations, we calculate viability probabilities as measures of improved resilience and employ dynamic programming to assess value losses. Recommendations for Resource Managers Adaptive heuristics can augment resilience management. Promoting heuristic modifications based on first‐best solutions of reduced models. Support decisions/actions in presence of uncertainty and nonstandard objectives. Resilience implies viability and ecosystem perspectives.
ISSN:0890-8575
1939-7445
DOI:10.1111/nrm.12367