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dc.contributor.authorLaw, Elizabeth
dc.contributor.authorLinnell, John Durrus
dc.contributor.authorVan Moorter, Bram
dc.contributor.authorNilsen, Erlend Birkeland
dc.date.accessioned2021-12-02T09:50:16Z
dc.date.available2021-12-02T09:50:16Z
dc.date.created2021-11-24T14:18:17Z
dc.date.issued2021
dc.identifier.citationLaw, E., Linnell, J. D., Van Moorter, B. & Nilsen, E. B. (2021). Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems. PLOS ONE, 16(11): e0260159. doi:en_US
dc.identifier.issn1932-6203
dc.identifier.urihttps://hdl.handle.net/11250/2832519
dc.description.abstractSustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.en_US
dc.language.isoengen_US
dc.publisherPLOSen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleHeuristics for the sustainable harvest of wildlife in stochastic social-ecological systemsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2021 The Author(s)en_US
dc.subject.nsiVDP::Økologi: 488en_US
dc.source.volume16en_US
dc.source.journalPLOS ONEen_US
dc.source.issue11en_US
dc.identifier.doi10.1371/journal.pone.0260159
dc.identifier.cristin1958447
dc.relation.projectThe Research Council of Norway: 251112en_US
dc.source.articlenumbere0260159en_US


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal