Combining stock, multispecies, and ecosystem level fishery objectives within an operational management procedure: simulations to start the conversation. (14th June 2016)

• Record Type: Journal Article
• Authors: Gaichas, Sarah K.; Fogarty, Michael; Fay, Gavin; Gamble, Robert; Lucey, Sean; Smith, Laurel
• Editors: Prellezo, Raúl
• Is Part Of: ICES journal of marine science. Volume 74:Number 2(2017)
• Page Start: 552
• Page End: 565
• Publication Date: 2016-06-14
• Subjects: Georges Bank -- management strategy evaluation -- multispecies fisheries -- multifleet fisheries -- simulation modelling; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsw119
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract : We explored alternative status determination criteria and reference points that could simplify fisheries management using a simulated multispecies/ecosystem-based operational management procedure. There are four components to the procedure: (i) limit total removals from the ecosystem; (ii) allocate the total removals limit among aggregate species groups; (iii) maintain individual species above minimum stock size thresholds; and (iv) optimize the species mix (within aggregates) based on bio-economic portfolio analysis. In this procedure, "overfishing" criteria are applied only to aggregates of species at the ecosystem and group level, but "overfished" criteria apply at the species/stock level. Previous work using multispecies production models identified conditions where conservation and yield objectives could be balanced: aggregations of species with similar life histories, species interactions, and responses to environmental forcing supported the highest yields while minimizing risks that individual stocks dropped below biomass thresholds. Here, we use a more complex length structured multispecies, multifleet simulation model to explore management procedure steps (i)–(iii). Different species aggregation rules were applied (single species, functional groups, and full system), and yield curves were constructed for each aggregation level by sequentially increasing effort in each of the fleets (alone and simultaneously), while recruitment for each species varied stochastically around a function based on spawning stock biomass. The performance of individual species and each aggregate type was then compared with respect to yield, biomass, and economic revenue objectives under changing environmental conditions. Our results evaluate the trade-offs between these objectives for the 10 species in the simulated system. Overall we found that there are aggregate catch limits that can both maximize yield and revenue while conserving biomass. However, community composition and revenue trade-off over a range of fishing effort. We consider this a starting point for further development with scientists, managers, fishermen, and other stakeholders in the region.