Säterberg, Torbjörn
- Institutionen för akvatiska resurser (SLU Aqua), Sveriges lantbruksuniversitet
- Linköpings universitet
Forskningsartikel2019Vetenskapligt granskadÖppen tillgång
Säterberg, Torbjörn; Casini, Michele; Gårdmark, Anna
Fisheries management is slowly evolving from its traditional single-species focus to a more holistic ecosystem-based approach. Yet, limits for exploitation are almost always set based on single-species models, treating species as isolated entities. This is problematic since the sustainability of a fishery hinges on its effects on the exploited community as a whole. Here, we develop a novel analytical approach of estimating exploitation rates that are sustainable with respect to the state of whole fish communities. Our approach simultaneously addresses species interactions, environmental covariates and natural variability of population sizes, yet it is framed around a simple and accessible objective. We derive Ecologically Sustainable Exploitation Rates, that is exploitation rates associated with a maximum acceptable probability (determined by management) that any interacting species decreases to an unacceptably low population size. Using models fitted to an exploited fish community, we show how accounting for species interactions constrains the possibilities for ecologically sustainable exploitation. The conventional omission of species interactions may thus result in overestimated exploitation limits. Moreover, our application rendered a counterintuitive result: it suggests that the exploitation of one species should increase, as compared to mean historical levels, for the purpose of conservation of the community as a whole. Such insights could impossibly be gained using single-species approaches, illustrating the need to adopt multispecies models in fisheries management. Analytical derivation of Ecologically Sustainable Exploitation Rates offers a mean to do so.
multispecies exploitation; multispecies objective; reference points; statistical modelling; stock assessment; viability modelling
Fish and Fisheries
2019, Volym: 20, nummer: 5, sidor: 952-961
Kust och hav
SDG14 Hav och marina resurser
Ekologi
Sannolikhetsteori och statistik
Fisk- och akvakulturforskning
DOI: https://doi.org/10.1111/faf.12390
https://res.slu.se/id/publ/100747