Selectivity metrics for fisheries management and advice. Issue 3 (11th March 2020)

• Record Type: Journal Article
• Authors: Vasilakopoulos, Paraskevas; Jardim, Ernesto; Konrad, Christoph; Rihan, Dominic; Mannini, Alessandro; Pinto, Cecilia; Casey, John; Mosqueira, Iago; O'Neill, Finbarr G.
• Is Part Of: Fish and fisheries. Volume 21:Issue 3(2020)
• Page Start: 621
• Page End: 638
• Publication Date: 2020-03-11
• Subjects: exploitation pattern -- fishing mortality -- landing obligation -- population selectivity -- simulation -- technical measures; Fisheries -- Periodicals; Fishes -- Periodicals; 639.2
• DOI: 10.1111/faf.12451
• Languages: English
• ISSNs: 1467-2960

Abstract

Abstract: Fisheries management typically aims at controlling exploitation rate (e.g., Fbar) to ensure sustainable levels of stock size in accordance with established reference points (e.g., FMSY, BMSY ). Population selectivity ("selectivity" hereafter), that is the distribution of fishing mortality over the different demographic components of an exploited fish stock, is also important because it affects both Maximum Sustainable Yield (MSY) and FMSY, as well as stock resilience to overfishing. The development of an appropriate metric could make selectivity operational as an additional lever for fisheries managers to achieve desirable outcomes. Additionally, such a selectivity metric could inform managers on the uptake by fleets and effects on stocks of various technical measures. Here, we introduce three criteria for selectivity metrics: (a) sensitivity to selectivity changes, (b) robustness to recruitment variability and (c) robustness to changes in Fbar. Subsequently, we test a range of different selectivity metrics against these three criteria to identify the optimal metric. First, we simulate changes in selectivity, recruitment and Fbar on a virtual fish stock to study the metrics under controlled conditions. We then apply two shortlisted selectivity metrics to six European fish stocks with a known history of technical measures to explore the metrics' response in real‐world situations. This process identified the ratio of F of the first recruited age–class to Fbar (Frec/Fbar) as an informative selectivity metric for fisheries management and advice.