Managing Fisheries with a Ruler LBB Rainer Froese
Managing Fisheries with a Ruler: LBB Rainer Froese, GEOMAR Advanced Course on Fisheries Biology in R 11 -15 November 2019 School of Biology, Aristotle University of Thessaloniki, Greece 1
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What is a Stock? • A stock is an exploited population of aquatic organisms • It has little exchange of genes with adjacent stocks (< 5%) • It reproduces at another time or place than adjacents stocks Examples: - a species in a lake - a non-migratory species in a bay - a roaming species in a marine ecoregion or LME - a wide-ranging migratory species such as tunas Data used in stock assessment have to be representative for the stock as a whole: total catches, typical cpue, typical length-frequencies 3
A Look at Data-Rich Stock Assessement 2018 assessment of one the best researched fish stocks in the world, North Sea cod. Despite the efforts of several fisheries institutes, several research vessels, hundreds of scientists and a huge bureaucracy of controls, next year‘s allowed catch is derived from a single uncertain number: the relative size of the stock. That‘s what LBB is about. 4
Too many stocks, too few data • New legislation in Canada, US and Asia requires management of all exploited stocks • New and old simple approches are needed to get reasonable assessments with less time and data • New data-light but computation-heavy methods come to the rescue: LBB: Length-based Bayesian Biomass Estimator Froese, R. , Winker, H. , Coro, G. , Demirel, N. , Tsikliras, A. C. , Dimarchopoulou, D. , Scarcella, G. , Probst, W. N. , Dureuil, M. and D. Pauly. 2018. A new approach for estimating stock status from length frequency data. ICES Journal of Marine Science 2018, 75(6): 2004 -2015. Froese, R. , Winker, H. , Coro, G. , Demirel, N. , Tsikliras, A. C. , Dimarchopoulou, D. , Scarcella, G. , Probst, W. N. , Dureuil, M. and D. Pauly. 2019. On the pile-up effect and priors for Linf and M/K: response to a comment by Hordyk et al. on “A new approach for estimating stock status from length frequency data”. ICES Journal of Marine Science, fsy 199 5
How to Measure Fish 6
Width of Length Classes Matters Too coarse Fine but more than needed 7
The LBB Method…. . 8
Conceptual Framework ? 9 Sim_23. xlsx
The Visible Length-Frequencies 10 Sim_23. xlsx
The LBB Parameters Lc Linf K M F N SLi CLi Length where 50% of the individuals are retained by the gear Asymptotic length of the von Bertalanffy growth equation Growth rate of the von Bertalanffy growth equation Natural mortality rate Fishing mortality rate Number of individuals Gear selectivity at length i Catch at length i 11
The LBB Equations Gear-selectivity: Survivors to Li: Vulnerable/ relative catch at Li : Using a Bayesian approach with priors derived from previous or aggregated LFs, all parameters are estimated simultaneously. 12
LBB Mortality Estimates Are Not Recent Mortality estimates of LBB are of limited use for management, because they are not recent but the average of the exploited length (Lx to Linf) and corresponding age range. 13
On the Dynamics of Exploited Fish Populations Ray Beverton (left) and Sidney Holt at Lowestoft (UK) in 1949, doing stock assessment of plaice. 14
Standard Yield per Recruit Equation Average growth and mortality parameters as estimated by LBB are the required input for Yield-per-Recruit equations. A combination of several of these equations then gives the current biomass relative to unexploited biomass (B/B 0) 15
Optimum Length at First Capture Lc_opt The length where cohort biomass is maximum in an unexploited population is given by Holt (1958) as: This is also the length where cohort fecundity is about maximum and thus this is the natural average length of spawners. Froese et al. (2016) present an equation for the length at first capture that will maximize catch and biomass for a given F and will result in Lopt being the mean length in the exploited population: 16
Proxy for Bmsy A proxy for the biomass that can produce the maximum sustainable yield can be calculated from standard equations by assuming that Lc = Lc_opt and F = M. The relative biomass and the length at first capture estimated by LBB can then be used directly for management of data-poor stocks: 1) If relative stock size B/B 0 is smaller than Bmsy/B 0, reduce catches 2) If length at first capture Lc is smaller than Lc_opt, start fishing at larger sizes. 17
Performance of LBB • LBB results for relative biomass or stock status have been validated against simulations and against real stocks • LBB predictions were not significantly different from the “true“ B/B 0 values of the simulations • LBB predictions for stock status were similar to those obtained from full stock assessments 18
Example Simulated Data for Cod True Values: Linf=120 Lc=35 Z/K=3. 08 M/K=1. 54 F/M=1 B/B 0=0. 26119
Example Simulated Gill-Net Selection True Values: Linf=15 Lmean=8 Z/K=3. 75 M/K=1. 25 F/K=2. 5 F/M=2 B/B 0=0. 37220
Example for Haddock in the North Sea 21
Example for Haddock in the North Sea LBB gives: F/M=3. 2 B/B 0=0. 16 B/Bmsy=0. 43 ICES: F/Fmsy=1. 6 SSB/Bmsy=0. 69 (Bmsy~2*Bpa) 22
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Example Thorny Skate NWA Only one year with data available LBB gives: F/M=3. 5 B/B 0=0. 15 Qualitative assessment suggests high exploitation and low biomass. (DFO 2003, 2017 a) 24
Conclusion • LBB gives preliminary estimates of stock status based on length frequency data from the fishery • LBB results provide objective B/B 0 priors for other assessment methods such as CMSY and AMSY • Measuring fish is good for you! 25
Thank You Questions? Rainer Froese rfroese@geomar. de www. fishbase. de/rfroese/ 26
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