in the offshore pelagic community Maxium length (ML) of fish in the - PowerPoint PPT Presentation

HELCOM Workshop on Fish Indicators HaV, Göteborg, 10 May 2016 Proportion of large fish (LFI) in the offshore pelagic community Maxium length (ML) of fish in the offshore pelagic community Michele Casini Swedish University of Agricultural Sciences www.slu.se

LFI in the offshore pelagic community • LFI: proportion in weight of fish above a certain size (W >size /W total ) • LFI tracks the size composition in the fish community • Estimated in biomass (weight), to reduce the effect of recruitment fluctuations • Community with relatively high biomass of large fish: higher functional diversity than community dominated by small fish • Fishing has a direct effect on the structure of fish communities: decrease of relative abundance of large fish, decrease of mean body size in population  LFI maps the fishing pressure • In the Baltic Sea, the main predatory fish (cod) is affected also by low oxygen levels at the bottom  LFI can also map eutrophication Swedish University of Agricultural Sciences www.slu.se

LFI in the offshore pelagic community Stage of development Indicator type Core State Legislative linkage: Primary importance Secondary importance BSAP Viable populations of species none stated Segment and Objective MSFD 4.2. Proportion of selected species at the top of food- none stated Descriptors and Criteria webs. Used in OSPAR M Casini, N Larson, F Käll, J Olsson, H Wennhage (SWE) O Thurid, C Pusch, R Froese (GER) A Lappalainen, J Raitaniemi (FIN) Swedish University of Agricultural Sciences www.slu.se

Important points considering the offshore LFI • LFI is a food-web indicator (at least in the MSFD) • Strongest links in the Baltic Sea: cod, sprat and herring • The fishery exploiting large species is mainly targetting cod Cod Herring Sprat Swedish University of Agricultural Sciences Benthos Flounder www.slu.se

Important points considering the offshore LFI • The offshore communities are constituted by very motile species • The indicator should not be estimated in too small areas (or within national boundaries) • Particularly true for the pelagic LFI Swedish University of Agricultural Sciences www.slu.se

LFI in the offshore pelagic community: estimation • Based on pelagic control hauls in acoustic surveys (BIAS) • 4 species included: sprat, herring, sticklebacks and cod (> 99% of the biomass) • CPUEs modelled by GAMs • Length threshold = 38 cm • Currently limited to Swedish/German data (no international catch database available) Swedish University of Agricultural Sciences www.slu.se

LFI LFI -8 -6 -4 -2 -2 -1 0 2 4 6 8 0 1 2 1979 1979 1981 1981 LFI in the offshore pelagic community: results 1983 1983 1985 1985 1987 1987 Assessment area 34 Assessment area 31 1989 1989 1991 1991 1993 1993 1995 1995 Year Year 1997 1997 1999 1999 2001 2001 2003 2003 2005 2005 2007 2007 2009 2009 2011 2011 2013 2013 LFI -3 -2 -1 0 1 2 3 4 1979 1981 1983 Swedish University of Agricultural Sciences 1985 1987 Assessment area 33 1989 1991 1993 1995 Year 1997 1999 2001 2003 www.slu.se 2005 2007 2009 2011 2013

LFI in the offshore pelagic community: results Assessment Whole Baltic Proper 3 areas 31,33,34 2 1 LFI 0 -1 -2 -3 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Year • Decrease in large species • Decrease in the mean size of each species • Increase in small species Swedish University of Agricultural Sciences www.slu.se

LFI in the offshore pelagic community: GES • Baseline approach • Prerequisites of the baseline: - stable - long enough to be at least 2 times the generation time of the most representative species (in our case, the cod) - decide if the baseline represent GES or sub-GES Eero et al. 2008 Whole Baltic Proper 3 2 1 LFI 0 -1 -2 -3 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Swedish University of Agricultural Sciences Year www.slu.se

LFI in the offshore pelagic community: GES Subjective choice and biased by the lack of data from before the initiation of extensive fishing Swedish University of Agricultural Sciences www.slu.se

Maximum length of fish in the pelagic community (ML) • ML: largest fish in the community • ML tracks the size-structure in the fish community • Fish community with larger fish: higher functional diversity than fish community dominated by small fish • Fishing has a direct effect on the structure of fish communities: decrease of relative abundance of large species  ML maps the fishing pressure • Good complement of LFI Swedish University of Agricultural Sciences www.slu.se

ML in the offshore pelagic community Stage of development Indicator type Candidate State Legislative linkage: Primary importance Secondary importance BSAP Segment and Objective MSFD 3.3. Proportion age and size distribution none stated Descriptors and Criteria 3.3.2 Mean maximum length across all species found in research vessel surveys (wrongly placed?) Used in OSPAR Swedish University of Agricultural Sciences www.slu.se

ML in the offshore pelagic community: estimation • Based on pelagic control hauls in acoustic surveys (BIAS) • CPUE modelled by GAMs • 4 species included: sprat, herring, sticklebacks and cod (> 99% of the biomass) • Currently limited to Swedish/German data (no international catch database available) Swedish University of Agricultural Sciences www.slu.se

ML in the offshore pelagic community: results • No GES proposed so far Swedish University of Agricultural Sciences www.slu.se

How to move on Short-term goals (meet HOLAS_II) • Continue the development of the pelagic LFI • Agree on the GES boundaries (or other methods of assessment) • Include data from other countries performing the BIAS survey, if possible: Estonia, Finland, Latvia, Lithuania, Poland, Russia (process started) • Hinder: lack of an international database Long-term goals • Include data from all the other countries performing the BIAS survey • Integrate the demersal habitat in the indicator (if considered necessary), using ICES DATRAS database • Ensure data-flow from international databases to indicator processing, for both pelagic and demersal habitat (transparency and automatization) Swedish University of Agricultural Sciences www.slu.se

Discussion points Short-term goals • Decide on GES • Set of GES is problematic. Is the use of LFI as sourveillance indicator an option (ex. for HOLAS_II)? Long-term goals • Do we need to integrate the demersal habitat? • In this case, how? • How to assure an efficient data-flow? Swedish University of Agricultural Sciences www.slu.se

THANK YOU! Contact: michele.casini@slu.se Swedish University of Agricultural Sciences www.slu.se

Cod from pelagic and demersal surveys 3000 35 Demersal 30 2500 Pelagic 25 Demersal (CPUE) Pelagic (CPUE) 2000 20 1500 15 1000 10 500 5 0 0 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Year Swedish University of Agricultural Sciences www.slu.se