Possible SST and NAO influences on the eastern bluefin tuna stock - the inexfish approach. (BFT_SYMP/027) Christopher R. Bridges 1, Oliver Krohn 1, Michele Deflorio 2 and Gregorio De Metrio 2 IN EX FISH 1 Düsseldorf, Germany. E-mail: bridges@uni-duesseldorf.de 2 Bari, Italy. E-mail g.demetrio@veterinaria.uniba.it
SUMMARY Through the auspices of the EU-Project IN-EXFISH an analysis of historical data sets on catch and also model generated data on SSB and recruitment have been used to look for possible influences of the NAO on the eastern Bluefin Tuna stock. Initial evidence has shown that total catch can be correlated to the Winter NAO but only after a lag of 2 years. A further analysis of remote sensing SST data for the main spawning areas in the Mediterranean (Balearic, Tyrrhenian, Ionian and Levantine seas) revealed a SST anomaly which is increasing and already indicates values in summer during the spawning season of up to +3 C. These changes in SST anomaly do not appear to be correlated with changes in the NAO. The influence of SST on SSB and recruitment will be discussed and their possible influence on short and long terms stock changes.
2006 Incorporating extrinsic drivers into fisheries management' is an EU funded project that aims to increase the responsiveness of fisheries management to a range of anthropogenic and non-anthropogenic forcing factors. end 2008 Recent years have seen fish stocks reach unprecedented low levels. While the fishing industry has been keen to identify pollution and global warming as the causes, it is also clear that fishing has removed large numbers of fish and altered the way the ecosystem works. Everybody would like to see the rebuilding of fish stocks and this can only be achieved if we understand all of the influences, human and natural, on fish dynamics.
The Workpackages 2006 Review WP1 Steering Group WP8 Coordination WP9 Metric developments WP2 Case study: North Atlantic: North Sea, ICES VIa and Icelandic Sea WP3 Case Study: Baltic Sea WP4 Case Study: Iberian Sea WP5 Case study: Mediterra -nean Sea WP6 BFT Swordfish Albacore end 2008 Synthesis & dissemination WP7 Project meetings Workshop shared information Steering committee meetings Links between work packages
Bluefin tuna Thunnus thynnus thynnus Large pelagic stock management is either nonexistent or not as extensive as compared to the other case study areas. Implementation of the existing regulations for the large pelagic species under study is not always observed.
Anthropogenic factor selected: Fisheries High fishing mortality both on juveniles and adults. Decline trends for R and SSB estimates. Anthropogenic factor under investigation: Endocrine disruption Evidence of intersexuality in the swordfish population of the Mediterranean. (17% of examined males) No data are available to evaluate the effects on the bluefin tuna and albacore populations in the Mediterranean Sea.
Way Forward for WP6 Large pelagics Access a) SST Data; b) NAO winter index (Hurrel). Global MED approach: access Data Banks from ICCAT and FAO and make general catch vs NAO/SST comparisons / analyses. Specific approach: select spawning and 3 main fishing statistic areas (east, central and western MED). Ascertain possibility of accessing raw data from EU and at National levels (for both global MED and specific approaches).
Non-anthropogenic factors selected: (climate factors) SST NAO/GSNW indices Salinity Mean Weight (in kg) 25 20 15 10 5 0 Age 3 Age 2 Age 1 Catch Influence on BFT spawning stock Influence on BFT recruitment Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months Mean weights of young BFT sampled from the French purse seine fleet between 1982 and 1998.
C. Ravier and J.-M. Fromentin 2004
Time series - General relationship
Influence of NAO (Hurrel) on Mediterranean Catch (ICCAT + FAO Data) 1970-2006 Lag Effects 0 offset 1970 1971 1972 1973 1974 NAO NAO NAO NAO NAO 0 +1 + 2 + 3 + 4 Catch Catch Catch Catch Catch
Simple linear regression Comparison Correlation between catch and NAO in the Mediterranean P value Tuna Catch 0 = 18161 + (556 * NAO ) R = 0,119 Rsqr = 0,0141 Adj Rsqr = 0,000 0,484 Tuna Catch +1 = 17838 + (1330 * NAO) R = 0,289 Rsqr = 0,0837 Adj Rsqr = 0,0568 0,087 Tuna Catch +2 = 17738 + (1815 * NAO) R = 0,406 Rsqr = 0,165 Adj Rsqr = 0,140 0,015 Tuna Catch +3 = 18212 + (1674 * NAO) R = 0,387 Rsqr = 0,150 Adj Rsqr = 0,123 0,024 Tuna Catch +4 = 18793 + (1462 * NAO) R = 0,351 Rsqr = 0,123 Adj Rsqr = 0,0950 0,045 Tuna Catch +5 = 18938+ (1534 * NAO) R = 0,373 Rsqr = 0,139 Adj Rsqr = 0,110 0,036 No corrrelation for Swordfish Catch and NAO No correlation for Albacore Catch and NAO
Rooker et al 2007 Heinisch et al 2007 REPRODOTT Project
Sea Surface Temperature: AVHRR Pathfinder SST v5
Software tool for extraction of SST data from HDF files Import data and choose dataset (e.g. SST, chloro.) Select area of interest in a rectangular or circular shape (line, point) Area may be selected by entering coordinates alternatively. Input decimal or degrees Download and save data on your local harddisk Choosen files will be listed here Select your area of interest easily in a zoomable map Once you selected your data, dataset and area of interest: Go and get my data!
Spawning Area Mean Monthly SST 1985-2006 Mean SST ( C) 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 Balearen Levantine Sea 1 2 3 4 5 6 7 8 9 10 11 12 Month of Year
Changes in SST Anom. from 1985-2006 for Balearen 3,0 2,0 1,0 0,0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006-1,0-2,0-3,0 YEAR Changes in SST Anom. from 1985-2006 for Levantine Sea 2 1,5 1 0,5 0-0,5-1 -1,5 JUNE JULY AUGUST SEPT SST ANOMALY ( C) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 YEAR JUNE JULY AUGUST SEPT SST Anomlay
Balearic Spawning Areas P-value June SST Anomaly = -144,708 + (0,0725 * YEAR) R = 0,536 Rsqr = 0,287 Adj Rsqr = 0,252 0,010 July SST Anomaly = -160,796 + (0,0806 * YEAR) R = 0,583 Rsqr = 0,339 Adj Rsqr = 0,306 0,004 August SST Anomaly = -77,303 + (0,0387 * YEAR) R = 0,354 Rsqr = 0,125 Adj Rsqr = 0,0814 0,106 September SST Anomaly = -31,602 + (0,0158 * YEAR) R = 0,135 Rsqr = 0,0183 Adj Rsqr = 0,000 0,548 Levantine Sea Spawning areas P-Value June SST Anomaly= -147,679 + (0,0740 * YEAR) R = 0,671 Rsqr = 0,450 Adj Rsqr = 0,422 <0,001 July SST Anomaly = -145,701 + (0,0730 * YEAR) R = 0,716 Rsqr = 0,513 Adj Rsqr = 0,489 <0,001 August SST Anomaly = -96,917 + (0,0486 * YEAR) R = 0,543 Rsqr = 0,294 Adj Rsqr = 0,259 0,009 Sept SST Anomaly = -79,373 + (0,0398 * YEAR) R = 0,479 Rsqr = 0,229 Adj Rsqr = 0,191 0,024 Balearic Spawning Areas SST Anom. No correlation with monthly or Hurrel NAO Levantine Sea Spawning Areas SST Anom. No correlation with monthly or Hurrel NAO
SST Anomaly in June v Tuna Catch 45000 40000 Tuna Catch (Metric Tonnes) 35000 30000 25000 20000 15000 10000 5000-3 -2-1 0 1 2 SST Anomaly in June June Cyprus SST Anomaly v Tuna Catch June Balearen SST Anomaly v Tuna Catch Tuna Catch = 24054 + (5720, * June SST Anom. Levantine Sea) R = 0,541 Rsqr = 0,293 Adj Rsqr = 0,257 P 0,009 Tuna Catch= 24071 + (2199 * June SST Anom. Balearen) R = 0,257 Rsqr = 0,0663 Adj Rsqr = 0,0196 P 0,247
FUTURE OUTLOOK Provide detailed fisheries data, from length, weight, age, maturation, etc., from which R, G, nm, M can be ascertained. Drawback historical series limited to perhaps 10 years. Apply these in FLR model (the best candidate) with help. Examine possible models for endocrine disruption. Evaluate comparative data from other species in other case studies.
This study is carried out with financial support from the Commission of the European Communities, specific RTD programme Specific Support to Policies, FP6 2004-SSP-4 Integrating and Strengthening the European Research Area. It does not necessarily reflect its views and in no way anticipates the Commission's future policy in this area