Climatic and marine environmental variations associated with fishing conditions of tuna species in the Indian Ocean

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1 Climatic and marine environmental variations associated with fishing conditions of tuna species in the Indian Ocean Kuo-Wei Lan and Ming-An Lee Department of Environmental Biology and Fisheries Science, National Taiwan Ocean University 2011 International Workshop on Climate and Ocean Fisheries Rarotonga, Cook Island 3-5 October, 2011

2 The environmental and climatological variability affects the distribution and production of tuna populations Skipjack tuna catches and ENSO in the Pacific Ocean CPUE(G) 29 C SOI El Niño El Nino La Niña El Nino La Nino (Lehodey et al., 1997) (Lu and Hseih et al., 2008)

3 High ST_105_Aomaly with High CPUE (a) Climate index- North Tropical Atlantic SST index EOF analysis for the tropical Atlantic SST anomalies (region 100 W 20 E, 30 S 30 N) to predict NTA using the 20 leading Empirical Orthogonal Functions. (Penland and Matrosova, 1998) (b) Low ST_105_Aomaly with low CPUE

4 Indian Ocean Dipole (IOD) and Dipole Mode Index (DMI) The Indian Ocean Dipole is a coupled ocean and atmosphere phenomenon in the equatorial Indian Ocean that affects the climate of Australia and other countries that surround the Indian Ocean basin (Saji et al. 1999). The Dipole Mode Index (DMI) is measured by the difference between SST in the western (50 E to 70 E and 10 S to 10 N) and eastern (90 E to 110 E and 10 S to 0 S) equatorial Indian Ocean SST anomalies are shaded (red color is for warm anomalies and blue is for cold). White patches indicate increased convective activities and arrows indicate anomalous wind directions during IOD events. (

5 The relationship of Indian Ocean Dipole ENSO Is there any connection between the ENSO and the IOD? It is shown by several researchers that the IOD in the Indian Ocean can evolve without the ENSO forcing from the tropical Pacific. (Saji et al.,1999) (Yamagata et al.,2003) However, some researchers argue positive phases of the IOD tend to co-occur with El Niño, and negative phases with La Niña. Izumo et al. (2010) indicated negative (positive) IODs tend to precede the development of El Niño (La Niña) events, whereas ENSO has no significant predictive skill of the IOD at one-year lead.

6 The Years of El Niño, La Niña, and Interactions with the Tropical Indian Ocean Composite averages of the SST anomaly (Meyers et al.,2007)

7 The Years of El Niño, La Niña, and Interactions with the Tropical Indian Ocean Percentage of years rainfall (Meyers et al.,2007)

8 Long-term trends and cycles of the standardized CPUE of the regular, deep longline, SST, Chl-a, D20 and DMI after seasonal adjustments Cross-wavelet coherence between environmental variables and standardized CPUE of the regular, deep longline

9 The purpose of present study For the tropical Pacific and Atlantic oceans, the apparent abundance of tuna species related to climatic oscillations have been recognized, but in the Indian Ocean a similar interaction has not yet been found. Topic 1: The catches and distributions of tuna species in relation to the climatic and marine environmental variations in the Indian Ocean. Topic 2: The large-scale climate change effect on the longline fishing grounds in the Indian Ocean. If we can know well of fishing ground through remote sensing and assimilation data, it will helpful for fishing management. This availability of oceanographic and biological information gained herein may be useful for the LL fishery and improve fishing operations as well as management of fishery resources.

10 The important commercially pelagic fish species catch by Taiwanese longline fishery in the Indian Ocean Super-cold freezers (Data source: IOTC)

11 The longline catch percentages of YFT, BET and ALB in the Indian Ocean Five sub fishing areas divided by Indian Ocean Tuna Commission (IOTC) in 2002 Yellowfin tuna (YFT) Bigeye tuna (BET) Albacore (ALB)

12 Flowchart of this dissertation Climatic and marine environmental variations associated with fishing conditions of tuna species in the Indian Ocean Data collecting Longline Fishery data IOTC 5 5 data ( ) Taiwanese 5 5 data ( ) Observer data ( ) Climatic and Environmental data Climatic Dipole Mode Index ( ) Environmental Pathfinder SST ( , 4x4 km) Net Primary Production ( , 9 9km) Monthly nominal CPUE Analysis method Time series analysis State-space time series Wavelet analysis Optimum SST and NPP Generalized additive models Histogram frequency Climatic variations effects on fishing condition Climate Change effects on fishing grounds Result and Discussion Distribution and concentration of tuna species SST increases of 1 C, 2 C and 4 C General summary, conclusion and recommendation

13 Cross-wavelet coherence between Dipole Mode Index (DMI) and tuna species CPUE in the Indian Ocean ( ) YFT - DMI It showed a long-term negative significant coherence between the YFT CPUE and DMI with a periodicity of 4 yr. ALB - DMI BET - DMI Time The solid black contour encloses regions of >95% confidence and the black lines indicates the cone of influence where edge effects become important. The phase relationship is shown as arrows, with in-phase pointing right, anti-phase pointing left.

14 The variations of the DMI and CPUE of yellowfin tuna in the Indian Ocean DMI YFT_CPU E_W 1960 YFT CPUE in the western Indian Ocean CPUE (fish/10 3 hooks) YFT_CPUE_E YFT CPUE in the eastern Indian Ocean CPUE (fish/10 3 hooks)

15 The distribution of yellowfin tuna nominal CPUE in the Indian Ocean YFT CPUE Mean ( ) 3 2 Positive IOD events (DMI+) 1 DMI 0-1 CPUE -2 Negative IOD events (DMI-) Positive IOD events (DMI+) Negative IOD events (DMI-) CPUE CPUE (1962,1986,1972,1975,1982,1987,1991,1994,1997,1999, 2003,2008) (1960, 1965, 1966, 1968, 1971, 1977, 1986, 1992, 1993, 1996, 2004, 2005)

16 The monthly mean CPUE of YFT in the western and eastern Indian Ocean Western Indian Ocean 12 Negative events Mean ( ) CPUE (fish/10 3 hooks) Positive events Eastern Indian Ocean CPUE (fish/10 3 hooks) Month Negative events Mean ( ) Positive events Month

17 YFT catch gravity in relation to DMI during the fishing seasons in the Indian Ocean YFT catch gravity (black line) Dipole Mode Index (gray line) By matching the YFT s concentration with climate variability of DMI, the variation trend was quite similar in the Indian Ocean.

18 YFT catch gravity in relation to zonal average of SST, NPP and DMI during the fishing seasons in the Indian Ocean SST zonal average YFT catch gravity (purple line) NPP zonal average CPUE ( C)

19 The relationship of SST, NPP and high YFT CPUE for in the Indian Ocean SST and High CPUE (>1.8) C GAM- SST and CPUE Taiwanese longlone observer data ( ) Percentage(%) SST( C) SST( C) 14 NPP and High CPUE (>1.8) GAM- NPP and CPUE Percentage(%) mg C/m 2 /d NPP (mg C/m 2 /d) NPP (mg C/m 2 /d) By using the Histograms and GAM analysis indicated that high YFT CPUEs were in the areas with sea surface temperature (SST) range of C and net primary production (NPP) in the range of mg C/m 2 /d.

20 Predicted optimal SST and NPP areas of higher YFT abundances Pathfinder AVHRR SST map MODIS NPP map (mg C/m 2 /d) Optimal SST map Optimal NPP map High SST (>29.5 C) Optimal SST ( C) Low SST (<26 C) High NPP >380 mg C/m2 /d Optimal NPP mg C/m2 /d Low NPP mg C/m 2 /d

21 Comparison of the optimal SST and NPP maps in negative and positive events Positive Event Optimal SST map (2007/05) Optimal NPP map (2007/05) High SST (>29.5 C) Optimal SST ( C) Low SST (<26 C) High NPP >380 mg C/m2 /d Optimal NPP Low NPP mg C/m 2 /d mg C/m 2 /d Negative Event Optimal SST map (2004/05) Optimal NPP map (2004/05) High SST (>29.5 C) Optimal SST ( C) Low SST (<26 C) High NPP >380 mg C/m2 /d Optimal NPP mg C/m 2 /d Low NPP mg C/m 2 /d

22 Comparisons of the potential fishing grounds in the positive and negative events CPUE

23 Positive (warm) and negative (cold) episodes associated with YFT fishing conditions in the Indian Ocean Positive DMI Event Increasing of SST, decreasing NPP in the western Indian Ocean Caused lower CPUE of YFT in the western Indian Ocean Negative DMI Event Decreasing of SST, increasing NPP in the western Indian Ocean Caused higher CPUE of YFT in the western Indian Ocean

24 Climate variability and purse seine catch rates in the West tropical Indian Ocean (Marsac, 2008)

25 Comparison of yellowfin tuna CPUE in the Atlantic and Indian Ocean Atlantic Ocean Indian Ocean Catch (N) CPUE 20 Catch (kg) CPUE Pacific Ocean?

26 Predicted Climate Change effects on YFT longline fishing grounds High SST (>29.5 C) Optimal SST ( C) Low SST (<26 C)

27 Conclusion The advanced time series analysis showed the significant coherence between the DMI and YFT CPUE with a periodicity of 2-3 yr. The DMI was also found to be negatively correlated with YFT CPUE in the western Indian Ocean. The areas with high CPUE were deceased in the western Indian Ocean during the positive IOD events and increased in the negative IOD events. Catch gravity of YFT would also migrated to the eastern (western) site of tropical Indian Ocean during the positive (negative) IOD events. It was suggested that decreasing the optimal areas of SST and NPP during the positive IOD events would cause the decrease YFT CPUE in the western Indian Ocean, while increasing the optimal areas would result in increasing YFT CPUE in the negative IOD events.

28 Thank you for your attention!

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