Syamsuddm et at: Effects of El Nino-Southern Oscillation on catches of Thunnus obesus in the eastern Indian Ocean 
185 
105°E 1 1 0°E 1 1 5°E 1 20°E 125°E 
1 05°E 1 1 0°E 1 1 5°E 120°E 125°E 
% Probability 
0 20 40 60 80 100 
Figure 7 
Spatial prediction for catch probabilities of Bigeye Tuna ( Thunnus obesus) overlaid with actual fishing 
locations of Bigeye Tuna catch in the eastern Indian Ocean off Java for the El Nino event in (A) Sep- 
tember 1997 and (B) October 1997 and for the La Nina event in (C) March 1999 and (D) April 1999. 
Color bars show the level of predicted catch probability of one or more Bigeye Tuna catches (0-100%); 
blue indicates the lowest catch probability (0), and red indicates the highest catch probability (100%). 
Circles outlined in black show the actual fishing locations for Bigeye Tuna catch (1° intervals). The 
original data set was gridded in 1° increments and smoothed for the purposes of better visualization. 
lowest contribution to the model prediction. However, 
the derived relationship between this parameter and 
catches of Bigeye Tuna was statistically significant 
(PcO.OOOl). Bigeye Tuna fishing sets were located in 
waters with relatively low-to-moderate chlorophyll- 
a values. Chlorophyll-a data is a valuable proxy for 
water mass boundaries and upwelling events. Overall, 
the GAM results showed that the distribution of Big- 
eye Tuna catch in the study area was influenced pri- 
marily by SST and SSHA. The lag time in food chain 
processes may explain the rather weak effect of chlo- 
rophyll-a concentration on HR. 
Bigeye Tuna catchability could be influenced by 
many factors, in addition to oceanographic parame- 
ters, such as the depth range of longline sets, dura- 
tion of longline operations, competition among gears, 
number of hooks, and experience level of the fisher- 
men (Polacheck, 1991; Ward, 2008). In this study, the 
fishermen used the same fishing gear with similar 
fishing techniques. Therefore, we assumed that differ- 
ences in fishing gear did not affect the catchability of 
Bigeye Tuna and we considered the number of hooks 
and environmental conditions to explain the catch- 
ability of Bigeye Tuna. Catchability fluctuated within 
and between years in relation to the number of hooks. 
During El Nino, high catchability coefficients occurred 
in May 1997 (1.56xl(D 7 ) and June 1998 ( 1.47x HD 7 ), 
coinciding with high HR of 0.94 and 0.83, respectively. 
This high coefficient number of catchability could be 
due to the higher number of hooks and catch of Bigeye 
Tuna during El Nino events related to oceanographic 
conditions favorable to Bigeye Tuna. The favorable 
oceanographic conditions were indicated by negative 
SSHA and by a colder SST than the normal condi- 
tion of around 28-29°C. Marsac and Blanc (1999) re- 
ported that the anomalous upwelling conditions that 
occurred in the EIO, providing biological enrichment 
and a shallower thermocline, should have favored 
catchability in the purse-seine fishery for Bigeye Tuna 
during the 1997-98 El Nino. The catchability coeffi- 
cient for November 2000 in our study appeared as an 
outlier. In that month, adverse weather conditions re- 
sulted in a decreased number of hooks and a lower 
HR; the increased catchability may have been due to 
the reduced fishing competition among longliners. 
The favorable oceanographic conditions for Bigeye 
Tuna catches during El Nino resulted in increasing 
predicted catch probabilities for Bigeye Tuna. The 
predicted distribution of Bigeye Tuna catch during El 
Nino showed a potential area with higher catch prob- 
ability compared with catch probability for La Nina 
events. Between the El Nino and La Nina events, fish- 
ing effort within the fishing grounds did not shift as 
much as did the predicted tuna habitat. Most catches 
