No abstract

Satellite-based oceanographic data of sea surface temperature (SST), sea surface chlorophyll-a concentration (SSC), and sea surface height anomaly (SSHA) together with catch data were used to investigate the relationship between albacore fishing ground and oceanographic conditions and also to predict potential habitats for albacore in the western North Pacific Ocean. Empirical cumulative distribution function and high catch data analyses were used to calculate preferred ranges of the three oceanographic conditions. Results indicate that highest catch per unit efforts (CPUEs) corresponded with areas of SST 18.5-21.5°C, SSC 0.2-0.4 mg m )3 , and SSHA )5.0 to 32.2 cm during the winter in the period 1998-2000. We used these ranges to generate a simple prediction map for detecting potential fishing grounds. Statistically, to predict spatial patterns of potential albacore habitats, we applied a combined generalized additive model (GAM) ⁄ generalized linear model (GLM). To build our model, we first constructed a GAM as an exploratory tool to identify the functional relationships between the environmental variables and CPUE; we then made parameters out of these relationships using the GLM to generate a robust prediction tool. The areas of highest CPUEs predicted by the models were consistent with the potential habitats on the simple prediction map and observation data, suggesting that the dynamics of ocean eddies (November 1998 and2000) and fronts (November 1999) may account for the spatial patterns of highest albacore catch rates predicted in the study area. The results also suggest that multispectrum satellite data can provide useful information to characterize and predict potential tuna habitats.

To describe potential fishing ground of albacore in relation to dynamics of bio‐physical of their environments, and to clarify impact of El Niño 1998 and La Niña 1999 on tuna fishery, satellite images of SST (TRMM/TMI and NOAA/AVHRR) and SSC (SeaWiFS) together with catch data were used. The 20°C SST and the 0.3 mg m−3 SSC were considered as good indicators of the productive fishing ground. Results showed that a small distance between latitudinal mean position of the SST and the SSC during winter term tended to significantly increase CPUEs. We suggest that albacore fishing grounds highly associated with the confluence of these proxy indicators where the fronts may well develop. These represent the meeting of optimum combination of chlorophyll and temperature fronts which capable of creating potential fishing ground. The proxy indicators appeared to well meet in La Niña 1999 in comparison to El Niño period in 1998.

Using remote sensing of sea surface temperature (SST), sea surface height anomaly (SSHA) and chlorophyll-a (Chl-a) together with catch data, we investigated the detection and persistence of important pelagic habitat hotspots for skipjack tuna in the Gulf of Bone-Flores Sea, Indonesia. We analyzed the data for the period between the northwest and southeast monsoon 2007–2011. A pelagic hotspot index was constructed from a model of multi-spectrum satellite-based oceanographic data in relation to skipjack fishing performance. Results showed that skipjack catch per unit efforts (CPUEs) increased significantly in areas of highest pelagic hotspot indices. The distribution and dynamics of habitat hotspots were detected by the synoptic measurements of SST, SSHA and Chl-a ranging from 29.5° to 31.5°C, from 2.5 to 12.5 cm and from 0.15 to 0.35 mg m-3, respectively. Total area of hotspots consistently peaked in May. Validation of skipjack CPUE predicted by our model against observed data from 2012 was highly significant. The key pelagic habitat corresponded with the Chl-a front, which could be related to the areas of relatively high prey abundance (enhanced feeding opportunity) for skipjack. We found that the area and persistence of the potential skipjack habitat hotspots for the 5 years were clearly identified by the 0.2 mg m-3 Chl-a isopleth, suggesting that the Chl-a front provides a key oceanographic indicator for global understanding on skipjack tuna habitat hotspots in the western tropical Pacific Ocean, especially within Coral Triangle tuna.

Potential fishing zones for skipjack tuna in the Bone Bay-Flores Sea were investigated from satellite-based oceanography and catch data, using a linear model (generalized linear model) constructed from generalized additive models and geographic information systems. Monthly mean remotely sensed sea surface temperature and surface chlorophyll-a concentration during the southeast monsoon (April-August) were used for the year 2012. The best generalized additive model was selected to assess the effect of marine environment variables (sea surface temperature and chlorophyll-a concentration) on skipjack tuna abundance (catch per unit effort). Then, the appropriate linear model was constructed from the functional relationship of the generalized additive model for generating a robust predictive model. Model selection process for the generalized additive model was based on significance of model terms, decrease in residual deviance, and increase in cumulative variance explained, whereas the model selection for the linear model was based on decrease in residual deviance, reduction in Akaike’s Information Criterion, increasing cumulative variance explained and significance of model terms. The best model was selected to predict skipjack tuna abundance and their spatial distribution patterns over entire study area. A simple linear model was used to verify the predicted values. Results indicated that the distribution pattern of potential fishing zones for skipjack during the southeast monsoon were well characterized by sea surface temperatures ranging from 28.5℃ to 30.5 ℃ and chlorophyll-a ranging from 0.10 to 0.20 mg·m^-3. Predicted highest catch per unit efforts were significantly consistent with the fishing data (P < 0.01, R² = 0.8), suggesting that the oceanographic indicators may correspond well with the potential feeding ground for skipjack tuna. This good feeding opportunity for skipjack was driven the dynamics of upwelling operating within study area which are capable of creating a highly potential fishing zone during the southeast monsoon.