North Atlantic Oscillation affects dolphinfish as target and bycatch species in fisheries from the western Mediterranean Sea

• ¹ Oceanographic Center of Málaga, Spanish Institute of Oceanography (IEO), Spain
• ² Other, Spain
• ³ Other, Spain
• ⁴ Other, Italy

Dolphinfish (Coryphaena hippurus) in the western Mediterranean Sea support both commercial small-scale fishing and recreational fisheries. This species is also caught as a bycatch of drifting longline fisheries. The Western Mediterranean Sea is an important fishing ground where a Spanish drifting longline fleet operates targeting mainly swordfish Xiphias gladius, bluefin tuna Thunnus thynnus and albacore T. alalunga. The North Atlantic Oscillation (NAO) reflects fluctuations in atmospheric pressure at sea–level between the Icelandic Low and the Azores High. The NAO is associated with many meteorological variations in the North Atlantic region, affecting wind speed and direction and differences in temperature and rainfall. The NAO is a dominant pattern of coupled ocean–climate variability in the North Atlantic and Mediterranean basin. Many authors have observed a relationship between the NAO and changes in fishery target species abundance and recruitment. The main aim of the present study is to understand the effect of NAO on the capture per unit effort of dolphinfish (CPUE) in Spanish drifting longline from Western Mediterranean Sea. This is basic to improve the assessment and management of the Mediterranean dolphinfish stocks. Catch and effort data for longline fisheries were collected in the framework of the Spanish Oceanographic Institute (IEO) on-board observer training Program, planned according to ICCAT recommendations. The IEO on-board observer Program provided commercial fish catch and bycatch data collected on-board longline vessels from 2000 to 2014. During the selected period, six metiers have been described : LLALB, Drifting surface longliners targeting albacore; LLHB, Traditional longliners targeting swordfish; LLAM, American longliners targeting swordfish; LLJAP, Drifting surface longliners targeting bluefin tuna; LLSP, Drifting semi-pelagic longliners targeting swordfish; and LLPB, Demersal longliners targeting swordfish. Of the 6 longline gears (metiers) pointed above, the LLHB and LLALB are the longlines gears that captured more dolphinfishes. Thus, for the current series we observed a correlation in the CPUE of the dolphinfish (r= 0.88; P=0.049). Thus due to the gaps per months observed in the series both LLALB and LLHB, and the high correlation between LLHB and LLALB CPUE of dolphinfish bycatch, we analyzed together both LLHB and LLALB gears. Therefore we estimated the CPUE of the dolphinfish between 20 and 80 cm in length, for the period between September and December of the years 2000 to 2014 pooling together the LLHB and LLALB gears. We use the NAO as a global climate index to describe the climatic conditions of the fishing area, theoretically affecting dolphinfish. Monthly values used of the NAO index were taken from the website of the USA National Oceanic and Atmospheric Administration: http://www.cpc.noaa.gov/products/precip/CWlink/pna/nao_index.html, and fttp://www.esrl.noaa.gov/psd/data/correlation/ao.data. The atmospheric oscillations present strong inter–annual and intra–annual variability. However, several studies have shown that changes in NAO trends have a delayed effect on aquatic ecosystems due to ecosystem inertia. For this reason, we used monthly gap, between one to six months. To find the relationship between NAO index and the number of dolphinfish per each 1000 hooks (i.e. CPUE of dolphinfish), we performed a logistic model, a binary logistic stepwise forward/backward regression to test whether the probability of obtain a CPUE of dolphinfish in the longline was to higher than mean or lower, in function to the NAO as an independent variable. Model` coefficients were assessed by means of an omnibus test and the goodness-of-fit between expected and observed proportions of by-catch events along ten classes of probability values and evaluated using the Hosmer and Lemeshow test (which also follows a Chi-square distribution; low p-0.05 would indicate lack of fit of the model). The Omnibus test examines whether there are significant differences between the -2LL (less than twice the natural logarithm of the likelihood) of the initial step, and the -2LL of the model, using a Chi-squared test with one degree of freedom. On the other hand, the Hosmer and Lemeshow test compares the observed and expected frequencies of each value of the binomial variable according to their probability. In addition, the discrimination capacity of the model (trade-off between sensitivity and specificity) was evaluated with the receiving operating characteristic (ROC) curve. Furthermore, the area under the ROC curve (AUC) provides a scalar value representing the expected discrimination capacity of the model. The relative importance of each variable within the model was assessed using the Wald test. The Figure 1 shows the spatial distribution of observed fishing effort of dolphinfish by-caught in drifting longline. For the monthly longline CPUE, we obtained a statistically significant logistic model, with the variables NAO1 previous month (NAO1) and NAO6 previous months (NAO6). The model's goodness-of fit-was significant according to the Omnibus test (Omnibus test= 10,532, df= 2, P < 0.01; Hosmer and Lemeshow test= 3.094, df= 7, P= 0.876), and its discrimination capacity was good (AUC = 0.8779). The logit function from logistic regression was: logit= -1.68-1.053*NAO1+1.019*NAO6 Studies on the impact of climate change on exploited marine fishes are numerous. However, the impact of these effects is hard to predict due to the inherent uncertainty in these models, and the lack of knowledge on the biological response of the target species in short time periods. Thus, some authors have modelled the response of marine species to large-scale climate phenomena, such as the NAO or El Niño South Oscillation (ENSO). Thus, through the response to climatic oscillations, the resilience capacity of marine resources can be understood. In the case of the dolphinfish from the Mediterranean Sea, our results indicate a strong linkage between NAO and CPUE of dolphinfish in the Spanish longline fleet in the Western Mediterranean, which could relate to processes affecting dolphinfish abundance, availability and catchability to the fleet. The stronger relationship with the NAO index with 6 month gap could indicate a possible effect of the NAO on the recruitment of dolphinfish to the Spanish Mediterranean fishery. Dolphinfish are fast growing species, reaching the sizes ranges analyzed in this paper (20 to 80 cm) in last than 6 months. A positive NAO phase results in dry and stable periods on Mediterranean areas. These prevailing conditions could favour dolphin fish larval survival.