DOES THE NORTH ATLANTIC OSCILLATION

SCRS/01/33

DOES THE NORTH ATLANTIC OSCILLATION CONTROL SOME PROCESSES INFLUENCING RECRUITMENT OF TEMPERATE TUNAS? by Ángel Borja1and Josu Santiago

ABSTRACT Environmental and climatic variability affects the distribution and recruitment of fish populations. AZTI has studied the relationships between some environmental processes generated by NAO and the recruitment of three tuna stocks: western and eastern bluefin (Thunnus thynnus) and northern albacore (Thunnus alalunga). The first study on these species was presented by Santiago (1997), considering the time period 1969-1992; on this study we present the most recent years, from 1969 to 1995. The state of the NAO controls the temporal fluctuations in the speed an direction of the surface westerlies across the mid-latitudes of the North Atlantic; influencing on temperature, precipitation and biological aspects of oceanography, such as the recruitment. Regression analysis indicates statistically significant relationship between NAO an eastern bluefin tuna recruitment at the 95% confidence level; at the 99% in the case of northern albacore; and the no existence of significant relationship between NAO and western bluefin recruitment. The relation of NAO with eastern bluefin is direct whereas it is inverse for northern albacore. KEY WORDS NAO, Thunnus thynnus, Thunnus alalunga, time series analysis, recruitment, environmental conditions, environmental effects, long-term changes INTRODUCTION There is ample evidence that environmental and climatological variability affects the distribution and production of tuna populations (Anon, 1989; ICCAT, 1997a). Some years ago, increased attention has been focused on the effect of environment in the dynamics of temperate tunas in the Atlantic Ocean, particularly albacore, Thunnus alalunga (ICCAT, 1994, 1997b). Albacore and bluefin (Thunnus thynnus) are temperate tunas widely distributed throughout the Atlantic Ocean and the Mediterranean. The Standing Committee for Research and Statistics (SCRS) of ICCAT assumes the existence of two bluefin tuna stocks in this ocean, West and East Atlantic (including the Mediterranean), and three albacore stocks, northern, southern and Mediterranean stocks. With the exception of the Mediterranean albacore, from which little information is available, temperate tuna stocks of the Northern Hemisphere are regularly assessed by the SCRS using tuned VPAs. Recent assessments on these stocks conducted by the SCRS have pointed out that the estimated levels of recruitment of eastern Atlantic bluefin tuna were 50% lower on average during the 70s than for the 1981-1992 period (ICCAT, 1997b). On the contrary, northern albacore recruitment estimates during the 70s were on average higher,

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AZTI. Herrera Kaia; Portualdea s/n; 20110 Pasaia (Gipuzkoa); Spain

e-mail: [email protected]

with a declining trend from 1975 to 1984. For both stocks, potential model-data interactions or deficiencies have been proposed as possible cause of the apparent wide differences in the estimated levels of recruitment. Another reason enunciated for the divergence in the recent level of recruitment, at least in the case of North Atlantic albacore, has been a possible role of long-term environmental changes in the dynamics of this stock (ICCAT, 1994, 1997b). Similar hypotheses have been proposed to explain periods of failures of albacore and bluefin tuna catches in the North Pacific. Thus Au (1995) shows the coincidence of periods of intensified atmospheric circulation in the North Pacific with declines in albacore CPUEs. And Polovina (1996) hypothesizes that the decline in the catches of bluefin in the eastern Pacific is due to a decline in the proportion of migrants from the western Pacific, in relation to climate-induced changes in prey abundance. Bard & Joanny (1996) argue that the inherent oceanographic stability of the Atlantic, compared to the Pacific Ocean, makes doubtful the hypothesis of a natural decline in North Atlantic albacore recruitment driven by environmental factors. Nevertheless, the relative stability in this ocean, if true, would be very far from being not significant. There are multiple examples where the variability of environmental factors has successfully explained changes in abundance and distribution of Atlantic fish populations (Cushing, 1982; Sissenwine, 1984; Wooster & Bailey, 1989, Beamish, 1995). Perhaps the most classical example is the climatically driven Russell Cycle in the North Atlantic. The purpose of this paper is to explore the incidence of long-term environmental variability on the recruitment of temperate tunas in the North Atlantic (western and eastern bluefin and northern albacore), following the first study on these species which was presented by Santiago (1997). He considered the time period 1969-1992; on this study we present the most recent years, from 1969 to 1995. The investigation is focused on the North Atlantic Oscillation (NAO), a global atmospheric pattern that constitutes a major source of interannual variability in the atmospheric circulation (Hurrell, 1995). This pattern is directly associated with changes in the band of westerly winds in middle latitudes (Rogers, 1985) which are the dominant feature in the weather and climate of the earth (Lamb, 1982). THE NORTH ATLANTIC OSCILLATION (NAO) The term North Atlantic Oscillation (NAO) refers to a large-scale alternation of atmospheric mass between the North Atlantic regions of subtropical high surface pressure and subpolar low surface pressure (Lamb & Peppler, 1987). These pressure field features are known as the Azores high, centred on the Azores, and the Icelandic low, centred on Iceland and extending east and south of Greenland. The NAO is a well-documented pattern both in pressure and temperature fields. It was first identified by G. Walker in the 1920s. He defined and named three coherent ‘oscillations’ in atmospheric variables between large regions of the earth’s surface: the Southern Oscillation, the North Pacific Oscillation and the North Atlantic Oscillation (Allan et al., 1996). The NAO constitutes the principal teleconnection pattern in the North Atlantic (Hurrell, 1995; Rodionov, 1995). The oscillation is present throughout the year but it is stronger during the winter months (Lamb et al, 1996). It is the dominant mode of variability of the surface atmospheric circulation in the North Atlantic and accounts for more than 36% of the variance of the mean December to March sea level pressure (SLP) (Hurrell, 1995). The state of the NAO controls the temporal fluctuations in the speed and direction of the surface westerlies across the mid-latitudes of the North Atlantic (Rogers, 1985), as well as the meridional heat and moisture transport (Hurrell, 1995). This results in changes in temperature and precipitation patterns over the North Atlantic and surrounding landmasses (Lamb & Peppler, 1987; Hurrell, 1995, 1996; Lamb et al., 1996). In addition to the association between the NAO and different large-scale atmospheric and oceanographic events, some biological processes in the North Atlantic has also been connected to this pattern. Thus, Fromentin & Planque (1996) evidence the influence of NAO on two Calanus species of the eastern North Atlantic and the North Sea; and Rodionov (1995) relates NAO and recruitment of North Atlantic cod stocks. The NAO index is defined as the difference in normalised SLP anomalies at or near the centres of teleconnection, and is usually calculated for the winter months (Rogers, 1984). Figure 1 shows the winter (December through March) index of the NAO based on the difference of normalised SLP anomalies between Lisbon (Portugal)

and Stykkisholmur (Iceland) from 1900 through 1997 (data provided by Jim Hurrell, pers. comm.). The 5-year running mean is also shown to bring out decadal and general trends. A high index reflects an enhanced poleward surface pressure gradient, associated with strong westerlies across the North Atlantic, low temperatures in Greenland and the east coast of Canada and warmer temperatures in western Europe. And a low index, the opposite: the pressure gradient is reduced, implying weaker westerlies, warmer temperatures in the Greenland area, and colder situation in Western Europe. Figure 1 evidences that there is considerable interannual variability in the NAO index. However, analysing the general trend (5-year running average) of the series, it is possible to distinguish four major periods: (1) 1900-1930, with the NAO index in general above the mean; (2) 1930-1950, when the index varies largely around the mean, over short periods, without tendency; (3) 1950-1970, with a clear downward trend and index values well below the mean; and (4) 1970-1995, period of large decadal variability and a general upward trend. Within this period, the 1983-1995 interval is characterised by unusually high values of the NAO index; in fact, the years 1983, 1989, 1990 and 1995 present the highest positive values of the NAO index recorded since the beginning of the century. The situation in 1996 has changed dramatically. The previous high positive anomalies observed during the recent years turned into the strongly negative anomaly of 1996, indicating a relaxation of the atmospheric circulation in the North Atlantic during this year. RECRUITMENT2 OF TEMPERATE TUNAS IN THE NORTH ATLANTIC There is not universal agreement on the stage of development when year-class strength is established in marine fish populations (Wooster & Bailey, 1989). The critical period of recruitment definition has been proposed to take place at very different phases of the early life history: from the early phases of larval development to later larvae or juvenile phase. According to Sissenwine (1984) recruitment is likely to be a multiplicative function of highly variable processes occurring throughout the first year of life, including the post-larval stage. As regards bluefin and albacore in the North Atlantic and the Mediterranean, little information exits regarding the spawning and the different developmental stages during their first year of life (Bard, 1981; Clay, 1991; Cort, 1995; ICCAT, 1996). In the following paragraphs a brief summary of what is known about early life stages of these stocks is presented together with the most recent estimates of recruitment obtained by the SCRS of ICCAT (ICCAT, 1997b, 2000). Bluefin (Thunnus thynnus) For assessment purposes, it is assumed the existence of two bluefin stocks in the Atlantic Ocean, East and West of 45ºW; the eastern stock includes the Mediterranean Sea. There is controversy however about the adequacy of this assumption due to some movements of individuals observed between both units (ICCAT, 1997). Eastern stock: Spawning seems to take place from June to August in waters of the western Mediterranean, including the Adriatic Sea. The highest concentrations of larvae are found between the Balearic Islands, Corsica and Sicily. Although little is known about the wintering areas, zero age fish are supposed to overwinter along the Moroccan coast and in the Canary Islands (Cort & Liourzu, 1991a,b). Western stock: Major spawning areas are located in the Gulf of Mexico and the Florida Straits where eggs are laid between April and June, somewhat earlier than in the western spawning ground. Zero age fish appear to migrate northward to the Cape Hatteras-Cape Cod area in mid summer. In October they migrate south to overwinter in the Sargasso Sea area (Rivas, 1977; Suzuki, 1991a,b). However, as in the case of albacore, the wintering areas of the zero age fish are not well known.

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The term recruitment refers here to the year-class strength when entering the fishery; it does not refer to what is known as ‘biological recruitment’, that is, when entering the reproductive population.

Figures 2a,b illustrate the spawning areas of both stocks and the most likely distribution during the first year of life. Table 1 and Figures 3a,b show the recruitment estimates, for the period corresponding to the 1969-1994 yearclasses, for both bluefin tuna stocks extracted from the ICCAT (1997) report. In the case of the eastern stock, recruitment shows a general upward trend. During the 70s it was relatively poor (average of 0.79 millions) compared to the 80s ands early 90s (average of 1.59 millions). Some decadal variability is also appreciable. The situation is very different in the case of the western bluefin tuna. The series starts with a decreasing trend during the 70s, from 0.33 to only 0.07 millions. This trend was interrupted by the particularly strong 1973 yearclass, with 0.49 millions of one-year-olds in 1974. The 80´s show stabilization at a low level between 0.06 and 0.12 millions, to decrease again during the recent years to the lowest levels of the analysed series. Albacore (Thunnus alalunga) Three stocks are assumed to inhabit the Atlantic and the Mediterranean. In this paper we will only refer to the population of North Atlantic. Again there is very little information on the spawning, early phases and the factors that affect the first year of life in this population (Bard, 1981; ICCAT, 1996). Spawning seems to take place in the western tropical Atlantic, in the Sargasso Sea area, during the spring-summer months. Observations of albacore larvae are rare in the North Atlantic; occurrences in the Sargasso have been documented by Ueyanagi (1971) and Nishikawa et al. (1985) (cited by Bard,1981). There is only testimonial information as regards the period between the larval phase in the western Atlantic and when they appear for the first time in the summer surface fishery in the eastern Atlantic (with more than 45 cm). Thus, Spanish fishermen referred the appearance of small albacore (less than 30 cm) in the Caribbean area during the colonial period in Cuba; and between 38-45 cm in areas off the Portuguese coast in October. In rare occasions the surface fishery of the Bay of Biscay catch individuals smaller than 40 cm. Figure 2c shows for the North Atlantic albacore the hypothetical spatial distribution of the spawning ground and the juvenile phase during the first year of life. Table 1 and Figure 3c show the recruitment estimates for the period 1969-1995 extracted from the ICCAT (2000) report, with the addition of the 1969-1973 period estimated by Bard (1981). The series shows a general downward trend, specially until mid-80s, interrupted by the strong 1977 year-class (1 year-old in 1978). From 1984 onwards recruitment appears to stabilise at a level between 8 and 11 millions. DOES THE NAO AFFECT RECRUITMENT OF TEMPERATE TUNAS ? As mentioned before, NAO dominates the surface atmospheric circulation in the North Atlantic affecting several atmospheric, oceanographic and biological processes. In the analysis presented in this work, the winter (December through March) index of the NAO has been selected due to the major strength of this pattern during the winter months. And, taking into account the characteristics of spring-summer spawners of the three tuna stocks considered, the possible effect of winter NAO on the definition of year-class strength may take place at various periods of the early life history. Figure 4 illustrates this consideration. In this diagram, the number of recruits at the beginning of year i+1 represents the strength of year-class i (Ri). It may be influenced by both NAO in year i (affecting the establishment of the ecosystem conditions at the beginning of the critical period of recruitment definition) and in year i+1 (affecting the overwintering conditions in the first year of life). Figures 3a-c show two different general patterns in the evolution of the recruitment of the three stocks considered: the trend displayed is upward, in conjunction with the NAO index, in the case of eastern bluefin tuna; and opposite to the trend exhibited by NAO in the case of western bluefin and northern albacore. It is also evident that the development of western bluefin recruitment during the analysed period is completely independent of the NAO evolution, especially after 1976 when recruitment stabilises at a very low level. The trend of recruitment of eastern bluefin tuna, as indicated by the 3-year running means, show some general synchrony with the NAO index. Periods of local maxima of the circulation index are associated with periods of increment in eastern bluefin recruitment; that is the case for the periods 1973-1976, 1982-1984 and 1989-1990. On

the other hand, periods of local minima, 1969-1971, 1977-1979 and 1984-1986, are in general associated with cycles of recruitment declining. The connection between the NAO pattern and recruitment trend is also evident for northern albacore. But in this case the trends are opposite; that is, periods of accentuated atmospheric circulation in the North Atlantic, i.e. high NAO years, are associated with reductions of albacore recruitment levels. On the contrary, low NAO situations appear associated with increments in year-class strength of albacore. Figure 5 shows mean recruitments estimated for the three stocks concerned in situations of low (< -1.8) and high (>2) NAO index. For both eastern bluefin and northern albacore, t-test indicates that there is a statistically significant difference at the 98% level between recruitments estimated for extreme situations of NAO. In the case of eastern bluefin (p=0.025), mean recruitment during high NAO situations is near double of the estimated for low NAO conditions. Oppositely, in the case of northern albacore (p=0.0001), recruitment during high NAO years is near half than during low NAO years. There are no differences in the case of western bluefin recruitment in NAO extreme situations (p=0.47). Other approximation to this comparison could be the use of the superposed epoch analysis (SEA) (Prager and Hoenig, 1989), which permits testing the impacts of extreme values of an extrinsic factor (e.g., NAO) on a given biological variable, without taking into account time contiguity (see ICCAT, 2001). Here, the null hypothesis of SEA is: there is no association between extreme NAO values (low or high) and tuna year-class strength. The extreme events are defined as the years during which the values of the NAO/NPI index are higher (lower) than the average plus (minus) one standard deviation. Adjacent years are defined as the years before and/or after each key-event year. SEA consists, then, in comparing (through a t-test) the values of tuna recruitment of the key-event years with those of the adjacent years (the significance being estimated by a Monte Carlo randomisation procedure). No significant relationships were found with extreme high NAO events, in contradiction with the above ttest analysis. It was noted that the extreme high NAO events occurred toward the end of the time series. For north Atlantic albacore, this corresponded with a period in which the variability in recruitment estimates is low and for which there are concerns about the accuracy of these recruitment estimates. These factors may have inhibited the ability to detect relationships between albacore recruitment and the high NAO events. Significant relationships were found with low NAO events and bluefin and albacore. However, for bluefin, there were factors that may call into question the conclusion of significance. The majority of the key event years fell adjacent to each other early in the time period. Therefore, the key event years in some cases were also components of the adjacent year sample, a situation which likely diminishes the robustness of the SEA. Additionally, a significant relationship was only found when the key event years were compared to adjacent prior years. Analyses for bluefin incorporating adjacent years following the key events did not show significance. In contrast, the results for albacore showed significance in all cases. Results from the regression analysis between the NAO index and recruitment estimates are shown in Table 2. P-values in the ANOVA tables indicate statistically significant relationship between NAO i and recruitment Ri at the 99% level in the case of northern albacore (p=0.0001); and the no existence of a statistically significant relationship between NAOi and eastern bluefin tuna (p=0.065); and western bluefin recruitment (p=0.155). In the case of western BFT, eliminating one outlier (year 1973, value for recruitment 487000), the correlation improves significantly (r: -0.59), explaining 34% of the variability. On the other hand, albacore presents the same problem in the year 1971, with a very high recruitment; eliminating this outlier the correlation reaches –0.71. Linear regression plots Ri vs. NAOi are shown in Figures 6ac. The R-Squared statistic indicates that the linear model as fitted explains 47% of the variability of northern albacore recruitment. The percentage increase up to 52% if fitting a second order polynomial. As regards eastern bluefin, the linear model Ri vs. NAOi explains only 13% of the year-class strength variability; but 49% when NAO indices of year i+1 are considered instead of indices of year i (Table 3). This relationship between eastern bluefin R i and NAOi+1 is statistically significant at the 99% confidence level (p=0.0097). The results reveal that there is a clear connection between the state of the NAO and the recruitment of eastern bluefin and northern albacore; and a lack of connection between NAO and recruitment of western bluefin. The correlation is positive for eastern bluefin and negative for northern albacore, indicating opposite effects of the

intensification of North Atlantic atmospheric circulation on both stocks. The relation in the case of eastern bluefin is stronger with a delay of one year. The last analysis made was the comparison between the detrended NAO and recruitment series. They were detrended by first fitting a 3 rd order polynomial to each series. The detrended series was calculated by subtracting the trend prediction from each observation, resulting in a new series that fluctuates around a mean of zero with no trend. The purpose of detrending each series was to enable the testing of year-to-year relationships without the influence of long-term trends. The trend fitted to the NAO (Figure 7a) for the north Atlantic Albacore exhibits a low frequency fluctuation. The albacore recruitment fitted trend is shown in Figure 7b. The detrended series of albacore recruitment are plotted in Figure 7c. The linear regression of the detrended series (Figure 7d) indicates that there is a significant relationship (p=0.015), with about 21% of the year-to-year variability in recruitment explained by NAO. Recruitment declines with increasing NAO index values. These results are consistent with the results shown by the previous analyses. In the case of western bluefin ICCAT (2001) re-analyzed data of Scott et al. (2001) considering separate early (1960-1973) and late (1974-1996) time periods. Although the results presented in our study, this analysis suggests that all of the apparent relationship between NAO and recruits is the result of changes over the long-term trend. The linear regression of the detrended series indicates that none of the year-to-year variability in recruitment can be explained by NAO. MECHANISMS FOR A POSSIBLE CONNECTION NAO-TUNA RECRUITMENT The finding of possible relations between teleconnection patterns and the dynamics of fish stocks and other aspects of marine ecology is a topic widely discussed in the literature. A well-known example is the Southern Oscillation, the associated El Niño phenomenon (ENSO) and its impact on the marine environment (see for example Glantz, 1996). Similarly to relevance of ENSO to the marine ecosystem of multiple areas of the world, the NAO plays a key role in the behave of several atmospheric, oceanographic and biological processes in the North Atlantic. Thus NAO is associated with the speed and direction of westerly winds (Rogers, 1985), heat and moisture transport (Hurrell, 1995), precipitation (Lamb & Peppler, 1987), air and sea surface temperature (Hurrell, 1995, 1996; Lamb et al., 1996). All of them are physical responses that are likely to affect in more or less extent the dynamics of the biological processes. However, the mechanisms by which environmental variability drive changes in the marine biota are not well known and require considerable investigation. A clear connection of NAO with biological aspects, found by Fromentin & Planque (1996) is that of the state of this index with the abundance of copepods, the dominant group of the zooplankton. The authors show a significant decrease of copepod production in the eastern North Atlantic during high NAO conditions; an inverse connection between NAO and abundance of C. finmarchicus (R2=0.58) and direct connection between NAO and abundance of C. helgolandicus (R2=0.26) with a delay of one year. The relation NAO-Calanus results from the effects of west wind stress on phytoplankton production and temperature and, in the case of C. helgolandicus, a third factor that is competition between the two copepod species. The three factors are directly or indirectly driven by NAO. The consequence on the abundance of Calanus is likely to affect the early phases of fish due to the fact that fish larvae feed mainly on copepods (Raymont, 1983). Thus Cushing (1982) relates Calanus production with recruitment of gadoids in the North Sea; McFarlane & Beamish (1992) propose that strong year-classes in sablefish populations occur when there is exceptional production of copepods. Again, like the mechanisms that link environmental variability with primary and secondary production, those that connect zooplankton abundance with fish recruitment remain unclear. Anyway, independently of the mechanisms that link environment with fish recruitment, it is clear that ultimately the dynamics of fish populations is controlled by climate; ‘... there are not parrot fish in boreal waters, nor are there codfish in the tropics‘ (Sissenwine, 1984). And, as stated before, the dominant feature in the weather and climate of the earth is the band of westerly winds in middle latitudes, which are in direct connection with the NAO state.

In the case of the tuna stocks considered in this working document, results from the comparison with NAO variability suggest that the state of this teleconnection pattern may play an important role in the determination of year-class strength of northern albacore and eastern bluefin tuna. The northern albacore is the stock which presents the closest connection with NAO, explaining up to 52% of the recruitment variability. Periods of accentuated atmospheric circulation in the North Atlantic, i.e. high NAO years, appear associated with reductions of albacore recruitment levels. On the contrary, low NAO situations are associated with increments in year-class strength of albacore. Similar connections have been observed for the albacore stock of the North Pacific. Thus Au (1995) discussed about the coincidence of periods of intensified atmospheric circulation in the North Pacific with declines in albacore CPUEs. The intensity of the atmospheric circulation was illustrated by the North Pacific circulation index (NP). In general terms, low values of NP indicate more intensified atmospheric circulation. Two different periods with low values were evident in the NP series, corresponding to the albacore failures of 1926-1937 and the one started in the mid-1970s. Previous works conducted in the past on albacore recruitment and environment are scarce and do not show consistent conclusions. Yamanaka & Yamanaka (1970, cited in Cushing, 1982) showed connections between stronger year-classes of albacore, yellowfin and bigeye and cooling in sea surface temperature. On the contrary, Leroy & Binet (1986) found a positive correlation between albacore recruitment and positive thermal anomalies in the supposed spawning area. However they arbitrarily eliminated several observations from the analysis that broke the apparent connection thermal regime-recruitment. Consequently these authors strongly recommended to take great care with such correlation due to several not well known factors: doubts about absolute age of albacore, period and area of spawning and the range of temperature considered to be a limiting factor. In fact, their assumption on absolute age of albacore and the one considered currently by ICCAT (Bard, 1981) differs in one year. According to our results, albacore year-class strength would be favoured by a cooling effect in the spawning-overwintering area associated directly with negative phases of NAO. In these situation the storming activity appears to increase in the area, specially in a narrow band following the main eastern US coastal baroclinic zone, increasing mixed-layer depth (Dickson et al., 1996). Bakun (1996) considers that among the “fundamental triad” underlying reproductive habitat suitability in fish, - enrichment, concentration and retention, the two first are critical in the case of albacore. The author hypothesizes that albacore spawning area in the North Pacific presents a surface wind stress driven couple of adjacent areas of divergence and convergence, responsible of enrichment processes (upwelling, mixing) and concentration of food organisms (convergent frontal formation). Retention is absent, making this habitat not very suitable for many types of fish. Albacore, however, would have solved the problem by, among other things, using the hydrodynamic advantages afforded by their growth to very large size (Bakun, op cit.). The connection between NAO and eastern bluefin tuna is also evident: in general terms, low (high) NAO years are associated with weak (strong) year classes. However, as it has been shown before, the percentage of recruitment Ri variability explained by NAO increases from 13% to 49% when NAO indices of year i+1 are considered instead of indices of year i. The search of a explanation for this possible association it is again not easy and needs further insights. Some keys may reside in the fact that NAO state seems to affect more significantly the overwintering area of eastern bluefin (along the Moroccan coast and in the Canary Islands) rather than the spawning area (western Mediterranean) as shown in Figures 3a,b. It is remarkable that the effect of NAO on SST is opposite in both overwintering areas of albacore and eastern bluefin. This dissimilarity in SST anomaly variations and its connection with NAO has been discussed recently by Krovnin (1995) who divided the North Atlantic into six major regions. SST anomalies of Regions 2A (south-western area) and 4A (south-eastern area) were negatively crosscorrelated (exceding the 95% significance level); and also were positively (region 2A) and negatively (region 4A) correlated with the NAO pattern. Another fact that may be considered as a possible factor for a linkage NAO-eastern bluefin recruitment is what Fromentin & Planque (1996) have observed concerning zooplankton abundance and its connection with NAO in the eastern Atlantic. As cited before, they demonstrated that Calanus species fluctuations were closely linked to the state of NAO. And from the two species analysed, the abundance of C. helgolandicus (warm-temperate species) was significantly higher during high NAO than during low ones; and the degree of significance increased also with a delay of one year. If the abundance of this dominant zooplanktonic group is compared with bluefin year-class

strength estimated for the same year, the relationship is statistically significant at the 99% confidence level 3, suggesting a direct connection between zooplankton abundance and recruitment success, as postulated for other fish stocks (Cushing, 1982; McFarlane & Beamish, 1992). As regards western bluefin tuna, global climatic variability considered in this document seems to play a minor role, at least during the analysed period. Several hypothesis may be put forward to explain this apparent lack of relation. Without considering the consequences of possible movements of individuals between the two bluefin populations assumed in the Atlantic, perhaps the most likely hypothesis is that density-independent mechanisms play a relatively minor role when the parental stock density is at a very low level. And this is the case for western bluefin tuna since the 70s. NAO – TUNA AND TUNA LIKE SPECIES: ADDITIONAL EVIDENCES FOR A POSSIBLE CONNECTION The analysis presented in this document deals with unbalanced series of information. On the one hand, long and reliable series of climatic data, the NAO; on the other, relatively short and less reliable biological information, recruitment estimates of North Atlantic temperate tunas. We will try in this brief section to review some additional information on the abundance and distribution of these two species. And also on other related species, the swordfish. -

The Norwegian bluefin fishery. This fishery, developed after de second world war, peaked in 1952 (11,400 t) and collapsed in the mid-1960s (Tiews, 1978) coinciding with a period of low NAO index. The same collapse was observed in the Danish and German fisheries in the North Sea that dropped from 2,400 t in 1952 to less than 100 t by mid-1960s. According to Tiews (op cit.) it was the lack of recruit year classes to the Northeast Atlantic tuna fishery which led to the absence of bluefin tuna in the central North Sea after 1962.

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Eastern bluefin recruitment in 1996. According to de la Serna (1997, pers. comm.) abundance of age-0 bluefin in the western Mediterranean in 1996 was extremely low. In this year the NAO index fell dramatically to –3.88 (J. Hurrell, pers. comm.) to the lowest value since 1969.

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Bluefin and swordfish in the Faroe and Iceland. Cushing (1982) refers to an increased abundance of bluefin tuna in the Northeast Atlantic during the period of warming, between the 1920s and 1950; bluefin tuna, together with swordfish, appeared off the Faroe Islands and Iceland during that period. This period coincides with high NAO (1920-1930) and consequent variations without tendency of this index. Recently, coinciding with the strong positive phase of NAO of the 90s, bluefin has appeared again in high latitude waters.

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Recruitment of northern stock of swordfish. The result of fitting a linear model to describe the relationship between North Atlantic swordfish year-class strength and NAO index indicates that there is a statistically significant relationship at the 95% confidence level. Like in the case of northern albacore, high NAO years are associated with low recruitments; and low NAO years with high recruitment levels. The model explains 33% of the variability of swordfish recruitment. Standardized CPUE indices of age 1 corresponding to the Spanish longline fleet from 1983-1995 were used as estimates of swordfish year-class strength (J. Mejuto, pers. comm; Table 8 of Mejuto & de la Serna, 1997).

CONCLUSIONS -

There is a clear connection between the North Atlantic Oscillation (NAO) and year-class strength of northern albacore (both detrended and not detrended series) and eastern bluefin tuna.

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NAO pattern explains 52% of the variability of northern albacore recruitment during the period 1969-1995. High NAO years are associated with low recruitment levels; and, oppositely, low NAO situations with high recruitment levels.

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NAO pattern explains 13% of the variability of eastern bluefin during the period 1969-1994. This percentage increases up to 49% if a delay of one year is taken into account. High NAO years are associated with high recruitment levels; and, oppositely, low NAO situations with low recruitment levels.

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Estimates of Calanus abundance have been grossly estimated from Fig. 5 of Fromentin & Planque (1996)

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The mechanisms linking NAO patterns with recruitment to temperate tuna stocks are not clear. NAO driven both thermal regimes and abundance of zooplankton appear to play an important role in the definition of year-class strength.

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According to the results presented here, the unusually high values of NAO in the period 1993-1995 would imply strong eastern bluefin and weak northern albacore year-classes.

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And the extremely low value of the NAO index in 1996, the third lowest of this century, would suggest weak (strong) eastern bluefin (northern albacore) recruitment success. In the case of albacore this was confirmed also by the Superposed Epoch Analysis.

Further research is needed to validate the hypotheses presented here concerning the influence of NAO on year-class strength of temperate tunas. Once properly validated, the corresponding relationships should be taken into account for stock assessment purposes. ACKNOWLEDGEMENTS We wish to acknowledge Dr. J.M. Fromentin for its help during the Workshop, specially with the Superposed Epoch Analysis. REFERENCES ANONYMUS, 1989. Thons et environment. Collection Colloques et Séminaires. ORSTOM. Paris. 84 p. AU, D.W., 1995. The 1976 climatic shift and North Pacific albacore. 14th North Pacific Albacore Workshop. Taipei, Taiwan. April 10-15, 1995. Working Paper. BARD, F.X., 1981. Le thon germon (Thunnus alalunga) de l’océan Atlantique. De la dynamique de population à la stratégie démographique. Thèse Doct. Univ. Paris 6, 330 p. BARD, F.X. & T. Joanny, 1996. The North Atlantic albacore (Thunnus alalunga) assessment problem. ICCAT Collec. Vol. Sci. Pap., Vol. XLIII, pp. 339-346. BEAMISH, R.J. [ed.], 1995. Climate change and northern fish populations. Can. Spec. Publ. Fish. Aquat. Sci., 121: 739 p. CLAY, D. [ed.], 1991. Atlantic Bluefin Tuna (Thunnus Thynnus thynnus (L.)): A review. In R.B. Deriso & W.H. Bayliff [ed.] Atlantic World meeting on stock assessment of bluefin tunas: strengths and weaknesses. IATTC Special Report No. 7: pp. 89-179. CORT, J.L., 1990. Biología y pesca del atún rojo, Thunnus thynnus (L.) del Mar Cantábrico. Publicaciones especiales, Inst. Esp. Oceanog., 4, 272 p. CORT, J.L. & B. Liourzu, 1991a. Reproduction-Eastern Atlantic and Mediterranean. . In D. Clay [ed.] Atlantic Bluefin Tuna (Thunnus Thynnus thynnus (L.)): A review. In R.B. Deriso & W.H. Bayliff [ed.] Atlantic World meeting on stock assessment of bluefin tunas: strengths and weaknesses. IATTC Special Report No. 7: pp. 99-101. CORT, J.L. & B. Liourzu, 1991b. Migration-Eastern Atlantic and Mediterranean. . In D. Clay [ed.] Atlantic Bluefin Tuna (Thunnus Thynnus thynnus (L.)): A review. In R.B. Deriso & W.H. Bayliff [ed.] Atlantic World meeting on stock assessment of bluefin tunas: strengths and weaknesses. IATTC Special Report No. 7: pp. 130-132. CUSHING, D.H., 1982. Climate and fisheries. Academic Press, London. 373 p. DIKSON, R., J. Lazier, J. Meincke, P. Rhines & J. Swift, 1996. Long-term coordinated changes in the convective activity of the North Atlantic. Prog. Oceanogr., 38: pp. 241-295. FROMENTIN, J-M & B. Planque, 1996. Calanus and environmenta in the eastern North Atlantic. II. Influence of the North Atlantic Oscillation on C. Finmarchicus and C. Helgolandicus. Mar. Ecol. Prog. Ser., 134: pp. 111-118. GLANTZ, M.H., 1996. Currents of Change: El Niño’s impact on Climate and Society. Cambridge University Press. 200 p.

HURRELL, J.W., 1995. Decadal trends in the North Atlantic Oscillation: regional temperatures and precipiation. Science, 269: pp. 676-679. HURRELL, J.W., 1996. Influence of variations in extratropical wintertime teleconnections on Northern Hemisphere temperature. Geophys. Res. Lett., 23 (6): pp. 665-668 ICCAT, 1994. Report of the Standing Committee on Research and Statistics: Albacore tuna. Report for biennial period 1992-1993, Part II. ICCAT, 1996. Report of the final meeting of the ICCAT Albacore Research Program. ICCAT Collec. Vol. Sci. Pap., Vol. XLIII, 395 p. ICCAT, 1997a, Informe del Simposio ICCAT sobre túnidos. Ponta Delgada, Azores (Portugal) – 10-18 de junio de 1996. COM-SCRS/96/16. ICCAT, 1997b. Report of the Standing Committee on Research and Statistics. Report for biennial period 1996-1997, Part II. ICCAT, 2000. Report of the Standing Committee on Research and Statistics. Report for biennial period 1999-2000, Part II. ICCAT, 2001. Report of ICCAT Workshop on Environment and Tuna Recruitment, Madrid, 7-12 May 2001, 30 p. KROVNIN, A.S., 1995. A comparative study of climatic changes in the North Pacific and North Atlantic and their relation to the abundance of fish stocks. In R.J. Beamish [ed.] Climate change and northern fish populations. Can. Spec. Publ. Fish. Aquat. Sci., 121: pp. 181-198. LAMB, P.J. & R.A. Peppler, 1987. North Atlantic Oscillation: Concept and an application. Bulletin of the American Meteorological Society, 68 (10): pp. 1218-1225. LAMB, P.J., M. El Hamly & D.H. Portis, 1996. North Atlantic Oscillation. Proceedings of International Workshop on Space Ocenography: Climate and Marine Resources in the Northwest of Africa, CRTS, Rabat, Morocco. (in press). LEROY, C. & D. Binet, 1986. Thermal anomalies in tropical areas of the Atlantic: possible consequences for albacore (Thunnus alalunga) recruitment. Int. Symp. Long Term Changes Mar. Fish Pop., pp. 291-299. MEJUTO, J. & J.M. de la Serna, 1997. Updated standardized catch rates by age for the swordfish (Xiphias gladius) from the Spanish longline fleet in the Atlantic using commercial trips from the period 1983-1995. ICCAT Collec. Vol. Sci. Pap., SCRS/96/141. McFARLANE, G.A. & R.J. Beamish, 1992. Climatic influence linking copepod production with strong year-classes in sablefish, Anopoploma fimbris. Can. J..Fish. Aquat. Sci., 49: pp. 743-753. PRAGER, M. & J. Hoenig. 1989. Superposed epoch analysis: a randomization test of environmental effects on recruitment with application to Chub Mackerel. Trans. Am. Fish. Soc. 118: pp. 608-618 RAYMONT, J.E.G., 1983. Plankton and productivity in the Oceans. 2nd edition. Volume 2. Zooplankton. Pergamon Press. Oxford. 824 p. RIVAS, L.R., 1978. Preliminary models of annual life history cycles of the North Atlantic bluefin tuna. In G.D. Sharp and A.E. Dizon [ed.] The physiological ecology of tunas. Academic Press, New York. Pp. 369-393. RODIONOV, S.N., 1995. Atmospheric teleconnections and coherent fluctuations in recruitment to North Atlantic cod (Gadus morhua) stocks. In R.J. Beamish [ed.] Climate change and northern fish populations. Can. Spec. Publ. Fish. Aquat. Sci., 121: pp. 45-55. ROGERS, J.C., 1985. Atmospheric circulation changes associated with the warming over the North Atlantic in the 1920s. J. Clim. Appl. Meteor., 24: pp. 1303-1310. SANTIAGO, J., 1997. The North Atlantic Oscillation and recruitment of temperate tunas. ICCAT SCRS/97/40, 20 pp. de la SERNA, J.M., E. Alot & P. Rioja, 1997. Nota sobre el reclutamiento de atún rojo (Thunnus thynnus L. 1758) en el Mediterráneo Occidental durante el año 1996. ICCAT SCRS/97/81.

SCOTT, G.P., C.A. Brown, C.E. Porch & S.C. Turner, 2001. Correlation between the North Atlantic Oscillation Index and stock-recruitment trends of Western Atlantic bluefin tuna (Thunnus thynnus). ICCAT SCRS/2001/032. SISSENWINE, M.P., 1984. Why do fish populations vary? In R.M. May [ed.] Exploitation of Marine Communities, pp. 59-94. Life Sciences Research Report 32. Springer-Verlag. Berlin. 366 p. SUZUKI, Z., 1991a. Reproduction-Western Atlantic. In D. Clay [ed.] Atlantic Bluefin Tuna (Thunnus Thynnus thynnus (L.)): A review. In R.B. Deriso & W.H. Bayliff [ed.] Atlantic World meeting on stock assessment of bluefin tunas: strengths and weaknesses. IATTC Special Report No. 7: pp. 97-98. SUZUKI, Z., 1991b. Migration-Western Atlantic. . In D. Clay [ed.] Atlantic Bluefin Tuna (Thunnus Thynnus thynnus (L.)): A review. In R.B. Deriso & W.H. Bayliff [ed.] Atlantic World meeting on stock assessment of bluefin tunas: strengths and weaknesses. IATTC Special Report No. 7: pp. 129-130. TIEWS, K., 1978. On the disappearance of bluefin tuna in the North Sea and its ecological implications for herring and mackerel. Rapp. P.-v. Réun. Cons. Int. Explor. Mer, 172: pp. 301-309. WOOSTER, W.S. & K.M. Bailey, 1989. Recruitment of marine fishes revisited. In R.J. Beamish and G.A. McFarlane [ed.] Effects of ocean variability on recruitment and an evaluation of parameters used in stock assessment models. Can. Spec. Publ. Fish. Aquat. Sci., 108: pp. 153-159.

TABLE 1. North Atlantic Oscillation (NAO) index and estimates of year-class-strength (n x 1000 of age 1 at year n+1) for eastern and western bluefin tuna (BFT) and northern albacore (ALB). For origin of data see text.

YEAR 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

NAO index -4.89 -1.89 -0.96 0.34 2.52 1.23 1.63 1.37 -2.14 0.17 -2.25 0.56 2.05 0.8 3.42 1.6 -0.63 0.5 -0.75 0.72 5.08 3.96 1.03 3.28 2.67 3.03 3.96

BFT east 503 635 524 725 1145 1342 977 813 578 650 1097 945 1543 2391 1251 1110 1911 1021 1830 1601 1880 1792 2252 1173 683 974

BFT west 330 254 216 107 487 144 137 87 56 79 66 61 56 94 66 71 88 66 91 65 121 68 36 27 10 17

ALB north 19918 15598 21405 16081 9539 11661 9778 12611 15994 8296 12186 10664 7986 7393 7314 8508 12032 9733 7923 8964 8702 9382 8782 10274 6589 9404 8036

TABLE 2. Results of fitting a linear model between NAO at year i (independent variable) and R i, one-year-olds at year i+1, of eastern bluefin, western bluefin for the 1969-1994 period and northern albacore (dependent variables), for the 1969-1995 period.

Eastern bluefin

----------------------------------------------------------------------------Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------Intercept 1127.74 108.711 10.3737 0.0000 Slope 90.19 46.62 1.93445 0.0649 ----------------------------------------------------------------------------Analysis of Variance ----------------------------------------------------------------------------Source Sum of Squares Df Mean Square F-Ratio P-Value ----------------------------------------------------------------------------Model 992146.0 1 992146.0 3.74 0.0649 Residual 6.36313E6 24 265130.0 ----------------------------------------------------------------------------Total (Corr.) 7.35528E6 25 Correlation Coefficient = 0.3673 R-squared = 13.49 percent Std Error Est. = 514.908

Western bluefin

----------------------------------------------------------------------------Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------Intercept 123.358 21.7437 5.67327 0.0000 Slope -13.6881 9.32559 -1.4678 0.1551 ----------------------------------------------------------------------------Analysis of Variance ----------------------------------------------------------------------------Source Sum of Squares Df Mean Square F-Ratio P-Value ----------------------------------------------------------------------------Model 22851.3 1 22851.3 2.15 0.1551 Residual 254559.0 24 10606.6 ----------------------------------------------------------------------------Total (Corr.) 277410.0 25 Correlation Coefficient = -0.287 R-squared = 8.237 percent Std Error Est. = 102.99

Northern albacore

----------------------------------------------------------------------------Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------Intercept 12051.6 596.586 20.2009 0.0000 Slope -1160.23 247.381 -4.69004 0.0001 ----------------------------------------------------------------------------Analysis of Variance ----------------------------------------------------------------------------Source Sum of Squares Df Mean Square F-Ratio P-Value ----------------------------------------------------------------------------Model 1.76606E8 1 1.76606E8 22.00 0.0001 Residual 2.0072E8 25 8.0288E6 ----------------------------------------------------------------------------Total (Corr.) 3.77326E8 26 Correlation Coefficient = -0.6841 R-squared = 46.8 percent Std Error Est. = 2833.51

TABLE 3. Results of fitting a linear model between NAO at year i+1 (independent variable) and R i, one-year-olds at year i+1 of eastern bluefin (dependent variable) for the 1969-1994 period; and results of fitting a second order polynomial between NAO at year i (independent variable) and Ri, one-year-olds at year i+1 of albacore for the 1969-1995 period.

Eastern bluefin

----------------------------------------------------------------------------Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------Intercept 1039.35 111.23 9.34419 0.0000 Slope 138.112 49.1576 2.80957 0.0097 ----------------------------------------------------------------------------Analysis of Variance ----------------------------------------------------------------------------Source Sum of Squares Df Mean Square F-Ratio P-Value ----------------------------------------------------------------------------Model 1.82043E6 1 1.82043E6 7.89 0.0097 Residual 5.53484E6 24 230619.0 ----------------------------------------------------------------------------Total (Corr.) 7.35528E6 25 Correlation Coefficient = 0.4975 R-squared = 24.75 percent Std Error Est. = 480.228

Northern albacore

----------------------------------------------------------------------------Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------CONSTANT 11435.5 695.814 16.4346 0.0000 NAO -1271.61 249.996 -5.08652 0.0000 NAO^2 124.675 78.1058 1.59623 0.1235 ----------------------------------------------------------------------------Analysis of Variance ----------------------------------------------------------------------------Source Sum of Squares Df Mean Square F-Ratio P-Value ----------------------------------------------------------------------------Model 1.9587E8 2 9.7935E7 12.95 0.0002 Residual 1.81456E8 24 7.56066E6 ----------------------------------------------------------------------------Total (Corr.) 3.77326E8 26 R-squared = 51.91 percent R-squared (adjusted for d.f.) = 47.9 percent Standard Error of Est. = 2749.66 Mean absolute error = 1855.12 Durbin-Watson statistic = 1.13 (p= 0.0043)

5 4 3 2 1 0 -1 -2 -3 -4 -5 1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

Figure 1. Winter (December trough March) index of the NAO, defined as the difference of normalized SLP between Lisbon (Portugal) and Stykkisholmur (Iceland), for the period 1900-1997 (Jim Hurrell, pers. comm.). Bold line represents 5-year running averages.

50

a 45

40

SPAWNING (June-August)

ER WIN TER ING

35

OV

30

25 -25

-20

-15

-10

-5

0

5

10

15

20

45

b 40

35

30

OVERWINTERING SPAWNING (April-June)

25

20

-95

-90

-85

-80

-75

-70

-65

-60

-50

-45

45

c 40

35

30

SPAWNING (spring-summer)

25

OVERWINTERING

20

15

10 -85

-80

-75

-70

-65

-60

-55

Figures 2a-c. Distribution of spawning and overwintering grounds during the 1st year of life of (a) eastern, (b) western Atlantic bluefin tuna and (c) northern albacore. Higher larval concentrations are indicated as closed ellipses. Redrawn from Rivas (1978), Bard (1981) and Clay (1991).

BFT east (N x 1.000)

2500 2000

a

1500 1000 500

BFT west (N x 1.000)

0 400 300 200 100 0 2000

ALB (N x 10.000)

1750

NAO index

b

1500

c

1250 1000 750 500 250 0 3 2 1 0 -1 -2 -3 -4

1970

1975

1980

1985

1990

Figures 3a-c. Estimates of year-class strength (as abundances of one-year olds) for the period 19691994 corresponding to (a) eastern, (b) western Atlantic bluefin and (c) northern albacore. ICCAT (1997b). NAO index are also shown at the bottom. Bold lines represent 5-year running averages.

CRITICAL PERIOD OF RECRUITMENT DEFINITION D

JFMAMJJASOND

NAO i

JFMAMJJASOND

NAO i+1

Ri Entering the fishery with 1-year-old

Figure 4. Illustration of the terms used in this document concerning the relations between NAO and recruitment.

2000

RECRUIMENT

1500

1000

500

0 BFT east

BFT west

ALB north

Figure 5. Mean recruitment of eastern and western bluefin (N x 1.000 recruits) and northern albacore (N x 10.000 recruits) estimated for low NAO years, i.e. less than –1.8 (1969, 1970, 1977, 1979) and high NAO years i.e. more than 2 (1973, 1981, 1983, 1989, 1990, 1992, 1993, 1994, 1995). Low NAO situations are expressed as blank boxes; high NAO as filled boxes. 95% confidence intervals are indicated.

Recruitment (x 1000)

2500

a- Eastern bluefin

2000 1500 1000 500 0 -6

-4

-2

0

2

4

6

2

4

6

2

4

6

NAO index

600

b- Western bluefin

Recruitment (x 1000)

500 400 300 200 100 0 -6

-4

-2

0 NAO index

c- Northern albacore

25000

Recruitment (x 1000)

20000 15000 10000 5000 0 -6

-4

-2

0 NAO index

Figures 6a-c. Linear regression plot between the NAO index (in year i) and year-class strength of year i (as one-year-olds in year i+1) of (a) eastern, (b) western Atlantic bluefin and (c) northern albacore from 1969 to 1996.

6

25000 NAO index

4

Poly (NAO index)

b

y = -1.8599x 3 + 105.59x 2 - 1992.5x + 21553 R2 = 0.6714

20000

ALB north Poly (ALB north)

15000 0

NAO 10000

-2 y = 0.0016x 3 - 0.068x 2 + 0.9682x - 3.5645 R2 = 0.4596

5000

4000

2 2000

1 0

0

-1

-2000

-2 -4000

-3 -4 69 19

-6000 71 19

73 19

75 19

77 19

79 19

81 19

83 19

85 19

87 19

89 19

91 19

93 19

95 19

6000

1995

1993

1991

1989

1987

1985

1983

1981

1979

1977

1975

1969

1995

1993

1991

1989

1987

1985

1983

1981

1979

1977

1975

1973

ALB det (poly)

ALB detrended (polynomial)

NAO detrended (polynomial)

3

6000

NAO det (poly)

c

0

ALB detrended (polynomial)

4

1971

1969

-6

1973

-4

1971

NAO

2

d

4000 2000 0 -2000

y = -610.7x - 16.005 R2 = 0.2133

-4000 -6000 -4

-2

0

2

NAO detrended (polynomial)

Figures 7a-d. Correlation tests between annual North Atlantic albacore tuna recruitment and North Atlantic Oscillation index (NAO). a: NAO and fitted trend, b: recruitment and fitted trend, c: detrended series of NAO and recruitment, d: relationship between detrended series.

4