The Atlantic bluefin tuna (hereafter referred to as “bluefin tuna”), one of the world’s most valuable and exploited fish species, has been declining in abundance throughout the Atlantic from the 1960s until the mid-2000s. Following the establishment of drastic management measures, the stock has started to recover recently and, as a result, stakeholders have raised catch quotas by 50% for the period 2017–2020. However, stock assessments still omit the natural, long-term variability in the species distribution. Here, we explore the century-scale fluctuations in bluefin tuna abundance and distribution to demonstrate a prevailing influence of the Atlantic Multidecadal Oscillation (AMO) to provide new insights into both the collapse of the Nordic bluefin tuna fishery circa 1963 and the recent increase in bluefin tuna abundance in the Northeast Atlantic. Our results demonstrate how climatic variability can modulate the distribution of a large migrating species to generate rapid changes in its regional abundance, and we argue that climatic variability must not be overlooked in stock management plans for effective conservation.

Bluefin tuna has shown centennial periodic fluctuations (up to threefold) in abundance in the Mediterranean Sea ( 6 ), and the extremely rapid 1960s decline of the Nordic fishery remains one of the world’s most spectacular fisheries’ collapses ( 7 ). While the Nordic fishery collapse is attributed to overfishing without clear evidence of hydroclimatic influences so far ( 8 ), environmental change could have played a role. Recurrent observations of bluefin tuna after the late 1990s suggest that bluefin tuna is returning to Nordic feeding grounds after three decades of depleted abundances ( 9 ). Since stock assessments have not suggested any recovery before the mid-2000s ( 4 ), it is currently unclear why bluefin tuna has reappeared in the Nordic region. At a time when the recent increase in bluefin tuna catch quotas will exacerbate the pressure on an IUCN Red List species ( 5 ), we have investigated the basin-scale variability in the distribution of bluefin tuna. Our goal is to determine whether the current return of bluefin tuna in the Nordic region can be explained by large-scale, hydroclimatic variability and, if so, whether the environment may explain some of the historical changes in the bluefin tuna’s abundance and distribution.

The Atlantic bluefin tuna (Thunnus thynnus, Linnaeus 1758) is a long-lived, widespread migrating species with the largest thermal tolerance among tunas ( 1 ); it is also one of the world’s most commercially exploited marine fishes ( 2 ). The bluefin tuna, currently managed as two separated stocks in the Atlantic ( 3 ), has been declining in abundance until the mid-2000s ( 4 ) and is listed as endangered on the International Union for Conservation of Nature (IUCN) Red List. Although electronic tagging programs begun in the late 1990s have provided new insights on the species’ migratory behavior to show that eastern (western) bluefin tuna may migrate to the western (eastern) Atlantic and remain there for a few months to a few years ( 3 ), little is known about the long-term variability in the migratory behavior, regional abundance, and the spatial distribution of bluefin tuna ( 5 ).

RESULTS AND DISCUSSION

The boosted regression tree (BRT) models used to examine the relationships between long-term variability in eastern bluefin tuna abundance and hydroclimatic variability (Materials and Methods and fig. S1) accurately reconstructed the century-scale fluctuations seen in the eastern bluefin tuna abundance index (Fig. 1). While several studies have previously explored the impact of the North Atlantic Oscillation (NAO), Northern Hemisphere temperature (NHT) anomalies, and total solar irradiance (TSI) on bluefin tuna abundance (10, 11), we found that most of the fluctuations are related to the Atlantic Multidecadal Oscillation (AMO) with a relative influence of 47.1% (Fig. 1B). Higher values of the eastern bluefin tuna abundance index occurred during positive (warm) AMO phases, whereas lower values were related to negative (cold) phases (fig. S2). The AMO still remained the most important hydroclimatic factor for predicting recruitment when we introduced a one-generation lag (i.e., 16 years; Materials and Methods), although its relative importance was slightly reduced (36%; fig. S2). We observed that the abundance of bluefin tuna in traps sometimes preceded shifts in AMO phase, e.g., during the Maunder minimum and at the end of the Dalton minimum, which suggests that the link between abundance and the environment may be more complex than simply through recruitment. For example, bluefin tuna can swim large distances quickly, and so, they are able to track environmental changes rapidly to follow the most favorable areas in the northeast (NE) Atlantic (3), where productivity is mainly driven by the AMO (12). So, while the relationship between the AMO and bluefin tuna may involve both recruitment and older stages, our results reveal that long-term changes in the AMO state can explain the periodic bluefin tuna fluctuations in the eastern Atlantic (Fig. 1 and fig. S3).

Fig. 1 Ensemble reconstructions of long-term fluctuations in Atlantic bluefin tuna abundance. (A and C) Historical records (black line) and predicted long-term fluctuations in abundance (averaged prediction as an orange line with 5 and 95% confidence intervals as gray shading) calculated from (A) 1634–1929 (preindustrial tuna fishery period) with no lag and (C) with a one-generation lag (16 years). (B and D) Mean relative influence [and associated SD (standard deviation)] of the four hydroclimatic variables used to reconstruct bluefin tuna abundance.

We found that the NAO was the second or third most important hydroclimatic variable influencing bluefin tuna (relative influences of 19.5% without a lag and 21.5% with a one-generation lag; Fig. 1B and fig. S2). Higher values of the adult abundance index occur during negative and positive NAO phases and lower abundances at intermediate values, while recruitment tends to increase with the NAO index (fig. S2); this observation may explain the contrasting results found previously for the influence of the NAO on bluefin tuna recruitment and abundance (10, 13, 14). Such a pattern could arise from the NAO’s multivariate effects on biological communities (15), which may influence both the bluefin tuna survival rates and feeding grounds’ productivity. We detected a more negative impact of high NHT on recruitment than on adult abundance, although trends were comparable (fig. S2), and this agrees with studies showing that eastern bluefin tuna abundance is negatively correlated with both Mediterranean Sea and global sea temperatures, which could be explained by long-term changes in migratory behavior (10, 11).

We found that the TSI, which has been negatively correlated with abundance (11), had the smallest influence on both adult bluefin tuna abundance and recruitment (Fig. 1, B and D). The effect of TSI was limited to very low irradiance periods, i.e., bluefin tuna abundance was systematically low when the TSI was below 1360.3 for adult abundance and 1360.1 for recruitment; no changes were seen when the TSI exceeded these thresholds (fig. S2), which may also explain why the relationship vanished in the 20th century (11) after irradiance increased at the end of the Little Ice Age (fig. S3).

While the effect of TSI and NHT were similar with and without a one-generation lag, the AMO and NAO showed a different effect at their extreme values (fig. S2). The most negative NAO phases had a negative impact on bluefin tuna recruitment (i.e., lower abundance 16 years later), and the most positive AMO phases were associated with low bluefin tuna recruitment. Nevertheless, the period of highest AMO and low bluefin tuna abundance only occurred in the 1700s to the 1720s, at the very end of the Maunder Minimum (fig. S3), and corresponded to the combination of the coldest NHT and the lowest irradiance levels. As highlighted by the BRT models, the irradiance effect on bluefin tuna abundance displayed a marked threshold and so that the NHT and TSI may have caused this sudden drop in bluefin tuna abundance regardless of the AMO phase.

We next investigated the long-term (1891–2011) spatiotemporal changes in habitat suitability of bluefin tuna in the Atlantic using ecological niche modeling (ENM) (fig. S1). While studies have shown changes in the habitat distribution and seasonal size-dependent feeding grounds (16), none has assessed the link with hydroclimatic variability. This procedure was repeated 30 times per model to provide the mean values and standard deviations (SDs) of the continuous Boyce index (CBI). The best model (CBI = 0.84; table S2) was obtained when each occurrence of bluefin tuna was associated to a unique triplet of environmental parameters; this configuration reproduced the overall bluefin tuna distribution well and was therefore used for subsequent analyses.

We applied a principal components analysis (PCA) on the annual anomalies of probabilities of occurrence of bluefin tuna (hereafter referred to as habitat suitability) modeled from 1891 to 2011. The spatial pattern of the first normalized eigenvector, which showed the highest significance (37.5% of the total variance), revealed an opposition between the northeastern and southwestern North Atlantic (fig. S4). Associated long-term changes (1891–2011) in the first principal component (PC) of habitat suitability correlated strongly with the abundance index of eastern bluefin tuna (r = 0.72, P < 0.001; fig. S4), and the link with historical fluctuations was even higher when reconstructed with PC1, PC2, and PC4 (r = 0.82, P < 0.001; Fig. 2). Our analysis therefore suggests that bluefin tuna occurrence in the North Atlantic is controlled by a northeastern/southwestern “seesaw” of habitat suitability so that long-term local fluctuations in bluefin tuna abundance may reflect changes in spatial distribution rather than changes in the size of eastern and western populations.

Fig. 2 Habitat-based reconstruction of Atlantic bluefin tuna abundance. Coefficient of linear correlation (r) and its associated probability (P) between historical records of Atlantic bluefin tuna abundance (from Fig. 1; black line) and long-term changes (1891–2011) in the species’ habitat suitability (orange line) reconstructed from the PCA computed on annual anomalies of probability of occurrence of bluefin tuna.

Spatial patterns of habitat suitability of bluefin tuna in the North Atlantic were assessed for positive (1929–1962 and 1995 to present) and negative (1896–1928 and 1963–1994) AMO phases (Fig. 3). This analysis showed that high records of bluefin tuna in the NE Atlantic coincided with high positive habitat suitability observed during positive AMO phases (Fig. 3A), while lower records occurred during negative AMO phases when habitat suitability became negative (Fig. 3B). Our analysis therefore highlights the AMO’s controlling role on bluefin tuna’s basin-scale distribution. When calculating the average habitat suitability of bluefin tuna around United Kingdom (Fig. 3B), we found that anomalies follow the main historical periods of bluefin tuna presence and absence: negative in the entire region until the mid-1920s, positive until the mid-1960s, negative until the mid-1990s, and returning to positive until today (Fig. 3C and fig. S5). Our analysis suggests that bluefin tuna persisted around the United Kingdom only during the two positive AMO phases from 1891 onward (fig. S3), which corresponded to periods of highest anomalies in habitat suitability (Fig. 3C). The spatial distribution of bluefin tuna modeled from the species’ ecological niche therefore captured the rise and fall of the Nordic fishery between the late 1920s and 1960s and its return after the late 1990s. The collapse of the Nordic bluefin tuna fishery circa 1963 coincided with an extremely rapid 2-year transition (1962–1963) from a highly positive AMO phase to its lowest recorded value (Figs. 3C and 4). The AMO reversed to a positive phase in 1996, and a fishery targeting mature fish was established around Iceland in 1997 when bluefin tuna returned to the region (17). Schools of bluefin tuna have also been seen around the United Kingdom since 1996 (9). Together, our observations suggest that the hydroclimatic variability influences bluefin tuna distribution strongly, with higher (warm AMO) and lower (cold AMO) utilization rates in the northern and southern regions of the North Atlantic, respectively. Although no time series is sufficiently long to validate the southwest/NE changes in distribution of the western stock (Materials and Methods), both stocks may follow the same pattern of variability as they have the same ecological niche.

Fig. 3 AMO phases and spatiotemporal variability in habitat suitability and distribution of Atlantic bluefin tuna. (A and B) Anomalies of habitat suitability, reported occurrences (per 1° by 1° geographical cell; red dots), and mass centroids of occurrences (black dots) during (A) positive (1929–1962 and 1995 to present; n bins = 964) and (B) negative (1896–1928 and 1963–1994; n bins = 979) AMO phases. (C) Time series of mean anomalies (blue line) in the Nordic region [inset in (B)] from 1891 to 2011. Vertical dashed lines indicate abrupt changes in habitat suitability, and horizontal lines indicate the mean habitat suitability for each phase. The size of the tuna is proportional to its frequency of occurrence.

Fig. 4 Habitat suitability of Atlantic bluefin tuna when the Nordic fishery collapsed. Mean anomalies of probability of occurrence of Atlantic bluefin tuna before the collapse (1959–1961; left) and when the fishery collapsed (1962–1963; right).

Long-term climate variability is known to influence fisheries production at various spatiotemporal scales (18). Here, we have shown that the AMO is an important determinant of the bluefin tuna’s spatial distribution and regional abundance in the North Atlantic and that the recent recovery of the eastern stock (4) may reflect the current positive AMO phase. Our analyses of environmental effects on bluefin tuna can therefore provide an insight to help interpret (i) the collapse of bluefin tuna in 1963 and (ii) the current increase of bluefin tuna in Nordic seas.

It is assumed that eastern bluefin tuna spawn exclusively in the Mediterranean Sea (2), where the influence of the AMO is lower than elsewhere (19). We tested the influence of hydroclimatic variability on recruitment and highlighted, in line with previous studies (10, 11), that high NHT negatively affects both the adult abundance in traps and the recruitment (fig. S2). However, the Mediterranean sea surface temperature (SST) [averaged from the Centennial Observation-Based Estimates (COBE) dataset; see Materials and Methods] and the recruitment year classes (4) were significantly and positively correlated over the period 1968–2014 (r = 0.59, P < 0.001), with the strongest correlations in summer (June, July, and August, i.e., immediately after the main spawning period), while SSB followed an opposite pattern (r = −0.63, P < 0.001). In response to rising temperatures, the average habitat suitability of bluefin tuna has also been decreasing in the Atlantic and Mediterranean Sea (correlated negatively with NHT; r = −0.49, P < 0.001). This suggests that, while higher local SST may enhance recruitment, it would still have a deleterious effect on adult bluefin tuna. If warming continues, then bluefin tuna may indeed become constrained by the upper thermal limit of its spawning preference in the Mediterranean Sea (fig. S6) (20) and could begin to use different regions in the Atlantic. This consequence of warming has been predicted in the Gulf of Mexico (21), and bluefin tuna have been discovered to spawn along the NE coast of the United States, which may constitute a recent expansion of spawning habitat (22–24). Consequently, future warming may also alter ecological barriers (25) and counterbalance the influence of future cold AMO phases on the species’ distribution, causing bluefin tuna to persist in Nordic seas.

To manage Atlantic bluefin tuna and other highly migrating species sustainably, long-term recovery plans should therefore be addressed at a basin scale by combining the effects of hydroclimatic variability, such as the AMO, global climate change and fishing, and local increases in abundance should not be used as a reason to relax quotas for commercial or recreational fisheries without having done so. Since large-scale changes in the abundance of top predators integrate changes at lower trophic levels (26), regional fluctuations in bluefin tuna abundance may also serve to indicate even wider ecological changes, providing useful insights for further research.