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Anticyclonic eddies aggregate pelagic predators in a subtropical gyre

Nature volume 609, pages 535–540 (2022)Cite this article

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Abstract

Ocean eddies are coherent, rotating features that can modulate pelagic ecosystems across many trophic levels. These mesoscale features, which are ubiquitous at mid-latitudes1, may increase productivity of nutrient-poor regions2,3, accumulate prey4 and modulate habitat conditions in the water column5. However, in nutrient-poor subtropical gyres—the largest marine biome—the role of eddies in modulating behaviour throughout the pelagic predator community remains unknown despite predictions for these gyres to expand6 and pelagic predators to become increasingly important for food security7. Using a large-scale fishery dataset in the North Pacific Subtropical Gyre, we show a pervasive pattern of increased pelagic predator catch inside anticyclonic eddies relative to cyclones and non-eddy areas. Our results indicate that increased mesopelagic prey abundance in anticyclone cores4,8 may be attracting diverse predators, forming ecological hotspots where these predators aggregate and exhibit increased abundance. In this energetically quiescent gyre, we expect that isolated mesoscale features (and the habitat conditions in them) exhibit primacy over peripheral submesoscale dynamics in structuring the foraging opportunities of pelagic predators. Our finding that eddies influence coupling of epi- to mesopelagic communities corroborates the growing evidence that deep scattering layer organisms are vital prey for a suite of commercially important predator species9 and, thus, provide valuable ecosystem services.

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Fig. 1: Nominal eddy-centric albacore catch.
Fig. 2: Eddy-centric catch metrics (high EKE).
Fig. 3: Potential mechanisms driving catch.

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Data availability

Fisheries data used in this paper are subject to confidentiality of information requirements under the Magnuson–Stevens Fishery Conservation and Management Act and are not available to the public except in summary aggregate form. Information on requesting access to these data can be found at https://inport.nmfs.noaa.gov/inport/item/2721 (logbook data) and https://www.fisheries.noaa.gov/inport/item/9027 (observer data). The oceanographic data used in this study are publicly available from AVISO’s Mesoscale Eddy Trajectory Atlas (https://www.aviso.altimetry.fr/en/data/products/value-added-products/global-mesoscale-eddy-trajectory-product.html), the EU Copernicus Marine Environment Monitoring Service (CMEMS, https://marine.copernicus.eu/) and NOAA National Centre for Environmental Information’s Argo Data Repository (https://www.nodc.noaa.gov/argo/floats_data.htm). All information graphed or tabulated in this paper is nonconfidential. Source data are provided with this paper.

Code availability

Eddy colocation code and catch-effort standardization code are provided with this paper.

Change history

  • 21 September 2022

    In the version of this article initially published, the eddy colocation code and catch-effort standardization code files were missing and are now included in the online version of the article.

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Acknowledgements

We thank L. Gallagher (Fishpics® and IMAR-DOP, University of the Azores) for producing fish artwork used in main text Figs. 1–3 and Extended Data Figs. 1–13 and 15, and K. Reading and M. LeDoux (UW APL) for producing main text Fig. 3. J. Brodziak (NOAA PIFSC) and R. Rykaczewski (NOAA PIFSC) reviewed a version of this manuscript before submission. M.C.A., C.D.B. and P.G. were supported by the NASA New Investigator Program grant no. 80NSSSC20K1132. M.C.A. and P.G. were also supported by NOAA project no. NA15OAR4320063. M.C.A. was also supported by the Postdoctoral Scholar Program at Woods Hole Oceanographic Institution with funding provided by the Dr. George D. Grice Postdoctoral Scholarship Fund, and C.D.B. was also supported by the NASA Earth Science Research Program no. 80NSSC19K0187 and The Investment in Science Program with funds from Woods Hole Oceanographic Institution.

Author information

Authors and Affiliations

  1. Air-Sea Interaction and Remote Sensing Department, Applied Physics Laboratory, University of Washington, Seattle, WA, USA

    Martin C. Arostegui & Peter Gaube

  2. Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

    Martin C. Arostegui & Camrin D. Braun

  3. Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration (NOAA), Honolulu, HI, USA

    Phoebe A. Woodworth-Jefcoats & Donald R. Kobayashi

  4. School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA

    Camrin D. Braun

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  1. Martin C. Arostegui
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  2. Peter Gaube
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  3. Phoebe A. Woodworth-Jefcoats
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  4. Donald R. Kobayashi
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  5. Camrin D. Braun
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Contributions

M.C.A. contributed to study design, conducted analyses, wrote the manuscript and helped acquire funding. P.G. contributed to study design, analyses, interpretation, revision and funding acquisition. P.A.W.-J. contributed to study design and revision. D.R.K. contributed to study design, revision and funding acquisition. C.D.B. contributed to study design, analyses, interpretation, revision and funding acquisition.

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Correspondence to Martin C. Arostegui.

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Extended data figures and tables

Extended Data Fig. 1 Nominal eddy-centric bigeye tuna catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of bigeye tuna catch probability – the % of longline sets catching at least one bigeye tuna – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 2 Nominal eddy-centric yellowfin tuna catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of yellowfin tuna catch probability – the % of longline sets catching at least one yellowfin tuna – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 3 Nominal eddy-centric skipjack tuna catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of skipjack tuna catch probability – the % of longline sets catching at least one skipjack tuna – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 4 Nominal eddy-centric striped marlin catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of striped marlin catch probability – the % of longline sets catching at least one striped marlin – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 5 Nominal eddy-centric blue marlin catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of blue marlin catch probability – the % of longline sets catching at least one blue marlin – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 6 Nominal eddy-centric shortbill spearfish catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of shortbill spearfish catch probability – the % of longline sets catching at least one shortbill spearfish – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 7 Nominal eddy-centric swordfish catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of swordfish catch probability – the % of longline sets catching at least one swordfish – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 8 Nominal eddy-centric blue shark catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of blue shark catch probability – the % of longline sets catching at least one blue shark – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 9 Nominal eddy-centric dolphinfish catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of dolphinfish catch probability – the % of longline sets catching at least one dolphinfish – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 10 Nominal eddy-centric escolar catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of escolar catch probability – the % of longline sets catching at least one escolar – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 11 Nominal eddy-centric opah catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of opah catch probability – the % of longline sets catching at least one opah – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 12 Nominal eddy-centric pomfret catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of pomfret catch probability – the % of longline sets catching at least one pomfret – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 13 Nominal eddy-centric wahoo catch.

Example eddy-centric 2D (a, b) and 1D (c) composites of wahoo catch probability – the % of longline sets catching at least one wahoo – from the nominal fishery data across the study region. In panels a–c, the eddy core (0 – R) and periphery (R – 2R) are separated by the solid black line, and the inner and outer zones of both the core (0 – 0.5R & 0.5R – R) and periphery (R – 1.5R & 1.5R – 2R) are separated by the dashed black lines. In panels a and b, N represents the total number of individuals captured in eddies of the respective polarities, catch probability is calculated per 0.2R x 0.2R cell, and north is up. In panel c, N per polarity is the same as in panels a and b, anticyclonic values are red and cyclonic values are blue, and polarity-specific mean catch probability (with the 95% confidence interval) is calculated per 0.2R width bin.

Extended Data Fig. 14 Eddy kinetic energy field. Mean eddy kinetic energy (EKE) derived from sea surface height.

The eddy dynamics subregions are demarcated by the 150 cm2s−2 contour (white) from a smoothed version of the data shown in the pseudocolor image. Fishing effort co-located to eddies is contoured (black) by the smoothed number of longline sets per degree2; the division of effort among eddy dynamics subregions is nearly equal – low EKE, n = 112,105; high EKE, n = 107,929.

Extended Data Fig. 15 Eddy-centric catch metrics (low EKE).

Catch odds ratios and catch rate ratios comparing a given zone of anticyclones against the corresponding zone of cyclones. Ratios of catch metrics are colour coded; > 1 - significantly higher in anticyclones (red), < 1 - significantly higher in cyclones (blue), = 1 - not significantly different among polarities (white), N/A - best-fit model did not include eddy-related effects for that metric (grey). Ratio values > 1.4 were truncated to aid in color discernment. Ratios not significantly different among polarities were set to equal 1. Eddy cores are separated from peripheries by the solid black line, and both are further differentiated into inner and outer zones by the dashed black lines. These model-estimated ratios come from the low EKE subregion, but see Fig. 2 for the ratios from the high EKE subregion and Extended Data Fig. 16 for the full results (ratios in both the high and low EKE subregions, including 95% confidence intervals determined with the delta method)

Source Data

Extended Data Fig. 16 Eddy-Centric Analysis – Species-specific odds and rate ratios, separated by eddy dynamics subregion, comparing catch metrics in a given zone of an anticyclone against the corresponding zone of a cyclone.

The mean effect estimate (circle) is filled when significant and open when not significant. The vertical black line indicates a ratio of 1 (equal odds or rates); if a 95% confidence interval (determined with the delta method) passes through this line the corresponding estimate is not significant. Missing estimates indicate that the best-fit model for that species did not include eddy-related effects in that component of the hurdle model. Identical estimates among the eddy dynamics subregions indicate that the best-fit model for that species included gyre-wide estimates in that component of the hurdle model. Each species-specific model used N = 220,034 longline sets (except that for blue shark, which used 219,837)

Source Data

Extended Data Fig. 17 Complementary Analysis with Non-Eddy Baseline – Species-specific odds and rate ratios, separated by eddy dynamics subregion, comparing catch metrics among the cores of eddies of both polarities and non-eddy areas.

The mean effect estimate (circle) is filled when significant and open when not significant. The vertical black line indicates a ratio of 1 (equal odds or rates); if a 95% confidence interval (determined with the delta method) passes through this line the corresponding estimate is not significant. Missing estimates indicate that the best-fit model for that species did not include eddy-related effects in that component of the hurdle model. Identical estimates among the eddy dynamics subregions indicate that the best-fit model for that species included gyre-wide estimates in that component of the hurdle model. Each species-specific model used N = 182,775 longline sets (except for blue shark, which used 182,629), and effect estimate significance was determined with the delta method

Source Data

Extended Data Fig. 18 Eddy vertical thermal structure.

Vertical temperature composites of anticyclones and cyclones within the high and low EKE subregions, as well as across the full study region. The vertical solid black lines at |R| = 1 designate the transition from the core (i.e., interior) to periphery (i.e., exterior) of an eddy. Sample size (number of Argo profiles) per panel – a) n = 6,808; b) n = 6,752; c) n = 19,362; d) n = 20,145, e) n = 26,170; f) n = 26,897.

Extended Data Table 1 Pelagic predators
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Extended Data Table 2 Eddy-Centric Analysis – Summary of model-estimated catch odds and rate ratios (anticyclone/cyclone) across species
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Extended Data Table 3 Eddy-Centric Analysis – Ratios (anticyclone/cyclone) of catch summed across the 14 pelagic predator species for the average longline set
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Extended Data Table 4 Eddy-Centric Analysis – Summary of species-specific proportional contributions (%) to the overall catch response predicted for the average longline set in the 16 unique combinations of eddy polarity, eddy zone, and eddy dynamics subregion
Full size table

Supplementary information

Supplementary Information

Supplementary Results, Tables 1–4 and Figs. 1–11.

Reporting Summary.

Peer Review File.

Supplementary Code

R code for eddy co-location.

Supplementary Code

R code for catch-effort standardization.

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Arostegui, M.C., Gaube, P., Woodworth-Jefcoats, P.A. et al. Anticyclonic eddies aggregate pelagic predators in a subtropical gyre. Nature 609, 535–540 (2022). https://doi.org/10.1038/s41586-022-05162-6

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