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Wrong-way migrations of benthic species driven by ocean warming and larval transport

Nature Climate Change volume 10, pages 1052–1056 (2020)Cite this article

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Abstract

Ocean warming has predictably driven some marine species to migrate polewards or to deeper water, matching rates of environmental temperature change (climate velocity) to remain at tolerable temperatures. Most species conforming to expectations are fish and other strong swimmers that can respond to temperature change by migrating as adults. On the Northwest Atlantic continental shelf, however, many benthic invertebrates’ ranges have instead shifted southwards and into shallower, warmer water. We tested whether these ‘wrong-way’ migrations could arise from warming-induced changes in the timing of spawning (phenology) and transport of drifting larvae. The results showed that larvae spawned earlier in the year encounter more downwelling-favourable winds and river discharge that drive transport onshore and southwards. Phenology and transport explained most observed range shifts, whereas climate velocity was a poor predictor. This study reveals a physical mechanism that counterintuitively pushes benthic species, including commercial shellfish, into warmer regions with higher mortality.

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Fig. 1: Spawning phenology would shift due to warming in the NWA and MAB regions.
Fig. 2: Phenological shifts from summer to spring would expose larvae to more onshore, down-shelf transport.
Fig. 3: In the MAB, most ranges shifted southwest, down-shelf and onshore to shallower, warmer regions with earlier spawning onset.
Fig. 4: Most phenological shifts would result in faster larval transport down the shelf, explaining adults’ along-shelf range shifts.

Data availability

All data analysed in this paper are publicly available. The species occurrence data are available from OBIS (https://www.iobis.org). The bathymetry data are available from NOAA (https://doi.org/10.7289/V5C8276M). The river data are available from USGS (http://waterdata.usgs.gov/nwis/). The wind data are available from NCAR (https://climatedataguide.ucar.edu/climate-data/corev2-air-sea-surface-fluxes). The temperature data are available from WOD (https://www.nodc.noaa.gov/OC5/WOD/pr_wod.html) and from Rutgers (https://esm.rutgers.edu/). All data used in the analyses are available in condensed form on Zenodo (https://doi.org/10.5281/zenodo.3934122).

Code availability

All codes necessary for data analysis and figure generation are available on Zenodo (https://doi.org/10.5281/zenodo.3946797).

References

  1. Perry, A. L., Low, P. J., Ellis, J. R. & Reynolds, J. D. Climate change and distribution shifts in marine fishes. Science 308, 1912–1915 (2005).

    CAS  Google Scholar 

  2. Dulvy, N. K. et al. Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. J. Appl. Ecol. 45, 1029–1039 (2008).

    Google Scholar 

  3. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Thermal tolerance and the global redistribution of animals. Nat. Clim. Change 2, 686–690 (2012).

    Google Scholar 

  4. Pinsky, M. L., Worm, B., Fogarty, M. J., Sarmiento, J. L. & Levin, S. A. Marine taxa track local climate velocities. Science 341, 1239–1242 (2013).

    CAS  Google Scholar 

  5. Hutchins, L. W. The bases for temperature zonation in geographical distribution. Ecol. Monogr. 17, 325–335 (1947).

    Google Scholar 

  6. Pineda, J., Reyns, N. B. & Starczak, V. R. Complexity and simplification in understanding recruitment in benthic populations. Pop. Ecol. 51, 17–32 (2009).

    Google Scholar 

  7. Morgan, S. G., Shanks, A. L., MacMahan, J. H., Reniers, A. J. H. M. & Feddersen, F. Planktonic subsidies to surf-zone and intertidal communities. Annu. Rev. Mar. Sci. 10, 345–369 (2018).

    Google Scholar 

  8. Gaylord, B. & Gaines, S. D. Temperature or transport? Range limits in marine species mediated solely by flow. Am. Nat. 155, 769–789 (2000).

    Google Scholar 

  9. García Molinos, J., Burrows, M. T. & Poloczanska, E. S. Ocean currents modify the coupling between climate change and biogeographical shifts. Sci. Rep. 7, 1332 (2017).

    Google Scholar 

  10. Kumagai, N. H. et al. Ocean currents and herbivory drive macroalgae-to-coral community shift under climate warming. Proc. Natl Acad. Sci. USA 115, 8990–8995 (2017).

    Google Scholar 

  11. Harley, C. D. G. et al. The impacts of climate change in coastal marine systems. Ecol. Lett. 9, 228–241 (2006).

    Google Scholar 

  12. Strathmann, M. F. Reproduction and Development of Marine Invertebrates of the Northern Pacific Coast (Univ. of Washington Press, 1987).

  13. Thorson, G. Reproductive and larval ecology of marine bottom invertebrates. Biol. Rev. 25, 1–45 (1950).

    CAS  Google Scholar 

  14. Olive, P. J. W. Annual breeding cycles in marine invertebrates and environmental temperature: probing the proximate and ultimate causes of reproductive synchrony. J. Therm. Biol. 20, 79–90 (1995).

    Google Scholar 

  15. Philippart, C. J. M. et al. Climate-related changes in recruitment of the bivalve Macoma balthica. Limnol. Oceanogr. 48, 2171–2185 (2003).

    Google Scholar 

  16. Asch, R. G. Climate change and decadal shifts in the phenology of larval fishes in the California Current Ecosystem. Proc. Natl Acad. Sci. USA 112, E4065–E4074 (2015).

    CAS  Google Scholar 

  17. Shearman, R. K. & Lentz, S. J. Long-term sea surface temperature variability along the U.S. East Coast. J. Phys. Oceanogr. 40, 1004–1017 (2010).

    Google Scholar 

  18. Saba, V. S. et al. Enhanced warming of the northwest Atlantic Ocean under climate change. J. Geophys. Res. Oceans 121, 118–132 (2016).

    Google Scholar 

  19. Castelao, R., Glenn, S. & Schofield, O. Temperature, salinity, and density variability in the central Middle Atlantic Bight. J. Geophys. Res. 115, C10005 (2010).

    Google Scholar 

  20. Richaud, B., Kwon, Y.-O., Joyce, T. M., Fratantoni, P. S. & Lentz, S. J. Surface and bottom temperature and salinity climatology along the continental shelf off the Canadian and U.S. East Coasts. Cont. Shelf Res. 124, 165–181 (2016).

    Google Scholar 

  21. Roughgarden, J., Gaines, S. & Possingham, H. Recruitment dynamics in complex life cycles. Science 241, 1460–1466 (1988).

    CAS  Google Scholar 

  22. Connolly, S. R., Menge, B. A. & Roughgarden, J. A latitudinal gradient in recruitment of intertidal invertebrates in the northeast Pacific Ocean. Ecology 82, 1799–1813 (2001).

    Google Scholar 

  23. Ma, H., Grassle, J. P. & Chant, R. J. Vertical distribution of bivalve larvae along a cross-shelf transect during summer upwelling and downwelling. Mar. Biol. 149, 1123–1138 (2006).

    Google Scholar 

  24. Shanks, A. L. & Brink, L. Upwelling, downwelling, and cross-shelf transport of bivalve larvae: test of a hypothesis. Mar. Ecol. Prog. Ser. 302, 1–12 (2005).

    Google Scholar 

  25. Drake, P. T., Edwards, C. A., Morgan, S. G. & Dever, E. P. Influence of larval behavior on transport and population connectivity in a realistic simulation of the California Current System. J. Mar. Res. 71, 317–350 (2013).

    Google Scholar 

  26. Shanks, A. L. & Morgan, S. G. Testing the intermittent upwelling hypothesis: upwelling, downwelling, and subsidies to the intertidal zone. Ecol. Monogr. 88, 22–35 (2018).

    Google Scholar 

  27. Menge, B. A. & Menge, D. N. L. Testing the intermittent upwelling hypothesis: comment. Ecology 100, e02476 (2019).

    Google Scholar 

  28. Lentz, S. J. Seasonal variations in the circulation over the Middle Atlantic Bight continental shelf. J. Phys. Oceanogr. 38, 1486–1500 (2008).

    Google Scholar 

  29. Gong, D., Kohut, J. T. & Glenn, S. M. Seasonal climatology of wind-driven circulation on the New Jersey Shelf. J. Geophys. Res. 115, C04006 (2010).

    Google Scholar 

  30. Whitney, M. M. & Garvine, R. W. Wind influence on a coastal buoyant outflow. J. Geophys. Res. 110, C03014 (2005).

    Google Scholar 

  31. Largier, J. L. Considerations in estimating larval dispersal distances from oceanographic data. Ecol. Appl. 13, S71–S89 (2003).

    Google Scholar 

  32. Byers, J. E. & Pringle, J. M. Going against the flow: retention, range limits and invasions in advective environments. Mar. Ecol. Prog. Ser. 313, 27–41 (2006).

    Google Scholar 

  33. Fuchs, H. L., Gerbi, G. P., Hunter, E. J. & Christman, A. J. Waves cue distinct behaviors and differentiate transport of congeneric snail larvae from sheltered versus wavy habitats. Proc. Natl Acad. Sci. USA 115, E7532–E7540 (2018).

    CAS  Google Scholar 

  34. Sunday, J. M., Bates, A. E. & Dulvy, N. K. Global analysis of thermal tolerance and latitude in ectotherms. Proc. R. Soc. B 278, 1823–1830 (2011).

    Google Scholar 

  35. Wilson, R. J. et al. Changes to the elevational limits and extent of species ranges associated with climate change. Ecol. Lett. 8, 1138–1146 (2005).

    Google Scholar 

  36. Freeman, B. G., Scholer, M. N., Ruiz-Guttierrez, V. & Fitzpatrick, J. W. Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. Proc. Natl Acad. Sci. USA 115, 11982–11987 (2018).

    CAS  Google Scholar 

  37. Free, C. M. et al. Impacts of historical warming on fisheries production. Science 363, 979–983 (2019).

    CAS  Google Scholar 

  38. Young, I. R. & Ribal, A. Multiplatform evaluation of global trends in wind speed and wave height. Science 364, 548–552 (2019).

    CAS  Google Scholar 

  39. Ocean Biogeographic Information System (Intergovernmental Oceanographic Commission of UNESCO, 2018); www.iobis.org

  40. Tingley, M. W. & Beissinger, S. R. Detecting range shifts from historical species occurrences: new perspectives on old data. Trends Ecol. Evol. 24, 625–633 (2009).

    Google Scholar 

  41. Wigley, R. L. & Theroux, R. B. Atlantic Continental Shelf and Slope of the United States; Macrobenthic Invertebrate Fauna of the Middle Atlantic Bight Region; Faunal Composition and Quantitative Distribution Professional Paper No. 529-N (USGS, 1981).

  42. Amante, C. & Eakins, B. W. ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis Technical Memorandum NESDIS NGDC-24 (National Geophysical Data Center, NOAA, 2009); https://doi.org/10.7289/V5C8276M

  43. Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1057 (2009).

    CAS  Google Scholar 

  44. Kang, D. & Curchitser, E. N. Gulf stream eddy characteristics in a high-resolution ocean model. J. Geophys. Res. Oceans 118, 4474–4487 (2013).

    Google Scholar 

  45. Narváez, D. A. et al. Long-term dynamics in Atlantic surfclam (Spisula solidissima) populations: the role of bottom water temperature. J. Mar. Sys. 141, 136–148 (2015).

    Google Scholar 

  46. Chen, Z., Curchitser, E., Chant, R. & Kang, D. Seasonal variability of the cold pool over the Mid-Atlantic Bight continental shelf. J. Geophys. Res. Oceans 123, 8203–8226 (2018).

    Google Scholar 

  47. D’Errico, J. inpaint_nans (MATLAB Central File Exchange, 2019); https://www.mathworks.com/matlabcentral/fileexchange/4551-inpaint_nans

  48. Gypaets trigradient2 (GitHub, 2020); https://www.github.com/Gypaets/trigradient2

  49. Yeager, S. & NCAR Staff The Climate Data Guide: COREv2 Air-Sea Surface Fluxes (UCAR, 2016); https://climatedataguide.ucar.edu/climate-data/corev2-air-sea-surface-fluxes

  50. National Water Information System Data (USGS, 2016); http://waterdata.usgs.gov/nwis/

  51. Lentz, S. J. Observations and a model of the mean circulation over the Middle Atlantic Bight continental shelf. J. Phys. Oceanogr. 38, 1203–1221 (2008).

    Google Scholar 

  52. Shanks, A. L. Pelagic larval duration and dispersal distance revisited. Biol. Bull. 216, 373–385 (2009).

    Google Scholar 

Download references

Acknowledgements

We thank P. Falkowski, J. Grassle and K. Sutherland for comments on the manuscript. This work was supported by a grant from the National Science Foundation (grant no. OCE-1756646).

Author information

Authors and Affiliations

  1. Department of Marine and Coastal Sciences, Rutgers University, New Brunswick, NJ, USA

    Heidi L. Fuchs, Robert J. Chant, Elias J. Hunter & Emily Y. Chen

  2. Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA

    Enrique N. Curchitser

  3. Physics Department, Skidmore College, Saratoga Springs, NY, USA

    Gregory P. Gerbi

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Contributions

H.L.F., R.J.C. and G.P.G. designed the study. H.L.F., R.J.C., E.J.H. and E.Y.C. compiled and analysed the data. E.N.C. contributed data. H.L.F. and R.J.C. wrote the paper.

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Correspondence to Heidi L. Fuchs.

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Peer review information Nature Climate Change thanks Matthew Ferner and Jorge García Molinos for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 In NWA region, most ranges shifted westward and into shallower, warmer regions with earlier spawning onset.

Bars show trends in latitude (a), longitude (b), and depth (c) computed from observed occurrence locations versus year (1950–2015) for each species. Mean climate velocities (d,e) and trends in bottom water temperature (f) and onset dates for spawning temperatures 8 to 14 oC (g-j) computed from model hindcast at occurrence locations versus year (1958–2012). Vertical line (f) indicates mean warming trend in temperature record. Trends included only if significant at α = 0.05. Symbols indicate taxon (blue circles, bivalves; cyan squares, gastropods; purple diamonds, polychaetes; green triangles, echinoderms); legend indicates species. Lon, longitude; Lat, latitude.

Extended Data Fig. 2 Bottom water temperatures from corrected model (HC) have mean spatial pattern and long-term trend matching observations (WOD).

Maps show long-term mean bottom water temperatures from uncorrected HC (a, \({T}_{{b}_{{\rm{H}}C}}\)), bias- and trend-corrected HC (b, \({T}_{{b}_{{\rm{H}}C}}^{\prime}\)), and re-weighted WOD data (c, \({T}_{{b}_{{\rm{W}}OD}}^{* }\)). d) Time series of spatial mean annual bottom water temperature from uncorrected HC (thick blue line), corrected HC (blue circles), and WOD (yellow line). Bias correction replaces the spatial mean annual temperature of HC with that of WOD data (Eq. (3)), preserving the spatial variability in warming. Thin blue line is linear regression of corrected HC or WOD (1958–2012) temperatures versus year (slope = 0.021oC y−1; p < 10−12; R2 = 0.65). Uncorrected HC temperature has no significant trend versus year.

Extended Data Fig. 3 Occurrence distributions over time are shown for selected species with known spawning temperatures (Supplementary Table 2).

Includes four commercial (fished) bivalves (a, 03 Arctica islandica; b, 12 Mytilus edulis; c, 18 Placopecten Magellanicus; d, 19 Spisula solidissima), two snails (e, 22 Crepidula fornicata; f, 27 Tritia trivittata), and a polychaete (g, 34 Glycera dibranchiata) where numbers indicate ordering in Supplementary Table 1. Dots are recorded occurrences, and colors indicate the year. Some dots overlap; see Supplementary Table 1 for total number of records.

Extended Data Fig. 4 Climate velocities of bottom water temperature varied with bathymetry and diverged mid-shelf in MAB.

Maps show \(\partial {T}_{{b}_{HC}}^{\prime}/\partial t\) (a), \(\partial \overline{{T}_{{b}_{HC}}^{\prime}}/\partial \,\text{Lat}\,\) (b), \(\partial \overline{{T}_{{b}_{HC}}^{\prime}}/\partial \,\text{Lon}\,\) (c), ∂Lat/∂t (d), and ∂Lon/∂t (e) computed from corrected hindcast annual mean temperatures (Eqns. (4)-(5)). Lon, longitude; Lat, latitude.

Extended Data Fig. 5 Range shift velocities were mostly uncorrelated with mean bottom water temperature velocities (climate velocities) across species ranges in NWA and MAB regions.

Data from NWA (a,b) and MAB (c,d). Range shift velocities are from Fig. 3a,b or Extended Data Fig. 1a,b, and mean climate velocities (Eq. (4)–(5)) are from Fig. 3g,h or Extended Data Fig. 1d,e. Positive velocities are northward for latitude and eastward for longitude. Symbols are estimates for each species where trends in latitude (a,c) or longitude (b,d) are significant; c,d omit species sparse in MAB (Supplementary Table 1). Colors indicate associated trends in \({T}_{{b}_{{\rm{HC}}}}^{\prime}\) at occurrence locations. Diagonal grey lines are 1:1; black line (d) is regression significant at α = 0.05 (p = 0.02, R2 = 0.15).

Extended Data Fig. 6 Spawning would occur earliest in the southern part of the study area but probably has shifted earlier due to warming throughout the region.

Maps show long-term averages (a-d) and temporal trends (e-h) in onset dates for spawning at four temperature thresholds (t8, t10, t12, t14) in the Northwest Atlantic region. Onset dates were calculated from corrected HC climatology, and trends were calculated from linear regression of onset dates versus year at each grid point. Regions with no color are always below the indicated temperature threshold.

Extended Data Fig. 7 Range shift velocities were mostly positively correlated with phenological shift rates in the Middle Atlantic Bight.

Range shift velocities shown in Lat/Lon (a-h) and shelf coordinates (i-p) versus phenological shift rates for four potential spawning temperatures (8, 10, 12, and 14 oC). Range shift velocities are from Fig. 3a-d, and phenological shift rates are from Fig. 3i-l. Symbols are estimates for each species where significant, omitting species sparse in MAB (Supplementary Table 1). Colors indicate associated trends in Tb at locations of occurrence. Black lines are linear regressions of all data (solid) or lower left quadrant only (dashed) where significant at α = 0.05.

Extended Data Fig. 8 Most estimated phenological shifts from 1960 to 2010 would result in increasingly negative (down-shelf) mean larval transport velocities.

Mean along-shelf transport velocity versus year from 1960 to 2010, averaged over the 30 days following estimated spawning onset dates. Negative velocities indicate down-shelf transport. Lines are estimates for individual species spawning at four potential temperature thresholds (a-d). Includes estimates where both phenological shift and range shift were significant at α < 0.05. Omits species sparse in MAB or sparse or absent in MAB after 1990 (Supplementary Table 1). Line colors indicate rate of range warming in MAB from observations in Fig. 3f.

Extended Data Fig. 9 Most species’ total range extents changed over time within NWA.

Range extents (vertical bars) of Lat (a), Lon (b), depth (c), and \({T}_{{b}_{HC}}^{\prime}\) (d) are plotted versus species number: #1–20, bivalves; #21–28, gastropods; #29–43, polychaetes; #1–50, echinoderms (Supplementary Table 1). Bars show 98% of data for 1951-1980 (grey) and 1981-2010 (black). The outer 2% of distributions were removed to eliminate outliers. Includes species with > 100 occurrence observations in each time period; absent bars indicate species with too few data in later time period. Range extents were estimated from occurrence locations; ranges of annual average bottom water temperatures were estimated from \({T}_{{b}_{{\rm{H}}C}}^{\prime}\).

Extended Data Fig. 10 Species’ ranges have contracted even where tolerable range area has expanded.

a-b) Change in tolerable habitat area from 1951-1980 to 1981-2010 within NWA (a) or MAB (b), estimated from corrected HC assuming all previously occupied range temperatures (Supplementary Table 5) are tolerable. c) Change in occupied range area from 1951-1980 to 1981-2010, estimated from occurrence locations within MAB, for species with > 200 occurrence observations in each time period as indicated by asterisks above x-axis (species number). Species’ occupied areas changed by an average of − 24.5% for bivalves (#1–20), − 29.5% for gastropods (#21–28), 12.7% for polychaetes (#29–43), and − 38.2% for one echinoderm with sufficient data. For species with estimates in c, tolerable ranges increased overall by an average of 3.3% in NWA and 0.02% in MAB. Within MAB, changes in occupied range area and tolerable range area were uncorrelated.

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Supplementary Figs. 1–3, Tables 1–5 and references.

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Fuchs, H.L., Chant, R.J., Hunter, E.J. et al. Wrong-way migrations of benthic species driven by ocean warming and larval transport. Nat. Clim. Chang. 10, 1052–1056 (2020). https://doi.org/10.1038/s41558-020-0894-x

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