Global change drives modern plankton communities away from the pre-industrial state

Abstract

The ocean—the Earth’s largest ecosystem—is increasingly affected by anthropogenic climate change1,2. Large and globally consistent shifts have been detected in species phenology, range extension and community composition in marine ecosystems3,4,5. However, despite evidence for ongoing change, it remains unknown whether marine ecosystems have entered an Anthropocene6 state beyond the natural decadal to centennial variability. This is because most observational time series lack a long-term baseline, and the few time series that extend back into the pre-industrial era have limited spatial coverage7,8. Here we use the unique potential of the sedimentary record of planktonic foraminifera—ubiquitous marine zooplankton—to provide a global pre-industrial baseline for the composition of modern species communities. We use a global compilation of 3,774 seafloor-derived planktonic foraminifera communities of pre-industrial age9 and compare these with communities from sediment-trap time series that have sampled plankton flux since ad 1978 (33 sites, 87 observation years). We find that the Anthropocene assemblages differ from their pre-industrial counterparts in proportion to the historical change in temperature. We observe community changes towards warmer or cooler compositions that are consistent with historical changes in temperature in 85% of the cases. These observations not only confirm the existing evidence for changes in marine zooplankton communities in historical times, but also demonstrate that Anthropocene communities of a globally distributed zooplankton group systematically differ from their unperturbed pre-industrial state.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Concept of the comparison between Anthropocene and pre-industrial communities.
Fig. 2: Changes in planktonic foraminifera communities in response to Anthropocene sea-surface temperature change.
Fig. 3: Global planktonic foraminifera communities change consistently with historical temperature trends.
Fig. 4: Robustness of the sign of change in planktonic foraminifera community composition.

Data availability

The ForCenS core top planktonic foraminifera dataset is available at Pangaea (https://doi.org/10.1594/PANGAEA.873570) and the HadISST data are available from the UK Met Office (https://www.metoffice.gov.uk/hadobs/hadisst/). NOAA ERSST v.5 data were provided by the NOAA/OAR/ESRL PSD (https://www.esrl.noaa.gov/psd/). Taxonomically harmonized shell flux data are available at https://doi.org/10.5281/zenodo.2638013.

Code availability

Code is available at https://doi.org/10.5281/zenodo.2638013.

References

  1. 1.

    IPCC. Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  2. 2.

    Abram, N. J. et al. Early onset of industrial-era warming across the oceans and continents. Nature 536, 411–418 (2016).

    CAS  Article  Google Scholar 

  3. 3.

    Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925 (2013).

    ADS  Article  Google Scholar 

  4. 4.

    Beaugrand, G., McQuatters-Gollop, A., Edwards, M. & Goberville, E. Long-term responses of North Atlantic calcifying plankton to climate change. Nat. Clim. Change 3, 263–267 (2013).

    ADS  CAS  Article  Google Scholar 

  5. 5.

    Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).

    ADS  CAS  Article  Google Scholar 

  6. 6.

    Waters, C. N. et al. The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science 351, aad2622 (2016).

    Article  Google Scholar 

  7. 7.

    Field, D. B., Baumgartner, T. R., Charles, C. D., Ferreira-Bartrina, V. & Ohman, M. D. Planktonic foraminifera of the California Current reflect 20th-century warming. Science 311, 63–66 (2006).

    ADS  CAS  Article  Google Scholar 

  8. 8.

    Spielhagen, R. F. et al. Enhanced modern heat transfer to the Arctic by warm Atlantic Water. Science 331, 450–453 (2011).

    ADS  CAS  Article  Google Scholar 

  9. 9.

    Siccha, M. & Kucera, M. ForCenS, a curated database of planktonic foraminifera census counts in marine surface sediment samples. Sci. Data 4, 170109 (2017).

    Article  Google Scholar 

  10. 10.

    Rosenzweig, C. et al. Attributing physical and biological impacts to anthropogenic climate change. Nature 453, 353–357 (2008).

    ADS  CAS  Article  Google Scholar 

  11. 11.

    Hillebrand, H. et al. Biodiversity change is uncoupled from species richness trends: consequences for conservation and monitoring. J. Appl. Ecol. 55, 169–184 (2018).

    Article  Google Scholar 

  12. 12.

    Gonzalez, A. et al. Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity. Ecology 97, 1949–1960 (2016).

    Article  Google Scholar 

  13. 13.

    Morey, A. E., Mix, A. C. & Pisias, N. G. Planktonic foraminiferal assemblages preserved in surface sediments correspond to multiple environment variables. Quat. Sci. Rev. 24, 925–950 (2005).

    ADS  Article  Google Scholar 

  14. 14.

    Bé, A. W. H. & Tolderlund, D. S. in The Micropaleontology of Oceans (eds Funnell, B. M. & Riedel, W. R.) Ch. 6, 105–149 (Cambridge Univ. Press, 1971).]

  15. 15.

    Morard, R. et al. Surface ocean metabarcoding confirms limited diversity in planktonic foraminifera but reveals unknown hyper-abundant lineages. Sci. Rep. 8, 2539 (2018).

    ADS  Article  Google Scholar 

  16. 16.

    Rebotim, A. et al. Factors controlling the depth habitat of planktonic foraminifera in the subtropical eastern North Atlantic. Biogeosciences 14, 827–859 (2017).

    ADS  CAS  Article  Google Scholar 

  17. 17.

    CLIMAP Project Members. Seasonal Reconstruction of the Earth’s surface at the Last Glacial Maximum. Map and Chart Series MC-36 (ed. McIntyre, A.) (Geological Society of America, 1981).

  18. 18.

    Kucera, M. et al. Reconstruction of sea-surface temperatures from assemblages of planktonic foraminifera: multi-technique approach based on geographically constrained calibration data sets and its application to glacial Atlantic and Pacific Oceans. Quat. Sci. Rev. 24, 951–998 (2005).

    ADS  Article  Google Scholar 

  19. 19.

    Ruddiman, W. F., Tolderlund, D. S. & Bé, A. W. H. Foraminiferal evidence of a modern warming of the North Atlantic Ocean. Deep Sea Res. 17, 141–155 (1970).

    Google Scholar 

  20. 20.

    Berger, W. H. Planktonic Foraminifera: selective solution and paleoclimatic interpretation. Deep Sea Res. 15, 31–43 (1968).

    ADS  Google Scholar 

  21. 21.

    Berger, W. H. Planktonic Foraminifera: selective solution and the lysocline. Mar. Geol. 8, 111–138 (1970).

    ADS  Article  Google Scholar 

  22. 22.

    Archer, D. E. An atlas of the distribution of calcium carbonate in sediments of the deep sea. Glob. Biogeochem. Cycles 10, 159–174 (1996).

    CAS  Article  Google Scholar 

  23. 23.

    von Gyldenfeldt, A.-B., Carstens, J. & Meincke, J. Estimation of the catchment area of a sediment trap by means of current meters and foraminiferal tests. Deep Sea Res. 47, 1701–1717 (2000).

    ADS  Article  Google Scholar 

  24. 24.

    van Sebille, E. et al. Ocean currents generate large footprints in marine palaeoclimate proxies. Nat. Commun. 6, 6521 (2015).

    ADS  Article  Google Scholar 

  25. 25.

    Enquist, B. J. et al. in Advances in Ecological Research Vol. 52 (eds Pawar, S. et al.) 249–318 (Academic, 2015).

  26. 26.

    Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407 (2003).

    Article  Google Scholar 

  27. 27.

    Jonkers, L. & Kučera, M. Global analysis of seasonality in the shell flux of extant planktonic Foraminifera. Biogeosciences 12, 2207–2226 (2015).

    ADS  Article  Google Scholar 

  28. 28.

    Prell, W. The Stability of Low-Latitude Sea-Surface Temperatures, an Evaluation of the CLIMAP Reconstruction with Emphasis on the Positive SST Anomalies. Report No. TR025 (US Department of Energy, 1985).

  29. 29.

    Darling, K. F. & Wade, C. M. The genetic diversity of planktic foraminifera and the global distribution of ribosomal RNA genotypes. Mar. Micropaleontol. 67, 216–238 (2008).

    ADS  Article  Google Scholar 

  30. 30.

    R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (R Foundation for Statistical Computing, 2016).

  31. 31.

    Juggins, S. rioja: Analysis of Quaternary Science Data. R package version 0.9-15.1 http://cran.r-project.org/package=rioja (2017).

  32. 32.

    Wickham, H. Reshaping data with the reshape package. J. Stat. Softw. 21, 1–20 (2007).

    Article  Google Scholar 

  33. 33.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).

  34. 34.

    Hijmans, R. J., Williams, E. & Vennes, C. geosphere: Spherical Trigonometry. R package version 1.5-7 https://CRAN.R-project.org/package=geosphere (2017).

  35. 35.

    Wickham, H. & Bryan, J. readxl: Read Excel Files. R package version 1.1.0 https://CRAN.R-project.org/package=readxl (2018).

  36. 36.

    Harrell, F. E. Jr. Hmisc: Harrell Miscellaneous. R package version 4.1-1 https://CRAN.R-project.org/package=Hmisc (2018).

  37. 37.

    Hijmans, R. J. et al. raster: Geographic Data Analysis and Modeling. R package version 2.6-7. https://CRAN.R-project.org/package=raster (2017).

  38. 38.

    Pebesma, E. J. & Bivand, R. S. Classes and methods for spatial data in R. R News 5, 9–13 (2005).

    Google Scholar 

  39. 39.

    Bivand, R. S., Pebesma, E. & Gómez-Rubio, V. Applied Spatial Data Analysis with R (Springer, 2008).

  40. 40.

    Bivand, R. et al. rgdal: Bindings for the 'Geospatial' Data Abstraction Library. R package version 1.3-1 https://CRAN.R-project.org/package=rgdal (2018).

  41. 41.

    Berger, W. H. & Heath, G. R. Vertical mixing in pelagic sediments. J. Mar. Res. 26, 134–143 (1968).

    Google Scholar 

  42. 42.

    Burwicz, E. B., Rüpke, L. H. & Wallmann, K. Estimation of the global amount of submarine gas hydrates formed via microbial methane formation based on numerical reaction-transport modeling and a novel parameterization of Holocene sedimentation. Geochim. Cosmochim. Acta 75, 4562–4576 (2011).

    ADS  CAS  Article  Google Scholar 

  43. 43.

    Boudreau, B. P. Mean mixed depth of sediments: the wherefore and the why. Limnol. Oceanogr. 43, 524–526 (1998).

    ADS  Article  Google Scholar 

  44. 44.

    Al-Sabouni, N., Kucera, M. & Schmidt, D. N. Vertical niche separation control of diversity and size disparity in planktonic foraminifera. Mar. Micropaleontol. 63, 75–90 (2007).

    ADS  Article  Google Scholar 

  45. 45.

    Huang, B. et al. NOAA Extended Reconstructed Sea Surface Temperature (ERSST). Version 5 https://doi.org/10.7289/V5T72FNM (NOAA National Centers for Environmental Information, 2017).

  46. 46.

    Huang, B. et al. Further exploring and quantifying uncertainties for extended reconstructed sea surface temperature (ERSST) version 4 (v4). J. Clim. 29, 3119–3142 (2016).

    ADS  Article  Google Scholar 

  47. 47.

    Asahi, H. & Takahashi, K. A 9-year time-series of planktonic foraminifer fluxes and environmental change in the Bering Sea and the central subarctic Pacific Ocean, 1990–1999. Prog. Oceanogr. 72, 343–363 (2007).

    ADS  Article  Google Scholar 

  48. 48.

    Deuser, W. G. & Ross, E. H. Seasonally abundant planktonic foraminifera of the Sargasso Sea; succession, deep-water fluxes, isotopic compositions, and paleoceanographic implications. J. Foraminiferal Res. 19, 268–293 (1989).

    Article  Google Scholar 

  49. 49.

    Deuser, W. G., Ross, E. H., Hemleben, C. & Spindler, M. Seasonal changes in species composition, numbers, mass, size, and isotopic composition of planktonic foraminifera settling into the deep Sargasso Sea. Palaeogeogr. Palaeoclimatol. Palaeoecol. 33, 103–127 (1981).

    Article  Google Scholar 

  50. 50.

    Northcote, L. C. & Neil, H. L. Seasonal variations in foraminiferal flux in the Southern Ocean, Campbell Plateau, New Zealand. Mar. Micropaleontol. 56, 122–137 (2005).

    ADS  Article  Google Scholar 

  51. 51.

    Guptha, M. V. S., Curry, W. B., Ittekkot, V. & Muralinath, A. S. Seasonal variation in the flux of planktic Foraminifera; sediment trap results from the Bay of Bengal, northern Indian Ocean. J. Foraminiferal Res. 27, 5–19 (1997).

    Article  Google Scholar 

  52. 52.

    Žarić, S., Donner, B., Fischer, G., Mulitza, S. & Wefer, G. Sensitivity of planktic foraminifera to sea surface temperature and export production as derived from sediment trap data. Mar. Micropaleontol. 55, 75–105 (2005).

    ADS  Article  Google Scholar 

  53. 53.

    Reuter, R. T., Jonkers, L. & Kucera, M. Planktonic foraminifera shell flux data from sediment trap CB-3. PANGAEA https://doi.org/10.1594/PANGAEA.899732 (2016).

  54. 54.

    Ortiz, J. D. & Mix, A. C. The spatial distribution and seasonal succession of planktonic foraminifera in the California Current off Oregon, September 1987 – September 1988. Geol. Soc. Lond. Spec. Publ. 64, 197–213 (1992).

    ADS  Article  Google Scholar 

  55. 55.

    Jensen, S. Planktische Foraminiferen im Europaischen Nordmeer: Verbreitung und Vertikalfluss sowie ihre Entwicklung wahrend der letzten 15000 Jahre. PhD thesis, Univ. Kiel (1998).

  56. 56.

    Poore, R. Z., Tedesco, K. A. & Spear, J. W. Seasonal flux and assemblage composition of planktic foraminifers from a sediment-trap study in the northern Gulf of Mexico. J. Coast. Res. 63, 6–19 (2013).

    CAS  Article  Google Scholar 

  57. 57.

    Reynolds, C. E., Richey, J. N. & Poore, R. Z. Seasonal Flux and Assemblage Composition of Planktic Foraminifera from the Northern Gulf of Mexico, 2008–2012. US Geological Survey Open-File Report 2013–1243 https://doi.org/10.3133/ofr20131243 (USGS, 2013).

  58. 58.

    Jonkers, L., Reynolds, C. E., Richey, J. & Hall, I. R. Lunar periodicity in the shell flux of planktonic foraminifera in the Gulf of Mexico. Biogeosciences 12, 3061–3070 (2015).

    ADS  Article  Google Scholar 

  59. 59.

    Wolfteich, C. M. Sattelite-Derived Sea Surface Temperature, Mesoscale Variability, And Foraminiferal Production in the North Atlantic. MSc thesis, MIT and WHOI (1994).

  60. 60.

    Jonkers, L., Brummer, G.-J. A., Peeters, F. J. C., van Aken, H. M. & De Jong, M. F. Seasonal stratification, shell flux, and oxygen isotope dynamics of left-coiling N. pachyderma and T. quinqueloba in the western subpolar North Atlantic. Paleoceanography 25, PA2204 (2010).

    ADS  Google Scholar 

  61. 61.

    Jonkers, L., van Heuven, S., Zahn, R. & Peeters, F. J. C. Seasonal patterns of shell flux, δ18O and δ13C of small and large N. pachyderma (s) and G. bulloides in the subpolar North Atlantic. Paleoceanography 28, 164–174 (2013).

    ADS  Article  Google Scholar 

  62. 62.

    Reuter, R. T., Jonkers, L., Brummer, G. J. & Kucera, M. Planktonic foraminifera shell flux data from sediment trap IRM-1. PANGAEA https://doi.org/10.1594/PANGAEA.899733 (2018).

  63. 63.

    Mohtadi, M. et al. Low-latitude control on seasonal and interannual changes in planktonic foraminiferal flux and shell geochemistry off south Java: A sediment trap study. Paleoceanography 24, PA1201 (2009).

    ADS  MathSciNet  Article  Google Scholar 

  64. 64.

    Rigual-Hernández, A. S., Sierro, F. J., Bárcena, M. A., Flores, J. A. & Heussner, S. Seasonal and interannual changes of planktic foraminiferal fluxes in the Gulf of Lions (NW Mediterranean) and their implications for paleoceanographic studies: two 12-year sediment trap records. Deep Sea Res. 66, 26–40 (2012).

    Article  Google Scholar 

  65. 65.

    Donner, B. & Wefer, G. Flux and stable isotope composition of Neogloboquadrina pachyderma and other planktonic foraminifers in the Southern Ocean (Atlantic sector). Deep Sea Res. 41, 1733–1743 (1994).

    Article  Google Scholar 

  66. 66.

    Storz, D., Schulz, H., Waniek, J. J., Schulz-Bull, D. E. & Kučera, M. Seasonal and interannual variability of the planktic foraminiferal flux in the vicinity of the Azores Current. Deep Sea Res. 56, 107–124 (2009).

    Article  Google Scholar 

  67. 67.

    Kuroyanagi, A., Kawahata, H., Nishi, H. & Honda, M. C. Seasonal changes in planktonic foraminifera in the northwestern North Pacific Ocean: sediment trap experiments from subarctic and subtropical gyres. Deep Sea Res. 49, 5627–5645 (2002).

    ADS  Article  Google Scholar 

  68. 68.

    Sagawa, T., Kuroyanagi, A., Irino, T., Kuwae, M. & Kawahata, H. Seasonal variations in planktonic foraminiferal flux and oxygen isotopic composition in the western North Pacific: implications for paleoceanographic reconstruction. Mar. Micropaleontol. 100, 11–20 (2013).

    ADS  Article  Google Scholar 

  69. 69.

    Alderman, S. E. Planktonic Foraminifera in the Sea of Okhotsk: Population and Stable Isotopic Analysis from a Sediment Trap. MSc thesis, MIT and WHOI (1996).

  70. 70.

    Sautter, L. R. & Thunell, R. C. Seasonal succession of planktonic foraminifera; results from a four-year time-series sediment trap experiment in the Northeast Pacific. J. Foraminiferal Res. 19, 253–267 (1989).

    Article  Google Scholar 

  71. 71.

    King, A. L. & Howard, W. R. Planktonic foraminiferal flux seasonality in Subantarctic sediment traps: a test for paleoclimate reconstructions. Paleoceanography 18, 1019 (2003).

    ADS  Article  Google Scholar 

  72. 72.

    Curry, W. B., Ostermann, D. R., Guptha, M. V. S. & Ittekkot, V. Foraminiferal production and monsoonal upwelling in the Arabian Sea: evidence from sediment traps. Geol. Soc. Lond. Spec. Publ. 64, 93–106 (1992).

    ADS  Article  Google Scholar 

  73. 73.

    Mohiuddin, M. M., Nishimura, A., Tanaka, Y. & Shimamoto, A. Regional and interannual productivity of biogenic components and planktonic foraminiferal fluxes in the northwestern Pacific Basin. Mar. Micropaleontol. 45, 57–82 (2002).

    ADS  Article  Google Scholar 

  74. 74.

    Mohiuddin, M. M., Nishimura, A. & Tanaka, Y. Seasonal succession, vertical distribution, and dissolution of planktonic foraminifera along the Subarctic Front: implications for paleoceanographic reconstruction in the northwestern Pacific. Mar. Micropaleontol. 55, 129–156 (2005).

    ADS  Article  Google Scholar 

  75. 75.

    Xiang, R. et al. Seasonal flux variability of planktonic foraminifera during 2009–2011 in a sediment trap from Xisha Trough, South China Sea. Aquat. Ecosyst. Health Manage. 18, 403–413 (2015).

    Article  Google Scholar 

Download references

Acknowledgements

We thank R. Reuter for help with foraminifera analysis and acknowledge funding by the Volkswagen Stiftung for the MarBAS (Marine Biodiversität—Analyse über zeitliche und räumliche Skalen) project as well as by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through Germany’s Excellence Strategy (EXC-2077, grant no 390741603). M.K. was funded through DFG-Research Center/Cluster of Excellence ‘The Ocean in the Earth System’.

Reviewer information

Nature thanks Andrew J. Fraass, Anthony Richardson and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

Authors

Contributions

L.J. and M.K. designed research. L.J. compiled and analysed the data. All authors discussed the results and contributed to the writing of the manuscript.

Corresponding author

Correspondence to Lukas Jonkers.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Pre-industrial age of the sedimentary samples.

Mean age in years of core top sediment estimate using the depth solution of a previous study41 (contours). The grey box denotes the likely average ages of the core top sediments based on our best estimate of sediment accumulation rate (in cm per 1,000 years (kyr)) and bioturbation depth. Irrespective of the sampling date (mostly pre-1980), the average sedimentary species composition predates the Anthropocene.

Extended Data Fig. 2 Linear regression between dissimilarity and latitudinal distance in the sedimentary species assemblages.

The relationship (shown in red) is used to estimate the latitudinal displacement based on the dissimilarity between the modern and pre-industrial species composition. Example for time series S47 from the south of New Zealand (Extended Data Table 1).

Extended Data Fig. 3 Insensitivity of planktonic foraminifera assemblage change to size fraction.

The direction of change for planktonic foraminifera species communities (warming or cooling) was inferred from sediment-trap time series for which the samples were larger than 125 μm and larger than 150 μm. Colours and symbols are as in Fig. 3b. W and C indicate warming and cooling, respectively, with the first letter indicating the historical change and the second the change as indicated by the species composition. Both small and large shell sizes are dominated by a change in the species community that is consistent with the direction of historical change in temperatures. The observed pattern is thus insensitive to the inclusion of sediment-trap time series that used a slightly smaller size fraction than the sediment samples.

Extended Data Fig. 4 Assessing uncertainty in the historical change in temperatures by comparing the HadISST and ERSST temperature products.

a, Comparison of the relationships between the historical change in temperature and the difference between the modern and sedimentary species composition (based on linear regression weighted to the duration of the time series; see also Fig. 2a). The relationship has a similar slope for both sea-surface temperature products, even though the relationship based on ERSST data has a larger uncertainty. Shaded error envelopes show 95% confidence intervals of the regression. b, Histograms of consistency and direction of changes in the species communities (Fig. 3a). The pattern of change is broadly similar for both products, which indicates that although the observations are to some degree sensitive to the uncertainty in the historical change in temperatures, they are largely consistent between the two datasets.

Extended Data Table 1 Sediment-trap time series used to determine modern species compositions

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jonkers, L., Hillebrand, H. & Kucera, M. Global change drives modern plankton communities away from the pre-industrial state. Nature 570, 372–375 (2019). https://doi.org/10.1038/s41586-019-1230-3

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing