Global satellite-observed daily vertical migrations of ocean animals

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Abstract

Every night across the world’s oceans, numerous marine animals arrive at the surface of the ocean to feed on plankton after an upward migration of hundreds of metres. Just before sunrise, this migration is reversed and the animals return to their daytime residence in the dark mesopelagic zone (at a depth of 200–1,000 m). This daily excursion, referred to as diel vertical migration (DVM), is thought of primarily as an adaptation to avoid visual predators in the sunlit surface layer1,2 and was first recorded using ship-net hauls nearly 200 years ago3. Nowadays, DVMs are routinely recorded by ship-mounted acoustic systems (for example, acoustic Doppler current profilers). These data show that night-time arrival and departure times are highly conserved across ocean regions4 and that daytime descent depths increase with water clarity4,5, indicating that animals have faster swimming speeds in clearer waters4. However, after decades of acoustic measurements, vast ocean areas remain unsampled and places for which data are available typically provide information for only a few months, resulting in an incomplete understanding of DVMs. Addressing this issue is important, because DVMs have a crucial role in global ocean biogeochemistry. Night-time feeding at the surface and daytime metabolism of this food at depth provide an efficient pathway for carbon and nutrient export6,7,8. Here we use observations from a satellite-mounted light-detection-and-ranging (lidar) instrument to describe global distributions of an optical signal from DVM animals that arrive in the surface ocean at night. Our findings reveal that these animals generally constitute a greater fraction of total plankton abundance in the clear subtropical gyres, consistent with the idea that the avoidance of visual predators is an important life strategy in these regions. Total DVM biomass, on the other hand, is higher in more productive regions in which the availability of food is increased. Furthermore, the 10-year satellite record reveals significant temporal trends in DVM biomass and correlated variations in DVM biomass and surface productivity. These results provide a detailed view of DVM activities globally and a path for refining the quantification of their biogeochemical importance.

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Fig. 1: Marine animal and phytoplankton influences on day-to-night changes in particulate backscattering coefficients and the biomass-normalized difference ratio.
Fig. 2: Global climatological signal of vertically migrating animals quantified as the normalized difference ratio.
Fig. 3: Comparison of CALIOP normalized difference ratios and field-based DVM measurements in the PSO.
Fig. 4: CALIOP-based estimates of vertically migrating animal biomass (DVMCALIOP) and temporal changes.

Data availability

The CALIOP lidar and field ADCP datasets analysed during the current study are available at http://www.science.oregonstate.edu/ocean.productivity/ and from the Joint Archive for Shipboard ADCP at http://ilikai.soest.hawaii.edu/sadcp/. Source Data for Figs. 3b–d, 4b and Extended Data Figs. 3, 68 are provided with the paper.

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Acknowledgements

This work was supported by the National Aeronautics and Space Administration’s North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) and EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) study. A.D.P. was supported by the Applied Physics Laboratory Science and Engineering Enrichment Development (SEED) fellowship. This project received funding from the European Union’s Horizon 2020 research and innovation program under Marie Sklodowska-Curie grant agreement number 749591.

Author information

M.J.B. designed the study. M.J.B., P.G., A.D.P., W.J.B., Y.H. and R.T.O. processed data and analysed results. M.J.B., P.G., A.D.P. and R.T.O. prepared display items. M.J.B. wrote the manuscript with contributions from all authors.

Correspondence to Michael J. Behrenfeld.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Daniele Bianchi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Fig. 1 Global CALIOP observational coverage.

ae, CALIOP ground tracks for 1 (a), 2 (b), 4 (c), 8 (d) and 16 (e) days. f, Number of months for each 2° × 2° bin with day and night retrievals of bbp for the 2008–2017 study period. The total number of months possible is 115. The north–south strip of low retrieval success in the middle of the Pacific is caused by a gap in ancillary AMSER surface wind data. AMSER wind data are used for flagging CALIOP data with potential bubble contamination (Methods).

Extended Data Fig. 2 Global distributions of monthly climatological mean values of ∆bbp.

Thin black line, contour of monthly mean sea surface temperature of 15 °C. Thick black lines, monthly extent of the 5 subtropical gyres in which annual mean surface chlorophyll concentrations are ≤0.08 mg m−3.

Extended Data Fig. 3 Time series of ∆bbp for the PSO.

ah, The 2008–2017 monthly values of ∆bbp (%) for the eight PSO regions described in Fig. 3a. Souce data

Extended Data Fig. 4 Global coverage of field ADCP data.

Number of days within each 5° × 5° bin for which paired day–night ADCP data are available from the 1985–2017 JASADCP-based field archive (http://ilikai.soest.hawaii.edu/sadcp/). The total number of days possible is 11,680. White bins, no data. Yellow/black line, contour of annual mean sea surface temperature of 15 °C. Thick white lines, boundaries of the eight PSO regions described in Fig. 3a.

Extended Data Fig. 5 Influence of phytoplankton division rate and of day length on calculated DVM backscatter for the PSO.

a, Values for c1 (equation (6)) over the range of phytoplankton division rates (µ) in the PSO (n = 999 monthly µ values for all PSO regions). Solid circle, mean value of µ and c1 for the PSO. The box shows ±1 s.d. of the mean of µ and the solid line shows values of c1 over the full range in µ for the PSO. b, Values for c2 (equation (7)) over the range of day lengths in the PSO (n = 999 monthly day length values for all PSO regions). Solid circle, mean day length and c2 value for the PSO. The box shows ±1 s.d. of the mean day length and the solid line shows values of c2 over the full range in day length for the PSO.

Extended Data Fig. 6 Seasonal cycles in monthly mean regionally integrated values of DVMCALIOP and phytoplankton biomass for high-latitude regions.

a, North Pacific. b, North Atlantic. c, Southern Ocean. These three regions are described in Fig. 4c. Vertical lines show ±1 s.d. (n = 111 monthly DVMCALIOP (g m−2) and Cphyto (mg C m−3) values for each region). Cphyto data are from the carbon-based production model (CbPM) and MODIS passive ocean-colour data (Methods). Source data

Extended Data Fig. 7 Comparison of CALIOP night–day bbp differences and field ADCP night–day differences in acoustic backscatter.

Dashed line, two-sided least-squares linear regression fit to data for the SPSG, NPSG, TP, STA, NASG and NTA (n = 6). For completeness, the mean value for PSO bins outside our eight primary regions is indicated by the white symbol. Symbols, regional mean ±s.e.m. (SISG, n = 19; SASG, n = 18; TP, n = 115; NASG, n = 16; NTA, n = 23; NPSG, n = 59; STA, n = 22; SPSG, n = 59; other, n = 302). Symbol colours identify region (labelled on the right) and correspond to the colours shown in Fig. 3a. Numbers next to each symbol indicate the median number of days with ADCP data within the 32-year field record for the 5°× 5° bins. Source data

Extended Data Fig. 8 Bin-to-bin comparison of CALIOP ∆bbp and field-based DVM measurements in the PSO.

a, CALIOP normalized difference ratios (∆bbp) versus field ADCP (∆BADCP) normalized difference ratios for 5° × 5° bins within the PSO. Black line, two-sided least-squares linear regression fit (F–test P value for slope; P < 0.001; n = 331 independent geographical bins) for all data from our eight primary PSO regions (coloured symbols are labelled on the right). White symbols, PSO values for 5° × 5° bins outside of the 8 primary regions. Inclusion of these data in the linear regression analysis increases the F-test value to P = 0.005 (n = 633 independent geographical bins). b, Relationship between field DVM biomass at the HOT site measured for a given calendar month and year (x axis) versus DVM biomass measured during all other years for the same calendar month (y axis). Source data

Extended Data Fig. 9 Field-based diel cycles in bbp.

Mean diel cycles in bbp from a previous study19 for mixing (blue line; n = 69 days of measurements), oligotrophy (green line; n = 322 days of measurements) and declining (red line; n = 32 days of measurements) conditions and the mean of these three cycles (black line), which corresponds to the diel cycle in Fig. 1b.

Supplementary information

Supplementary Discussion

The Supplementary Discussion provides additional information regarding: (1) CALIOP orbits and data binning, (2) high-latitude spatial variability in CALIOP retrievals, (3) normalized difference ratio data and results in figure 3 of the main manuscript, (4) calculation of the phytoplankton diel bbp cycle, (5) additional details on calculations of DVM biomass, and (6) directions for future research.

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Behrenfeld, M.J., Gaube, P., Della Penna, A. et al. Global satellite-observed daily vertical migrations of ocean animals. Nature 576, 257–261 (2019) doi:10.1038/s41586-019-1796-9

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