Fortune telling seabirds: sooty shearwaters (Puffinus griseus) predict shifts in Pacific climate

Abstract

Indices calculated from “muttonbirding” diaries collected by the Rakiura Māori of New Zealand were correlated with future values of the Southern Oscillation Index (SOI), and the Pacific Decadal Oscillation (PDO) from 1957 to 2010. Spearman correlations showed that La Niña events tended to occur after those harvest seasons with relatively high success and chick size, whereas El Niño events tended to occur after harvest seasons with relatively low success and chick size. Generalized boosted regression models show that chick size alone is able to predict shifts in SOI from 0 to 12 months after the harvest. A model that included chick size, 2-year average PDO (prior to the harvest), and one year averages of SOI (prior to the harvest), was able to predict shifts in SOI 13–20 months after the harvest. It is likely that sooty shearwater adults (and therefore chick size and quantity) are being affected by oceanographic conditions that are also precursors to shifts in SOI, and that there is a complex interaction between PDO prior to the harvest, the harvest indices and SOI. The location and timing of adult birds at the time they are provisioning chicks could lead to potential mechanisms and requires further study.

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References

  1. Adams J, Flora S (2009) Correlating seabird movements with ocean winds: linking satellite telemetry with ocean scatterometry. Mar Biol 157:915–929. doi:10.1007/s00227-009-1367-y

    Article  Google Scholar 

  2. Ainley D, Clarke E, Arrigo K et al (2005a) Decadal-scale changes in the climate and biota of the Pacific sector of the Southern Ocean, 1950s to the 1990s. Antarct Sci 17:171–182. doi:10.1017/S0954102005002567

    Article  Google Scholar 

  3. Ainley D, Spear L, Tynan C et al (2005b) Physical and biological variables affecting seabird distributions during the upwelling season of the northern California Current. Deep Sea Res Part II Top Stud Oceanogr 52:123–143. doi:10.1016/j.dsr2.2004.08.016

    Article  Google Scholar 

  4. Ashmole N (1971) Seabird ecology and the marine environment. In: Farner D, JR K (eds) Avian biology. Academic Press, New York, New York, pp 223–286

  5. Baird P (1990) Influence of abiotic factors and prey distribution on diet and reprodcutive success of three seabird species in Alaska. Ornis Scand 21:224–235

    Article  Google Scholar 

  6. Barnston A, Tippett M, L’Heureux M et al (2012) Skill of real-time seasonal ENSO model predictions during 2002–11: is our capability increasing? Bull Am Meteorol Soc 93:631–651. doi:10.1175/BAMS-D-11-00111.1

    Article  Google Scholar 

  7. Bjerknes J (1969) Atmospheric teleconnections from the equatorial pacific. Mon Weather Rev 97:163–172

    Article  Google Scholar 

  8. Breiman L (2001) Random forests. Mach Learn 45:5–32

    Article  Google Scholar 

  9. Clucas R (2011) Long-term population trends of Sooty Shearwater (Puffinus griseus) revealed by hunt success. Ecol Appl 21:1308–1326

    Article  Google Scholar 

  10. Clucas R, Moller H, Bragg C (2012) Rakiura Māori muttonbirding diaries: monitoring trends in tītī (Puffinus griseus) abundance in New Zealand. New Zeal J Zool 39:37–41

    Article  Google Scholar 

  11. Cunningham G, Strauss V, Ryan P (2008) African penguins (Spheniscus demersus) can detect dimethyl sulphide, a prey-related odour. J Exp Biol 211:3123–3127. doi:10.1242/jeb.018325

    Article  Google Scholar 

  12. Cutler D, Edwards T, Beard K et al (2007) Random forests for classification in ecology. Ecology 88:2783–2792

    Article  Google Scholar 

  13. Devney CA, Short M, Congdon BC (2009) Sensitivity of tropical seabirds to El Niño precursors. Ecology 90:1175–1183

    Article  Google Scholar 

  14. Durant J, Anker-nilssen T, Stenseth N (2003) Trophic interactions under climate fluctuations: as an example the Atlantic puffin. Proc Biol Sci 270:1461–1466

    Article  Google Scholar 

  15. Erikstad K, Fauchald P, Tveraa T, Steen H (1998) On the cost of reproduction in long-lived birds: the influence of environmental variability. Ecology 79:1781–1788

    Article  Google Scholar 

  16. Furness R, Camphuysen K (1997) Seabirds as monitors of the marine environment. ICES J Mar Sci 54:726–737

    Article  Google Scholar 

  17. Gaston A, Gilchrist H, Mallory M, Smith P (2009) Changes in seasonal events, peak food availability, and consequent breeding adjustment in a marine bird: a case of progressive mismatching. Condor 111:111–119. doi:10.1525/cond.2009.080077

    Article  Google Scholar 

  18. Genuer R, Poggi J, Tuleau-Malot C (2010) Variable selection using random forests. Pattern Recognit Lett 31:2225–2236. doi:10.1016/j.patrec.2010.03.014

    Article  Google Scholar 

  19. Grémillet D, Welcker J, Karnovsky N et al (2012) Little auks buffer the impact of current Arctic climate change. Mar Ecol Prog Ser 454:197–206. doi:10.3354/meps09590

    Article  Google Scholar 

  20. Hansen J (2002) Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges. Agric Syst 74:309–330

    Article  Google Scholar 

  21. Harrison D, Larkin N (1998) El Nino-Southern oscillation sea surface temperature and wind anomalies, 1946–1993. Rev Geophys 36:353–399

    Article  Google Scholar 

  22. Humphries GRW (2014) Using long term harvest records of sooty shearwaters (Titi; Puffinus griseus) to predict shifts in the Southern Oscillation (Thesis, Doctor of Philosophy). University of Otago, Dunedin

  23. Humphries GRW, Velarde E, Anderson DW, Haase B, Sydeman WJ (2015) Seabirds as early warning indicators of climate events in the Pacific. PICES Press 23:18–20

    Google Scholar 

  24. Hunt G Jr (1991) Occurrence of polar seabirds at sea in relation to prey concentrations and oceanographic factors. Polar Res 10:553–560

    Article  Google Scholar 

  25. Hunt G Jr, Stabeno P, Walters G et al (2002) Climate change and control of the southeastern Bering Sea pelagic ecosystem. Deep Sea Res II 49:5821–5853

    Article  Google Scholar 

  26. Jenouvrier S, Barbraud C, Weimerskirch H (2005) Long-term contrasted responses to climate of two Antarctic seabird species. Ecology 86:2889–2903. doi:10.1890/05-0514

    Article  Google Scholar 

  27. Kitson J, Moller H (2008) Looking after your ground: resource management practice by Rakiura Maori titi harvesters. Pap Proc R Soc Tasmania 142:161–176

    Google Scholar 

  28. Lack DL (1966) Population studies of birds. Clarendon Press, Oxford

  29. Liaw A, Wiener M (2002) Classification and regression by randomForest. R News 2:18–22

    Google Scholar 

  30. Lovvorn JR, Richman SF, Grebmeir JM et al (2003) Diet and body condition of spectacled eiders wintering in pack ice of the Bering Sea. Polar Biol 26:259–267

    Google Scholar 

  31. Ludescher J, Gozolchiani A, Bogachev M et al (2014) Very early warning of next El Nino. Proc Natl Acad Sci 111:2064–2066. doi:10.1073/pnas.1323058111

    CAS  Google Scholar 

  32. Lyver P, Moller H, Thompson C (1999) Changes in sooty shearwater Puffinus griseus chick production and harvest precede ENSO events. Mar Ecol Prog Ser 188:237–248. doi:10.3354/meps188237

    Article  Google Scholar 

  33. Mantua N, Hare S (2002) The Pacific decadal oscillation. J Oceanogr 58:35–44

    Article  Google Scholar 

  34. McPhaden MJ, Yu X (1999) Equatorial waves and the 1997–98 El Niño. Geophy Res Lett 26:2961

    Article  Google Scholar 

  35. Newman M, Compo G, Alexander M (2003) ENSO-forced variability of the Pacific decadal oscillation. J Clim 16:3853–3857

    Article  Google Scholar 

  36. Paiva VH, Geraldes P, Marques V, Rodriguez R, Garthe S, Ramos JA (2013) Effects of environmental variability on different trophic levels of the North Atlantic food web. Mar Ecol Prog Ser 477:15–28

    Article  Google Scholar 

  37. Peterson R, White W (1998) Slow oceanic teleconnections linking the Antarctic Circumpolar Wave with the tropical El Niño-Southern Oscillation. J Geophys Res 103:24573–24583. doi:10.1029/98JC01947

    Article  Google Scholar 

  38. Prasad A, Iverson L, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9:181–199

    Article  Google Scholar 

  39. Rasmusson E, Wang X, Ropelewski C (1990) The biennial component of ENSO variability. J Mar Syst 1:71–96

    Article  Google Scholar 

  40. Raymond B, Shaffer S, Sokolov S et al (2010) Shearwater foraging in the Southern Ocean: the roles of prey availability and winds. PLoS One 5:e10960. doi:10.1371/journal.pone.0010960

    Article  Google Scholar 

  41. Ricklefs R (1990) Seabird life histories and the marine environment: some speculations. Colon Waterbirds 13:1–6

    Article  Google Scholar 

  42. Rolland V, Weimerskirch H, Barbraud C (2010) Relative influence of fisheries and climate on the demography of four albatross species. Glob Change Biol 16:1910–1922

    Article  Google Scholar 

  43. Sæther B, Andersen R, Pedersen H (1993) Regulation of parental effort in a long-lived seabird an experimental manipulation of the cost of reproduction in the antarctic petrel, Thalassoica antarctica. Behav Ecol Sociobiol 33:147–150

    Article  Google Scholar 

  44. Salihoglu B, Fraser W, Hofmann E (2001) Factors affecting fledging weight of Adélie penguin (Pygoscelis adeliae) chicks: a modeling study. Polar Biol 24:328–337. doi:10.1007/s003000000215

    Article  Google Scholar 

  45. Sandvik H, Erikstad KE, Barrett RT et al (2005) The effect of climate on adult survival in five species of North Atlantic seabirds. J Anim Ecol 74:817–831

    Article  Google Scholar 

  46. Shaffer S, Tremblay Y, Weimerskirch H et al (2006) Migratory shearwaters integrate oceanic resources across the Pacific Ocean in an endless summer. Proc Natl Acad Sci 103:12799

    CAS  Article  Google Scholar 

  47. Shaffer S, Weimerskirch H, Scott D et al (2009) Spatiotemporal habitat use by breeding sooty shearwaters Puffinus griseus. Mar Ecol Prog Ser 391:209–220. doi:10.3354/meps07932

    Article  Google Scholar 

  48. Shuntov VE (1974) Seabirds and the biological structure of the ocean. Springfield, VA

    Google Scholar 

  49. Soreide N, McCarty L, McClurg D (1995) Mosaic access to real-time data from the TOGA-TAO array of moored buoys. Comput Netw ISDN Syst 28:189–197. doi:10.1016/0169-7552(95)00099-7

    Article  Google Scholar 

  50. Spear L, Ainley D (1999) Migration routes of sooty shearwaters in the Pacific Ocean. Condor 101:205–218. doi:10.2307/1369984

    Article  Google Scholar 

  51. Spear L, Ainley D (2008) The seabird community of the Peru Current, 1980–1995, with comparisons to other eastern boundary currents. Mar Ornithol 36:125–144

    Google Scholar 

  52. Stearns SC (1992) The evolution of life histories, vol 249. Oxford University Press, Oxford

    Google Scholar 

  53. Stenseth N, Ottersen G, Hurrell J et al (2003) Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Nino Southern Oscillation and beyond. Proc R Soc B 270:2087–2096

    Article  Google Scholar 

  54. Tarroux A, Weimerskirch H, Wang SH (2016) Flexible flight response to challenging wind conditions in a commuting Antarctic seabird: do you catch the drift? Anim beh 113:99–112

    Article  Google Scholar 

  55. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Accessed 06 July 2015

  56. Thorne LH, Conners MG, Hazen EL et al (2016) Effects of El Niño-driven changes in wind patterns on North Pacific albatrosses. J R Soc Interface 13:20160196

    Article  Google Scholar 

  57. Trenberth K, Shea D (1987) On the evolution of the southern oscillation. Mon Weather Rev 115:3078–3095

    Article  Google Scholar 

  58. Veit R, Pyle P, McGowan J (1996) Ocean warming and long-term change in pelagic bird abundance within the California current system. Mar Ecol Prog Ser 139:11–18

    Article  Google Scholar 

  59. Veit R, McGowan J, Ainley D et al (1997) Apex marine predator declines ninety percent in association with changing oceanic climate. Glob Chang Biol 3:23–28

    Article  Google Scholar 

  60. Velarde E, Ezcurra E, Cisneros-Mata M, Lavin M (2004) Seabird ecology, El Nino anomalies, and prediction of sardine fisheries in the Gulf of California. Ecol Appl 14:607–615

    Article  Google Scholar 

  61. Vermeer K (1981) The importance of plankton to Cassin’s auklets during breeding. J Plankton Res 3:315–329

    Article  Google Scholar 

  62. Wang S-Y, L’Heureux M, Chia H-H (2012) ENSO prediction one year in advance using western North Pacific sea surface temperatures. Geophys Res Lett. doi:10.1029/2012GL050909

    Google Scholar 

  63. Wang C, Deser C, Yu J-Y et al (2016) El Niño and southern oscillation (ENSO): a review. Coral reefs of the eastern Pacific. Springer, Netherlands, pp 85–106

    Google Scholar 

  64. Weimerskirch H (1998) How can a pelagic seabird provision its chick when relying on a distant food resource? Cyclic attendance at the colony, foraging decision and body condition in sooty shearwaters. J Anim Ecol 67:99–109

    Article  Google Scholar 

  65. Weimerskirch H, Chastel O, Ackermann L (1995) Adjustment of parental effort to manipulated foraging ability in a pelagic seabird, the thin-billed prion Pachyptila belcheri. Behav Ecol Sociobiol 36:11–16

    Article  Google Scholar 

  66. Wells B, Field J, Thayer J et al (2008) Untangling the relationships among climate, prey and top predators in an ocean ecosystem. Mar Ecol Prog Ser 364:15–29. doi:10.3354/meps07486

    Article  Google Scholar 

  67. Zhu J, Zhou G-Q, Zhang R-H, Sun Z (2013) Improving ENSO prediction in a hybrid coupled model with an embedded entrainment temperature parameterisation. Int J Climatol 33:343–355. doi:10.1002/joc.3426

    Article  Google Scholar 

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Acknowledgements

Due to contractual agreements and cultural sensitivities, data used to perform this study are unable to be shared. Additional support for analysis and edits on the manuscript were given by J. Overton, F. Huettmann, C. Strobl, T. Hawthorne, W. Sydeman, J. Elith and S. Oppel. We would also like to thank Axios Review for their help in preparing the manuscript.

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Correspondence to Grant R. W. Humphries.

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This research was funded by the Department of Zoology at the University of Otago and by National Geographic Grant# WGS249-12 on behalf of the Waitt foundation.

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G. R. W. Humphries declares that he has no conflict of interest. H. Moller declares that he has no conflict of interest.

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Humphries, G.R.W., Möller, H. Fortune telling seabirds: sooty shearwaters (Puffinus griseus) predict shifts in Pacific climate. Mar Biol 164, 150 (2017). https://doi.org/10.1007/s00227-017-3182-1

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