Climate-driven range shifts of the king penguin in a fragmented ecosystem

  • 1.

    Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).

  • 2.

    Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–224 (2015).

  • 3.

    Charmantier, A. et al. Adaptive phenotypic plasticity in response to climate change in a wild bird population. Science 320, 800–803 (2008).

  • 4.

    Garcia, R. A., Cabeza, M., Rahbek, C. & Araújo, M. B. Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579 (2014).

  • 5.

    Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).

  • 6.

    Gouveia, S. F. et al. Climate and land use changes will degrade the configuration of the landscape for titi monkeys in eastern Brazil. Glob. Change Biol. 22, 2003–2012 (2016).

  • 7.

    Edwards, M. & Richardson, A. J. Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430, 881–884 (2004).

  • 8.

    Saraux, C. et al. Reliability of flipper-banded penguins as indicators of climate change. Nature 469, 203–206 (2011).

  • 9.

    Kearney, M. & Porter, W. Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges. Ecol. Lett. 12, 334–350 (2009).

  • 10.

    Thuiller, W. et al. A road map for integrating eco-evolutionary processes into biodiversity models. Ecol. Lett. 16, 94–105 (2013).

  • 11.

    Elith, J., Kearney, M. & Phillips, S. The art of modelling range‐shifting species. Methods Ecol. Evol. 1, 330–342 (2010).

  • 12.

    Fordham, D. A. et al. Population dynamics can be more important than physiological limits for determining range shifts under climate change. Glob. Change Biol. 19, 3224–3237 (2013).

  • 13.

    Fordham, D. A., Brook, B. W., Moritz, C. & Nogués-Bravo, D. Better forecasts of range dynamics using genetic data. Trends Ecol. Evol. 29, 436–443 (2014).

  • 14.

    Fordham, D. A. et al. Predicting and mitigating future biodiversity loss using long-term ecological proxies. Nat. Clim. Change 6, 909–916 (2016).

  • 15.

    Alter, S. E. et al. Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100. Mol. Ecol. 24, 1510–1522 (2015).

  • 16.

    Kearney, M., Porter, W. P., Williams, C., Ritchie, S. & Hoffmann, A. A. Integrating biophysical models and evolutionary theory to predict climatic impacts on species’ ranges: the dengue mosquito in Australia. Funct. Ecol. 23, 528–538 (2009).

  • 17.

    Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).

  • 18.

    Bost, C. A. et al. Large-scale climatic anomalies affect marine predator foraging behaviour and demography. Nat. Commun. 6, 8220 (2015).

  • 19.

    Trucchi, E. et al. King penguin demography since the last glaciation inferred from genome-wide data. Proc. R. Soc. B 281, 20140528 (2014).

  • 20.

    Péron, C., Weimerskirch, H. & Bost, C.-A. Projected poleward shift of king penguins’ (Aptenodytes patagonicus) foraging range at the Crozet Islands, southern Indian Ocean. Proc. R. Soc. B 279, 2515–2523 (2012).

  • 21.

    Le Bohec, C. et al. King penguin population threatened by Southern Ocean warming. Proc. Natl Acad. Sci. USA 105, 2493–2497 (2008).

  • 22.

    Engler, R. et al. Predicting future distributions of mountain plants under climate change: does dispersal capacity matter. Ecography 32, 34–45 (2009).

  • 23.

    Clucas, G. V. et al. Dispersal in the sub-Antarctic: king penguins show remarkably little population genetic differentiation across their range. BMC Evol. Biol. 16, 211 (2016).

  • 24.

    Barrat, A. Quelques aspects de la biologie et de l’écologie du manchot royal Aptenodytes patagonicus des îles Crozet. Com. Natl Fr. Rech. Antarct. 40, 9–51 (1976).

  • 25.

    Heupink, T. H., van den Hoff, J. & Lambert, D. M. King penguin population on Macquarie Island recovers ancient DNA diversity after heavy exploitation in historic times. Biol. Lett. 8, 586–589 (2012).

  • 26.

    Pistorius, P. A., Baylis, A., Crofts, S. & Pütz, K. Population development and historical occurrence of king penguins at the Falkland Islands. Antarct. Sci. 24, 435–440 (2012).

  • 27.

    Kusch, A. & Marín, M. Sobre la distribución del Pingüino Rey Aptenodytes Patagonicus (Aves: Spheniscidae) en Chile. An. Inst. Patagonia 40, 157–163 (2012).

  • 28.

    Wallberg, A. et al. A worldwide survey of genome sequence variation provides insight into the evolutionary history of the honeybee Apis mellifera. Nat. Genet. 46, 1081–1088 (2014).

  • 29.

    Pearson, R. G. & Dawson, T. P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob. Ecol. Biogeog. 12, 361–371 (2003).

  • 30.

    Bost, C.-A. et al. The importance of oceanographic fronts to marine birds and mammals of the southern oceans. J. Mar. Syst. 78, 363–376 (2009).

  • 31.

    Wolff, E. W. et al. Southern Ocean sea-ice extent, productivity and iron flux over the past eight glacial cycles. Nature 440, 491–496 (2006).

  • 32.

    Kohfeld, K. E. et al. Southern Hemisphere westerly wind changes during the Last Glacial Maximum: paleo-data synthesis. Quat. Sci. Rev. 68, 76–95 (2013).

  • 33.

    Gersonde, R., Crosta, X., Abelmann, A. & Armand, L. Sea-surface temperature and sea ice distribution of the Southern Ocean at the EPILOG Last Glacial Maximum: a circum-Antarctic view based on siliceous microfossil records. Quat. Sci. Rev. 24, 869–896 (2005).

  • 34.

    Hodgson, D. A. et al. Terrestrial and submarine evidence for the extent and timing of the Last Glacial Maximum and the onset of deglaciation on the maritime-Antarctic and sub-Antarctic islands. Quat. Sci. Rev. 100, 137–158 (2014).

  • 35.

    Liu, X. & Fu, Y.-X. Exploring population size changes using SNP frequency spectra. Nat. Genet. 47, 555–559 (2015).

  • 36.

    Cristofari, R. et al. Full circumpolar migration ensures evolutionary unity in the Emperor penguin. Nat. Commun. 7, 11842 (2016).

  • 37.

    Borboroglu, P. G. & Boersma, P. D. Penguins: Natural History and Conservation (University of Washington Press, Seattle & London, 2013).

  • 38.

    Austin, J. J. et al. The origins of the enigmatic Falkland Islands wolf. Nat. Commun. 4, 1552 (2013).

  • 39.

    Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011).

  • 40.

    Carr, M.-E. et al. A comparison of global estimates of marine primary production from ocean color. Deep Sea Res. II 53, 741–770 (2006).

  • 41.

    Froneman, P. W., Laubscher, R. K. & McQuaid, C. D. Size-fractionated primary production in the south Atlantic and Atlantic sectors of the Southern Ocean. J. Plankton Res. 23, 611–622 (2001).

  • 42.

    Pütz, K. & Cherel, Y. The diving behaviour of brooding king penguins (Aptenodytes patagonicus) from the Falkland Islands: variation in dive profiles and synchronous underwater swimming provide new insights into their foraging strategies. Mar. Biol. 147, 281–290 (2005).

  • 43.

    Hoffmann, A. A. & Sgrò, C. M. Climate change and evolutionary adaptation. Nature 470, 479–485 (2011).

  • 44.

    Norberg, J., Urban, M. C., Vellend, M., Klausmeier, C. A. & Loeuille, N. Eco-evolutionary responses of biodiversity to climate change. Nat. Clim. Change 2, 747–751 (2012).

  • 45.

    Hope, A. G., Waltari, E., Payer, D. C., Cook, J. A. & Talbot, S. L. Future distribution of tundra refugia in northern Alaska. Nat. Clim. Change 3, 931–938 (2013).

  • 46.

    Roberge, J. M. & Angelstam, P. Usefulness of the umbrella species concept as a conservation tool. Conserv. Biol. 18, 76–85 (2004).

  • 47.

    Jackson, J. B. C. Ecological extinction and evolution in the brave new ocean. Proc. Natl Acad. Sci. USA 105, 11458–11465 (2008).

  • 48.

    Kuhlbrodt, T. et al. An integrated assessment of changes in the thermohaline circulation. Clim. Change 96, 489–537 (2009).

  • 49.

    Travis, J. M. Climate change and habitat destruction: a deadly anthropogenic cocktail. Proc. R. Soc. B 270, 467–473 (2003).

  • 50.

    Ewers, R. M. & Didham, R. K. Confounding factors in the detection of species responses to habitat fragmentation. Biol. Rev. 81, 117–142 (2006).

  • 51.

    Augustin, L. et al. Eight glacial cycles from an Antarctic ice core. Nature 429, 623–628 (2004).

  • 52.

    Li, C. et al. Two Antarctic penguin genomes reveal insights into their evolutionary history and molecular changes related to the Antarctic environment. Gigascience 3, 27 (2014).

  • 53.

    Zhou, Q. et al. Complex evolutionary trajectories of sex chromosomes across bird taxa. Science 346, 1246338 (2014).

  • 54.

    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

  • 55.

    Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: Analysis of Next Generation Sequencing Data. BMC Bioinformatics 15, 356 (2014).

  • 56.

    Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).

  • 57.

    Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).

  • 58.

    Hanson-Smith, V., Kolaczkowski, B. & Thornton, J. W. Robustness of ancestral sequence reconstruction to phylogenetic uncertainty. Molecular Biol. Evol. 27, 1988–1999 (2010).

  • 59.

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  • 60.

    Excoffier, L., Laval, G. & Schneider, S. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol. Bioinform. Online 1, 47–50 (2005).

  • 61.

    Reich, D., Thangaraj, K., Patterson, N., Price, A. L. & Singh, L. Reconstructing Indian population history. Nature 461, 489–494 (2009).

  • 62.

    Romiguier, J. et al. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature 515, 261–263 (2014).

  • 63.

    Fumagalli, M., Vieira, F. G., Linderoth, T. & Nielsen, R. ngsTools: methods for population genetics analyses from next-generation sequencing data. Bioinformatics 30, 1486–1487 (2014).

  • 64.

    Jombart, T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).

  • 65.

    Skotte, L., Korneliussen, T. S. SpringerAmpamp; Albrechtsen, A. Estimating individual admixture proportions from next generation sequencing data. Genetics 195, 693–702 (2013).

  • 66.

    Raj, A., Stephens, M. & Pritchard, J. K. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197, 573–589 (2014).

  • 67.

    Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  • 68.

    Huson, D. H. & Bryant, D. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267 (2006).

  • 69.

    Gutenkunst, R. N., Hernandez, R. D., Williamson, S. H. & Bustamante, C. D. Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genet. 5, e1000695 (2009).

  • 70.

    Saether, B. E. et al. Generation time and temporal scaling of bird population dynamics. Nature 436, 99–102 (2005).

  • 71.

    Millar, C. D. et al. Mutation and evolutionary rates in Adélie penguins from the Antarctic. PLoS Genet. 4, e1000209 (2008).

  • 72.

    Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).

  • 73.

    Schiffels, S. & Durbin, R. Inferring human population size and separation history from multiple genome sequences. Nat. Genet. 46, 919–927 (2014).

  • 74.

    Staab, P. R., Zhu, S., Metzler, D. & Lunter, G. scrm: efficiently simulating long sequences using the approximated coalescent with recombination. Bioinformatics 31, 1680–1682 (2015).

  • 75.

    Rambaut, A. & Grass, N. C. Seq-Gen: an application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees. Comput. Appl. Biosci. 13, 235–238 (1997).

  • 76.

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Met. Soc. 93, 485–498 (2012).

  • 77.

    Meijers, A. J. S. The Southern Ocean in the Coupled Model Intercomparison Project phase 5. Phil. Trans. R. Soc. A 372, 20130296 (2014).

  • 78.

    Moore, J. K., Abbott, M. R. & Richman, J. G. Location and dynamics of the Antarctic Polar Front from satellite sea surface temperature data. J. Geophys. Res. 104, 3059–3073 (1999).

  • 79.

    Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C. & Wang, W. An improved in situ and satellite SST analysis for climate. J. Clim. 15, 1609–1625 (2002).

  • 80.

    Adams, N. J. & Klages, N. T. Seasonal variation in the diet of the king penguin (Aptenodytes patagonicus) at sub Antarctic Marion Island. J. Zool. 212, 303–324 (1987).

  • 81.

    Koudil, M., Charrassin, J.-B., Le Maho, Y. & Bost, C.-A. Seabirds as monitors of upper-ocean thermal structure. King penguins at the Antarctic polar front, east of Kerguelen sector. Comptes Rendus Acad. Sci. 323, 377–384 (2000).

  • 82.

    Pütz, K. Spatial and temporal variability in the foraging areas of breeding king penguins. Condor 104, 528–538 (2002).

  • 83.

    Moore, G. J., Robertson, G. & Wienecke, B. Food requirements of breeding king penguins at Heard Island and potential overlap with commercial fisheries. Polar Biol. 20, 293–302 (1998).

  • 84.

    Wienecke, B. & Robertson, G. Foraging areas of king penguins from Macquarie Island in relation to a marine protected area. Environ. Manag. 29, 662–672 (2002).

  • 85.

    Halpern, B. S. et al. A global map of human impact on marine ecosystems. Science 319, 948–952 (2008).

  • 86.

    Turner, J., Bracegirdle, T. J., Phillips, T., Marshall, G. J. & Hosking, J. S. An initial assessment of Antarctic sea ice extent in the CMIP5 models. J. Clim. 26, 1473–1484 (2013).

  • 87.

    Xu, S. et al. Simulation of sea ice in FGOALS-g2: Climatology and late 20th century changes. Adv. Atmos. Sci. 30, 658–673 (2013).

  • 88.

    Shu, Q., Song, Z. & Qiao, F. Assessment of sea ice simulations in the CMIP5 models. Cryosphere 9, 399–409 (2015).

  • 89.

    Goberville, E., Beaugrand, G., Hautekèete, N. C., Piquot, Y. & Luczak, C. Uncertainties in the projection of species distributions related to general circulation models. Ecol. Evol. 5, 1100–1116 (2015).

  • 90.

    Raybaud, V. et al. Decline in kelp in west Europe and climate. PloS One 8, e66044 (2013).

  • 91.

    Cabré, A., Marinov, I., Bernardello, R. & Bianchi, D. Oxygen minimum zones in the tropical Pacific across CMIP5 models: mean state differences and climate change trends. Biogeosciences 12, 5429–5454 (2015).