4.8 Article

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models

Journal

GLOBAL CHANGE BIOLOGY
Volume 18, Issue 9, Pages 2756-2770

Publisher

WILEY
DOI: 10.1111/j.1365-2486.2012.02744.x

Keywords

IPCC; sea ice; seabirds; stochastic climate forecast; stochastic matrix population model; uncertainties

Funding

  1. Expeditions Polaires Francaises
  2. Institut Paul Emile Victor (Programme IPEV 109)
  3. Terres Australes et Antarctiques Francaises
  4. REMIGE (Behavioural and demographic REsponses of Indian Ocean Marine top predators to Global Environmental changes) program
  5. ANR (Agence Nationale de la Recherche) Biodiversite (ANR Biodiv 011)
  6. National Science Foundation [DEB-0816514]
  7. WHOI Arctic Research Initiative
  8. Alexander von Humboldt Foundation
  9. Division Of Environmental Biology
  10. Direct For Biological Sciences [0816514] Funding Source: National Science Foundation

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Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adelie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa, because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa. We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adelie. The output of this ensemble is used to produce stochastic forecasts of SICa, which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adelie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.

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