Premium
Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models
Author(s) -
Jenouvrier Stéphanie,
Holland Marika,
Stroeve Julienne,
Barbraud Christophe,
Weimerskirch Henri,
Serreze Mark,
Caswell Hal
Publication year - 2012
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2012.02744.x
Subject(s) - population , climate change , climatology , sea ice , climate model , vital rates , population model , environmental science , population growth , emperor , sea surface temperature , geography , physical geography , ecology , demography , biology , geology , sociology
Sea ice conditions in the A ntarctic affect the life cycle of the emperor penguin ( A ptenodytes forsteri ). We present a population projection for the emperor penguin population of T erre A délie, A ntarctica, 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 ( SIC a ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SIC a , 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 SIC a . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in T erre A délie. The output of this ensemble is used to produce stochastic forecasts of SIC a , 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 T erre A délie 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.