Biology Department, MS-34, Woods Hole Oceanographic Institution, Woods Hole, MA, 02543, USA; Centre d'Etudes Biologiques de Chizé, Centre National de la Recherche Scientifique, F-79360, Villiers en Bois, France; National Snow and Ice Data Center, Boulder, 80309, CO, USA; Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, 80309-0449, CO, USA.
Glob Chang Biol. 2012 Sep;18(9):2756-70. doi: 10.1111/j.1365-2486.2012.02744.x. Epub 2012 Jul 3.
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 Adélie, 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 Adélie. 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 Adélie 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.
南极的海冰状况会影响帝企鹅(Aptenodytes forsteri)的生命周期。我们通过将人口模型(分阶段、季节性、非线性、两性矩阵人口模型)与来自 IPCC 气候模型集合的海冰预测联系起来,为南极洲阿德雷地的帝企鹅种群提出了一个预测。基于最大似然捕获-标记-再捕获分析,我们发现季节性海冰浓度异常(SICa)会影响成年企鹅的存活率和繁殖成功率。人口模型表明,无论是确定性还是随机的种群增长率,在 SICa 的年平均值适中时达到最大值,因为完全没有海冰或厚重而持久的海冰都不会为帝企鹅提供满意的条件。我们表明,在某些情况下,SICa 的方差会对随机增长率产生积极影响。我们确定了一组五个通用循环气候模型,其输出结果与阿德雷地的历史海冰浓度记录非常吻合。该集合的输出结果用于产生 SICa 的随机预测,进而驱动人口模型。通过纳入多个气候模型和包含由于模型选择和估计误差引起的参数不确定性的参数引导程序,来纳入不确定性。这些模拟的中位数预测,到 2100 年,阿德雷地帝企鹅种群将减少 81%。我们发现,种群减少 90%或更多的可能性为 43%。人口预测的不确定性反映了气候模型在预测未来海冰条件方面存在很大差异。其中一个模型预测,在整个世纪中,人口会增加,但总体而言,模型集合预测,种群减少的可能性远远大于种群增加的可能性。我们得出的结论是,气候变化是帝企鹅面临的一个重大风险。我们的分析方法,即将人口模型与 IPCC 气候模型联系起来,是强大的,并且通常适用于其他物种和系统。