Author Posting. © Ecological Society of America, 2017. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecology 98 (2017): 940-951, doi:10.1002/ecy.1749.
Evidence of climate-change-driven shifts in plant and animal phenology have raised concerns that certain trophic interactions may be increasingly mismatched in time, resulting in declines in reproductive success. Given the constraints imposed by extreme seasonality at high latitudes and the rapid shifts in phenology seen in the Arctic, we would also expect Antarctic species to be highly vulnerable to climate-change-driven phenological mismatches with their environment. However, few studies have assessed the impacts of phenological change in Antarctica. Using the largest database of phytoplankton phenology, sea-ice phenology, and Adélie Penguin breeding phenology and breeding success assembled to date, we find that, while a temporal match between Penguin breeding phenology and optimal environmental conditions sets an upper limit on breeding success, only a weak relationship to the mean exists. Despite previous work suggesting that divergent trends in Adélie Penguin breeding phenology are apparent across the Antarctic continent, we find no such trends. Furthermore, we find no trend in the magnitude of phenological mismatch, suggesting that mismatch is driven by interannual variability in environmental conditions rather than climate-change-driven trends, as observed in other systems. We propose several criteria necessary for a species to experience a strong climate-change-driven phenological mismatch, of which several may be violated by this system.
Funding to H. J. Lynch
and C. Youngflesh was provided by the National Science
Foundation Grant OPP/GSS 1255058, to S. Jenouvrier, H. J.
Lynch, C. Youngflesh, Y. Li, and R. Ji by the National Science
Foundation Grant 1341474, to S. Jenouvrier, Y. Li, and R. Ji by
NASA grant NNX14AH74G, to D. G. Ainley, G. Ballard, and
K. M. Dugger by the National Science Foundation Grants OPP
9526865, 9814882, 0125608, 0944411 and 0440643, to P. O’B.
Lyver by New Zealand’s Ministry of Business, Innovation, and
Employment Grants C09X0510 and C01X1001, and Ministry
of Primary Industry grants with logistic support from Antarctica
Anna Karenina Principle
Bayesian hierarchical model
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