Multitasking and the evolution of optimal clutch size in fluctuating environments
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Published on: November 28, 2019
Ming Liu1,2, Dustin R Rubenstein3,4, Siew-Ann Cheong5,6
1Biodiversity Research Center Academia Sinica Taipei Taiwan.
Abstract:
Adaptive studies of avian clutch size variation across environmental gradients have resulted in what has become known as the fecundity gradient paradox, the observation that clutch size typically decreases with increasing breeding season length along latitudinal gradients, but increases with increasing breeding season length along elevational gradients. These puzzling findings challenge the common belief that organisms should reduce their clutch size in favor of additional nesting attempts as the length of the breeding season increases, an approach typically described as a bet-hedging strategy. Here, we propose an alternative hypothesis-the multitasking hypothesis-and show that laying smaller clutches represents a multitasking strategy of switching between breeding and recovery from breeding. Both our individual-based and analytical models demonstrate that a small clutch size strategy is favored during shorter breeding seasons because less time and energy are wasted under the severe time constraints associated with breeding multiply within a season. Our model also shows that a within-generation bet-hedging strategy is not favored by natural selection, even under a high risk of predation and in long breeding seasons. Thus, saving time-wasting less time as a result of an inability to complete a breeding cycle at the end of breeding season-is likely to be the primary benefit favoring the evolution of small avian clutch sizes during short breeding seasons. We also synthesize the seasonality hypothesis (pronounced seasonality leads to larger clutch size) and clutch size-dependent predation hypothesis (larger clutch size causes higher predation risks) within our multitasking hypothesis to develop an integrative model to help resolve the paradox of contrasting patterns of clutch size along elevational and latitudinal gradients. Ultimately, our models provide a new perspective for understanding life-history evolution under fluctuating environments.
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