Evol Ecol Res 6: 1003-1020 (2004)     Full PDF if your library subscribes.

Expectation, explanation and masting

Andrew J. Kerkhoff*

Department of Ecology and Evolutionary Biology, University of Arizona, Biosciences West, 1041 E. Lowell Street, Tucson, AZ 85721, USA

e-mail: kerkhoff@email.arizona.edu


Masting is the synchronous, episodic production of large seed crops by perennial plant populations. Generally, hypotheses concerning the evolutionary origin and maintenance of masting entail economies of scale, where the benefit of large, synchronous reproductive events accrues by overcoming some environmental constraint, such as pollen limitation or seed predation. Because all perennial plants face some degree of inter-annual environmental variability, assessing the importance of selection via economies of scale requires a clear expectation for the reproductive dynamics of plants adapted to variable environments. Using a dynamic life-history model, I demonstrate that the observed range of reproductive variability and several other aspects of masting should be expected for size-structured populations of plants utilizing optimal allocation strategies in variable environments, even in the absence of economies of scale benefits. Thus, life-history evolution in even modestly variable environments may predispose species to realize reproductive benefits via economies of scale. However, distinguishing the effects of evolved responses to environmental variability from the effects of economies of scale using current criteria is difficult, if not impossible. My results reinforce the dictum that ecologists and evolutionary biologists must carefully consider their expectations before generating and testing explanations for observed phenomena. As variations on an established evolutionary theme, economies of scale undoubtedly provide selective advantages. However, caution should be exercised when inferring that they are the major ecological and evolutionary determinant of reproductive variability of plant populations.

Keywords: optimal life histories, reproductive allocation, seed production, stochastic-dynamic modelling.

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