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The eco-evolutionary consequences of interspecific phenological asynchrony - a theoretical perspective

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OIKOS
卷 124, 期 1, 页码 102-112

出版社

WILEY
DOI: 10.1111/oik.01909

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  1. research program BECC (Biodiversity and Ecosystem Services in a Changing Climate) at Lund Univ.
  2. Univ. of Gothenburg
  3. Swedish Research Council [2012-3620, 2013-4386]

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The timing of biological events (phenology) is an important aspect of both a species' life cycle and how it interacts with other species and its environment. Patterns of phenological change have been given much scientific attention, particularly recently in relation to climate change. For pairs of interacting species, if their rates of phenological change differ, then this may lead to asynchrony between them and disruption of their ecological interactions. However it is often difficult to interpret differential rates of phenological change and to predict their ecological and evolutionary consequences. We review theoretical results regarding this topic, with special emphasis on those arising from life history theory, evolutionary game theory and population dynamic models. Much ecological research on phenological change builds upon the concept of match/mismatch, so we start by putting forward a simple but general model that captures essential elements of this concept. We then systematically compare the predictions of this baseline model with expectations from theory in which additional ecological mechanisms and features of species life cycles are taken into account. We discuss the ways in which the fitness consequences of interspecific phenological asynchrony may be weak, strong, or idiosyncratic. We discuss theory showing that synchrony is not necessarily an expected evolutionary outcome, and how population densities are not necessarily maximized by adaptation, and the implications of these findings. By bringing together theoretical developments regarding the eco-evolutionary consequences of phenological asynchrony, we provide an overview of available alternative hypotheses for interpreting empirical patterns as well as the starting point for the next generation of theory in this field.

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