Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 559105
Title Comparing two measures of phenological synchrony in a predator–prey interaction: Simpler works better
Author(s) Ramakers, Jip J.C.; Gienapp, Phillip; Visser, Marcel E.
Source Journal of Animal Ecology 89 (2020)3. - ISSN 0021-8790 - p. 745 - 756.
DOI https://doi.org/10.1111/1365-2656.13143
Department(s) Mathematical and Statistical Methods - Biometris
Publication type Refereed Article in a scientific journal
Publication year 2020
Keyword(s) demographic processes - global climate change - match–mismatch hypothesis - Parus major - phenology - selection
Abstract

Global climate change has sparked a vast research effort into the demographic and evolutionary consequences of mismatches between consumer and resource phenology. Many studies have used the difference in peak dates to quantify phenological synchrony (match in dates, MD), but this approach has been suggested to be inconclusive, since it does not incorporate the temporal overlap between the phenological distributions (match in overlap, MO). We used 24 years of detailed data on the phenology of a predator–prey system, the great tit (Parus major) and the main food for its nestlings, caterpillars, to estimate MD and MO at the population and brood levels. We compared the performance of both metrics on two key demographic parameters: offspring recruitment probability and selection on the timing of reproduction. Although MD and MO correlated quadratically as expected, MD was a better predictor for both offspring recruitment and selection on timing than MO. We argue—and verify through simulations—that this is because quantifying MO has to be based on nontrivial, difficult-to-verify assumptions that likely render MO too inaccurate as a proxy for food availability in practice. Our results have important implications for the allocation of research efforts in long-term population studies in highly seasonal environments.

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