Comparing two measures of phenological synchrony in a predator–prey interaction: Simpler works better. Issue 3 (17th December 2019)

• Record Type: Journal Article
• Authors: Ramakers, Jip J. C.; Gienapp, Phillip; Visser, Marcel E.
• Editors: Phillimore, Albert
• Is Part Of: Journal of animal ecology. Volume 89:Issue 3(2020)
• Page Start: 745
• Page End: 756
• Publication Date: 2019-12-17
• Subjects: demographic processes -- global climate change -- match–mismatch hypothesis -- Parus major -- phenology -- selection; Animal ecology -- Periodicals; 591.7
• DOI: 10.1111/1365-2656.13143
• Languages: English
• ISSNs: 0021-8790

Abstract

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. Abstract : Phenological mismatch can have important demographic consequences, but the most widely used measure of mismatch by biologists has been argued to be too simplistic. An alternative, theoretically more complete measure has been proposed, but the authors show with empirical data and simulations that this measure is difficult to estimate accurately and hence practically useless. This has important consequences for the collection of resource data for long‐term study populations.