Litcius/Paper detail

How phenological tracking shapes species and communities in non‐stationary environments

E. M. Wolkovich, Megan J. Donahue

2021Biological reviews/Biological reviews of the Cambridge Philosophical Society41 citationsDOI

Abstract

Climate change alters the environments of all species. Predicting species responses requires understanding how species track environmental change, and how such tracking shapes communities. Growing empirical evidence suggests that how species track phenologically - how an organism shifts the timing of major biological events in response to the environment - is linked to species performance and community structure. Such research tantalizingly suggests a potential framework to predict the winners and losers of climate change, and the future communities we can expect. But developing this framework requires far greater efforts to ground empirical studies of phenological tracking in relevant ecological theory. Here we review the concept of phenological tracking in empirical studies and through the lens of coexistence theory to show why a community-level perspective is critical to accurate predictions with climate change. While much current theory for tracking ignores the importance of a multi-species context, basic community assembly theory predicts that competition will drive variation in tracking and trade-offs with other traits. We highlight how existing community assembly theory can help understand tracking in stationary and non-stationary systems. But major advances in predicting the species- and community-level consequences of climate change will require advances in theoretical and empirical studies. We outline a path forward built on greater efforts to integrate priority effects into modern coexistence theory, improved empirical estimates of multivariate environmental change, and clearly defined estimates of phenological tracking and its underlying environmental cues.

Topics & Concepts

Climate changeTracking (education)Context (archaeology)EcologyEnvironmental changeEmpirical researchMultivariate statisticsEnvironmental resource managementBiologyComputer scienceEnvironmental scienceMachine learningSociologyStatisticsPaleontologyMathematicsPedagogySpecies Distribution and Climate ChangeEcology and Vegetation Dynamics StudiesPlant and animal studies