Abstract
Concern regarding the biological effects of climate change has led to a recent surge in research to understand the consequences of phenological change for species interactions. This rapidly expanding research program is centered on three lines of inquiry: (1) how the phenological overlap of interacting species is changing, (2) why the phenological overlap of interacting species is changing, and (3) how the phenological overlap of interacting species will change under future climate scenarios. We synthesize the widely disparate approaches currently being used to investigate these questions: (1) interpretation of long-term phenological data, (2) field observations, (3) experimental manipulations, (4) simulations and nonmechanistic models, and (5) mechanistic models. We present a conceptual framework for selecting approaches that are best matched to the question of interest. We weigh the merits and limitations of each approach, survey the recent literature from diverse systems to quantify their use, and characterize the types of interactions being studied by each of them. We highlight the value of combining approaches and the importance of long-term data for establishing a baseline of phenological synchrony. Future work that scales up from pairwise species interactions to communities and ecosystems, emphasizing the use of predictive approaches, will be particularly valuable for reaching a broader understanding of the complex effects of climate change on the phenological overlap of interacting species. It will also be important to study a broader range of interactions: to date, most of the research on climate-induced phenological shifts has focused on terrestrial pairwise resource–consumer interactions, especially those between plants and insects.
Highlights
Shifts in the timing of life-history events are among the strongest biological signals of anthropogenic climate change (Root et al 2003; Cleland et al 2007)
We can identify five approaches for studying climatedriven phenological shifts and species interactions: (1) interpretation of long-term phenological data, which relies on time series of adequate duration to allow comparisons between past and present phenologies; (2) field observations, which take advantage of phenological variation over shorter timescales; (3) experimental manipulations, which enable researchers to directly measure the consequences of altering the phenologies of study organisms; (4) simulations and nonmechanistic models, which generate predictions under future climate change scenarios; and (5) mechanistic models, which shed light on the cues and triggers that shape phenologies
Our survey of the literature identified five approaches used in recent years to investigate the effects of climate change on the phenological overlap of interacting species and brought to light several key questions driving this work
Summary
Shifts in the timing of life-history events are among the strongest biological signals of anthropogenic climate change (Root et al 2003; Cleland et al 2007). We can identify five approaches for studying climatedriven phenological shifts and species interactions: (1) interpretation of long-term phenological data, which relies on time series of adequate duration to allow comparisons between past and present phenologies; (2) field observations, which take advantage of phenological variation over shorter timescales; (3) experimental manipulations, which enable researchers to directly measure the consequences of altering the phenologies of study organisms; (4) simulations and nonmechanistic models, which generate predictions under future climate change scenarios; and (5) mechanistic models, which shed light on the cues and triggers that shape phenologies Variables quantified with these approaches include extent of temporal overlap of interacting species, ideally measured in terms that are biologically meaningful for the species of interest (Visser and Both 2005), interaction frequency, fitness measures, demographic parameters, and population persistence.
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