Phenology as a process rather than an event: from individual reaction norms to community metrics

Abstract

Measures of the seasonal timing of biological events are key to addressing questions about how phenology evolves, modifies species interactions, and mediates biological responses to climate change. Phenology is often characterized in terms of discrete events, such as a date of first flowering or arrival of first migrants. We discuss how phenological events that are typically measured at the population or species level arise from distributions of phenological events across seasons, and from norms of reaction of these phenological events across environments. We argue that individual variation in phenological distributions and reaction norms has important implications for how we should collect, analyze, and interpret phenological information. Regarding phenology as a reaction norm rather than one year's specific values implies that selection acts on the phenologies that an individual expresses over its lifetime. To understand how climate change is likely to influence phenology, we need to consider not only plastic responses along the reaction norm but changes in the reaction norm itself. We show that when individuals vary in their reaction norms, correlations between reaction norm elevation and slope make first events particularly poor estimators of population sensitivity to climate change, and variation in slopes can obscure the pattern of selection on phenology. We also show that knowing the shape of the distribution of phenological events across the season is important for predicting biologically important phenological mismatches with climate change. Last, because phenological events are parts of a continuous developmental process, we suggest that the approach of measuring phenology by recording developmental stages of individuals in a population at a single point in time should be used more widely. We conclude that failure to account for phenological distributions and reaction norms may lead to overinterpretation of metrics based on single events, such as commonly recorded first event dates, and may confound meta‐analyses that use a range of metrics. Rather than prescribing a single universal approach to studying phenology, we point out limitations of inferences based on single metrics and encourage work that considers the multivariate nature of phenology and more tightly links data collection and analyses with biological hypotheses.

Grasshopper phenological responses to climate gradients, variability, and change

“…, Inouye et al. ), examining developmental progression provides detailed insight into the drivers influencing developmental rates and ultimately the variability associated with the timing to adulthood. Examining both environmental exposure and organismal sensitivity is important to understanding the mechanisms underlying phenological variability, but such an approach is elusive for many systems.…”

“…Many studies have compared phenological responses across environmental gradients (reviewed by Chmura et al 2018), and some have examined gradients of organismal sensitivity (at the species or population level; Thackeray et al 2016), but few have explored the role of shifting developmental trajectories (Yang and Rudolf 2010). As metrics for adult phenology (e.g., first appearance, percentile individual, peak abundance) are subject to detection biases and can fail to capture the nuances of phenological shifts (Diez et al 2012, CaraDonna et al 2014, Brown et al 2016, Inouye et al 2019, examining developmental progression provides detailed insight into the drivers influencing developmental rates and ultimately the variability associated with the timing to adulthood. Examining both environmental exposure and organismal sensitivity is important to understanding the mechanisms underlying phenological variability, but such an approach is elusive for many systems.…”

“Estimating abundance and phenology from transect count data with GLMs”

“…Ecologists have long been interested in understanding phenology, the timing of organismal life history events. In the face of climate change, there has been increased interest in quantifying and analyzing phenological trends (e.g., Inouye et al 2019, Chmura et al 2019.…”

“…Nonetheless, in spite of widespread interest in phenology, analyses of phenological variables from monitoring data can be surprisingly problematic (cf. Inouye et al 2019).…”

“…Roy andSparks 2000, Fric et al 2020). Mean dates can be a useful first analysis, but changes in the mean date do not always correspond to changes in first or last events (Inouye et al 2019). For many types of data sets, observations of first and last events are known to be biased (Strien et al 2008, Miller-Rushing et al 2008, Inouye et al 2019).…”