Abstract
Quantifying how individuals adjust the seasonal timings of life-history events (i.e. their phenology) in response to seasonal environmental conditions is fundamental to predicting impacts of changing seasonality. However, the current standard approach of inferring phenological responses by directly analysing observed event dates relies on foundational assumptions that could be invalidated by changing seasonality, and excludes individuals that do not express focal events, potentially generating misleading inferences. To overcome these limitations, we devised a Phenological Threshold Model (PTM) that conceptualizes phenological events as switches between discrete life-history states and primarily estimates variation in underlying latent dynamic responses to seasonal progression, from which event dates secondarily arise. We demonstrate that the PTM can accurately retrieve simulated parameter values, including given incomplete seasonal field observations. Application to multi-year data on annual breeding in black-legged kittiwakes (Rissa tridactyla) demonstrated substantial among-individual variation in latent responses to seasonally varying environmental drivers, and associated daily probabilities that individuals will initiate breeding, revealing how annual distributions of breeding dates and proportions of non-breeders jointly arise. We thereby formalise a new conceptual and statistical framework for quantifying the potential for, and constraints on, rapid plastic and micro-evolutionary changes in phenology in changing seasonal climatic and environmental regimes.