Extended molt phenology models improve inferences about molt duration and timing

Molt is an essential life-history event in birds and many mammals, as maintenance of feathers and fur is critical for survival. Despite this molt remains an understudied life-history event. Non-standard statistical techniques are required to estimate the phenology of molt from observations of plumage or pelage state, and existing molt phenology models have strict sampling requirements that can be difficult to meet under real-world conditions. We present an extended modelling framework that can accommodate features of real-world molt datasets, such as re-encounters of individuals, misclassified molt states, and/or molt state-dependent sampling bias. We demonstrate that such features can lead to biased inferences when using existing molt phenology models, and show that our model extensions can improve inferences about molt phenology under a wide range of sampling conditions. We hope that our novel modelling framework removes barriers for modelling molt phenology data from real-world datasets and thereby further facilitates the uptake of appropriate statistical methods for such data. Although we focus on molt, the modelling framework is applicable to other phenological processes that can be recorded using either ordered categories or approximately linear progress scores. Molt is an essential but understudied life-history event in birds and many mammals. The analysis of molt data requires non-standard statistical techniques and existing molt phenology models have strict sampling requirements that can be difficult to meet. We present new statistical models for molt timing and duration. We demonstrate that these models improve inferences about molt duration and timing under a wide range of realistic sampling conditions. La muda es un evento esencial en la historia de vida de las aves y de muchos mamíferos, ya que el mantenimiento de las plumas y del pelaje es crucial para la supervivencia. A pesar de esto, la muda sigue siendo un evento de la historia de vida poco estudiado. Se requieren técnicas estadísticas no convencionales para estimar la fenología de la muda a partir de observaciones del estado del plumaje o pelaje, y los modelos de fenología de la muda existentes tienen requisitos estrictos de muestreo que pueden ser difíciles de cumplir en condiciones del mundo real. Presentamos un marco de modelado extendido que puede adaptarse a las características de los sets de datos de la muda del mundo real, como reencuentros de individuos, estados de la muda mal cl