Extended molt phenology models improve inferences about molt duration and timing

Philipp H Boersch-Supan, Hugh J Hanmer, Robert A Robinson
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Abstract

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.
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扩展的蜕皮物候模型改进了对蜕皮持续时间和时机的推断
蜕皮是鸟类和许多哺乳动物必不可少的生命史事件,因为羽毛和皮毛的保养对生存至关重要。尽管如此,蜕皮仍然是一个研究不足的生命史事件。根据对羽毛或皮毛状态的观察来估计蜕皮的表型需要非标准的统计技术,而现有的蜕皮表型模型有严格的取样要求,在现实条件下很难满足。我们提出了一个扩展的建模框架,该框架可以适应真实世界蜕皮数据集的特征,如再次遇到个体、蜕皮状态分类错误和/或蜕皮状态相关的取样偏差。我们证明了在使用现有的蜕皮物候学模型时,这些特征可能会导致有偏差的推断,并表明我们的模型扩展可以改进在各种采样条件下对蜕皮物候学的推断。我们希望我们新颖的建模框架能消除现实世界数据集中蜕皮物候数据建模的障碍,从而进一步促进对此类数据采用适当的统计方法。虽然我们关注的是蜕皮,但建模框架也适用于其他物候过程,这些物候过程可以使用有序类别或近似线性进展评分来记录。
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