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It is well established that migratory birds in general have advanced theirarrival times in spring, and in this paper we investigate potential ways ofenhancing the level of detail in future phenological analyses. We performsingle as well as multiple species analyses, using linear models on empiricalquantiles, non-parametric quantile regression and likelihood-based parametricquantile regression with asymmetric Laplace distributed error terms. Weconclude that non-parametric quantile regression appears most suited for singleas well as multiple species analyses.

A Comparison Between Quantile Regression and Linear Regression on  Empirical Quantiles for Phenological Analysis in Migratory Response to  Climate Change