The impact of climate change on the advancement of plant phenological events has been heavily studied in the last decade. Although the majority of spring plant phenological events have been trending earlier, this is not universally true. Recent work has suggested that species that are not advancing in their spring phenological behavior are responding more to lack of winter chill than increased spring heat. One way to test this...

This paper describes long‐term changes of global atmospheric temperature, using a strict Bayesian approach which considers three different models to describe the time series: the constant model, the linear model and a change point model. The change point model allows the description of nonlinear annual rates of change with associated confidence intervals. We calculate the probabilities of each of the three models and average f...

The recent quantification of changes in time series of phenology data with Bayesian methods has provided compelling evidence for changes during the last 20 years. In this paper we correlate the phenological observations with spring temperature time series. We provide quantitative answers to the question whether changes in temperature and phenological time series should be regarded as coherent or independent. For the three cons...

The identification of changes in observational data relating to the climate change hypothesis remains a topic of paramount importance. In particular, scientifically sound and rigorous methods for detecting changes are urgently needed. In this paper, we develop a Bayesian approach to nonparametric function estimation. The method is applied to blossom time series of Prunus avium L., Galanthus nivalis L. and Tilia platyphyllos SC...