6 Conclusion

Accurately representing vegetation phenology, a first order control on ecosystem productivity, under future conditions is key in understanding feedbacks between the climate and the biosphere. Here, we demonstrated the advantages of the phenor R package and modelling framework, through a worked example, by quickly and easily comparing 20 spring phenology models and their model skill for three plant functional types. Our results corroborate previous analysis, showing little or no difference in predictive power between models, which suggest convenient tools for further analysis or novel model development are needed to capture current and future phenological changes as well as their underlying physiological processes. We hope the phenor phenology modelling framework in R will allow for a better integration of observational and experimental data providing opportunities to better understand the environmental factors driving seasonality, and past and future responses of vegetation to climate change and variability.