Reflectance spectra capture temporal variation in functional traits and leaf phenology
Plant function depends not on single traits but on how traits covary, yet trait integration is typically estimated from a peak-season snapshot and treated as fixed. Currently, we do not understand if integration has a phenology and how it affects spectral trait models that depend on trait covariance. We measured traits and reflectance spectra weekly across a growing season in seven temperate species (7,515 spectra), compared trait and spectral correlation structure across three phenophases, and tested PLSR models trained on the full season or peak season alone, alongside a widely used published model. Traits followed species-specific trajectories, with spectral lability concentrated in the visible region. Correlation structure shifted with phenology: LMA--EWT, C--N, and N--QY held across phenophases, whereas LMA--N and VIS--NIR spectral correlations reversed sign. Full-season models tracked trait dynamics, whereas peak-season and published models failed outside their window, producing biologically impossible estimates. Traits and their integration have themselves a phenology, and a peak-season correlation matrix does not fully capture trait integration. Spectra recover trait dynamics only with phenologically representative training data, since models calibrated in one phenophase inherit its correlation structure -- a shift that coincides with, and may underlie, their failure outside it.