Abstract
More robust statistical methods are required for examining phenological time series as they are often noisy and non-stationary. Wavelet analytic methods easily handle such data. A maximal overlap discrete wavelet transform (MODWT) analysis of flowering records (1940–1970) of Eucalyptus tricarpa, E. leucoxylon, E. microcarpa and E. polyanthemos identified four subcomponents in each flowering series: characterized as a non-flowering phase, duration, annual and intensity cycles. A decreasing overall trend in flowering was identified by the MODWT smoothed series. Wavelet correlation found the same contemporaneous effects of climate on flowering for Eucalyptus tricarpa and E. leucoxylon, and for E. microcarpa and E. polyanthemos. Wavelet cross-correlation analysis identified the cyclical influence of temperature and rainfall on peak flowering intensity (P < 0.0001). For each species there are 6 months of the annual cycle in which any given climate variable positively influences flowering intensity and 6 months of negative influence. For all species, rainfall exerts a negative influence when temperature is positive.
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