Integral regressive analysis on the responses of first flowering date of eight woody species to climate change in Baoding, China

Based on the observed weather data and phonological information during the period 1986—2011 at Baoding city, we studied the responses of first flowering date of eight woody species to climate change with integral regressive method, and established integral regressive forecasting model of first flowering date. Results showed that: the first flowering dates of the eight species were jointly affected by three climate factors: air temperature, precipitation and sunlight, and the degree of their effect was ranked as air temperature > precipitation > sunlight. The patterns of the effect and driving force of first flowering date by each climate factor changed with time. The effect of climate factors on the first flowering date for each species could be both positive and negative several months before first flowering. Air temperature had negative effects on the first flowering date of six out of the eight species (except for Ulmus pumila and Ziziphus jujuba) a few days before first flowering. The multi-variable model established with integral regression had a high precision of predicting first flowering date of plants. The simulation showed that, in mid-March, when the temperature changes by 1℃, the precipitation changes by 1mm and the sunshine duration changes by 1h, the first flowing date of the eight woody species would change by about 0.1-1.6d.