Summary: The 'Cherry Tree Phenology' is an analysis of phenological cherry tree
flowering observations. The data covers the extended Swiss Plateau
region from Alps to the Basel area. The 280-year composite series
includes a set of 14 different records of the 'flowering of the cherry
tree' from 1721-2000. The contributions consist of observations from
phenological networks as well as records by independent observers.
This interdisciplinary study includes methods from phenological biology,
plant physiology, climatology and history. The influence of global and
climate change processes on the flowering dates of the cherry tree
blossoms are described from different perspectives. In particular,
the relation of pre-flowering mean temperature and the flowering date
is assessed. When available, observations from phenological networks
were averaged into yearly mean flowering dates in order to remove
microclimatic and cultivar specific differences. A comparison between
the yearly mean dates of the network observations and independent
observations show that the series are well correlated for the
1951/1978-2000 period. Correlation coefficients range between r = 0.78
and 0.91. Mean and single flowering dates from 1721 to 2000 were
corrected for altitude to a reference level of 550 m a.s.l. which is the
median station height of the Swiss Phenological Network in the study area.
The dates were adjusted by + (-) 2.5 days per 100 meters below (above)
the reference altitude. The most important environmental impact factor
for the cherry tree flowering date is temperature. For the 1951-2000
period, the most influential pre-flowering mean temperature period was
assessed by comparison of the flowering date with monthly and seasonal
means at the representative station (Zuerich-SMA). A comparison of monthly
and combined monthly mean temperatures with the flowering date revealed
that the February-April period were highest correlated (r = - 0.82).
The correlation is even higher with a subperiod of the Liestal-Record
(r= - 0.88). The negative sign describes the inverse physical dependence
of the flowering date from temperatures. Thus, warmer mean February-April
temperatures result in an earlier flowering date and vice versa.
Based on this relationship a linear regression model, calculated from
a predictor set of European monthly mean temperatures, was used to
predict the annual flowering date. The correlation coefficient in the
calibrating period 1951-1995 was r = 0.84. The comparison of the
observed and reconstructed flowering date for the 1721-1995 period
revealed a high common variability (r = 0.61). Systematic differences
before 1900 can be attributed to differences in the definition of the
phenological phase. The longterm mean of the observed flowering date
1721-2000 is April 21 (day of year 111) with a standard deviation of
approximately ten days. For the reconstructed series 1721-1995
the mean flowering day is on April 26 (day of year 116) with a
standard deviation of five days. In order to assess the quality of
the observation series, subperiods of the contributing records were
compared with the statistical reconstruction. Correlation analysis
was applied to compare variability. Coefficients range from 0.38 to 0.91.
Systematic differences are revealed by comparing mean values for the 14
subperiods. In addition, suprasegmental comparison was assessed by
moving correlation analysis with a 31-year time window. Even though
significant at 99 % level during the whole study period, three time
windows showed a systematic lower moving correlation coefficient.
Whereas the lower correlation during the 1827-1845 period can be
attributed to unprecise observations, the other two periods (1755-1765,
1885-1895) seem to reveal a lower dependency of the flowering dates
on spring temperature. Systematic differences between observed and
reconstructed was additionally assessed with historical source analysis.
It is shown that metadata such as biographical notes of the observer
and detailed place and phenological phase descriptions, can explain
some of the bias in the series.
More Info on Historical Data |
