Investor Presentaiton
Climate 2020, 8, 46
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cold period of the year, for the Belgorod Region this is October to March. The variable Pm is the total
precipitation for the warm period of the year, here April to September [14,17].
Regional sugar beet yield data were collected directly from Belgorod Region farming operations.
These data are archived at the Department of Agriculture and Environmental Reproduction (DAER)
of the Belgorod Region, and these archived data were used in this research. The weighted average
yield for
sugar beet in the Belgorod Region during the period ranged from 11.0 to 42.4 tons ha¯¹.
The weighted average yield from the entire planting area in the Belgorod Region is calculated by
dividing the gross harvest by planting area.
The mathematical and statistical methodologies used here can be found in, for example, [14,24].
A correlation analysis was used to determine the dependence of sugar beet yield with the main indexes
based on agrometeorological conditions. The trend lines and higher order functions were calculated
to describe the dynamics of changes in the yield of sugar beet and its sugar content over the 65-year
period. All the trend lines were tested at the 95% confidence level using analysis of variance (ANOVA)
techniques and the F-test in particular. Additionally, the trends were tested using the Mann-Kendall
(e.g., [28]) and Theil-Sen [29] tests at the 95% confidence level, which are generally regarded as more
stringent or able to handle outliers better than the F-test.
In order to analyze the weather and sugar beet yield character time series data, Fourier transforms
were applied to the series from 1960 to 2018 after the mean for all variables and trend for the yield data
were removed. Removing the mean and the trend for yield data was done in order to at least partly
account for increases in yield due to technology (e.g., [9]). Fourier transforms are used routinely to
convert data in Cartesian space (x, y, z, t) to wave space. Plots of the wave power versus wave number
then can be analyzed in order to extract dominant periods from a time series. These spectral peaks can
be tested for statistical significance against a red or white noise continuum (e.g., [28]). This depends on
whether there is an a priori expectation that low frequency (red) or no particular frequencies (white)
should be dominant. Occasionally, this type of analysis is referred to as the 'method of cycles' (e.g.,
reference [9] and references therein). The underlying assumption is that the system being studied
behaves like a regular pendulum or is cyclical (or at least quasi-cyclical).
A cross-spectral analysis (e.g., [30]) then was performed using the HTC, sugar beet yield and beet
sugar content time series in order to determine the link between sugar beet yield character and weather.
This analysis involves the convolving of two spectra and then examining the resultant spectrum (or the
covariance). These spectral peaks were also tested for statistical significance using the same techniques
used for the original spectra.
3. Results
3.1. Climatology of the Belgorod Region-Previous Results
Climatic factors, especially temperature, have a direct impact on the state and functioning of
the components of terrestrial ecosystems, their biodiversity and productivity. This section will set
the climatological context for the Belgorod Region and the next section will be related to sugar beet
productivity. The mean winter season long-term temperature within the Belgorod Region has increased
significantly over the past 65 years (e.g., [22]). The mean January temperature alone has increased
by about 4 °C (see [22]). In recent years, however, there has been a tendency to increase the annual
amplitude for temperature—mainly due to increases in the July temperature (Figure 2). Since the
middle of the 20th century, annual temperature amplitude has averaged at 25.5 °C and 28.0 °C in the
northern and southern parts of the Belgorod Region, respectively [31]. Additionally, in the last 15 years,
there has been an increase in the surface temperatures during the warm season of about 1.3 °C [32].
The increase in Belgorod Region seasonal mean temperatures for the period 1971-2015 has been
accompanied by an increase in the length of the warm season or vegetated period by five to seven days
and an increase in warm season mean temperature (0.4 °C-significant at the 90% confidence level,View entire presentation