The phenological phases of field crops have shifted to earlier times in the Czech Republic in recent decades; additionally, they have shown correlations with temperatures from previous spring months. Using a thermal time model called PhenoClim, the correlations between temperatures and phenophases allow us to evaluate the strongest predictors (i.e., maximum temperature) and indicators of base temperatures and growing degree days for the selected phenophases of winter wheat (Triticum aestivum L.). With the help of this model, it is possible to explain 0.6–0.82% of the phase variability and to estimate the onset of phenophases for the selected time period and stations (with the RMSE values of 9.4 days for jointing, 4.3 days for heading, and 5.3 days for full ripeness). To further refine the modeled onsets of phenophases, we used satellite data, specifically the normalized difference vegetation index and the enhanced vegetation index 2 from MODIS; based on these vegetation indices, the start of the growing season (SOS) was determined. After including SOS to model PhenoClim, we modeled the onsets of phenophases, with average accuracies ranging from 6.2 to 15.2. By combining the thermal time model and remote sensing data, specifically the data concerning the determination of SOS, we can refine the modeling of the onset of full ripeness in some locations.

Winter oilseed rape (Brassica napus) is one of the most cultivated oilseeds in the Czech Republic and belongs among major pollen allergens. Pollen allergies have an extensive clinical impact worldwide, and as well as in the Czech Republic. In this paper, meteorological variables such as mean air temperature, maximum and minimum air temperature, precipitation total and number of rainy days in the period 1991–2012 were studied using the PhenoClim phenological model to find the best predictor of the beginning of flowering of the Brassica napus in the Czech Republic. In addition, temporal and spatial evaluations of the beginning of flowering of the Brassica napus were examined at individual stations in different climatic zones within the same period. In total, three phenological stations at altitudes from 270 m asl to 533 m asl located in warm (W2), medium warm (MW7) or cold (C7) climatic zones were used for detailed evaluation. Based on the observation results at selected stations, the beginning of flowering of the Brassica napus advanced progressively in timing (nearly −15 days) in the 1991–2012 period. The base temperature and temperature sums were calculated for the beginning of flowering of the winter oilseed rape using the PhenoClim computer tool. As the most accurate predictor for the beginning of flowering of the Brassica napus, the mean air temperature was determined. The optimal start day for calculation was 30th January, the threshold (base temperature) was 6.0 °C and the temperature sum was 157.0 °C. The RMSE value was 4.77 and the MBE value was −3.00. The simulated data had a good correlation with the real observed data (the correlation coefficients were within the range from 0.56 to 0.76), and the PhenoClim model results indicate using them in the forecast modeling of the beginning of flowering of the Brassica napus in the Czech Republic.

The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at the Vranovice site (48°48′ N, 16°46′ E, 170 m above mean sea level) representing the Plaček’ forest National Reserve. The observed plants and bird species showed statistically significant (p < 0.05) shifts in phenological terms to an earlier date of the year, but the rate of the shift among the observed species differed. The most progressive shifts were detected for the herbs (14 days), followed by the shrubs (13 days), trees (9 days), and finally by the bird species (8 days). All the phenophases were significantly correlated with the daily maximum temperature (r = 0.72–0.91). The results also showed a decline in the correlation for species among the phenophases of the herbs and trees. The phenophases that were highly correlated in the past were less correlated and had higher variability in the last decades. We conclude that the phenological response of the ecosystem to warming in the spring resulted in higher variability and a lower correlation among the observed phenophases mainly caused by the most expressive phenological shifts of the early herbs.

Climate change affects the agroecological conditions and persistence of cherry tree flowering. Detailed evaluation of minimum air temperature and occurrence of synoptic events occurrence during spring frosts within the cherry tree flowering in the Czech Republic (Central Europe) is missing. The main objective of this study was to evaluate the above-mentioned variables during the cherry tree flowering in different parts of the country from 1924 to 2012. Our question was how the frequency of frost days occurrence changed during the cherry tree flowering. A trend analysis was conducted with the Mann-Kendall test. The onset of the beginning of flowering and end of flowering shifted to an earlier date per the whole examined period (up to −13.9 and −8.1 days) and the period of flowering extended (up to 4.1 days). The shifts were more pronounced at higher elevations. During the period of the cherry tree flowering, the trend in change of the number of frost days was negative at the lowland station (−0.3 day) and positive at the highland station (+1.2 day). At all stations, “Ap3” synoptic event (anticyclone) occurrence during cherry tree flowering on days with the highest spring frost risk (T_min at 2 m < −1.1 °C) prevailed. The positive trend of frost-day occurrence and the negative trend of minimum air temperature in cherry tree flowering indicate that blossoms are more endangered at higher elevations.

Using remote sensing data to assess plant phenology is a useful method for monitoring areas at larger spatial scales. One of the most widely used methods for analyzing changes in the timing of the growing season is the employment of vegetation indices and phenological metrics (phenometrics) derived from them. Using phenometrics, it is possible to evaluate changes in the growing season for different land covers and different environmental conditions not only at the local level but also in larger areas. At the larger scales, the meteorological conditions and especially their influence on plant phenology can be more diverse. For the determination of basic phenometrics (the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LGS)), we used Enhanced Vegetation Index2 (EVI2) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Phenometrics and their trends were calculated for four different land covers (arable land, broad-leaved forest, coniferous forest, and grassland) in the time period from 2000 to 2022 in the central European region. Furthermore, the changes in the timing of the growing season were calculated in different altitude and environmental zones and their trends were compared with meteorological variables (e.g., minimum and maximum air temperature, length of day, global radiation, precipitation, soil moisture, etc.). Based on this analysis, the main factors influencing phenological changes for different land covers were evaluated in different environmental conditions.Acknowledgment: This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic (grant AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation (CZ.02.01.01/00/22_008/0004635).

Phenological shifts represent one of the most evident biological responses to climate change. This study used the two-band Enhanced Vegetation Index derived from Moderate Resolution Imaging Spectroradiometer satellite data to analyze changes in the growing seasons of arable land, broad-leaved forest, coniferous forest, and grassland across the central European region from 2000 to 2022. Phenological metrics included the start, end, and length of the growing season. Nonparametric Theil–Sen regression indicated an earlier start of the season (median of trends for all land cover classes ranging from -9.3 to -17.5 days per decade), a later end of the season (ranging from +8.1 to +11.4 days per decade), and consequently longer length of the season (ranging from +13.3 to +25.0 days per decade), with advancing start of the season identified as the primary driver of length of the season prolongation. The most pronounced changes across all phenological metrics were associated with arable land. Elevation zone-based analysis showed that the highest median of trends of start and length of the season was found for arable land and coniferous forest in elevations below 600 m a.s.l., with values decreasing progressively with increasing elevation. The analysis of environmental zones revealed a higher median of trends of the start and length of the season in cool-moist and warm-mesic zones, while end-of-season-related changes were more pronounced in cold-wet zones. This study demonstrates coherent long-term trends in vegetation phenology across different land cover classes, with stronger acceleration over arable land, highlighting potential implications for agricultural systems.