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We evaluated the long-term pattern of leaf area index (LAI) dynamics and radiation use efficiency (RUE) in short rotation poplar in uncoppice (single stem) and coppice (multi-stem) plantations, and compared them to annual field crops (AFCs) as an alternative for bioenergy production while being more sensitive to weather fluctuation and climate change. The aim of this study was to evaluate the potential of LAI and RUE as indicators for bioenergy production and indicators of response to changing environmental conditions. For this study, we selected poplar clone J-105 (Populus nigra L. × P. maximowiczii A. Henry) and AFCs such as barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), maize (Zea mays L.), and oilseed rape (Brassica napus L.), and compared their aboveground dry mass (AGDM) production in relation to their LAI development and RUE. The results of the study showed the long-term maximum LAI (LAImax) to be 9.5 in coppice poplar when compared to AFCs, where LAImax did not exceed the value 6. The RUE varied between 1.02 and 1.48 g MJ−1 in short rotation poplar and between 0.72 and 2.06 g MJ−1 in AFCs. We found both LAI and RUE contributed to AGDM production in short rotation poplar and RUE only contributed in AFCs. The study confirms that RUE may be considered an AGDM predictor of short rotation poplar and AFCs. This may be utilized for empirical estimates of yields and also contribute to improve the models of short rotation poplar and AFCs for the precise prediction of biomass accumulation in different environmental conditions.

We evaluated the long-term pattern of leaf area index (LAI) dynamics and radiation use efficiency (RUE) in short rotation poplar in uncoppice (single stem) and coppice (multi-stem) plantations, and compared them to annual field crops (AFCs) as an alternative for bioenergy production while being more sensitive to weather fluctuation and climate change. The aim of this study was to evaluate the potential of LAI and RUE as indicators for bioenergy production and indicators of response to changing environmental conditions. For this study, we selected poplar clone J-105 (Populus nigra L. × P. maximowiczii A. Henry) and AFCs such as barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), maize (Zea mays L.), and oilseed rape (Brassica napus L.), and compared their aboveground dry mass (AGDM) production in relation to their LAI development and RUE. The results of the study showed the long-term maximum LAI (LAImax) to be 9.5 in coppice poplar when compared to AFCs, where LAImax did not exceed the value 6. The RUE varied between 1.02 and 1.48 g MJ−1 in short rotation poplar and between 0.72 and 2.06 g MJ−1 in AFCs. We found both LAI and RUE contributed to AGDM production in short rotation poplar and RUE only contributed in AFCs. The study confirms that RUE may be considered an AGDM predictor of short rotation poplar and AFCs. This may be utilized for empirical estimates of yields and also contribute to improve the models of short rotation poplar and AFCs for the precise prediction of biomass accumulation in different environmental conditions.

Abstract Phenological shifts in wild-growing plants and wild animal phenophases are well documented at many European sites. Less is known about phenological shifts in agricultural plants and how wild ecosystem phenology interacts with crop phenology. Here, we present long-term phenological observations (1961-2021) from the Czech Republic for wild plants and agricultural crops and how the timing of phenophases differs from each other. The phenology of wild-growing plants was observed at various experimental sites with no agriculture or forestry management within the Czech Hydrometeorological Institute observations. The phenological data of the crops were collected from small experimental plots at the Central Institute for Supervising and Testing in Agriculture. The data clearly show a tendency to shift to earlier times during the whole observation period. The data also show some asynchrony in phenological shifts. Compared with wild plants, agricultural crops showed more expressive shifts to the start of the season. Phenological trends for crop plants (Triticum aestivum) showed accelerated shifts of 4.1 and 5.1 days per decade at low and middle altitudes, respectively; on the other hand, the average phenological shift for wild plants showed smaller shifts of 2.7 and 2.9 days per decade at low and middle altitudes, respectively. Phenological data also showed variability in correlations with climate parameters (only one phenophase of T. aestivum, heading, showed a statistically significant correlation not only with temperature but also with precipitation). To better understand theimpacts of climate on phenological changes, it is optimal to evaluate natural and unaffected plant responses in wild species.

Abstract Phenological shifts in wild-growing plants and wild animal phenophases are well documented at many European sites. Less is known about phenological shifts in agricultural plants and how wild ecosystem phenology interacts with crop phenology. Here, we present long-term phenological observations (1961-2021) from the Czech Republic for wild plants and agricultural crops and how the timing of phenophases differs from each other. The phenology of wild-growing plants was observed at various experimental sites with no agriculture or forestry management within the Czech Hydrometeorological Institute observations. The phenological data of the crops were collected from small experimental plots at the Central Institute for Supervising and Testing in Agriculture. The data clearly show a tendency to shift to earlier times during the whole observation period. The data also show some asynchrony in phenological shifts. Compared with wild plants, agricultural crops showed more expressive shifts to the start of the season. Phenological trends for crop plants (Triticum aestivum) showed accelerated shifts of 4.1 and 5.1 days per decade at low and middle altitudes, respectively; on the other hand, the average phenological shift for wild plants showed smaller shifts of 2.7 and 2.9 days per decade at low and middle altitudes, respectively. Phenological data also showed variability in correlations with climate parameters (only one phenophase of T. aestivum, heading, showed a statistically significant correlation not only with temperature but also with precipitation). To better understand theimpacts of climate on phenological changes, it is optimal to evaluate natural and unaffected plant responses in wild species.