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首页> 外文期刊>International Journal of Biometeorology: Journal of the International Society of Biometeorology >Forecasting plant phenology: evaluating the phenological models for Betula pendula and Padus racemosa spring phases, Latvia
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Forecasting plant phenology: evaluating the phenological models for Betula pendula and Padus racemosa spring phases, Latvia

机译:预测植物物候:评估拉脱维亚Betula pendula和Padus racemosa春季期的物候模型

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摘要

A historical phenological record and meteorological data of the period 1960-2009 are used to analyse the ability of seven phenological models to predict leaf unfolding and beginning of flowering for two tree species-silver birch Betula pendula and bird cherry Padus racemosa-in Latvia. Model stability is estimated performing multiple model fitting runs using half of the data for model training and the other half for evaluation. Correlation coefficient, mean absolute error and mean squared error are used to evaluate model performance. UniChill (a model using sigmoidal development rate and temperature relationship and taking into account the necessity for dormancy release) and DDcos (a simple degree-day model considering the diurnal temperature fluctuations) are found to be the best models for describing the considered spring phases. A strong collinearity between base temperature and required heat sum is found for several model fitting runs of the simple degree-day based models. Large variation of the model parameters between different model fitting runs in case of more complex models indicates similar collinearity and over-parameterization of these models. It is suggested that model performance can be improved by incorporating the resolved daily temperature fluctuations of the DDcos model into the framework of the more complex models (e.g. UniChill). The average base temperature, as found by DDcos model, for B. pendula leaf unfolding is 5.6 A degrees C and for the start of the flowering 6.7 A degrees C; for P. racemosa, the respective base temperatures are 3.2 A degrees C and 3.4 A degrees C.
机译:使用1960-2009年期间的历史物候记录和气象数据来分析七个物候模型预测两种树种(拉脱维亚的白桦桦木和樱桃樱桃Padus racemosa-in)的叶片展开和开花开始的能力。使用一半的数据用于模型训练,另一半的数据用于评估,可以估计执行多个模型拟合运行所需的模型稳定性。相关系数,平均绝对误差和均方误差用于评估模型性能。发现UniChill(一种使用S型曲线发展速度和温度关系并考虑了休眠释放的必要性的模型)和DDcos(一种考虑日间温度波动的简单度日模型)是描述所考虑的春季阶段的最佳模型。对于基于简单度日的模型的数次模型拟合,发现基本温度与所需热量之和之间存在很强的共线性。在更复杂的模型的情况下,不同模型拟合之间模型参数的较大差异表明这些模型具有相似的共线性和过度参数化。建议通过将DDcos模型的已解决的每日温度波动纳入更复杂的模型(例如UniChill)的框架中,可以提高模型性能。由DDcos模型发现的平均温度为,剑叶双叶展开为5.6 A,开花开始时为6.7 A;对于消旋毕赤酵母,各自的基本温度分别为3.2 A摄氏度和3.4 A摄氏度。

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