Cenci C A, Ceschia M
Department BEA, University of Udine, Italy.
Int J Biometeorol. 2000 Aug;44(2):88-96. doi: 10.1007/s004840000065.
It is well known that forecasting the flowering time of wild vegetation is useful for various sectors of human activity, particularly for all agricultural practices. Therefore, continuing previous work by Cenci et al., we will present here three new phenoclimatic models of the flowering time for a set of wild species, based on an original data sample of flowering dates for more than 500 species, observed at Guidonia (42 degrees N in central Italy) by Montelucci in the period 1960-1982. However, on applying the bootstrap technique to each species sample to check its basic statistical parameters, we found only about 200 to have data samples with an approximately Gaussian distribution. Eventually only 57 species (subdivided into eight monthly subsets from February to September) were used to formulate the models satisfactorily. The flowering date (represented by the z variable), is expressed in terms of two variables x and y by a nonlinear equation of the form z=axbeta+gammay. The x variable represents either the degree-day sum (in model 1), or the daily-maximum-temperature sum (in model 2), or the daily-global-insolation sum (in model 3), while y for all three models corresponds to the rainy-day sum. Note that all summations involved in the computation of the variables x and y take place over a certain period of time (preceding the flowering phase), which is a parameter to be determined by the fitting procedure. This parameter, together with the threshold temperature (needed to compute the degree-days in model 1), represents the two implicit parameters of the process, thus the total number of parameters (including these last two) becomes respectively, five for model 1, and four for the other two models. The preliminary results of this work were reported at the XVI International Botanical Congress (1-7 August 1999, St. Louis, Missouri USA).
众所周知，预测野生植物的开花时间对人类活动的各个领域都很有用，特别是对所有农业实践而言。因此，在延续Cenci等人先前工作的基础上，我们将在此展示一组野生物种开花时间的三个新的物候气候模型，这些模型基于1960 - 1982年期间Montelucci在意大利中部Guidonia（北纬42度）观测到的500多种物种的开花日期原始数据样本。然而，在对每个物种样本应用自助法技术来检查其基本统计参数时，我们发现只有约200个物种的数据样本具有近似高斯分布。最终，仅使用了57个物种（从2月到9月细分为八个月度子集）来令人满意地构建模型。开花日期（由z变量表示）通过形式为z = axβ + γy的非线性方程用两个变量x和y来表示。x变量在模型1中表示度日总和，在模型2中表示日最高温度总和，在模型3中表示日总日照量总和，而对于所有三个模型，y都对应于雨日总和。请注意，变量x和y计算中涉及的所有求和都在特定时间段内进行（在开花阶段之前），这是一个需要通过拟合过程确定的参数。这个参数与阈值温度（在模型1中计算度日所需）一起代表了该过程的两个隐含参数，因此参数总数（包括这最后两个）对于模型1分别为五个，对于其他两个模型为四个。这项工作的初步结果在第十六届国际植物学大会（1999年8月1 - 7日，美国密苏里州圣路易斯）上进行了报告。
