Forecasting of the flowering time for wild species observed at Guidonia, central Italy

It is well known that forecasting the flowering time of wild vegetation is useful for various sectors of human activity, particularly for all agricult ural practices. Therefore, continuing previous work by Cenci et al., we wil l present here three new phenoclimatic models of the flowering time for a s et 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 Gaussi an distribution. Eventually only 57 species (subdivided into eight monthly subsets from February to September) were used to formulate the models satis factorily. 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=al pha x(beta)+gamma y. The x variable represents either the degree-day sum (i n model 1), or the daily-maximum-temperature sum (in model 2), or the daily -global-insolation sum (in model 3), while 4 for all three models correspon ds to the rainy-day sum. Note that all summations involved in the computati on of the variables x and y take place over a certain period of time (prece ding the flowering phase), which is a parameter to be determined by the fit ting procedure. This parameter, together with the threshold temperature (ne eded to compute the degree-days in model 1), represents the two implicit pa rameters of the process, thus the total number of parameters (including the se 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) .