| Forecasting of the flowering time for wild species observed at Guidonia, central Italy. | |
| | |
MedLine Citation:
|
PMID: 10993563 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
|
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). |
| | |
Authors:
|
C A Cenci; M Ceschia |
Related Documents
:
|
16401283 - Improving removal-based estimates of abundance by sampling a population of spatially di... 9692183 - Unification of some literature models of aromaticity: calculational and conceptual stud... 19716433 - The ngram chief complaint classifier: a novel method of automatically creating chief co... |
Publication Detail:
|
Type: Journal Article |
Journal Detail:
|
Title: International journal of biometeorology Volume: 44 ISSN: 0020-7128 ISO Abbreviation: Int J Biometeorol Publication Date: 2000 Aug |
Date Detail:
|
Created Date: 2000-10-19 Completed Date: 2000-10-19 Revised Date: 2004-11-17 |
Medline Journal Info:
|
Nlm Unique ID: 0374716 Medline TA: Int J Biometeorol Country: UNITED STATES |
Other Details:
|
Languages: eng Pagination: 88-96 Citation Subset: IM |
Affiliation:
|
Department BEA, University of Udine, Italy. |
Export Citation:
|
APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
|
Agriculture* Climate* Environmental Monitoring Forecasting Humans Italy Models, Theoretical Plants / growth & development* Population Dynamics |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
Previous Document: An examination of the relationship between flowering times and temperature at the national scale usi...
Next Document: Determining the growing season of land vegetation on the basis of plant phenology and satellite data...