Statistical modeling and forecasting of fruit crop phenology under climate change. Issue 8 (15th September 2014)

• Record Type: Journal Article
• Authors: Cai, S.; Zidek, James V.; Newlands, Nathaniel K.; Neilsen, Denise; Guttorp, Peter; Piegorsch, Walter W.
• Is Part Of: Environmetrics. Volume 25:Issue 8(2014:Dec.)
• Page Start: 621
• Page End: 629
• Publication Date: 2014-09-15
• Subjects: Environmental sciences -- Statistical methods -- Periodicals; 550.72
• DOI: 10.1002/env.2304
• Languages: English
• ISSNs: 1180-4009

Abstract

<abstract abstract-type="main" id="env2304-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="env2304-para-0001">Phenology, the study of the association between biological development stages and variations in climate, has greatly increased in importance because of concerns arising from climate change. This paper presents a general stochastic approach to the modeling of the relationship between phenological events and climate variables, and gives a prediction method based on this approach to provide full predictive distributions for future events. The proposed methods are then applied to the modeling and prediction of the bloom dates of six high‐valued fruit crops. In particular, we use our approach to explore how the bloom dates are related to the accumulation of growing degree days, to provide a sensible estimate of an important parameter <italic>T</italic>_{<italic>b</italic><italic>a</italic><italic>s</italic><italic>e</italic>} in phenological study, and to assess the prediction of bloom dates with a leave‐one‐out procedure. Most importantly, the impact of future climate change on bloom dates is studied with temperature outputs from well‐established coupled global climate models under a high greenhouse gases scenario. Copyright © 2014 John Wiley &amp; Sons, Ltd.</p> </abstract>