Simplified Modelling of Apple Flowering Phenology for Application in Climate Change Scenarios

被引:0
作者
Stoeckli, S. [1 ]
Samietz, J. [1 ]
机构
[1] Agroscope Changins Wadenswil Res Stn ACW, CH-8820 Wadenswil, Switzerland
来源
IX INTERNATIONAL SYMPOSIUM ON MODELLING IN FRUIT RESEARCH AND ORCHARD MANAGEMENT | 2015年 / 1068卷
关键词
phenology; temperature sum; forcing date and threshold; heating model; climate change; pest and disease simulations; PLANT PHENOLOGY; PEAR TREE; RESISTANCE; EUROPE; TRENDS; TIME;
D O I
暂无
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Plant phenology has a strong sensitivity to temperature and therefore high relevance to document responses to climate change. Flowering phenology plays a major role as a relevant set-point (i.e., biofix) in tree fruit pest and disease modelling. Projected climate change largely affects the range and phenology of pests and diseases, which requires adaptations of plant protection strategies to maintain their sustainability. The aim of the present study was (1) to elucidate a change in apple fruit phenology during the last decades and (2) to develop a simple heating model that only relies on present-year accumulated temperature sums. The results showed that apple flowering advanced on average 3.1 days/decade from 1960 to 2010. From 1981 to 2011, full bloom even advanced on average 5.1 days/decade. These shifts are similar to other phenological events of temperate deciduous trees reported in literature. For beginning of flowering, full bloom, and flowering termination (BBCH 60, 65, 69), the variation in temperature sums (coefficient of variation) was smallest for forcing day of year (DOY) 45 and forcing temperature threshold of 0 degrees C. The corresponding temperature sums from DOY 45 were 10368 degree-hours (degrees h) (BBCH 60), 12546 degrees h (BBCH 65), and 15914 degrees h (BBCH 69). For BBCH 60 and 65, the validation of the simplified heating model for apple flowering revealed a good relationship between observed DOY and simulated DOY across all years and sites. Those models are simple, do not rely on data of the previous year and are therefore easily applicable in climate change scenarios, for pest and disease simulations.
引用
收藏
页码:153 / 160
页数:8
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