Evaluation of recent trends in Australian pome fruit spring phenology

Abstract

Temporal and temperature driven analyses were conducted for eight spring phenology datasets from three Australian pome fruit growing regions ranging from 24 to 43 years in length. This, the first such analysis for Australia, indicated significant temporal change in phenophase timing for only one of the datasets. To determine relationships to temperature, a sequential chill and growth method as well as mean springtime temperatures were used to estimate phenophase timing. Expected advancement of phenophase ranged from 4.1 to 7.7 days per degree Celsius increase in temperature. The sequential chill and growth approach proved superior, with coefficients of determination between 0.49 and 0.85, indicating the inclusion of chill conditions are important for spring phenology modelling. Compared to similar phenological research in the Northern Hemisphere, the changes in response variables were often shallower in Australia, although significance of observed hemispheric differences were not found.

Future climate change impacts on apple flowering date in a Mediterranean subbasin

“…Some authors have published flowering apple advancements during the recent past in France , Germany (Blanke and Kunz, 2009;Chmielewski et al, 2004), Japan (Fujisawa and Kobayashi, (Eccel et al, 2009) and Central Europe (Legave et al, 2013). Moreover, other studies have verified flowering advancements in the recent past for apple together with pear and other temperate fruits in South Africa (Grab and Craparo, 2011), Australia (Darbyshire et al, 2013), New Zealand (Clothier et al, 2012), Germany (Blanke and Kunz, 2009;Estrella et al, 2007), France (Guedon and Legave, 2008), and Central Europe (Menzel et al, 2006). Other studies using climate model projections showed also advancements of apple or other temperate fruits: apple in North Italy (Eccel et al, 2009) and Germany (Hoffmann and Rath, 2013), fruit trees in general in Central Europe (Trnka et al, 2011), grapevine in France for the end of the Century (García de Cortázar Atauri, 2006) and in Australia for mid century (Webb et al, 2007;Darbyshire et al, 2014).…”

“…In cold regions as North-Central Europe a flowering advancement is produced because of winter chill is not a limiting factor for reaching flowering and heat is accomplished faster because of future or recent warming effects. Consequently, in these cold areas, the spring frost risk may substantially increase because full bloom could advance at a faster rate than spring frosts retreat (Darbyshire et al, 2013;Eccel et al, 2009). However, in Mediterranean fruit-growing areas blooming may be affected in the future by excessive delays in chilling satisfaction because chill accumulation would be limited and the satisfaction of CR for high-chill cultivars would be incomplete (Campoy et al, 2011b;Legave et al, 2013) delaying flowering date despite a faster heat phase.…”

“…Some other models also perform reasonably well (Luedeling et al, 2011) -or even better in non Mediterranean areas (Maulión et al, 2014) -in reproducing observed flowering patterns, but their suitability for climate change projections has been questioned (Luedeling, 2012). Although Darbyshire et al (2013Darbyshire et al ( , 2014,) suggested that the sequential modeling may need improvement, especially in the context of climate projections, and they advocated for more field and laboratory work to validate and define in a better way both chilling and forcing procedures, they also noted that the sequential model composed by the Dynamic chilling model and GDH growth model dominated the best performing models across all the data series in their study. However, Harrington et al (2010) proposed a new general concept of chilling and forcing requirements in which low chilling can be compensated by high forcing.…”

“…For the chill phase, we used the Dynamic Model because of the higher credibility of projections with this model (Luedeling et al, 2011;Darbyshire et al, 2013). Some other models also perform reasonably well (Luedeling et al, 2011) -or even better in non Mediterranean areas (Maulión et al, 2014) -in reproducing observed flowering patterns, but their suitability for climate change projections has been questioned (Luedeling, 2012).…”

Statistical identification of chilling and heat requirements for apricot flower buds in Beijing, China

“…However, other models (mainly the 0-7.2 • C and the Utah Model) are still widely used, because their chill metrics are much more easily calculated, and in some cases other models have appeared equally robust as the Dynamic Model (Alburquerque et al, 2008;Ruiz et al, 2007;Wang et al, 2003). Methods for quantifying the HR for plant flowering have been developed, with the Growing Degree Hour (GDH) Model most widely used across the world compared with other forcing models (Anderson et al, 1985;Darbyshire et al, 2013;Luedeling et al, 2009d).…”