Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break. (29th July 2016)

• Record Type: Journal Article
• Authors: Chuine, Isabelle; Bonhomme, Marc; Legave, Jean‐Michel; García de Cortázar‐Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
• Is Part Of: Global change biology. Volume 22:Number 10(2016:Oct.)
• Page Start: 3444
• Page End: 3460
• Publication Date: 2016-07-29
• Subjects: budbreak -- climate change impact -- endodormancy break -- flowering -- Juglans regia -- process‐based phenological models -- Prunus armeniaca -- Prunus persica; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.13383
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process‐based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.