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Warming-induced changes in bud dormancy and their effects on leaf phenology in common European tree species

Warming-induced changes in bud dormancy and their effects on leaf phenology in common European tree species
变暖引起的欧洲常见树种芽休眠变化及其对叶片物候的影响
批准号:
403176259
负责人:
Dr. Andrey Malyshev
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2018
资助国家:
德国
项目状态:
已结题
起止时间:
2017-12-31 至 2022-12-31

项目摘要

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中文摘要
翻译
春季落叶的时间和秋季植物衰老的时间在很大程度上决定了植物生长季节的长度,并在生态系统的净生产力中发挥着重要作用。春季和秋季较温暖的温度分别与春季提前落叶和延缓植物衰老密切相关。然而,最近观察到的在过去几十年中每度变暖的春季绿色化速度的下降反映了植物物候对气候变暖的非线性反应。未来的预测表明,对于某些物种来说,春季落叶的进展可能会停止甚至推迟。秋季的衰老更加不可预测,新的证据表明,在春季较早的萌芽之后,秋季衰老可能会提前,而更温暖的秋季气温可能会推迟秋季衰老。因此,对于更好地预测未来生态系统功能、植物群落组成和动植物相互作用的变化,了解物种特有物候变化应对气候变化的机制原因至关重要。到目前为止,气候变化下植物物候的变化大多是以观测的方式进行的,将历史物候日期与温度记录联系起来。最近,对花蕾休眠的更好理解为花蕾萌发日期背后的生物控制提供了更好的解释。例如,在花蕾休眠诱导期间加温可以增加花蕾休眠深度,并导致春季发芽延迟。因此,花蕾休眠的变化已经开始被纳入物候模型,并导致了对萌发日期的改进预测。然而,芽休眠诱导的特定物种的光周期和/或温度控制尚不清楚,需要量化。植物物候学不是简单地由秋季和春季的温度决定的。芽的休眠深度、光周期敏感性以及季节和年度效应已被证明是植物物候的重要驱动因素。因此,本项目的实验将主要集中在a)光周期和温度对花蕾休眠深度的相对影响,b)增温引起的花蕾休眠深度的变化,c)春季物候期对随后的叶片衰老和春季萌发日期的遗传效应。物种间和物种内的差异将通过对常见的欧洲树种和欧洲最重要的原生树种--青冈的生态型进行实验来量化。总而言之,温度和光周期的操纵将被用来量化变暖引起的芽休眠变化和随后的叶物候的种间和种内差异。实验结果表明,物候变化不仅是温度驱动的黑匣子效应,而且与芽休眠的具体变化有关,这将加深我们对植物物候的机理理解,并将为未来的物候学模型提供有价值的基础。
英文摘要
The timing of leaf-out in the spring and plant senescence in the fall largely determines the length of a plant’s growing season and plays a major role in the net productivity of an ecosystem. Warmer spring and fall temperatures have been closely linked with advanced spring leaf-out and delayed plant senescence, respectively. However, a recently observed reduction in the rate of advancement of spring green-up per degree of warming over the last decades reflects a nonlinear response of plant phenology to climate warming. Future projections indicate that for certain species, advancement in spring leaf-out can stop or even be delayed. Fall senescence is much more unpredictable, with new evidence showing that it can be advanced following an earlier budburst in the spring and be delayed by warmer fall temperatures. Understanding the mechanistic causes of species-specific shifts in phenology in response to climate change is thus essential to better project future changes in ecosystem functions, plant community compositions and plant-animal interactions. To date changes in plant phenology under climate change have mostly been addressed in an observational manner, correlating historical phenological dates with temperature records. Recently, a better understanding of bud dormancy has provided an improved explanation for the biological controls behind bud burst dates. For example, warming during bud dormancy induction can increase bud dormancy depth and lead to a delayed spring budburst. As a result, bud dormancy changes have started to be incorporated into phenological models and have led to improved budburst date predictions. The species-specific photoperiodic and/or temperature control of bud dormancy induction is not known however and needs to be quantified. Plant phenology is not simply driven by fall and spring temperatures. Bud dormancy depth, photoperiod sensitivity and seasonal as well as yearly carry-over effects have been shown to be important drivers of plant phenology. The experiments in this project will thus primarily focus on a) the relative influence of photoperiod and temperature on bud dormancy depth, b) warming-induced changes in bud dormancy depth and c) legacy effects of spring phenology timing on subsequent leaf senescence and spring budburst dates. Among- as well as within-species variation will be quantified by conducting the experiments on common European tree species and ecotypes of Fagus sylvatica, arguably the most important native tree species in Europe. Taken together, manipulation of temperature and photoperiod will be used to quantify among- and within-species variation in warming-induced bud dormancy changes and subsequent leaf phenology. Experimental results where phenological changes are not merely left to temperature-driven "black box" effects but are linked to specific changes in bud dormancy will deepen our mechanistic understanding of plant phenology and will be a valuable basis for future phenology models.
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