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欧洲山毛榉种子产量的空间格局和大范围天气线索。

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

机构信息

DISAFA, University of Turin, Largo Braccini 2, 10095, Grugliasco (TO), Italy.

St Catherine's College, Manor Road, Oxford, OX1 3UJ, UK.

出版信息

New Phytol. 2017 Jul;215(2):595-608. doi: 10.1111/nph.14600. Epub 2017 May 18.

DOI:10.1111/nph.14600
PMID:28631320
Abstract

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data.

摘要

结实是许多树种中至关重要的种群过程,但在大陆尺度上,其时空模式和驱动因素仍不清楚。使用一个大型数据集(1950 年至 2014 年欧洲 8000 次结实观测),我们分析了欧洲山毛榉整个地理范围内结实的空间模式,研究了结实如何受到降水、温度和干旱的影响,以及结实-天气相关性的时间和空间稳定性。山毛榉结实表现出一般的距离依赖性同步性和以三个广泛的地理群为结构的模式,与大陆气候模式一致。Spearman 相关分析和逻辑回归表明,山毛榉结实一般与结实前 2 年夏季的温度呈负相关,与结实前 1 年夏季的温度呈正相关(即 2T 模型)。前两个夏季的温度差(DeltaT 模型)也是一个很好的预测指标。应用于最长的 8 个序列(74-114 年)的移动相关分析揭示了温度和结实之间稳定的相关性,证实了天气线索在空间和时间上的一致性。这些结果证实了结实对温度的广泛依赖性,并为使用温度数据重建和预测结实年提供了稳健性。

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