Siniscalco Consolata, Caramiello Rosanna, Migliavacca Mirco, Busetto Lorenzo, Mercalli Luca, Colombo Roberto, Richardson Andrew D
Department of Life Sciences and Systems Biology, University of Torino, Viale Mattioli, 25, 10125, Torino, Italy,
Int J Biometeorol. 2015 Jul;59(7):837-48. doi: 10.1007/s00484-014-0901-x. Epub 2014 Sep 19.
Aerobiological data can be used as indirect but reliable measures of flowering phenology to analyze the response of plant species to ongoing climate changes. The aims of this study are to evaluate the performance of several phenological models for predicting the pollen start of season (PSS) in seven spring-flowering trees (Alnus glutinosa, Acer negundo, Carpinus betulus, Platanus occidentalis, Juglans nigra, Alnus viridis, and Castanea sativa) and in two summer-flowering herbaceous species (Artemisia vulgaris and Ambrosia artemisiifolia) by using a 26-year aerobiological data set collected in Turin (Northern Italy). Data showed a reduced interannual variability of the PSS in the summer-flowering species compared to the spring-flowering ones. Spring warming models with photoperiod limitation performed best for the greater majority of the studied species, while chilling class models were selected only for the early spring flowering species. For Ambrosia and Artemisia, spring warming models were also selected as the best models, indicating that temperature sums are positively related to flowering. However, the poor variance explained by the models suggests that further analyses have to be carried out in order to develop better models for predicting the PSS in these two species. Modeling the pollen season start on a very wide data set provided a new opportunity to highlight the limits of models in elucidating the environmental factors driving the pollen season start when some factors are always fulfilled, as chilling or photoperiod or when the variance is very poor and is not explained by the models.
气传生物学数据可作为开花物候的间接但可靠的指标，用于分析植物物种对当前气候变化的响应。本研究的目的是通过使用在意大利北部都灵收集的长达26年的气传生物学数据集，评估几种物候模型预测七种春季开花树木（欧洲桤木、复叶槭、欧洲鹅耳枥、美国梧桐、黑胡桃、绿桤木和欧洲栗）以及两种夏季开花草本植物（普通蒿和豚草）花粉季开始时间（PSS）的性能。数据显示，与春季开花物种相比，夏季开花物种的PSS年际变异性较小。对于大多数研究物种，具有光周期限制的春季变暖模型表现最佳，而仅对早春开花物种选择了需冷量等级模型。对于豚草和普通蒿，春季变暖模型也被选为最佳模型，这表明积温与开花呈正相关。然而，模型解释的方差较差，这表明必须进行进一步分析，以便为预测这两个物种的PSS开发更好的模型。在非常广泛的数据集上对花粉季开始进行建模，为突出模型在阐明驱动花粉季开始的环境因素方面的局限性提供了新机会，当一些因素总是满足时，如需冷量或光周期，或者当方差非常小且无法由模型解释时。
