Assessing plant phenological changes based on drivers of spring phenology

Understanding plant phenological responses to climate warming is crucial for predicting changes in plant communities and ecosystems, but difficult with sensitivity analysis that is not linked to drivers of spring phenology. In this article, we present a new measure phenological lag to quantify the overall effect of phenological constraints, including insufficient winter chilling, photoperiod, and environmental stresses, based on observed response and that expected from species-specific changes in spring temperatures, i.e., changes in spring forcing (degree days) from warming and average temperature at the time of species events. We applied this new analytical framework to a global dataset with 980 species and 1527 responses to synthesize observed changes in spring phenology and investigate the contributions of forcing change, growth temperature, and phenological lag to differential phenological responses reported previously.
, , # Assessing plant phenological changes based on drivers of spring phenology

Dryad DOI: [https://doi.org/10.5061/dryad.dncjsxm9x](https://doi.org/10.5061/dryad.dncjsxm9x)

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Main file: PhenologySynthesis.zip

Note that this package contains temperature data from different sources and R codes required for calculating forcing change, expected response, budburst temperature, and spring warming, examining statistical variations among different research approaches, species origins, climate types, and growth forms, identifying climatic, phenological, biological variables that strongly influence plant phenological responses in spring, and generating tables (Tables 1 and 2) and figures (Figure 1).

* Forcing change (degree-days above 0 °C), expected response (days), budburst temperature (°C), and spring warming (change in average spring temperature, °C) are calculated using daily mean temperature (°C) by individual study due to variations in temperature format among different data sources an...,

解析植物物候对气候变暖的响应，对预测植物群落与生态系统的动态变化至关重要，但倘若敏感性分析未结合春季物候驱动因子展开，则此类研究往往难以获得可靠结果。
本文提出一种全新的物候滞后期（phenological lag）度量方法，基于实测物候响应与基于物种特异性春季温度变化——即气候变暖引发的春季积温（degree days）变化，以及物种物候发生时刻的平均温度——所预测的理论响应，量化冬季需冷量不足、光周期限制与环境胁迫等各类物候约束的综合效应。
我们将这一全新分析框架应用于包含980个物种、1527条物候响应记录的全球数据集，整合已观测到的春季物候变化，并探究积温变化、生长温度与物候滞后期对此前文献报道的差异化春季物候响应的贡献程度。

# 基于春季物候驱动因子的植物物候变化评估

Dryad数据集DOI：[https://doi.org/10.5061/dryad.dncjsxm9x](https://doi.org/10.5061/dryad.dncjsxm9x)

--- 主文件：PhenologySynthesis.zip

请注意，本压缩包包含多源温度数据，以及用于计算积温变化、理论物候响应、芽萌动温度与春季变暖幅度的R代码；其功能涵盖：检验不同研究方法、物种起源、气候类型与生长型间的统计差异，筛选对春季植物物候响应具有显著影响的气候、物候与生物学变量，以及生成表1、表2与图1。

* 积温变化（0℃以上度日数）、理论物候响应（天数）、芽萌动温度（℃）与春季变暖幅度（春季平均温度变化量，℃）的计算采用各研究单独提取的日平均温度（℃），这是由于不同数据源的温度格式存在差异……