Extreme temperatures help in identifying thresholds in phenological responses

Aim: To investigate temperature drivers of the spring phenology of 12 flowering events and 6 leafing events. Boreal phenology has previously exhibited only a modest response to temperature but record breaking temperatures in March 2020 led to some extreme phenological timing and provided the opportunity for a more rigorous look at the nature and complexity of the relationship between temperature and phenology.

Location: Boreal habitat in the Tatarstan Republic of Russia

Time period: 1989-2020

Major taxa studied: 18 plant species

Methods: We examined for changes over time in the timing of phenological events and the relationship with temperature drivers using a range of regression techniques. Extreme temperatures caused some extreme phenology and visually suggested temperature thresholds which were investigated using segmented regression (broken stick models). The performance of these models was subsequently compared to more complex alternatives based on accumulated daily temperatures.

Results: Temperatures in March 2020 were the warmest for this month in a record covering 200 years and were 5.9°C above the 1989-2020 average. Significant advances over time were detected for only seven of the events, but all events demonstrated significant relationships with temperature variables. Segmented regression identified significant temperature thresholds for 13 of the events with substantially stronger temperature relationships above these thresholds. Segmented regressions outperformed models based on accumulated daily temperatures for 12 of 18 events.

Main conclusions: The threshold models were a significant improvement over a linear response to temperature for 13 of the 18 events. The presence of thresholds partly explains why the response of boreal phenology to temperature previously seemed lower than in, for example, Western Europe. Responses to temperature above the identified thresholds were closer to those widely published from milder locations.

Methods
Dates of first observed flowering or leafing on study transects.

研究目的：探究12次开花事件与6次展叶事件的春季物候的温度驱动因子。寒带物候（Boreal phenology）此前对温度的响应仅表现为小幅变化，但2020年3月打破历史纪录的高温引发了部分极端物候期，为更严谨地剖析温度与物候之间关系的本质与复杂性提供了契机。
研究区域：俄罗斯鞑靼斯坦共和国境内的寒带生境（Boreal habitat）
研究时段：1989年—2020年
研究类群：18种植物
研究方法：我们采用多种回归分析技术，探究了物候事件发生时间的年际变化及其与温度驱动因子的关联。极端高温催生了极端物候现象，且直观呈现出温度阈值特征，我们通过分段回归（segmented regression）结合折断棍模型（broken stick models）对该阈值开展了分析。随后，将此类模型的拟合性能与基于逐日积温构建的更复杂替代模型进行了对比。
研究结果：2020年3月的气温为该地区200年有记录以来同期最高值，较1989—2020年的平均气温高出5.9℃。仅7项物候事件检测到随时间推移的显著物候提前，但所有事件均与温度变量存在显著关联。分段回归为其中13项事件识别出显著温度阈值，且阈值以上的温度与物候的关联强度显著提升。在18个物候事件中，有12个事件的分段回归模型拟合效果优于基于逐日积温的模型。
主要结论：针对18项物候事件中的13项，阈值模型相较于温度线性响应模型均实现了显著优化。阈值的存在在一定程度上解释了为何此前寒带物候对温度的响应强度看似低于西欧等地区——在达到所识别的温度阈值后，物候对温度的响应与温和地区已发表的主流研究结果更为接近。
研究方法：记录研究样带上首次观测到的开花或展叶日期。