Bee phenology is predicted by climatic variation and functional traits

Climate change is shifting the environmental cues that determine the phenology of interacting species. Plant-pollinator systems may be susceptible to temporal mismatch if bees and flowering plants differ in their phenological responses to warming temperatures. While the cues that trigger flowering are well-understood, little is known about what determines bee phenology. Using Generalized Additive Models, we analyzed time-series data representing 67 bee species collected over nine years in the Colorado Rocky Mountains to perform the first community-wide quantification of the drivers of bee phenology. Bee emergence was sensitive to climatic variation, advancing with earlier snowmelt timing, while later phenophases were best explained by functional traits including overwintering stage and nest location. Comparison of these findings to a long-term flower study showed that bee phenology is less sensitive than flower phenology to climatic variation, indicating potential for reduced synchrony of flowers and pollinators under climate change.
Methods
We gathered data at 18 sites around the Rocky Mountain Biological Laboratory (RMBL) in the Elk Mountains of western Colorado, USA from 2009 to 2017. Sites were located along an elevation transect (2456-3438 meters above sea-level) in montane and sub-alpine habitats dominated by a diverse mixture of perennial flowering species. We sampled bees in habitat types that were representative of dominant vegetation types: wet meadows dominated by Veratrum tenuipetalum, those dominated by Salix spp., rocky dry meadows, and Artemisia spp. steppe. We conducted biweekly bee abundance surveys at each site using pan traps (following LeBuhn et al. 2003). We set out 10 each of white, fluorescent yellow, and fluorescent blue pan traps along two approx. perpendicular 45-meter transects at intervals of 3 meters, an array that passively attracts bees by mimicking a display of flowers. We deployed pan traps between at approx. 0800 and 1700 (the period of maximum bee activity) only on warm, calm, sunny days and removed traps when these conditions changed drastically. Further details of the bee sampling are provided by Gezon et al. (2015).

The catches per day and sampling method are given, and the data processing code is included.

气候变化正在改变调控物种间相互作用物候的环境线索。若蜜蜂与显花植物对升温的物候响应存在差异，植物-传粉者系统可能出现时间错配。尽管学界对触发植物开花的环境线索已有充分认知，但关于调控蜜蜂物候的驱动因子却鲜有研究。本研究借助广义可加模型（Generalized Additive Models），分析了美国科罗拉多落基山脉地区9年间采集的67种蜂类的时间序列数据，首次完成了蜂类物候驱动因子的群落尺度量化分析。结果显示，蜜蜂出土时间对气候变异较为敏感，会随融雪时间提前而提前；而后续物候阶段则可通过越冬阶段、筑巢位置等功能性状得到最佳解释。将本研究结果与一项长期开花植物研究对比后发现，蜜蜂物候对气候变异的敏感性低于开花植物物候，这表明在气候变化背景下，花与传粉者的同步性或有所降低。

方法
本研究于2009年至2017年间，在美国科罗拉多州西部埃尔克山脉的落基山生物实验室（Rocky Mountain Biological Laboratory, RMBL）周边18个样地收集数据。样地沿海拔梯度（海拔2456~3438米）布设，生境涵盖山地与亚高山带，优势植被为多种多年生显花植物的混合群落。我们针对占主导的植被类型对应的生境开展蜂类采样：以狭藜芦（Veratrum tenuipetalum）为优势种的湿草甸、柳属（Salix spp.）群落草甸、岩石干燥草甸以及蒿属（Artemisia spp.）草原。采用碗诱法（参照LeBuhn等2003年的研究方法）在每个样地进行双周一次的蜂类丰度调查：在两条近似垂直的45米样带上，以3米间隔分别布设10个白色、荧光黄色和荧光蓝色的碗诱捕器，该装置通过模拟花朵花色来被动吸引蜂类。仅在温暖、无风且晴朗的日子，于当日约08:00至17:00（蜂类活动高峰期）布设诱捕器，当天气条件剧变时及时移除诱捕器。蜂类采样的更多细节可参见Gezon等（2015年）的研究。

本数据集提供了每日诱捕量与采样方法信息，并附带数据处理代码。