The USA National Phenology Network (USA-NPN) hosts the largest volunteer-contributed collection of plant phenology observations in the USA. The potential contributions of these spatially and temporally explicit observations of flowers and pollen cones to the field of aerobiology remain largely unexplored. Here, we introduce this freely available dataset and demonstrate its prospective applications for modeling airborne pollen in a case study. Specifically, we compare the timing of 4265 observations of flowering for oak (Quercus) trees in the eastern USA to winter–spring temperatures. We then use this relationship to predict the day of peak flowering at 15 pollen monitoring stations in 15 years and compare the predicted day of peak flowering to the peak day of measured pollen (n = 111 station-years). There was a strong association between winter–spring temperature and the presence of open flowers (r² = 0.66, p < 0.0001) and the predicted peak flowering was strongly correlated with peak airborne pollen concentrations (r² = 0.81, p < 0.0001). These results demonstrate the potential for the USA-NPN’s phenological observations to underpin source-based models of airborne pollen. We also highlight opportunities for leveraging and enhancing this near real-time dataset for aerobiological applications.

美国国家物候网络 (USA-NPN) 拥有美国最大的志愿者贡献的植物物候观测资料库。这些对花朵和花粉锥的空间和时间明确观察对有氧生物学领域的潜在贡献在很大程度上尚未得到探索。在这里，我们介绍这个免费提供的数据集，并在案例研究中展示其在模拟空气花粉方面的预期应用。具体来说，我们将美国东部4265 个橡树 ( Quercus ) 树开花时间的观察结果与冬春季气温进行了比较。然后，我们利用这种关系来预测 15 年 15 个花粉监测站的开花高峰日，并将预测的开花高峰日与测量的花粉高峰日进行比较（n  = 111 个站年）。冬春温度与开放花朵之间存在很强的相关性（r ²  = 0.66，p  < 0.0001），并且预测的开花高峰与空气中花粉浓度峰值密切相关（r ²  = 0.81，p  < 0.0001）。这些结果表明 USA-NPN 的物候观测有可能支持基于来源的空气花粉模型。我们还强调了利用和增强空气生物学应用的近实时数据集的机会。