Repeat digital photography at or near ground-level is a proven and efficient approach for tracking plant phenology. Here, we explored the potential to monitor phenology using the Snapshot Wisconsin (SW) trail camera network, a citizen science program. Using three curve-fitting methods for characterizing phenological transition dates, we assessed the phenological offset between understory vegetation and the overstory canopy in the trailcam observations and compared variations in derived phenology over the different spatial scales represented by trailcams (~20–50 m), Harmonized Landsat and Sentinel-2 (HLS, 30 m), and Moderate Resolution Imaging Spectroradiometer (MODIS, 500 m). Our results showed that the apparent phenological offset between understory and overstory vegetation differed among forest types: in broadleaf deciduous forests, understory vegetation had an earlier start-of-spring (SOS) and later end-of-autumn (EOA) than the overstory canopy; in mixed forests, the understory showed an earlier SOS than the overstory, but no significant difference in EOA; in evergreen conifer forests, neither SOS nor EOA differed significantly between the understory and overstory. We found moderate correlations (0.25 ≤ r ≤ 0.57) between trailcam- and satellite-derived phenological dates. Moreover, those derived dates varied significantly among the applied curve-fitting methods: total growing season length (from SOS to EOA) could be 19 days longer for a threshold-based method than for a logistic curve-fitting method (our reference model), but 17 days shorter than the logistic method when using a piecewise-continuous method based on fitted sine curves. Despite the spatial limitations of trailcams for characterizing phenology on landscape and regional scales, trailcam networks have considerable potential for informing local phenological studies and disentangling the many drivers of phenology that can remain undetected from the satellite perspective.

在地面或接近地面的地方重复进行数字摄影是跟踪植物物候的一种行之有效的方法。在这里，我们探索了使用公民科学计划“快照威斯康星州（SW）追踪摄像机网络”监视物候的潜力。我们使用三种曲线拟合方法来表征物候转换日期，我们在追踪摄像机的观测结果中评估了林下植被和地上林冠之间的物候偏移，并比较了由追踪摄像机（〜20-50 m）代表的不同空间尺度上的衍生物候变化。统一的Landsat和Sentinel-2（HLS，30 m）和中等分辨率成像光谱仪（MODIS，500 m）。我们的研究结果表明，不同类型的森林之间，林下植被和林下植被的表观物候偏移不同：在阔叶落叶林中，与上层林冠相比，下层植被的春季开始（SOS）和秋季结束（EOA）的时间要早​​。在混交林中，林下的SOS比林上的SOS早，但EOA没有显着差异。在常绿针叶林中，林下和林下的SOS和EOA均无显着差异。我们发现中等相关性（0.25≤ ř  ≤0.57）之间trailcam-和卫星衍生的物候日期。此外，在采用的曲线拟合方法中，得出的日期差异很大：基于阈值的方法的总生长期（从SOS到EOA）可能比逻辑曲线拟合方法（我们的参考模型）长19天，但当使用基于拟合正弦曲线的分段连续方法时，与逻辑方法相比要短17天。尽管跟踪摄像头在景观和区域尺度上表征物候特征的空间限制，但跟踪摄像头网络仍具有相当大的潜力，可为当地的物候研究提供信息，并解开从卫星的角度仍然无法发现的许多物候驱动因素。