## 4 Discussion  
We used two years of concurrent UAV observations and sap flow measurements across 17 species to evaluate the potential of UAV-derived leaf phenological metrics for tracking the seasonal dynamics of sap flow (i.e., sap flow phenology). Although both leaf and sap flow phenology showed large inter- and intra-species variations, daytime total sap flux density (SFD\({}_{\text{day}}\)) estimated by the UAV-derived metrics was significantly correlated with the measured SFD\({}_{\text{day}}\) across species and seasons (Figures 5 and A7), suggesting that UAV-derived metrics have potential as predictors of individual-level sap flow phenology in this ecosystem. However, the predictive ability of the UAV metrics largely differed among the metrics, with Hue showing the highest performance (RMSE = 0.135 for all pooled data), the green chromatic coordinate (GCC) and green excess index (GEI) showing the lowest (RMSE = 0.190), and the green-red vegetation index (GRVI) showing intermediate performance (RMSE = 0.154). The superior performance of Hue has also been reported in ecosystem-level comparisons between photosynthesis and phenocam-derived metrics in temperate deciduous forests [23; 24]. Because differences in spring trajectories among the UAV metrics were generally small, the observed differences in predictive ability were attributed to differences in summer to autumn trajectories (Figures 1 and A5), that is, Hue had a long peak period, the GCC and GEI showed a continuous decline, and the GRVI had an intermediate pattern between GCC and Hue. From summer to autumn, both Hue and \(\text{CLC}_{\text{ground}}\) showed similar trajectories with optimized SFD\({}_{\text{day}}\) (SFD\({}_{\text{opt}}\)) for most individuals (Figures 6 and A5), but the overall performance for predicting SFD\({}_{\text{day}}\) was higher for \(\text{CLC}_{\text{ground}}\) than for Hue (Figure 5). Because \(\text{CLC}_{\text{ground}}\) reflects the phenology of only leaf amount, like leaf area index (LAI), the similar trajectory between \(\text{CLC}_{\text{ground}}\) and SFD\({}_{\text{opt}}\) suggests that SFD\({}_{\text{day}}\) during the summer to autumn period is mainly controlled by leaf amount and not by leaf physiological properties, such as stomatal conductance (\(g_{\text{s}}\)). This might be a surprising result because both leaf amount and leaf \(g_{\text{s}}\) are important factors for controlling tree transpiration, e.g., [43]; furthermore, previous studies have reported that autumn decreases \(g_{\text{s}}\) accompanied by leaf coloring, which generally starts before leaf fall in deciduous tree species, e.g., [44; 45; 46]. On the other hand, empirical evidence indicates that seasonal dynamics of sap flow can be described using environmental factors and LAI in temperate deciduous broad-leaved species [39; 47]. Regarding the cause of the small contribution of \(g_{\text{s}}\), [PERSON] et al. [48] found  
Figure 6: Comparison of phenological transition dates between optimized sap flux density (SFD\({}_{\text{opt}}\)) and leaf phenological metrics. Each point represents data for an individual tree. Dotted lines are 1:1 lines and solid lines are the significant linear regression equations (\(p\) < 0.05). For panel (**D**), three outlier points surrounded by the thick dotted line were excluded from the analysis (when the outlier points were included in the regression analysis, the significant correlations in crown leaf cover based on ground observation \(\text{CLC}_{\text{ground}}\) and Hue were still maintained). Abbreviations: GCC, green chromatic coordinate; GEI, green excess index; GRVI, green-red vegetation index. that \(g_{\text{s}}\) of colored leaves maintained high values until late autumn in _Quercus serrata_ Murray in a Japanese temperate forest.