Vegetation phenology is a sensitive indicator of ecosystem responses to climate change, and thus the accurate estimation of vegetation phenology is critical to evaluate the impact of climate change on terrestrial ecosystems. Common structural vegetation indices (VIs) such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Near-infrared Reflectance of Vegetation (NIRv) and Plant Phenology Index (PPI), are the most widely used indicators of phenology, but they have limited potential in tracking autumn phenology, especially for evergreen species with low seasonal variability of canopy greenness. Given the important role of carotenoid pigments in regulating photosynthetic activity and plant phenology, we hypothesize that satellite-based indicators of leaf pigments derived from MODIS ocean bands could be useful for phenology modeling. Using 624 site-years of flux data at 84 FLUXNET sites and 9979 ground observations at 138 PEP725 sites, we first explored the potential of different forms of scaled photochemical reflectance index (sPRI_ref) in monitoring photosynthetic activity, and found that band 10 and band 13 were more suitable for tracking gross primary productivity (GPP) than other reference bands. By comparing with canopy photosynthetic phenology, sPRI₁₀ and sPRI₁₃ showed improved representation of phenological transitions (the start and end of growing season, SOS and EOS, respectively) than structural VIs. In spring, all VIs exhibited comparable performances for estimating SOS at deciduous broadleaf forests (DBF) and grasslands (GRA) sites; however, sPRI₁₀ and sPRI₁₃ were better predictors of SOS than structural VIs at evergreen needleleaf forests (ENF) and mixed forests (MF) sites. In autumn, sPRI₁₀ and sPRI₁₃ showed improved predictive strength of EOS than structural VIs for ENF, MF and GRA sites. Further investigations using the ground observed phenological records also confirmed the improved performances of sPRI₁₀ and sPRI₁₃ for both SOS and EOS estimation. We also investigated the spatial patterns of sPRI₁₀-derived SOS and EOS over the Northern Hemisphere with respect to different plant functional types. We showed that sPRI₁₀ reliably tracked plant phenology with 83.0% and 78.8% success in detecting SOS and EOS, respectively. Spatial patterns of SOS exhibited obvious latitudinal gradients, while EOS showed a strong regional heterogeneity. In addition, sPRI₁₀ predicted an overall earlier SOS (61.8%) and later EOS (51.2%) than the MODIS phenology product (VNP22Q2 v001) estimated from structural VI, suggesting the latter underestimated the greening potential of the Northern Hemisphere. Our results suggest that MODIS PRI could be useful to monitor vegetation phenology, and further reveal the importance of underappreciated carotenoid pigments in tracking plant seasonal changes, particularly in autumn months.

植被物候是生态系统对气候变化响应的敏感指标，因此准确估计植被物候对于评估气候变化对陆地生态系统的影响至关重要。归一化植被指数 (NDVI)、增强植被指数 (EVI)、植被近红外反射率 (NIRv) 和植物物候指数 (PPI) 等常见的结构植被指数 (VI) 是应用最广泛的物候指标，但它们在跟踪秋季物候学方面的潜力有限，特别是对于冠层绿色季节性变化较小的常绿物种。鉴于类胡萝卜素色素在调节光合活性和植物物候中的重要作用，我们假设基于卫星的来自 MODIS 海洋带的叶色素指标可用于物候建模。使用 84 个 FLUXNET 站点的 624 个站点年通量数据和 138 个 PEP725 站点的 9979 个地面观测，我们首先探索了不同形式的标度光化学反射指数 (sPRI_ref ) 监测光合活动，发现波段 10 和波段 13 比其他参考波段更适合跟踪总初级生产力 (GPP)。通过与冠层光合物候进行比较，sPRI ₁₀和 sPRI ₁₃表现出比结构 VI 更好地表示物候转换（生长季节的开始和结束，分别为 SOS 和 EOS）。在春季，所有 VI 在评估落叶阔叶林 (DBF) 和草地 (GRA) 站点的 SOS 时表现出可比的性能；然而，在常绿针叶林 (ENF) 和混交林 (MF) 地点，sPRI ₁₀和 sPRI _{13比结构 VI 更能预测 SOS。}秋季，sPRI ₁₀和 sPRI_图13显示 EOS 的预测强度高于 ENF、MF 和 GRA 位点的结构 VI。使用地面观察到的物候记录的进一步调查也证实了 sPRI ₁₀和 sPRI ₁₃在 SOS 和 EOS 估计方面的改进性能。我们还研究了北半球 sPRI ₁₀衍生的 SOS 和 EOS 在不同植物功能类型方面的空间模式。我们表明，sPRI ₁₀可靠地跟踪植物物候，检测 SOS 和 EOS 的成功率分别为 83.0% 和 78.8%。SOS的空间格局呈现明显的纬度梯度，而EOS则表现出强烈的区域异质性。此外，sPRI ₁₀预测总体上比结构 VI 估计的 MODIS 物候产品 (VNP22Q2 v001) 更早的 SOS (61.8%) 和更晚的 EOS (51.2%)，表明后者低估了北半球的绿化潜力。我们的研究结果表明，MODIS PRI 可用于监测植被物候，并进一步揭示未被充分认识的类胡萝卜素色素在追踪植物季节性变化中的重要性，尤其是在秋季。