Autumn canopy phenological transitions are increasing in length as a consequence of climate change. Here, we assess how well hyperspectral indices in the visible and near-infrared (NIR) wavelengths predict nitrogen (N) concentrations in lower-canopy leaves in the autumn phenological transition as they are generally understudied in leaf trait research. Using a Bayesian framework, we tested how well published indices are able to predict N concentrations in Fagus grandifolia Ehrh., Liriodendron tulipifera L., and Betula lenta L. from mid-summer through senescence, and how related the indices are to autumn phenological change. No indices were able to determine a trend in differences in N in mid-summer leaves. Indices that included wavelengths in the green and NIR ranges were the first indices able to detect a trend and had among the highest correlations with N concentration in both the last green collection and the senescing collection. Models were unique when indices were fit to data from different phenophases. Indices that focused on only the red edge (i.e., the sharp increase in reflectance between the red and NIR wavelengths) had the strongest explanatory power across the autumn phenological transition, but had less explanatory power for individual collections. These indices, as well as those that have been correlated with chlorophyll (CCI) and carotenoids (PRI), were the strongest descriptors of autumn progression. This study provides insights on challenges and capabilities to monitor a leaf's N concentration throughout and across canopy senescence.

中文翻译：

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可见和近红外高光谱指数解释了秋季比夏季低冠叶氮含量的变化更大。

由于气候变化，秋季冠层物候过渡的长度在增加。在这里，我们评估了秋季物候过渡期中可见光和近红外（NIR）波长中的高光谱指数如何很好地预测了低冠层叶片中的氮（N）浓度，因为它们通常在叶片性状研究中得到了研究。使用贝叶斯框架，我们测试了已发表的指数能够预测仲夏至衰老期间大叶青海杨，鹅掌Li和桦桦的氮含量，以及这些指数与秋季物候变化之间的相关性。 。没有指数能够确定仲夏叶片氮素差异的趋势。包含绿色和NIR范围内的波长的指数是第一个能够检测趋势的指数，并且在最后一个绿色集合和敏感集合中与N浓度的相关性最高。当索引适合来自不同表相的数据时，模型是唯一的。仅关注红色边缘的指标（即红色和NIR波长之间反射率的急剧增加）在整个秋季物候过渡过程中具有最强的解释力，但对于单个集合而言则具有较小的解释力。这些指数以及与叶绿素（CCI）和类胡萝卜素（PRI）相关的指数是秋季进展的最强描述符。这项研究提供了有关挑战和监控叶子的能力的见解