Time series analyses of pigment concentrations are key to understanding past aquatic ecosystem dynamics. As lake sediments provide a window into longer-term changes, innovative paleolimnological chlorophyll quantification could provide impactful insights into past environmental processes. Lab-based hyperspectral imaging of sediment cores is an emerging technique to develop rapid, non-destructive, high-resolution chlorophyll inferences but it requires more extensive vetting. Despite recent advances in model development, there is still a knowledge gap about the reliability of chlorophyll models when applied in lakes with diverse properties, as well as the potential confounding effects of physical sediment properties on these models. We assessed the performance of 23 chlorophyll indices based on paired measurements collected via hyperspectral imaging and spectrophotometry for 202 samples spread across seven Canadian lake sediment cores. The best performance was by a new index based on the wavelength of the red-edge minimum point (λREMP). We tested the applicability of λREMP to a broad range of sediment cores using a database of 116 cores, and found the index to provide reliable reconstructions of ƩChl (i.e., chlorophyll a and b and their degradation products) trends in 84% of sites. Further analyses indicated that sediment characteristics including particle size, organic matter content, water content, and density had no systematic impact on ƩChl, but greater sediment brightness did increase ƩChl inferences from hyperspectral images. Hyperspectral core scanning is poised to facilitate the generation of high-resolution chlorophyll time series data, which could greatly improve our understanding of trajectories of change from the local to global scales.

中文翻译：

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沉积物岩心高光谱成像快速生成叶绿素时间序列的新索引

色素浓度的时间序列分析是了解过去水生生态系统动态的关键。由于湖泊沉积物为了解长期变化提供了一个窗口，创新的古湖泊学叶绿素定量可以为过去的环境过程提供有影响力的见解。基于实验室的沉积物岩心高光谱成像是一种新兴技术，可用于开发快速、无损、高分辨率叶绿素推断，但需要更广泛的审查。尽管模型开发最近取得了进展，但对于叶绿素模型应用于具有不同属性的湖泊时的可靠性以及物理沉积物属性对这些模型的潜在混杂影响仍然存在知识差距。我们根据通过高光谱成像和分光光度法收集的 202 个样本（分布在加拿大 7 个湖泊沉积物岩心）的配对测量结果，评估了 23 种叶绿素指数的性能。最佳性能是基于红边极小点 (λREMP) 波长的新指数。我们使用 116 个岩心的数据库测试了 λREMP 对各种沉积物岩心的适用性，并发现该指数可以可靠地重建 84% 地点的 ƩChl（即叶绿素 a 和 b 及其降解产物）趋势。进一步分析表明，沉积物特征（包括粒径、有机质含量、含水量和密度）对ƩChl没有系统性影响，但较大的沉积物亮度确实增加了高光谱图像中ƩChl的推断。高光谱核心扫描有望促进高分辨率叶绿素时间序列数据的生成，这可以极大地提高我们对从局部到全球尺度的变化轨迹的理解。