A new index for the rapid generation of chlorophyll time series from hyperspectral imaging of sediment cores

Abstract

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.