Ultra-high-resolution reflected-light imaging for dendrochronology

Abstract

Dendroclimatic reconstructions play a key role in contextualizing recent climate change by improving our understanding of past climate variability. The Blue Intensity (BI) measurement technique is gaining prominence as a more accessible alternative to X-ray densitometry for producing climatically highly-sensitive tree-ring predictors. Nevertheless, accurately representing low-frequency trends and high-frequency extremes using scanner-based BI remains a challenge due to color biases and resolution limitations. Herein we introduce several methodological advances in sample surfacing, imaging, and image processing which yield measurement series analogous to BI from ultra-high-resolution (UHR; ∼74 700 dpi) images. Such series capture changes in tree-ring anatomical density by representing wood anatomical structure using binary (i.e., black-white) segmentation of sample images. We refer to this novel technique as Binary Surface Intensity (BSI). By utilizing a UHR system and entirely eliminating color and light intensity as variables, the most substantial drawbacks of scanner BI (i.e., discoloration and resolution biases) are bypassed, resulting in more accurate representations of low-frequency climatic trends and high-frequency extremes. Comparisons of several chronologies developed with the BSI and BI techniques, including a multiparameter dataset from Björklund et al. (2019), showed that BSI datasets outperform BI in terms of common signal (r-bar), but also contain strong climatic signals that can exceed those obtained from BI and X-ray density, and even match density datasets based on quantitative wood anatomy. However, measurement software advancements are still required to unlock the full potential of tree-ring parameters produced using the BSI technique. Ongoing development of this new technique will not only aid the attainment of long unbiased chronologies by overcoming color biases and resolution limitations, but also holds promise for unlocking UHR analyses of surface anatomical (sQWA) parameter datasets from reflected-light images. These advances will lead to more accurate tree-ring-based paleoclimatic reconstructions and could also serve a wider range of dendrochronological applications.