High-resolution wood surface imaging for dendrochronology: towards the development of unbiased reflected light timeseries

Climate change is a global-scale issue of societal, economic, and political importance and so understanding the climate of the present within the context of past climate variability is of vital importance. Dendroclimatic reconstructions play a key role in contextualizing recent climate change by improving our understanding of historical climate conditions. The climatically-sensitive blue intensity (BI) tree-ring parameter is gaining prominence as a more affordable and accessible alternative to traditional X-ray densitometry. Yet the accurate representation of low-frequency trends and high-frequency extremes using scanner-based BI remains a challenge due to color-related biases and resolution limitations. As part of the REPLICATE project, which aims to develop a set of robust multi-parameter temperature reconstructions from Carpathian Norway spruce (Picea abies) tree rings, methodological advances in sample surface preparation, imaging and measurement techniques have produced series analogous to BI from ultra-high resolution (~74 700 true dpi) images. Series from these microscope-based reflected light images of the tree-ring sample surface, termed surface intensity (SI), represent the binary (black-white) segmentation of wood anatomical structure, which approximates anatomical density. By eliminating color altogether and using a high-resolution system, the most substantial drawbacks of scanner BI (i.e., discoloration and resolution biases) are bypassed and hence climate signal optimization is achieved by more accurately representing low-frequency climatic trends and high-frequency extremes. A comparison of SI chronologies with a multi-parameter tree-ring dataset from a large-scale parameter assessment study by Björklund et al. (2019) showed that this novel SI parameter can outperform its BI couterpart in terms of common signal (interseries correlation) and climate signal strength, and that it is on par with the best-performing X-ray densitometric chronologies. However, existing programs are not currently designed to effectively capture SI measurements and so additional development of measurement software is required to unlock the full potential of this new parameter. Continued improvement of high-resolution imaging techniques will aid the attainment of unbiased long tree-ring chronologies by overcoming color biases and resolution issues, but also holds promise for the development of surface quantitative wood anatomy (sQWA) datasets from reflected light images of samples. These improvements will therefore not only lead to more accurate dendrochronological paleoclimatic records and climate reconstructions but will also find future application in a broad range of dendrochronological contexts.