Evaluating the influence of high-resolution image capture on the signal strength of blue intensity and quantitative wood anatomy metrics from whitebark pine

Abstract

Ring-density parameters, such as maximum latewood density (MXD), blue intensity (BI), and quantitative wood anatomy (QWA), can be highly sensitive to summer temperatures. While MXD is traditionally obtained through resource-intensive X-ray densitometry, advancements in high-resolution image processing offer alternative methods for measuring density metrics. This study evaluates latewood BI (LWBI) chronologies developed from two image resolutions (Epson: 2400 dpi and Skippy: 6700 dpi) against QWA-derived MXD (aMXD) for whitebark pine (Pinus albicaulis, PIAL) in the Greater Yellowstone Ecoregion, USA. LWBI metrics exhibited robust linear relationships with June–August (JJA) maximum temperatures (i.e., R² = 0.27 for Epson and R² = 0.31 for Skippy; p < 0.01), but differences between image resolutions were not statistically significant. Spatial relationships were robust for LWBI, though the relationships with Epson and Skippy were similar. Additionally, Skippy may have captured a longer growing season signal (June–September) compared with Epson, while Epson improved with selections of a larger fraction of darkest pixels (e.g., 30–50 %). Our findings also indicate that% darkest pixel selections affect outcomes differently when measuring LWBI from Epson and Skippy images. This pilot study highlights the potential of LWBI as a faster alternative to QWA, with both metrics demonstrating significant climate sensitivity in PIAL. By successfully capturing strong temperature signals from PIAL, an understudied and ecologically critical species, this research supports the fusion of dendroclimatological applications to produce a more robust climate signal, as well as the development of millennial-length climate reconstructions in high-elevation ecosystems of North America.