Tree-ring width series of white spruce (Picea glauca) trees (Coppermine River Canada) 1676 - 2003

• Main Authors: Rosanne D’Arrigo, Brendan Buckley, Rose Oelkers, Mathieu Levesque, Laia Andreu-Hayles
• Format: Dataset
• Language: unknown
• Published: Arctic Data Center 2023
• Subjects: Picea glauca; glauca; Arctic; Nunavut; Canada; Buckley; Coppermine River; Subarctic
• Online Access: https://doi.org/10.18739/A2QJ78043

Tree-ring width records of white spruce (Picea glauca [Moench] Voss) trees sampled along the Coppermine River (67º23’N / 115º92’W, 210 m a.s.l.) in 2004. When using this dataset, please cite: Lévesque, M., Andreu-Hayles, L., D’Arrigo, R., Oelkers, R., & Buckley, B. M. (2023). Non-linear Growth and Physiological Responses of White Spruce at North American Arctic Treeline. Journal of Geophysical Research: Biogeosciences, 128, e2022JG007096. https://doi.org/10.1029/2022JG007096 Project abstract: Temperatures in Arctic and subarctic North America are rising and are projected to continue to rise. Furthermore, atmospheric carbon dioxide is increasing around the globe. This project evaluates the response of white spruce to these ongoing changes. It uses archived samples from ten sites, standard tree-ring methodologies supplemented by novel chemical analyses, and numerical models to understand tree growth response to changing environmental drivers. Extending traditional tree-ring width and maximum latewood density records, the principal investigators established a high latitude network of stable carbon (d13C) and oxygen (d18O) isotope measurements, which provide an independent constraint on such changes relative to traditional dendroclimatological measurements. This project represents an interdisciplinary opportunity to combine three distinct disciplines: (1) basic dendrochronological techniques, which allow for precisely-dated, quantitative and verifiable long-term tree-ring records; (2) low temperature geochemical tools to measure del13C and del18O ratios that independently reflect environmental variables including temperature, precipitation, relative humidity and long-term physiological information on water use efficiency in natural forests; and (3) the joint use of a process-based mechanistic model, MAIDENiso, to distinguish between the confounding effects of increases in temperatures and atmospheric CO2 and to predict boreal forest response under different scenarios, and the NASA GISS ModelE2 general circulation model to provide inputs to MAIDENiso.