Evaluating Nondestructive Age Estimation Methods for Big Sagebrush, a Long-Lived, Wide-Ranging Shrub

Accurately assessing the age structure of plant populations is essential for understanding their dynamics and predicting responses to environmental change. Long-lived shrubs, like big sagebrush ( Artemisia tridentata ), play foundational roles in sagebrush ecosystems across Western North America. Yet, their age demographics are often underexplored due to the challenges of nondestructively estimating age. Here, we first assessed nondestructive techniques for estimating age in one subspecies of big sagebrush, identifying basal stem circumference as the morphological trait most strongly correlated with age ( r 2 = 0.508). However, the strength of this relationship differed considerably across sites, with r² values spanning from 0.116 to 0.709. We then evaluated the predictive accuracy of this trait across populations of two subspecies of big sagebrush. While basal stem circumference remained a robust predictor of age, its accuracy varied between subspecies and across populations, suggesting that local environmental factors may influence its reliability. Prediction accuracy was modest overall, with errors exceeding 10 yr and accuracy declining at the youngest and oldest ages. Prediction accuracy varied among subspecies and sites in response to local environmental conditions. Despite these limitations, these methods have practical implications for conservation and restoration, as circumference-based estimates can help managers quickly gauge whether recovering stands contain a mix of age classes, evaluate restoration success without destructive sampling, and anticipate how sagebrush populations may respond to disturbance or climate change.