A Rapid Hard‐Mast Index From Acorn Presence‐Absence Tallies

Abstract

Abstract: We used 21 years of acorn data from visual surveys of oak ( Quercus spp.) trees ( n = 20,113) conducted in western North Carolina, USA, to develop predictive equations for hard‐mast indices (HMIs) based on the proportion of trees bearing acorns (PBA). We calculated PBA using visual estimates of the percentage of oak crown with acorns (PCA), assigning acorn presence if PCA ≥ 33.5%.The proportion of trees bearing acorns and average PCA were highly correlated, and PBA alone was a successful predictor of HMIs. Precise estimates of PBA (therefore HMIs) at a 95% confidence level required 139‐385 sample trees for each oak subgroup or spatial scale of interest, and the sample size required varied with the true PBA. Substituting this faster, simpler visual survey method for others involving labor‐intensive counts of twigs and acorns means that more trees can be sampled (if needed) with less time and effort for improved PBA (therefore HMI) precision. We offer a reliable method for predicting HMIs that are comparable to past HMI estimates for states using the Whitehead (1969) method, thus providing continuity in tracking long‐term acorn production patterns. We also developed categories for subjectively ranking acorn crop sizes based on the range of PBA observed during 21 years. We recommend that PBA be adopted by resource management agencies as a standard, stand‐alone index of acorn production to ensure comparable data among years and across the eastern United States. A standardized protocol for assigning acorn presence or absence must be used for consistent, comparable regional use of PBA in predicting HMIs or by itself as an index of acorn production.