Accuracy of Whitebark Pine and Limber Pine Identification by Forest Inventory and Analysis Field Crews

Abstract

Abstract Accurate identification of whitebark and limber pine has become increasingly important following the 2022 listing of whitebark pine as a threatened species under the Endangered Species Act. However, morphological similarities make identification of the two species difficult where ranges overlap. Using a genetic test that differentiates whitebark and limber pine, we compared field identification by Forest Inventory and Analysis field crews with genetic identification for needle samples from 371 trees. Field identifications were 100% correct for the 76 samples collected from outside regions of species’ range overlap. A total of 83% of the field identifications were correct in regions of range overlap (89% for large trees, 88% for saplings, and 78% for seedlings). Field-identified samples were correct 60% of the time for limber pine and >99% for whitebark pine. Random forests analysis revealed that identification accuracy is influenced by crew experience, large (≥ 12.7cm diameter) limber or whitebark pines recorded by field crews on the plot, elevation, Julian day of sample collection, and habitat type. We found that whitebark pine has likely been underestimated, and limber pine overestimated, within their overlapping ranges. We provide insights on improving accuracy of future monitoring where these species overlap. Study Implications: Accurate identification of whitebark pine is critical for monitoring this threatened species, yet distinguishing whitebark from limber pine can be difficult. Genetic analysis determined accuracy of field identification by Forest Inventory and Analysis (FIA) crews was 83% where the species’ ranges overlap. Virtually all individuals identified as whitebark pine were genetically confirmed to be whitebark pine, although nearly 40% of individuals identified as limber pine were actually whitebark pine. Thus, previous data underestimated whitebark and overestimated limber pine abundance in the species’ range overlap. These results quantify reliability of FIA data for whitebark pine assessments and identify areas for improvement.