Sapes, GerardSchroeder, LucyScott, AllisonClark, IsaiahJuzwik, JenniferMontgomery, RebeccaGuzman Q., J. AntonioCavender-Bares, Jeannine2024-01-042024-01-042024-01-04https://hdl.handle.net/11299/259318Zip file contains folder structure with R code and data files for all processing, analysis and figures. Plots: Where plots generated in the code are saved; Results: Where results can be saved if desired; Data: Contains all the data needed to reproduce the manuscript. See the Readme file for more information.Tree mortality due to global change-including range expansion of invasive pests and pathogens- is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen to detect and distinguish both types of stressors. We also performed a field experiment where we validated the capacity of spectral reflectance models to predict physiological status and distinguish oak wilt from healthy trees. The data and code provided here address these goals.CC0 1.0 Universaldroughtoak wiltprevisual detectionspectral reflectancetree mortalityDatasethttps://doi.org/10.13020/0bt3-pd25