Data and Code for Mechanistic links between physiology and spectral reflectance enable pre-visual detection of oak wilt and drought stress

Abstract

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.