Mechanistic links between physiology and spectral reflectance enable previsual detection of oak wilt and drought stress

Gerard Sapes, Lucy Schroeder, Allison Scott, Isaiah Clark, Jennifer Juzwik, Rebecca A. Montgomery, J. Q. Antonio Guzmán, Jeannine Cavender-Bares

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

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. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content, and cellular damage detected oak wilt and drought 12 d before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.

Original languageEnglish (US)
Article numbere2316164121
JournalProceedings of the National Academy of Sciences of the United States of America
Volume121
Issue number7
DOIs
StatePublished - Feb 13 2024

Bibliographical note

Publisher Copyright:
© 2024 the Author(s). Published by PNAS.

Keywords

  • drought
  • oak wilt
  • previsual detection
  • spectral reflectance
  • tree mortality

PubMed: MeSH publication types

  • Journal Article

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