Remotely sensed predictors of conifer tree mortality during severe drought

P. G. Brodrick, G. P. Asner

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Widespread, drought-induced forest mortality has been documented on every forested continent over the last two decades, yet early pre-mortality indicators of tree death remain poorly understood. Remotely sensed physiological-based measures offer a means for large-scale analysis to understand and predict drought-induced mortality. Here, we use laser-guided imaging spectroscopy from multiple years of aerial surveys to assess the impact of sustained canopy water loss on tree mortality. We analyze both gross canopy mortality in 2016 and the change in mortality between 2015 and 2016 in millions of sampled conifer forest locations throughout the Sierra Nevada mountains in California. On average, sustained water loss and gross mortality are strongly related, and year-to-year water loss within the drought indicates subsequent mortality. Both relationships are consistent after controlling for location and tree community composition, suggesting that these metrics may serve as indicators of mortality during a drought.

Original languageEnglish (US)
Article number115013
JournalEnvironmental Research Letters
Volume12
Issue number11
DOIs
StatePublished - Nov 16 2017
Externally publishedYes

Fingerprint

Coniferophyta
Drought
Droughts
coniferous tree
drought
mortality
Mortality
Water
Spectroscopy
Antennas
Imaging techniques
canopy
Lasers
aerial survey
Chemical analysis
water
community composition
Spectrum Analysis
laser
spectroscopy

Keywords

  • California
  • canopy water content
  • forest vulnerability
  • imaging spectroscopy
  • progressive water stress
  • Sierra Nevada

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Public Health, Environmental and Occupational Health

Cite this

Remotely sensed predictors of conifer tree mortality during severe drought. / Brodrick, P. G.; Asner, G. P.

In: Environmental Research Letters, Vol. 12, No. 11, 115013, 16.11.2017.

Research output: Contribution to journalArticle

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