Dead again: Predictions of repeat tree die-off under hotter droughts confirm mortality thresholds for a dryland conifer species
AffiliationSchool of Natural Resources and the Environment, Department of Ecology and Evolutionary Biology, University of Arizona
Keywordsaerial detection surveys (ADS)
Pinus edulis (pinyon pine)
MetadataShow full item record
PublisherInstitute of Physics
CitationWion, A. P., Breshears, D. D., Carroll, C. J. W., Cobb, N. S., Hart, S. J., Law, D. J., Meneses, N., & Redmond, M. D. (2022). Dead again: Predictions of repeat tree die-off under hotter droughts confirm mortality thresholds for a dryland conifer species. Environmental Research Letters, 17(7).
JournalEnvironmental Research Letters
RightsCopyright © 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractTree die-off, driven by extreme drought and exacerbated by a warming climate, is occurring rapidly across every wooded continent - threatening carbon sinks and other ecosystem services provided by forests and woodlands. Forecasting the spatial patterns of tree die-off in response to drought is a priority for the management and conservation of forested ecosystems under projected future hotter and drier climates. Several thresholds derived from drought-metrics have been proposed to predict mortality of Pinus edulis, a model tree species in many studies of drought-induced tree die-off. To improve future capacity to forecast tree mortality, we used a severe drought as a natural experiment. We compared the ability of existing mortality thresholds derived from four drought metrics (the Forest Drought Severity Index (FDSI), the Standardized Precipitation Evapotranspiration Index, and raw values of precipitation (PPT) and vapor pressure deficit, calculated using 4 km PRISM data) to predict areas of P. edulis die-off following an extreme drought in 2018 across the southwestern US. Using aerial detection surveys of tree mortality in combination with gridded climate data, we calculated the agreement between these four proposed thresholds and the presence and absence of regional-scale tree die-off using sensitivity, specificity, and the area under the curve (AUC). Overall, existing mortality thresholds tended to over predict the spatial extent of tree die-off across the landscape, yet some retain moderate skill in discriminating between areas that experienced and did not experience tree die-off. The simple PPT threshold had the highest AUC score (71%) as well as fair sensitivity and specificity, but the FDSI had the greatest sensitivity to die-off (85.9%). We highlight that empirically derived climate thresholds may be useful forecasting tools to identify vulnerable areas to drought induced die-off, allowing for targeted responses to future droughts and improved management of at-risk areas. © 2022 The Author(s). Published by IOP Publishing Ltd.
NoteOpen access journal
VersionFinal published version
Except where otherwise noted, this item's license is described as Copyright © 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.