Accounting for landscape heterogeneity improves spatial predictions of tree vulnerability to drought
PAROLARI, Anthony J.
Department of Civil and Environmental Engineering
Department of Civil, Construction, and Environmental Engineering
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Department of Civil and Environmental Engineering
Department of Civil, Construction, and Environmental Engineering
PAROLARI, Anthony J.
Department of Civil and Environmental Engineering
Department of Civil, Construction, and Environmental Engineering
Department of Civil and Environmental Engineering
Department of Civil, Construction, and Environmental Engineering
JOHNSON, Daniel M.
Nicholas School of the Environment
Warnell School of Forestry and Natural Resources
Nicholas School of the Environment
Warnell School of Forestry and Natural Resources
DOMEC, Jean-Christophe
Interactions Sol Plante Atmosphère [UMR ISPA]
Nicholas School of the Environment
Interactions Sol Plante Atmosphère [UMR ISPA]
Nicholas School of the Environment
PELAK, Norman
Department of Civil and Environmental Engineering
Princeton Environmental Institute [Princeton University] [PEI]
Department of Civil and Environmental Engineering
Princeton Environmental Institute [Princeton University] [PEI]
PORPORATO, Amilcare
Department of Civil and Environmental Engineering
Princeton Environmental Institute [Princeton University] [PEI]
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Department of Civil and Environmental Engineering
Princeton Environmental Institute [Princeton University] [PEI]
Langue
en
Article de revue
Ce document a été publié dans
New Phytologist. 2018, vol. 220, n° 1, p. 132-146
Wiley
Résumé en anglais
As climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability varies regionally and locally through landscape position. Also, most models used in forecasting forest responses ...Lire la suite >
As climate change continues, forest vulnerability to droughts and heatwaves is increasing, but vulnerability varies regionally and locally through landscape position. Also, most models used in forecasting forest responses to heat and drought do not incorporate relevant spatial processes. In order to improve spatial predictions of tree vulnerability, we employed a nonlinear stochastic model of soil moisture dynamics accounting for landscape differences in aspect, topography and soils. Across a watershed in central Texas we modeled dynamic water stress for a dominant tree species, Juniperus ashei, and projected future dynamic water stress through the 21st century. Modeled dynamic water stress tracked spatial patterns of remotely sensed drought-induced canopy loss. Accuracy in predicting drought-impacted stands increased from 60%, accounting for spatially variable soil conditions, to 72% when also including lateral redistribution of water and radiation/temperature effects attributable to aspect. Our analysis also suggests that dynamic water stress will increase through the 21st century, with trees persisting at only selected microsites. Favorable microsites/refugia may exist across a landscape where trees can persist; however, if future droughts are too severe, the buffering capacity of an heterogeneous landscape could be overwhelmed. Incorporating spatial data will improve projections of future tree water stress and identification of potential resilient refugia.< Réduire
Mots clés
soil moisture
Mots clés en anglais
climate change
drought-induced tree mortality
heat load
landscape diversity
stochastic processes
topographic convergence
water stress
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