Accounting for landscape heterogeneity improves spatial predictions of tree vulnerability to drought.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Schwantes, AM; Parolari, AJ; Swenson, JJ; Johnson, DM; Domec, J-C; Jackson, RB; Pelak, N; Porporato, A

Published Date

  • October 2018

Published In

Volume / Issue

  • 220 / 1

Start / End Page

  • 132 - 146

PubMed ID

  • 29974958

Pubmed Central ID

  • 29974958

Electronic International Standard Serial Number (EISSN)

  • 1469-8137

International Standard Serial Number (ISSN)

  • 0028-646X

Digital Object Identifier (DOI)

  • 10.1111/nph.15274

Language

  • eng