Annual precipitation explains variability in dryland vegetation greenness globally but not locally

Anna M. Ukkola*, Martin G. De Kauwe, Michael L. Roderick, Arden Burrell, Peter Lehmann, Andy J. Pitman

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Dryland vegetation productivity is strongly modulated by water availability. As precipitation patterns and variability are altered by climate change, there is a pressing need to better understand vegetation responses to precipitation variability in these ecologically fragile regions. Here we present a global analysis of dryland sensitivity to annual precipitation variations using long-term records of normalized difference vegetation index (NDVI). We show that while precipitation explains 66% of spatial gradients in NDVI across dryland regions, precipitation only accounts for <26% of temporal NDVI variability over most (>75%) dryland regions. We observed this weaker temporal relative to spatial relationship between NDVI and precipitation across all global drylands. We confirmed this result using three alternative water availability metrics that account for water loss to evaporation, and growing season and precipitation timing. This suggests that predicting vegetation responses to future rainfall using space-for-time substitution will strongly overestimate precipitation control on interannual variability in aboveground growth. We explore multiple mechanisms to explain the discrepancy between spatial and temporal responses and find contributions from multiple factors including local-scale vegetation characteristics, climate and soil properties. Earth system models (ESMs) from the latest Coupled Model Intercomparison Project overestimate the observed vegetation sensitivity to precipitation variability up to threefold, particularly during dry years. Given projections of increasing meteorological drought, ESMs are likely to overestimate the impacts of future drought on dryland vegetation with observations suggesting that dryland vegetation is more resistant to annual precipitation variations than ESMs project.

Original languageEnglish
Pages (from-to)4367-4380
Number of pages14
JournalGlobal Change Biology
Volume27
Issue number18
Early online date5 Jun 2021
DOIs
Publication statusPublished - Sep 2021

Bibliographical note

Funding Information:
The research was funded by the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). MDK acknowledges support from the NSW Research Attraction and Acceleration Program and the Australian Research Council (Discovery Grants DP190101823 and DP190102025). AMU acknowledges support from the Australian Research Council (DE200100086). We are grateful to the National Computational Infrastructure at the Australian National University and the Earth System Grid Federation for making the CMIP6 model outputs available. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.

Funding Information:
The research was funded by the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). MDK acknowledges support from the NSW Research Attraction and Acceleration Program and the Australian Research Council (Discovery Grants DP190101823 and DP190102025). AMU acknowledges support from the Australian Research Council (DE200100086). We are grateful to the National Computational Infrastructure at the Australian National University and the Earth System Grid Federation for making the CMIP6 model outputs available. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.

Keywords

  • climate change
  • drylands
  • Earth system models
  • precipitation
  • space-for-time substitution
  • vegetation

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