Response of potential woody cover of Texas savanna to climate change in the 21st century

Xuebin Yang, Kelley A. Crews, Peter Kedron

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Potential woody cover of savanna ecosystems is highly relevant to their dynamics and management, especially with regard to the widespread phenomenon of woody plant encroachment. Prior studies suggest that water availability is the primary factor limiting potential woody cover. To this end, variations in future water availability due to climate change are likely to alter localized potential woody cover. This study aims to test this hypothesis in the savanna of central Texas, USA during the 21st century, with application of climate projection of Coupled Model Intercomparison Project Phase 5 (CMIP5). The established relationship between potential woody cover and observed mean annual precipitation (MAP) of 1981-2010 in the study area works as the basis in this study. It turns out that the vast majority of Texas savanna will receive less precipitation in the rest of the 21st century to different degrees, depending on temporal stages and Representative Concentration Pathways (RCPs). However, the potential woody cover does not necessarily change with precipitation. The semiarid region of Texas savanna and the very west portion of the mesic region will have lower potential woody cover. Whereas, potential woody cover in the arid region and most of the mesic region will remain the same. It is worth noting that discrepancy in projected potential woody cover maps exists between RCP4.5 and RCP8.5. This discrepancy highlights the varying effect that different government policies of greenhouse gas emission can impose on savanna ecosystems in the long run.

Original languageEnglish (US)
Article number109177
JournalEcological Modelling
Volume431
DOIs
StatePublished - Sep 1 2020

Keywords

  • 21st century
  • CMIP5
  • Climate change
  • Potential woody cover
  • Projection
  • Texas savanna

ASJC Scopus subject areas

  • Ecological Modeling

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