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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  02 Jul 2020

02 Jul 2020

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This preprint is currently under review for the journal BG.

Contrasting responses of woody and herbaceous vegetation to altered rainfall characteristics in the Sahel

Wim Verbruggen1,2, Guy Schurgers2, Stéphanie Horion2, Jonas Ardö3, Paulo Negri Bernardino4,5, Bernard Cappelaere6, Jérôme Demarty6, Rasmus Fensholt2, Laurent Kergoat7, Thomas Sibret1, Torbern Tagesson2,3, and Hans Verbeeck1 Wim Verbruggen et al.
  • 1CAVElab, Department of Environment, Ghent University, Ghent, 9000, Belgium
  • 2Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
  • 3Department of Physical Geography and Ecosystem Science, Lund University, Lund, 22100, Sweden
  • 4Department of Earth and Environmental Sciences, KULeuven, Leuven, 3000, Belgium
  • 5Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Wageningen, 6708, the Netherlands
  • 6HydroSciences Montpellier, IRD/CNRS, Université de Montpellier, Montpellier, 34090, France
  • 7Géosciences Environnement Toulouse, CNRS/UPS/IRD, Toulouse, 31400, France

Abstract. Dryland ecosystems form a major land cover, accounting for about 40 % of Earth's terrestrial surface and net primary productivity, and housing more than 30 % of the human population. These ecosystems are subject to climate extremes (e.g. large-scale droughts) that are projected to increase in frequency and severity under most future climate scenarios. In this modelling study we assessed the impact of single years of extreme (high or low) rainfall on dryland vegetation in the Sahel. The magnitude and legacy of these impacts were quantified on both the plant functional type and the ecosystem levels. In order to understand the signature of the rainy season characteristics, these rainfall anomalies were driven by changing either rainfall intensity, event frequency or season length. The Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model was parameterized to represent dryland plant functional types (PFTs) and was validated against fluxtower measurements across the Sahel. Different scenarios of extreme rainfall were derived from existing Sahel rainfall products such that meteorological consistency was maintained, and applied during a single year of the model simulation timeline. Herbaceous vegetation responded immediately to the different scenarios, while woody vegetation had a weaker and slower response, integrating precipitation changes over a longer timeframe. An increased season length had a larger impact than increased intensity or frequency, while impacts of decreased rainfall scenarios were strong and independent of the season characteristics. Soil control on surface water balance explains these contrasts between the scenarios. Semi-arid ecosystems are known to play a dominant role in the trend and variability of the terrestrial CO2 sink. We showed that single extremely dry and wet years can have strong and long-term impact on the productivity of drylands ecosystems, shedding new light on potential drivers and mechanisms behind this variability.

Wim Verbruggen et al.

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Status: final response (author comments only)
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Wim Verbruggen et al.

Wim Verbruggen et al.


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Latest update: 27 Sep 2020
Publications Copernicus
Short summary
A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO2 uptake.
A large part of Earth's land surface is covered by dryland ecosystems, which are subject to...