Dryland ecosystems are a major source of land cover, accountfor about 40% of Earth's terrestrial surface and net primaryproductivity, and house more than 30 % of the human population. Theseecosystems are subject to climate extremes (e.g. large-scale droughts andextreme floods) that are projected to increase in frequency and severityunder most future climate scenarios. In this modelling study we assessed theimpact of single years of extreme (high or low) rainfall on drylandvegetation in the Sahel. The magnitude and legacy of these impacts werequantified on both the plant functional type and the ecosystem levels. Inorder to understand the impact of differences in the rainfall distributionover the year, these rainfall anomalies were driven by changing eitherrainfall intensity, event frequency or rainy-season length. TheLund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetationmodel was parameterized to represent dryland plant functional types (PFTs)and was validated against flux tower measurements across the Sahel.Different scenarios of extreme rainfall were derived from existing Sahelrainfall products and applied during a single year of the model simulationtimeline. Herbaceous vegetation responded immediately to the differentscenarios, while woody vegetation had a weaker and slower response,integrating precipitation changes over a longer timeframe. An increasedseason length had a larger impact than increased intensity or frequency,while impacts of decreased rainfall scenarios were strong and independent ofthe season characteristics. Soil control on surface water balance explainsthese contrasts between the scenarios. None of the applied disturbancescaused a permanent vegetation shift in the simulations. Dryland ecosystemsare known to play a dominant role in the trend and variability of the globalterrestrial CO2 sink. We showed that single extremely dry and wet yearscan have a strong impact on the productivity of drylands ecosystems, whichtypically lasts an order of magnitude longer than the duration of thedisturbance. Therefore, this study sheds new light on potential drivers andmechanisms behind this variability.
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