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

Abstract

Abstract. Dryland ecosystems are a major source of land cover, account for about 40% of Earth's terrestrial surface and net primary productivity, and house more than 30 % of the human population. These ecosystems are subject to climate extremes (e.g. large-scale droughts and extreme floods) 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 impact of differences in the rainfall distribution over the year, these rainfall anomalies were driven by changing either rainfall intensity, event frequency or rainy-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 flux tower measurements across the Sahel. Different scenarios of extreme rainfall were derived from existing Sahel rainfall products 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. None of the applied disturbances caused a permanent vegetation shift in the simulations. Dryland ecosystems are known to play a dominant role in the trend and variability of the global terrestrial CO2 sink. We showed that single extremely dry and wet years can have a strong impact on the productivity of drylands ecosystems, which typically lasts an order of magnitude longer than the duration of the disturbance. Therefore, this study sheds new light on potential drivers and mechanisms behind this variability.

Insensitivity of Ecosystem Productivity to Predicted Changes in Fine‐Scale Rainfall Variability

“…This finding, along with the dominance of WRF‐projected changes in mean annual rainfall and rainfall seasonality over changes in the temporal structure of rainfall, coincides with previous research that reported the ability of ecosystems to dampen high‐frequency rainfall variability (Stoy et al., 2009). Water precipitated at the fine‐scale is buffered by soils and can remain available to plants for longer periods (McColl et al., 2017) and, hence, high‐frequency rainfall variability is essentially integrated over coarser temporal scales in the root zone (Paschalis et al., 2015; Verbruggen et al., 2021).…”

“…Increased vegetation stress can reduce photosynthetic and plant transpiration rates (Fatichi, Pappas, & Ivanov, 2016; Manzoni et al., 2013), and even lead to plant mortality (Preisler et al., 2021). Temporal structure can be particularly important for shallow rooted herbaceous species, which are highly responsive to rainfall pulses (Verbruggen et al., 2021), due to their lack of access to deep water stores. However, even forested ecosystems have been found to be sensitive to changes in rainfall temporal structure, since drought conditions can trigger a number of processes in trees, such as growth limitation, reduction of carbon and water fluxes, and even carbon starvation and hydraulic failure, leading to tree mortality (McDowell, 2011).…”

Simulation of Vegetation Cover Based on the Theory of Ecohydrological Optimality in the Yongding River Watershed, China

“…Changes in the needleleaf forest are more dependent on precipitation than ET due to their smaller leaf area and thicker leaf blade, which prevents heat accumulation and water evaporation on the leaf surface [63]. In addition, the variability in the precipitation characteristic factors, especially 𝑚 and 𝑚 , changes the spatiotemporal availability of soil water uptake by plants and has a significant impact on vegetation [64]. Zhang [65] found that the number of rainy days, heavy-rainfall events, and consecutive dry days are three important indicators affecting the NDVI in the growing season across the Sahel.…”

Contrasting responses of two typical plant communities to precipitation variability in horqin sandy land, northeast China

“…Currently, the effects of precipitation variability on ecosystems are receiving growing attention from ecologists (Fernandez-Going et al 2012, Cleland et al 2013, Kulmatiski and Beard 2013, Zhang et al 2019, Paschalis et al 2020, Verbruggen et al 2021, Yue et al 2023, because of the incontrovertible evidence for changes in precipitation regimes IPCC Climate Change (2022). Most general circulation models project that the precipitation regime is changing and will intensify in the coming decades as a consequence of global warming, including the change in total amount, increasing variability in event size and event intervals, and increases in the frequency and severity of storms and droughts (IPCC 2012).…”

“…There are a few experimental studies on effects of altered precipitation regimes on communities with contrasting soil and vegetation characteristics (Grime et al 2008, Heisler-White et al 2009, Fernandez-Going et al 2012, which suggested that vegetation and soil properties can influence a community's response to shifts of precipitation regime. For example, the aboveground biomass and precipitation use efficiency in some grassland communities composed of stress-tolerant species showed less responsive to precipitation variability (O'Connor et al 2001, Grime et al 2008, Fernandez-Going et al 2012; annual plants are more sensitive to rainfall changes than perennials because of specific functional traits (Kandlikar et al 2022); herbaceous vegetation responded immediately to the different rainfall scenarios, while the woody vegetation had a weaker and slower response (Verbruggen et al 2021).…”