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The impact of inter-annual rainfall variability on African savannas changes with mean rainfall

  • Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520–780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580–780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wetSavannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520–780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580–780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during ‘dry’ extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability.show moreshow less

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Metadaten
Author details:Alexis D. SynodinosORCiD, Britta TietjenORCiD, Dirk LohmannORCiDGND, Florian JeltschORCiDGND
DOI:https://doi.org/10.1016/j.jtbi.2017.10.019
ISSN:0022-5193
ISSN:1095-8541
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/29054812
Title of parent work (English):Journal of theoretical biology
Publisher:Elsevier Ltd.
Place of publishing:London
Publication type:Article
Language:English
Date of first publication:2017/10/18
Publication year:2018
Release date:2022/02/11
Tag:Coexistence mechanisms; Fire; Rainfall variability; Savanna-grassland bistability; Stochastic differential equations
Volume:437
Number of pages:9
First page:92
Last Page:100
Funding institution:German Research Foundation (DFG)German Research Foundation (DFG) [GRK 1364]; German Federal Ministry of Education and Research (Bundesministerium fur Bildung und Forschung)Federal Ministry of Education & Research (BMBF) [01LL1302A, 01LL1302B]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
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