Ecosystem functions are resistant to extreme changes to rainfall regimes in a mesotrophic grassland
Major changes to rainfall regimes are predicted for the future but the effect of such changes on terrestrial ecosystem function is largely unknown. We created a rainfall manipulation experiment to investigate the effects of extreme changes in rainfall regimes on ecosystem functioning in a grassland system.
We applied two rainfall regimes; a prolonged drought treatment (30 % reduction over spring and summer) and drought/downpour treatment (long periods of no rainfall interspersed with downpours), with an ambient control. Both rainfall manipulations included increased winter rainfall. We measured plant community composition, CO2 fluxes and soil nutrient availability.
Plant species richness and cover were lower in the drought/downpour treatment, and showed little recovery after the treatment ceased. Ecosystem processes were less affected, possibly due to winter rainfall additions buffering reduced summer rainfall, which saw relatively small soil moisture changes. However, soil extractable P and ecosystem respiration were significantly higher in rainfall change treatments than in the control.
This grassland appears fairly resistant, in the short term, to even the more extreme rainfall changes that are predicted for the region, although prolonged study is needed to measure longer-term impacts. Differences in ecosystem responses between the two treatments emphasise the variety of ecosystem responses to changes in both the size and frequency of rainfall events. Given that model predictions are inconsistent there is therefore a need to assess ecosystem function under a range of potential climate change scenarios.
KeywordsExtreme climate change Ecosystem function Temperate grassland CO2 fluxes Soil N and P availability
ELF was funded by a PhD studentship from the Grantham Institute for Climate Change at Imperial College, London URL http://www3.imperial.ac.uk/climatechange. The authors also gratefully acknowledge funding from UK POPnet, Centre for Population Biology and the UK Big Lottery Fund. We also thank C. Tang for help with figure preparation, and five anonymous reviewers whose insights have considerably strengthened the paper.
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