| 1. |
- Hovenden, Mark J., et al.
(författare)
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Globally consistent influences of seasonal precipitation limit grassland biomass response to elevated CO2
- 2019
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Ingår i: Nature Plants. - : Springer Science and Business Media LLC. - 2055-0278. ; 5, s. 167-173
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Tidskriftsartikel (refereegranskat)abstract
- © 2019, The Author(s), under exclusive licence to Springer Nature Limited. Rising atmospheric carbon dioxide concentration should stimulate biomass production directly via biochemical stimulation of carbon assimilation, and indirectly via water savings caused by increased plant water-use efficiency. Because of these water savings, the CO 2 fertilization effect (CFE) should be stronger at drier sites, yet large differences among experiments in grassland biomass response to elevated CO 2 appear to be unrelated to annual precipitation, preventing useful generalizations. Here, we show that, as predicted, the impact of elevated CO 2 on biomass production in 19 globally distributed temperate grassland experiments reduces as mean precipitation in seasons other than spring increases, but that it rises unexpectedly as mean spring precipitation increases. Moreover, because sites with high spring precipitation also tend to have high precipitation at other times, these effects of spring and non-spring precipitation on the CO 2 response offset each other, constraining the response of ecosystem productivity to rising CO 2 . This explains why previous analyses were unable to discern a reliable trend between site dryness and the CFE. Thus, the CFE in temperate grasslands worldwide will be constrained by their natural rainfall seasonality such that the stimulation of biomass by rising CO 2 could be substantially less than anticipated.
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| 2. |
- Prager, Case M., et al.
(författare)
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Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment : An example from the WaRM Network
- 2022
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Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 12:10
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Tidskriftsartikel (refereegranskat)abstract
- A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.
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