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Using models to guide field experiments: a priori predictions for the CO2 response of a nutrient‐ and water‐limited native Eucalypt woodland

Authors: K. A. Luus; Richard J. Norby; David S. Ellsworth; Sally A. Power; Catriona A. Macdonald; Xiaojuan Yang; Martin G. De Kauwe; +14 Authors

Using models to guide field experiments: a priori predictions for the CO2 response of a nutrient‐ and water‐limited native Eucalypt woodland

Abstract

AbstractThe response of terrestrial ecosystems to rising atmospheric CO2 concentration (Ca), particularly under nutrient‐limited conditions, is a major uncertainty in Earth System models. The Eucalyptus Free‐Air CO2 Enrichment (EucFACE) experiment, recently established in a nutrient‐ and water‐limited woodland presents a unique opportunity to address this uncertainty, but can best do so if key model uncertainties have been identified in advance. We applied seven vegetation models, which have previously been comprehensively assessed against earlier forest FACE experiments, to simulate a priori possible outcomes from EucFACE. Our goals were to provide quantitative projections against which to evaluate data as they are collected, and to identify key measurements that should be made in the experiment to allow discrimination among alternative model assumptions in a postexperiment model intercomparison. Simulated responses of annual net primary productivity (NPP) to elevated Ca ranged from 0.5 to 25% across models. The simulated reduction of NPP during a low‐rainfall year also varied widely, from 24 to 70%. Key processes where assumptions caused disagreement among models included nutrient limitations to growth; feedbacks to nutrient uptake; autotrophic respiration; and the impact of low soil moisture availability on plant processes. Knowledge of the causes of variation among models is now guiding data collection in the experiment, with the expectation that the experimental data can optimally inform future model improvements.

Countries
United Kingdom, France
Keywords

[SDE] Environmental Sciences, 550, [SDV]Life Sciences [q-bio], Climate Change, ecosystem model, drought, Forests, 551, Carbon Cycle, XXXXXX - Unknown, phosphorus, Photosynthesis, Ecosystem, 580, Eucalyptus, droughts, carbon dioxide, Water, Carbon Dioxide, Eucalyptus tereticornis, [SDV] Life Sciences [q-bio], [SDE]Environmental Sciences, ecosystems

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    80
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
80
Top 1%
Top 10%
Top 10%
Green
hybrid