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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2019-175
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2019-175
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 27 May 2019

Submitted as: research article | 27 May 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Leaf Area Index Changes Explain GPP Variation across an Amazon Drought Stress Gradient

Sophie Flack-Prain1, Patrick Meir1,2, Yadvinder Malhi4, Thomas Luke Smallman1,3, and Mathew Williams1,3 Sophie Flack-Prain et al.
  • 1School of GeoSciences, University of Edinburgh, Edinburgh, UK
  • 2Research School of Biology, Australian National University, Canberra, ACT, Australia
  • 3National Centre for Earth Observation, University of Edinburgh, UK
  • 4Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK

Abstract. The capacity of Amazon forests to sequester carbon is threatened by climate change-induced shifts in precipitation patterns. However, the relative importance of plant physiology, ecosystem structure, and trait composition responses in determining variation in GPP, remain largely unquantified, and vary among models. We evaluate the relative importance of key climate constraints to gross primary productivity (GPP), comparing direct plant physiological responses to water availability and indirect structural and trait responses (via changes to leaf area index (LAI), roots and photosynthetic capacity). To separate these factors we combined the Soil-Plant-Atmosphere model with forcing and observational data from seven intensively studied forest plots along an Amazon soil moisture-stress gradient. We also used machine learning to evaluate the relative importance of individual climate factors across sites. Our model experiments showed that variation in LAI was the principal driver of differences in GPP across the gradient, accounting for 33 % of observed variation. Differences in photosynthetic capacity (Vcmax and Jmax) accounted for 21 % of variance, and climate (which included physiological responses) accounted for 16 %. Sensitivity to differences in climate was highest where shallow rooting depth was coupled with high LAI. On sub-annual timescales, the relative importance of LAI in driving GPP increased with soil moisture-stress (R2 = 0.72), whilst the importance of solar radiation decreased (R2 = 0.90). Given the role of LAI in driving GPP across Amazon forests, improved mapping of canopy dynamics is critical, opportunities for which are offered by new satellite-based remote sensing missions such as GEDI, Sentinel and FLEX.

Sophie Flack-Prain et al.
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Sophie Flack-Prain et al.
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Short summary
Across the Amazon rainforest, trees take in carbon through photosynthesis. However, photosynthesis across the basin is threatened by predicted shifts in rainfall patterns. To unpick how changes in rainfall affect photosynthesis, we use a model which combines climate data with our knowledge of photosynthesis and other plant processes. We find that stomatal constraints are less important, and instead shifts in leaf surface area and leaf properties drive changes in photosynthesis with rainfall.
Across the Amazon rainforest, trees take in carbon through photosynthesis. However,...
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