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Data from: Age‐dependent leaf physiology and consequences for crown‐scale carbon uptake during the dry season in an Amazon evergreen forest

Albert, Loren P.; Wu, Jin; Prohaska, Neill; de Camargo, Plinio Barbosa; Huxman, Travis E.; Tribuzy, Edgard S.; Ivanov, Valeriy Y.; Oliveira, Rafael S.; Garcia, Sabrina; Smith, Marielle N.; Oliveira Junior, Raimundo Cosme; Restrepo-Coupe, Natalia; da Silva, Rodrigo; Stark, Scott C.; Martins, Giordane A.; Penha, Deliane V.; Saleska, Scott R.

* Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. * We conducted demographic surveys of leaf age composition, and measured age-dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used this data to independently test the much-debated hypothesis—arising from satellite and tower-based observations—that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. * Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. * These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interaction between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests.

Funding provided by: National Science Foundation
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001
Award Number: OISE-0730305

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