Increases in atmospheric CO2 have little influence on transpiration of a temperate forest canopy. Issue 2 (27th October 2014)

• Record Type: Journal Article
• Authors: Tor‐ngern, Pantana; Oren, Ram; Ward, Eric J.; Palmroth, Sari; McCarthy, Heather R.; Domec, Jean‐Christophe
• Is Part Of: New phytologist. Volume 205:Issue 2(2015)
• Page Start: 518
• Page End: 525
• Publication Date: 2014-10-27
• Subjects: canopy stomatal conductance -- elevated CO2 -- free‐air CO2 enrichment (FACE) -- Liquidambar styraciflua -- Pinus taeda -- transpiration; Botany -- Periodicals; 580
• DOI: 10.1111/nph.13148
• Languages: English
• ISSNs: 0028-646X

Abstract

Summary: Models of forest energy, water and carbon cycles assume decreased stomatal conductance with elevated atmospheric CO2 concentration ([CO2 ]) based on leaf‐scale measurements, a response not directly translatable to canopies. Where canopy–atmosphere are well‐coupled, [CO2 ]‐induced structural changes, such as increasing leaf‐area index ( L D ), may cause, or compensate for, reduced mean canopy stomatal conductance ( G S ), keeping transpiration ( E C ) and, hence, runoff unaltered. We investigated G S responses to increasing [CO2 ] of conifer and broadleaved trees in a temperate forest subjected to 17‐yr free‐air CO2 enrichment (FACE; + 200 μmol mol −1 ). During the final phase of the experiment, we employed step changes of [CO2 ] in four elevated‐[CO2 ] plots, separating direct response to changing [CO2 ] in the leaf‐internal air‐space from indirect effects of slow changes via leaf hydraulic adjustments and canopy development. Short‐term manipulations caused no direct response up to 1.8 × ambient [CO2 ], suggesting that the observed long‐term 21% reduction of G S was an indirect effect of decreased leaf hydraulic conductance and increased leaf shading. Thus, E C was unaffected by [CO2 ] because 19% higher canopy L D nullified the effect of leaf hydraulic acclimation on G S . We advocate long‐term experiments of duration sufficient for slow responses to manifest, and modifying models predicting forest water, energy and carbon cycles accordingly.