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A meta-analysis of mesophyll conductance to CO2 in relation to major abiotic stresses in poplar species.

Raed ElferjaniLahcen BenomarMina MomayyeziRoberto TognettiÜlo NiinemetsRaju Y SoolanayakanahallyGuillaume Théroux-RancourtTiina TosensFrancesco RipulloneSimon Bilodeau-GauthierMohammed S LamhamediCarlo CalfapietraMebarek Lamara
Published in: Journal of experimental botany (2021)
Mesophyll conductance (gm) determines the diffusion of CO2 from the substomatal cavities to the site of carboxylation in the chloroplasts and represents a critical component of the diffusive limitation of photosynthesis. In this study, we evaluated the average effect sizes of different environmental constraints on gm in Populus spp., a forest tree model. We collected raw data of 815 A-Ci response curves from 26 datasets to estimate gm, using a single curve-fitting method to alleviate method-related bias. We performed a meta-analysis to assess the effects of different abiotic stresses on gm. We found a significant increase in gm from the bottom to the top of the canopy that was concomitant with the increase of maximum rate of carboxylation and light-saturated photosynthetic rate (Amax). gm was positively associated with increases in soil moisture and nutrient availability, but was insensitive to increasing soil copper concentration and did not vary with atmospheric CO2 concentration. Our results showed that gm was strongly related to Amax and to a lesser extent to stomatal conductance (gs). Moreover, a negative exponential relationship was obtained between gm and specific leaf area, which may be used to scale-up gm within the canopy.
Keyphrases
  • climate change
  • machine learning
  • deep learning
  • single cell