New calculations for photosynthesis measurement systems: what's the impact for physiologists and modelers?

Lamour, Julien; Davidson, Kenneth; Ely, Kim; Li, Qianyu; Serbin, Shawn P.; Rogers, Alistair

doi:10.1111/nph.17762

Cited by 10 publications

(16 citation statements)

References 31 publications

(51 reference statements)

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“…The minimum conductance in leaves ( g sw,dark ) is assumed to be caused by imperfectly closed stomata as well as non‐negligible cuticular conductance (Duursma et al, 2019; Lamour et al, 2022b; Márquez et al, 2021; Slot et al, 2021) and may be a key trait for explaining plant vulnerability to drought in addition to other traits such as the xylem vulnerability to cavitation, leaf deciduousness, or nonstructural carbohydrate storage (Choat et al, 2018; Cochard, 2021; Maréchaux et al, 2015; Martin‐StPaul et al, 2017; McDowell et al, 2018; O'Brien et al, 2014). LWD and HWD species had similar g sw,dark in this forest.…”

Section: Discussionmentioning

confidence: 99%

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Lamour,

Souza,

Gimenez

et al. 2023

Plant Cell & Environment

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Forest disturbances increase the proportion of fast‐growing tree species compared to slow‐growing ones. To understand their relative capacity for carbon uptake and their vulnerability to climate change, and to represent those differences in Earth system models, it is necessary to characterise the physiological differences in their leaf‐level control of water use efficiency and carbon assimilation. We used wood density as a proxy for the fast‐slow growth spectrum and tested the assumption that trees with a low wood density (LWD) have a lower water‐use efficiency than trees with a high wood density (HWD). We selected 5 LWD tree species and 5 HWD tree species growing in the same location in an Amazonian tropical forest and measured in situ steady‐state gas exchange on top‐of‐canopy leaves with parallel sampling and measurement of leaf mass area and leaf nitrogen content. We found that LWD species invested more nitrogen in photosynthetic capacity than HWD species, had higher photosynthetic rates and higher stomatal conductance. However, contrary to expectations, we showed that the stomatal control of the balance between transpiration and carbon assimilation was similar in LWD and HWD species and that they had the same dark respiration rates.

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Section: Discussionmentioning

confidence: 99%

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Lamour,

Souza,

Gimenez

et al. 2023

Plant Cell & Environment

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“…The parameters g 1 and g 0 are mathematically identical in Eqns 1, 2 (Lamour et al ., 2022b); however, Eqn 2 provides for simpler graphical depiction of the data. Eqn 2 also uses C a in place of C s , as when using gas exchange systems, the terms are very similar (Lamour et al ., 2022c).

g_{normals} - \frac{1.6 \times A}{C_{a}} = g_{0} + g_{1} \times \frac{1.6 \times A}{()(, \sqrt{D} goodbreak\times C_{a})} .

…”

Section: Methodsmentioning

confidence: 99%

Short‐term variation in leaf‐level water use efficiency in a tropical forest

et al. 2023

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Summary The representation of stomatal regulation of transpiration and CO2 assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (gs) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g1 (stomatal slope, inversely proportional to water use efficiency) and g0 (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf‐level response curves of six tropical broadleaf evergreen tree species. g1 estimated from ex situ response curves averaged 50% less than g1 estimated from survey data. While g0 and g1 varied between leaves of different phenological stages, the trend was not consistent among species. We identified a diurnal trend associated with g1 and g0 that significantly improved model projections of diurnal trends in transpiration. The accuracy of modeled gs can be improved by accounting for variation in stomatal behavior across diurnal periods, and between measurement approaches, rather than focusing on phenological variation in stomatal behavior. Additional investigation into the primary mechanisms responsible for diurnal variation in g1 will be required to account for this phenomenon in land‐surface models.

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“…The impact on c i calculations of neglecting cuticular fluxes using von Caemmerer & Farquhar (1981) equations has been discussed in previous studies (Boyer et al ., 1997; Boyer, 2015; Hanson et al ., 2016; Lamour et al ., 2021; Márquez et al ., 2021a,b). Márquez et al .…”

Section: Methodsmentioning

confidence: 99%

“…The impact on c i calculations of neglecting cuticular fluxes using von Caemmerer & Farquhar (1981) equations has been discussed in previous studies (Boyer et al, 1997;Boyer, 2015;Hanson et al, 2016;Lamour et al, 2021;Márquez et al, 2021a,b). Márquez et al (2021a) equations (MSF) include the cuticular conductance from the outset of the derivation, so MSF equations are used for the main analyses here.…”

Section: Calculation Of C Imentioning

confidence: 99%

Assessing the CO₂ concentration at the surface of photosynthetic mesophyll cells

et al. 2023

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We present a robust estimation of the CO 2 concentration at the surface of photosynthetic mesophyll cells (c w ), applicable under reasonable assumptions of assimilation distribution within the leaf. We used Capsicum annuum, Helianthus annuus and Gossypium hirsutumas model plants for our experiments.We introduce calculations to estimate c w using independent adaxial and abaxial gas exchange measurements, and accounting for the mesophyll airspace resistances.The c w was lower than adaxial and abaxial estimated intercellular CO 2 concentrations (c i ). Differences between c w and the c i of each surface were usually larger than 10 μmol mol −1 . Differences between adaxial and abaxial c i ranged from a few μmol mol −1 to almost 50 μmol mol −1 , where the largest differences were found at high air saturation deficits (ASD). Differences between adaxial and abaxial c i and the c i estimated by mixing both fluxes ranged from −30 to +20 μmol mol −1 , where the largest differences were found under high ASD or high ambient CO 2 concentrations.Accounting for c w improves the information that can be extracted from gas exchange experiments, allowing a more detailed description of the CO 2 and water vapor gradients within the leaf.

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New calculations for photosynthesis measurement systems: what's the impact for physiologists and modelers?

Cited by 10 publications

References 31 publications

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Short‐term variation in leaf‐level water use efficiency in a tropical forest

Assessing the CO₂ concentration at the surface of photosynthetic mesophyll cells

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New calculations for photosynthesis measurement systems: what's the impact for physiologists and modelers?

Cited by 10 publications

References 31 publications

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Wood‐density has no effect on stomatal control of leaf‐level water use efficiency in an Amazonian forest

Short‐term variation in leaf‐level water use efficiency in a tropical forest

Assessing the CO2 concentration at the surface of photosynthetic mesophyll cells

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Assessing the CO₂ concentration at the surface of photosynthetic mesophyll cells