Publications
2026
- The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacityJ. Lamour, S. P. Serbin, A. Rogers, and 86 more authorsEarth System Science Data, 2026
- Improved model representation of the photosynthetic light reactions reduces estimates of global gross primary productivityJulien Lamour, Jérôme Chave, Jennifer Johnson, and 12 more authorsbioRxiv, 2026
The assimilation of carbon dioxide by plants can be predicted by the Farquhar, von Caemmerer and Berry model of photosynthesis. This largely mechanistic model is central to understanding how plants influence Earth’s climate. However, it represents the use of light by photosynthesis using an empirical formulation. Johnson and Berry proposed an alternative mechanistic formulation based on the functioning of the cytochrome b6f complex that includes key steps in light harvesting and electron transport. We compared both formulations using photosynthetic light response measurements from 146 C3 species spanning arctic to tropical biomes and implemented them in the terrestrial biosphere model ELM-FATES to simulate global photosynthesis. The Johnson and Berry formulation better fitted the measured response of leaf-level photosynthesis to light, and predicted lower photosynthetic rates at intermediate light levels, which decreased global estimations of terrestrial photosynthesis by 8%. Our findings support adopting the Johnson and Berry formulation to improve model representation of global carbon cycle modeling.Competing Interest StatementThe authors have declared no competing interest.U.S Department of energy, DE-AC02-05CH11231, DE-SC0012704
- The effect of relative humidity and temperature on the response of stomatal conductance to vapor pressure deficit in tropical treesJulien Lamour, Kenneth J Davidson, Jérôme Chave, and 3 more authorsTree Physiology, Jun 2026
Understanding how leaf gas exchange responds to changes in vapor pressure deficit (VPD) is key to predicting tropical forest resilience to climate change. Stomata regulate leaf water and CO2 diffusion, and respond to changes in temperature and relative humidity (RH), two drivers of VPD. At high temperatures, the cuticular pathway may also become significant and participate in the overall leaf conductance. Here, we measured gas exchange under light and dark conditions to investigate the stomatal and cuticular responses to temperature and RH on detached branches in five tropical tree species. Leaf conductance in the dark, when stomata are essentially closed, was not markedly impacted by temperature and RH, suggesting a minimal response of the cuticular pathway to these conditions. We compared six steady-state conductance models incorporating different effects of photosynthesis and evaporative demand on stomatal control. All models performed well (residual standard deviation, σ, < 0.025 mol m−2 s−1), but the best-fitting model (σ = 0.017 mol m−2 s−1) used a nonlinear relationship between photosynthesis and stomatal conductance and incorporated RH rather than vapor pressure difference. All models overestimated the steady-state conductance at high RH. Furthermore, leaf conductance immediately increased after a decrease in RH (wrong-way response), but not after an increase in leaf temperature. This suggests that the mechanisms underlying stomatal response to VPD need further investigation. The non-linear coupling between photosynthetic rate and stomatal conductance indicates a sharper physiological response than previously acknowledged.
- Amazon rainforests are rejuvenating their canopies by producing more photosynthetically efficient young leaves under climate changeXueqin Yang, Jie Tian, Philippe Ciais, and 34 more authorsNature Plants, Mar 2026
Leaf age structure strongly regulates canopy photosynthesis in Amazon rainforests yet its large-scale patterns and dynamics remain poorly understood. Here we map the fraction of leaf area of photosynthetically efficient young leaves (fyoung) using remote sensing data and assess its spatiotemporal variability from 2001 to 2023. We find that fyoung varies markedly with elevation and canopy height: tall or mountain forests (canopy >=32 m or elevation >=300 m) exhibit higher fyoung than short or lowland forests, reflecting higher leaf turnover driven by stronger radiation, greater atmospheric dryness and longer dry seasons. Across the basin, fyoung increased significantly in 85.2% of forests during 2001–2023, linked to decreasing precipitation, rising sunlight, intensifying atmospheric dryness and lengthening dry seasons. This widespread trend towards more juvenile leaves is projected to persist under future climate change. Our findings reveal a fundamental shift in Amazon leaf age structure and highlight its importance for predicting future photosynthetic responses in a warmer, drier climate.
- Leaf Elementomes Reveal Close Links With Leaf Water-Use Strategies Across Diverse Forest Ecosystems: Insights From Trait Coordination and Reflectance SpectroscopyNan Yang, Fengqi Wu, Lawren Sack, and 17 more authorsPlant, Cell & Environment, Mar 2026
ABSTRACT Leaf intrinsic water use efficiency (iWUE) quantifies the trade-off between carbon assimilation and water loss in plants, and is constrained by leaf traits such as maximum carboxylation capacity (Vc,max) and stomatal conductance. Yet, the potential links of iWUE with leaf elementomes across different forest types remain unclear. Here, we analyzed iWUE (estimated by leaf carbon isotopes) variability and its associations with Vc,max, stomatal conductance (estimated by 18O enrichment in leaf dry matter above source water, Δ18O), and leaf elementomes across 82 tree species from temperate, subtropical and tropical forests, and evaluated the effectiveness of leaf reflectance spectroscopy as an indicator of iWUE variability and trait–iWUE associations. Across species, Vc,max, Δ18O, leaf mass per area (LMA) and leaf iron, nitrogen, sodium and manganese concentrations were the traits most strongly associated with cross-site iWUE variability. Furthermore, climatic factors (mean annual precipitation, mean annual temperature and climate moisture index) shaped trait–iWUE covariation by negatively linking leaf elements and positively with LMA, which affected iWUE more directly than indirectly via Vc,max and Δ18O. Leaf reflectance spectroscopy accurately predicted iWUE (R2 = 0.83), and the trait–iWUE relationships derived from spectral modelling were consistent with those obtained through field measurements. These findings reveal strong linkages between the leaf elementomes and iWUE, and highlight the potential of reflectance spectroscopy for characterizing iWUE variability and trait–iWUE relationships, thereby improving process modelling of forest carbon and water cycles.
2025
- Linking leaf dark respiration to leaf traits and reflectance spectroscopy across diverse forest typesFengqi Wu, Shuwen Liu, Julien Lamour, and 20 more authorsNew Phytologist, Apr 2025Publisher: John Wiley & Sons, Ltd
Leaf dark respiration (Rdark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (Vcmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed. Here, we analyzed Rdark variability and its associations with Vcmax and other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative. We found that leaf magnesium and calcium concentrations were more significant in explaining cross-site Rdark than commonly used traits like LMA, N and P concentrations, but univariate trait?Rdark relationships were always weak (r2?≤?0.15) and forest-specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait?Rdark relationships, accurately predicted cross-site Rdark (r2?=?0.65) and pinpointed the factors contributing to Rdark variability. Our findings reveal a few novel traits with greater cross-site scalability regarding Rdark, challenging the use of empirical trait?Rdark relationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimating Rdark, which could ultimately improve process modeling of terrestrial plant respiration.
- Vertical canopy gradients of respiration drive plant carbon budgets and leaf area indexJessica F. Needham, Sharmila Dey, Charles D. Koven, and 7 more authorsNew Phytologist, Apr 2025Publisher: John Wiley & Sons, Ltd
Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model???Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (Rdark). We ran global and point simulations varying the canopy gradient of Rdark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of Rdark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of Rdark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in Rdark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.
- Constraining Light-Driven Plasticity in Leaf Traits With Observations Improves the Prediction of Tropical Forest Demography, Structure, and Biomass DynamicsYixin Ma, Paul R. Moorcroft, S. Joseph Wright, and 6 more authorsJournal of Geophysical Research: Biogeosciences, Jun 2025Publisher: John Wiley & Sons, Ltd
Predicting tropical tree demography is a key challenge in understanding the future dynamics of tropical forests. Although demographic processes are known to be regulated by leaf trait diversity, only the effect of inter-specific trait variation has been evaluated, and it remains unclear as to what degree the intra-specific trait plasticity across light gradients (hereafter light plasticity) regulates tree demography, and how this will further shape long-term community and ecosystem dynamics. By combining in situ trait measurements and forest census data with a terrestrial biosphere model, we evaluated the impact of observation-constrained light plasticity on demography, forest structure, and biomass dynamics in a Panamanian tropical moist forest. Modeled leaf physiological traits vary across and within plant functional types (PFT), which represent the inter-specific trait variation and the intra-specific light plasticity, respectively. The simulation using three non-plastic PFTs underestimated 20-year average understory growth rates by 41%, leading to a biased forest size structure and leaf area profile, and a 44% underestimate in long-term biomass. The simulation using three plastic PFTs generated accurate understory growth rates, resulting in a realistic forest structure and a smaller biomass underestimate of 15%. Expanding simulated trait diversity using 18 nonplastic PFTs similarly improved the prediction of demography and biomass. However, only the plasticity-enabled model predicted realistic long-term PFT composition and within-canopy trait profiles. Our results highlight the distinct role of light plasticity in regulating forest dynamics that cannot be replaced by inter-specific trait diversity. Accurately representing light plasticity is thus crucial for trait-based prediction of tropical forest dynamics.
- Deciphering the variability of leaf phosphorus-allocation strategies using leaf economic traits and reflectance spectroscopy across diverse forest typesTingting Dong, Fengqi Wu, Yuki Tsujii, and 23 more authorsNew Phytologist, May 2025Publisher: John Wiley & Sons, Ltd
Allocation of leaf phosphorus (P) among different functional fractions represents a crucial adaptive strategy for optimizing P use. However, it remains challenging to monitor the variability in leaf P fractions and, ultimately, to understand P-use strategies across diverse plant communities. We explored relationships between five leaf P fractions (orthophosphate P, Pi; lipid P, PL; nucleic acid P, PN; metabolite P, PM; and residual P, PR) and 11 leaf economic traits of 58 woody species from three biomes in China, including temperate, subtropical and tropical forests. Then, we developed trait-based models and spectral models for leaf P fractions and compared their predictive abilities. We found that plants exhibiting conservative strategies increased the proportions of PN and PM, but decreased the proportions of Pi and PL, thus enhancing photosynthetic P-use efficiency, especially under P limitation. Spectral models outperformed trait-based models in predicting cross-site leaf P fractions, regardless of concentrations (R2?=?0.50?0.88 vs 0.34?0.74) or proportions (R2?=?0.43?0.70 vs 0.06?0.45). These findings enhance our understanding of leaf P-allocation strategies and highlight reflectance spectroscopy as a promising alternative for characterizing large-scale leaf P fractions and plant P-use strategies, which could ultimately improve the physiological representation of the plant P cycle in land surface models.
2023
- The effect of the vertical gradients of photosynthetic parameters on the CO2 assimilation and transpiration of a Panamanian tropical forestJulien Lamour, Kenneth J. Davidson, Kim S. Ely, and 9 more authorsNew Phytologist, Jun 2023Publisher: John Wiley & Sons, Ltd
Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy-scale CO2 and water fluxes. Comparison between observed and TBM trait gradients showed divergence that impacted canopy-scale simulations of water vapor and CO2 exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top-of-canopy, leaf-level water-use efficiency was markedly higher at the top-of-canopy, and the decrease in maximum carboxylation rate from the top-of-canopy to the ground was less than TBM assumptions. The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within-individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species-rich, complex tropical forests.
- Short-term variation in leaf-level water use efficiency in a tropical forestKenneth J. Davidson, Julien Lamour, Alistair Rogers, and 8 more authorsNew Phytologist, Mar 2023Publisher: John Wiley & Sons, Ltd
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.
- Seasonal trends in leaf-level photosynthetic capacity and water use efficiency in a North American Eastern deciduous forest and their impact on canopy-scale gas exchangeKenneth J. Davidson, Julien Lamour, Anna McPherran, and 2 more authorsNew Phytologist, Oct 2023Publisher: John Wiley & Sons, Ltd
Vegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems. We investigated seasonal patterns in leaf-level physiological, hydraulic, and anatomical properties, including the seasonal progress of the stomatal slope parameter (g1; inversely proportional to WUE) and the maximum carboxylation rate (Vcmax). Vcmax and g1 were seasonally variable; however, their patterns were not temporally synchronized. g1 generally showed an increasing trend until late in the season, while Vcmax peaked during the midsummer months. Seasonal progression of Vcmax was primarily driven by changes in leaf structural, and anatomical characteristics, while seasonal changes in g1 were most strongly related to changes in Vcmax and leaf hydraulics. Using a seasonally variable Vcmax and g1 to parameterize a canopy-scale gas exchange model increased seasonally aggregated A and E by 3% and 16%, respectively.
- Wood-density has no effect on stomatal control of leaf-level water use efficiency in an Amazonian forestJulien Lamour, Daisy C. Souza, Bruno O. Gimenez, and 4 more authorsPlant, Cell & Environment, Dec 2023Publisher: John Wiley & Sons, Ltd
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.
2022
- Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)Q. Li, S. P. Serbin, J. Lamour, and 3 more authorsGeoscientific Model Development, Dec 2022
Stomata play a central role in regulating the exchange of carbon dioxide and water vapor between ecosystems and the atmosphere. Their function is represented in land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and physiological dynamics. To evaluate the effect of stomatal conductance model formulation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model – the Medlyn (MED) model – that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball–Woodrow–Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to climate forcing, including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit in the air (VPDa). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the stomatal intercept parameter (g0) constant for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPDa exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal changes of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Comparison of modeled soil water content from FATES to a reanalysis product showed that FATES captured soil drying well, but translation of drying soil to modeled physiology reduced the models’ ability to match observations. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.
- An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness-of-fit across diverse data setsJulien Lamour, Kenneth J. Davidson, Kim S. Ely, and 5 more authorsGlobal Change Biology, Jun 2022
Stomata play a central role in surface atmosphere exchange by controlling the flux of water and CO2 between the leaf and the atmosphere. Representation of stomatal conductance (gsw) is therefore an essential component of models that seek to simulate water and CO2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between gsw and photosynthetic CO2 assimilation (A). However, measurement of leaf-level gsw response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of gsw and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between gsw and A was not linear, challenging the key assumption upon which optimality theory is based that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in gsw at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g0 and g1. Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g1 and other leaf traits. We also observed nonlinear behavior between A and gsw in independent data sets that included data collected from attached and detached leaves, and from plants grown at elevated CO2 concentration. We propose that this empirical modification of the USO model can improve the measurement of gsw parameters and the estimation of plant and ecosystem-scale water and CO2 fluxes.
- New calculations for photosynthesis measurement systems: what’s the impact for physiologists and modelers?Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and 3 more authorsNew Phytologist, Jan 2022Publisher: John Wiley & Sons, Ltd
- Late-day measurement of excised branches results in uncertainty in the estimation of two stomatal parameters derived from response curves in Populus deltoides Bartr. × Populus nigra L.Kenneth J Davidson, Julien Lamour, Alistair Rogers, and 1 more authorTree Physiology, Jul 2022
Many terrestrial biosphere models depend on an understanding of the relationship between stomatal conductance and photosynthesis. However, unlike the measurement of photosynthetic parameters, such as the maximum carboxylation capacity, where standard methods (e.g., CO2 response or ACi curves) are widely accepted, a consensus method for empirically measuring parameters representing stomatal response has not yet emerged. Most models of stomatal response to environment represent stomatal conductance as being bounded by a lower intercept parameter (g0), and linearly scaled based on a multivariate term described by the stomatal slope parameter (g1). Here we employ the widely used Unified Stomatal Optimization model, to test whether g1 and g0 parameters are impacted by the choice of measurement method, either on an intact branch or a cut branch segment stored in water. We measured paired stomatal response curves on intact and excised branches of a hybrid poplar clone (Populus deltoides Bartr. × Populus nigra L. OP367), measured twice over a diurnal period. We found that predawn branch excision did not significantly affect measured g0 and g1 when measured within 4 h of excision. Measurement in the afternoon resulted in significantly higher values of g1 and lower values of g0, with values changing by 55% and 56%, respectively. Excision combined with afternoon measurement resulted in a marked effect on parameter estimates, with g1 increasing 89% from morning to afternoon and a 25% lower g1 for cut branches than those measured in situ. We also show that in hybrid poplar the differences in parameter estimates obtained from plants measured under different conditions can directly impact models of canopy function, reducing modeled transpiration by 18% over a simulated 12.5-h period. Although these results are only for a single isohydric woody species, our findings suggest that stomatal optimality parameters may not remain constant throughout the day.
- Remote sensing from unoccupied aerial systems: Opportunities to enhance Arctic plant ecology in a changing climateDedi Yang, Bailey D. Morrison, Kenneth J. Davidson, and 11 more authorsJournal of Ecology, Dec 2022Publisher: John Wiley & Sons, Ltd
Improved ecological understanding and model representation of arctic vegetation is needed to forecast the fate of the Arctic in a rapidly changing climate. Observations from UASs provide an approach to address this need, however, the use of this technology in the Arctic currently remains limited. Here we share recommendations to better enable and encourage the use of UASs to improve the description, scaling and model representation of arctic vegetation.
2021
- Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopyJulien Lamour, Kenneth J. Davidson, Kim S. Ely, and 4 more authorsPLOS ONE, Oct 2021
Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration (Rdark25), the maximum rate of carboxylation by the enzyme Rubisco (Vcmax25), the maximum rate of electron transport (Jmax25), and the triose phosphate utilization rate (Tp25), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for Vcmax25, Jmax25, Tp25 and Rdark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m-2 s-1, and R2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.
- A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regressionAngela C Burnett, Jeremiah Anderson, Kenneth J Davidson, and 7 more authorsJournal of Experimental Botany, Sep 2021
Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. We provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.
- A reporting format for leaf-level gas exchange data and metadataKim S. Ely, Alistair Rogers, Deborah A. Agarwal, and 79 more authorsEcological Informatics, Mar 2021
Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy’s ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.
- Seasonal trends in photosynthesis and leaf traits in scarlet oakAngela C Burnett, Shawn P Serbin, Julien Lamour, and 4 more authorsTree Physiology, Aug 2021
Understanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.e., at the time of peak photoperiod. Contrary to expectations, our results reveal a late-season peak in both photosynthetic capacity and rate before the expected sharp decrease at the start of senescence. This late-season maximum occurred after the higher summer temperatures and vapor pressure deficit and was correlated with the recovery of leaf water content and increased stomatal conductance. We modeled photosynthesis at the top of the canopy and found that the simulated results closely tracked the maximum carboxylation capacity of Rubisco. For both photosynthetic capacity and modeled top-of-canopy photosynthesis, the maximum value was therefore not observed at the summer solstice. Rather, in each case, the measurements at and around the solstice were close to the overall seasonal mean, with values later in the season leading to deviations from the mean by up to 41 and 52%, respectively. Overall, we found that the expected Gaussian pattern of photosynthesis was not observed. We conclude that an understanding of species- and environment-specific changes in photosynthesis across the season is essential for correct estimation of seasonal photosynthetic capacity.