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Knauer J, Cuntz M, Smith B, Canadell JG, Medlyn BE, Bennett AC, Caldararu S, Haverd V. Higher global gross primary productivity under future climate with more advanced representations of photosynthesis. SCIENCE ADVANCES 2023; 9:eadh9444. [PMID: 37976364 PMCID: PMC10656065 DOI: 10.1126/sciadv.adh9444] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/17/2023] [Indexed: 11/19/2023]
Abstract
Gross primary productivity (GPP) is the key determinant of land carbon uptake, but its representation in terrestrial biosphere models (TBMs) does not reflect our latest physiological understanding. We implemented three empirically well supported but often omitted mechanisms into the TBM CABLE-POP: photosynthetic temperature acclimation, explicit mesophyll conductance, and photosynthetic optimization through redistribution of leaf nitrogen. We used the RCP8.5 climate scenario to conduct factorial model simulations characterizing the individual and combined effects of the three mechanisms on projections of GPP. Simulated global GPP increased more strongly (up to 20% by 2070-2099) in more comprehensive representations of photosynthesis compared to the model lacking the three mechanisms. The experiments revealed non-additive interactions among the mechanisms as combined effects were stronger than the sum of the individual effects. The modeled responses are explained by changes in the photosynthetic sensitivity to temperature and CO2 caused by the added mechanisms. Our results suggest that current TBMs underestimate GPP responses to future CO2 and climate conditions.
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Affiliation(s)
- Jürgen Knauer
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
- CSIRO Environment, Canberra, ACT, Australia
| | - Matthias Cuntz
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, Nancy, France
| | - Benjamin Smith
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
| | | | - Belinda E. Medlyn
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
| | - Alison C. Bennett
- School of Ecosystem and Forest Science, University of Melbourne, Richmond, VIC, Australia
| | - Silvia Caldararu
- Botany, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland
- iCRAG SFI Research Centre in Applied Geosciences
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Sun Y, Gu L, Wen J, van der Tol C, Porcar-Castell A, Joiner J, Chang CY, Magney T, Wang L, Hu L, Rascher U, Zarco-Tejada P, Barrett CB, Lai J, Han J, Luo Z. From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I-Harnessing theory. GLOBAL CHANGE BIOLOGY 2023; 29:2926-2952. [PMID: 36799496 DOI: 10.1111/gcb.16634] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 11/08/2022] [Indexed: 05/03/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question-How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.
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Affiliation(s)
- Ying Sun
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Christiaan van der Tol
- Affiliation Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - Albert Porcar-Castell
- Optics of Photosynthesis Laboratory, Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, Viikki Plant Science Center (ViPS), University of Helsinki, Helsinki, Finland
| | - Joanna Joiner
- National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, Maryland, USA
| | - Christine Y Chang
- US Department of Agriculture, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, Maryland, USA
| | - Troy Magney
- Department of Plant Sciences, University of California, Davis, Davis, California, USA
| | - Lixin Wang
- Department of Earth Sciences, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, Indiana, USA
| | - Leiqiu Hu
- Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, Alabama, USA
| | - Uwe Rascher
- Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Pablo Zarco-Tejada
- School of Agriculture and Food (SAF-FVAS) and Faculty of Engineering and Information Technology (IE-FEIT), University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher B Barrett
- Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, New York, USA
| | - Jiameng Lai
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Jimei Han
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Zhenqi Luo
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
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Bugmann H, Seidl R. The evolution, complexity and diversity of models of long-term forest dynamics. THE JOURNAL OF ECOLOGY 2022; 110:2288-2307. [PMID: 36632361 PMCID: PMC9826524 DOI: 10.1111/1365-2745.13989] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 08/01/2022] [Indexed: 06/17/2023]
Abstract
To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies.We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis.Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes.Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the 'prevailing spirit of the epoch'. The lack of firm theories, laws and 'first principles' in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity-with the exception of global models-can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking.
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Affiliation(s)
- Harald Bugmann
- Forest Ecology, Institute of Terrestrial Ecosystems, Department of Environmental Systems ScienceETH ZurichZürichSwitzerland
- Ecosystem Dynamics and Forest ManagementTechnical University of MunichFreisingGermany
| | - Rupert Seidl
- Ecosystem Dynamics and Forest ManagementTechnical University of MunichFreisingGermany
- Berchtesgaden National ParkBerchtesgadenGermany
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Davidson KJ, Lamour J, Rogers A, Serbin SP. 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. TREE PHYSIOLOGY 2022; 42:1377-1395. [PMID: 35134232 DOI: 10.1093/treephys/tpac006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 01/17/2022] [Indexed: 06/14/2023]
Abstract
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.
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Affiliation(s)
- Kenneth J Davidson
- Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, NY 11973, USA
- Department of Ecology and Evolution, Stony Brook University, 650 Life Sciences Building, Stony Brook, NY 11794, USA
| | - Julien Lamour
- Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Alistair Rogers
- Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Shawn P Serbin
- Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, NY 11973, USA
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Mathematical Modeling to Estimate Photosynthesis: A State of the Art. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Photosynthesis is a process that indicates the productivity of crops. The estimation of this variable can be achieved through methods based on mathematical models. Mathematical models are usually classified as empirical, mechanistic, and hybrid. To mathematically model photosynthesis, it is essential to know: the input/output variables and their units; the modeling to be used based on its classification (empirical, mechanistic, or hybrid); existing measurement methods and their invasiveness; the validation shapes and the plant species required for experimentation. Until now, a collection of such information in a single reference has not been found in the literature, so the objective of this manuscript is to analyze the most relevant mathematical models for the photosynthesis estimation and discuss their formulation, complexity, validation, number of samples, units of the input/output variables, and invasiveness in the estimation method. According to the state of the art reviewed here, 67% of the photosynthesis measurement models are mechanistic, 13% are empirical and 20% hybrid. These models estimate gross photosynthesis, net photosynthesis, photosynthesis rate, biomass, or carbon assimilation. Therefore, this review provides an update on the state of research and mathematical modeling of photosynthesis.
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Han J, Chang CYY, Gu L, Zhang Y, Meeker EW, Magney TS, Walker AP, Wen J, Kira O, McNaull S, Sun Y. The physiological basis for estimating photosynthesis from Chla fluorescence. THE NEW PHYTOLOGIST 2022; 234:1206-1219. [PMID: 35181903 DOI: 10.1111/nph.18045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/09/2022] [Indexed: 06/14/2023]
Abstract
Solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIFPSII ) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level. The MLR-SIF model is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIFPSII . Once inferred from direct observables of SIF, SIFPSII provides 'parameter savings' to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.
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Affiliation(s)
- Jimei Han
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
| | - Christine Y-Y Chang
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
- USDA, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, MD, 20705, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Yongjiang Zhang
- School of Biology and Ecology, University of Maine, Orono, ME, 04469, USA
| | - Eliot W Meeker
- Department of Chemical Engineering, University of California, Davis, CA, 95616, USA
| | - Troy S Magney
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
| | - Anthony P Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
| | - Oz Kira
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
- Department of Civil and Environmental Engineering, Ben-Gurion University of the Negev, Negev, 8410501, Israel
| | - Sarah McNaull
- Cornell Botanic Gardens, Cornell University, Ithaca, NY, 14850, USA
| | - Ying Sun
- School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA
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Han J, Gu L, Wen J, Sun Y. Inference of photosynthetic capacity parameters from chlorophyll a fluorescence is affected by redox state of PSII reaction centers. PLANT, CELL & ENVIRONMENT 2022; 45:1298-1314. [PMID: 35098552 DOI: 10.1111/pce.14271] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) has been used to infer photosynthetic capacity parameters (e.g., the maximum carboxylation rate Vcmax , and the maximum electron transport rate Jmax ). However, the precise mechanism and practical utility of such approach under dynamic environments remain unclear. We used the balance between the light and carbon reactions to derive theoretical equations relating chlorophyll a fluorescence (ChlF) emission and photosynthetic capacity parameters, and formulated testable hypotheses regarding the dynamic relationships between the true total ChlF emitted from PSII (SIFPSII ) and Vcmax and Jmax . We employed concurrent measurements of gas exchanges and ChlF parameters for 15 species from six biomes to test the formulated hypotheses across species, temperatures, and limitation state of carboxylation. Our results revealed that SIFPSII alone is incapable of informing the variations in Vcmax and Jmax across species, even when SIFPSII is determined under the same environmental conditions. In contrast, the product of SIFPSII and the fraction of open PSII reactions qL , which indicates the redox state of PSII, is a strong predictor of both Vcmax and Jmax , although their precise relationships vary somewhat with environmental conditions. Our findings suggest the redox state of PSII strongly influences the relationship between SIFPSII and Vcmax and Jmax .
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Affiliation(s)
- Jimei Han
- College of Agriculture and Life Sciences, School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, New York, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Jiaming Wen
- College of Agriculture and Life Sciences, School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, New York, USA
| | - Ying Sun
- College of Agriculture and Life Sciences, School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, New York, USA
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Lamour J, Davidson KJ, Ely KS, Li Q, Serbin SP, Rogers A. New calculations for photosynthesis measurement systems: what's the impact for physiologists and modelers? THE NEW PHYTOLOGIST 2022; 233:592-598. [PMID: 34605019 DOI: 10.1111/nph.17762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 09/13/2021] [Accepted: 09/19/2021] [Indexed: 06/13/2023]
Affiliation(s)
- Julien Lamour
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Kenneth J Davidson
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11794-5245, USA
| | - Kim S Ely
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Qianyu Li
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Shawn P Serbin
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Alistair Rogers
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
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9
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Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy. PLoS One 2021; 16:e0258791. [PMID: 34665822 PMCID: PMC8525780 DOI: 10.1371/journal.pone.0258791] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 10/06/2021] [Indexed: 11/20/2022] Open
Abstract
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.
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Stinziano JR, Roback C, Sargent D, Murphy BK, Hudson PJ, Muir CD. Principles of resilient coding for plant ecophysiologists. AOB PLANTS 2021; 13:plab059. [PMID: 34646435 PMCID: PMC8501907 DOI: 10.1093/aobpla/plab059] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 09/15/2021] [Indexed: 06/02/2023]
Abstract
Plant ecophysiology is founded on a rich body of physical and chemical theory, but it is challenging to connect theory with data in unambiguous, analytically rigorous and reproducible ways. Custom scripts written in computer programming languages (coding) enable plant ecophysiologists to model plant processes and fit models to data reproducibly using advanced statistical techniques. Since many ecophysiologists lack formal programming education, we have yet to adopt a unified set of coding principles and standards that could make coding easier to learn, use and modify. We identify eight principles to help in plant ecophysiologists without much programming experience to write resilient code: (i) standardized nomenclature, (ii) consistency in style, (iii) increased modularity/extensibility for easier editing and understanding, (iv) code scalability for application to large data sets, (v) documented contingencies for code maintenance, (vi) documentation to facilitate user understanding; (vii) extensive tutorials and (viii) unit testing and benchmarking. We illustrate these principles using a new R package, {photosynthesis}, which provides a set of analytical and simulation tools for plant ecophysiology. Our goal with these principles is to advance scientific discovery in plant ecophysiology by making it easier to use code for simulation and data analysis, reproduce results and rapidly incorporate new biological understanding and analytical tools.
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Affiliation(s)
- Jospeh R Stinziano
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Cassaundra Roback
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Demi Sargent
- Hawkesbury Institute for the Environment, Western Sydney University, Sydney 2753, Australia
| | - Bridget K Murphy
- Department of Biology, University of Toronto, Mississauga L5L 1C6, Canada
| | - Patrick J Hudson
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
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11
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Rogers A, Kumarathunge DP, Lombardozzi DL, Medlyn BE, Serbin SP, Walker AP. Triose phosphate utilization limitation: an unnecessary complexity in terrestrial biosphere model representation of photosynthesis. THE NEW PHYTOLOGIST 2021; 230:17-22. [PMID: 33217768 DOI: 10.1111/nph.17092] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 11/15/2020] [Indexed: 06/11/2023]
Affiliation(s)
- Alistair Rogers
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Dushan P Kumarathunge
- Plant Physiology Division, Coconut Research Institute of Sri Lanka, Lunuwila, 61150, Sri Lanka
| | - Danica L Lombardozzi
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, 80307-3000, USA
| | - Belinda E Medlyn
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1791, Penrith, NSW, 2751, Australia
| | - Shawn P Serbin
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA
| | - Anthony P Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831-6301, USA
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12
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Huntingford C, Oliver RJ. Converging towards a common representation of large-scale photosynthesis. GLOBAL CHANGE BIOLOGY 2021; 27:716-718. [PMID: 33064919 DOI: 10.1111/gcb.15398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 09/28/2020] [Indexed: 06/11/2023]
Abstract
Much ecological research has focused on determining how different environmental factors limit photosynthesis. Far less attention is placed on how to model the transition between limitations accurately as drivers change. Whether such changes are modelled as a single switch or there is an intermediate period of co-limitation can have a substantial impact on the estimated levels of photosynthesis.
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