Fluctuations of CO2 in Free-Air CO2 Enrichment (FACE) depress plant photosynthesis, growth, and yield

Allen, L. H.; Kimball, Bruce A.; Bunce, James A.; Yoshimoto, Mayumi; Harazono, Yoshinobu; Baker, Jeffrey T.; Boote, Kenneth J.; White, Jeffrey W.

doi:10.1016/j.agrformet.2020.107899

Cited by 67 publications

(66 citation statements)

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“…The low (bounded) value of the fluctuations is the ambient CO 2 concentration. The high (unbounded) values of the fluctuations were more than twice the enrichment setpoint CO 2 concentration above the ambient CO 2 concentration ( Figure 1A and Allen et al, 2020;Bunce, 2011;Hendrey, Ellsworth, Lewin, & Nagy, 1999;Hendrey & Miglietta, 2006;Okada et al, 2001). These wide fluctuations are a consequence of natural turbulence near the crop Hour of day F I G U R E 2 Example of SPAR chamber control to setpoint CO 2 concentration of 700 ppm (black line) and 350 ppm (blue line) recorded at 5-min intervals at Gainesville, FL, on 5 Sept. 1994 at 52 d after sowing of rice (Oryza sativa L. 'IR-72').…”

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 92%

“…Desjardins, Allen, and Lemon (1978) found that means and standard deviations of CO 2 concentration within a maize (Zea mays L.) canopy near midday ranged from 309.0 ± 2.4 ppm to 302.4 ± 5.3 ppm. Fluctuations of CO 2 concentration in FACE plots ( Figure 1A) are much larger than in control plots ( Figure 1B) (Allen et al, 2020). The FACE plot at Maricopa, AZ, had a CO 2 concentration standard deviation (SD) of 109 ppm ( Figure 1A) whereas the unenriched control plot had a CO 2 concentration SD of 11 ppm ( Figure 1B).…”

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 94%

“…They reported FACE studies with a mean yield response ratio of 1.14 for average ambient and average elevated CO 2 concentration of 367 and 583 ppm, respectively, whereas enclosure studies with steady CO 2 concentration had a mean yield response ratio of 1.31 for average ambient and elevated CO 2 concentration of 373 and 565 ppm. These data gave a relative response ratio of [(1.14 -1.00)/(1.31 -1.00)] = 0.45 (Allen et al, 2020). After eliminating problematic data from the Supplementary Information of Ainsworth et al (2008), the average values of the relative response ratio converged to 0.66 (Allen et al, 2020).…”

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 99%

“…These data gave a relative response ratio of [(1.14 -1.00)/(1.31 -1.00)] = 0.45 (Allen et al, 2020). After eliminating problematic data from the Supplementary Information of Ainsworth et al (2008), the average values of the relative response ratio converged to 0.66 (Allen et al, 2020).…”

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 99%

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Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

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Unique capabilities of various systems for studying the impacts of rising atmospheric CO 2 concentration and other environmental factors on growth and yield of plants are presented. These systems include soil-plant-atmosphere research (SPAR) chambers, free-air carbon dioxide enrichment (FACE) facilities, temperature-gradient greenhouses (TGG), and open top chambers (OTC). The SPAR chambers have several advantages compared to FACE and other facilities, including: (a) constant CO 2 concentration and stabile setpoints; (b) CO 2 concentration controlled to any range of sub-ambient through supra-ambient levels, providing comparison of plant responses to past and future climates; (c) precise air and dewpoint temperature setpoints; (d) calculation of whole-canopy photosynthesis and evapotranspiration rates at short time intervals; (e) calculation of whole-canopy respiration rates during the night; (f) determination of plant responses to temperature alone or including other factors; (g) multiple chambers for simultaneous comparison of plant responses to varying environments, providing data for plant growth modeling; (h) low operating expense for CO 2 concentration; and (i) capability of measuring N 2 fixation rates in the rooting zone of legumes or methane emissions from rice (Oryza sativa L.). SPAR systems were better suited than FACE systems for more than half of the attributes of enrichment systems identified in this paper. Limitations of plant responses due to fluctuating elevated CO 2 concentration and limitations of range of elevated CO 2 concentration exist for FACE systems. Controlled environments are needed for developing mathematical growth response functions under a wide range of conditions. Finally, we identified a use of portable SPAR chambers within FACE experiments for confirmation of diminished plant photosynthesis in fluctuating CO 2 concentration. Abbreviations: FACE, free-air CO 2 enrichment; OTC, open top chamber; PPFD, photosynthetic photon flux density; SD, standard deviation; SPAR, soil-plant-atmosphere research; TGG/TGC/TGT, temperature-gradient greenhouse/temperature-gradient chamber/temperature-gradient tunnel;

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Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 92%

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 94%

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 99%

Section: Capabilities and Limitations Of Face Spar Tgg And Otcmentioning

confidence: 99%

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Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

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“…Moreover, FACE experiments have shown positive impacts on yields of C4 crops such as maize and sorghum only under water-limited conditions (Kimball, 2016). The responses of crops submitted to FACE experiments are now challenged because oscillating and irregular fluctuating elevated [CO2] that happen in these experiments are likely to underestimate the benefits of CO2 enrichment (Allen et al, 2020). The positive CO2 effect on RUE, one of the most sensitive parameters in the APSIM-Sugar model , certainly helped to minimise the likely impacts of future climate changes on previous impacts assessments.…”

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confidence: 99%

Sugarcane variety trait modelling: evaluating and improving the APSIM-Sugar model for simulating crop performance under current and future climates across Brazil

Dias¹

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Sugarcane variety trait modelling: evaluating and improving the APSIM-Sugar model for simulating crop performance under current and future climates across Brazil Brazil is the largest sugarcane producer in the world and the production systems across the country are very complex with large spatial and temporal variations in yields. This is a result of large Genotype × Environment × Management (G × E × M) interactions that ultimately affect crop performance. Moreover, likely changes in the climate conditions are expected in the future imposing additional challenges to sugarcane production. Process-based crop modelling is scientifically accepted as a way to understand those interactions. Upon that, this thesis aimed to integrate field experiments datasets with the APSIM-Sugar model for better understanding the G × E × M interactions in Brazilian cropping systems. The capability of the model was first evaluated with default settings and then modifications and traits were proposed to effectively predict G (varieties) differences. With APSIM-Sugar upgraded, an up-to-date projection of future climate impacts on sugarcane yields across Brazil was performed. The sugarcane dataset came from large field experiments carried out between 2012 and 2017 at two tropical sites in Brazil: Guadalupe, in the state of Piauí (PI), and São Romão, in the state of Minas Gerais (MG), where several varieties were cultivated under non-limiting (potential) conditions. These data were analysed and employed to characterise variety traits for use in APSIM-Sugar. Substantial changes were required to enable the model to simulate canopy development and stalk yield appropriately. The outcomes from the modelling studies showed that the model is now able, although yet empirically, to account for ageing processes, known as the reduced growth phenomenon, to get better yield predictions in high yielding environments, as well as the ability to distinguish between varieties when it comes to yield gains above ~ 150 t/ha (~ 40 t/ha in dry mass). The findings suggest it is reasonable to hypothesise that the APSIM-Sugar modifications and traits are plausible and are an important step for unravelling G × E × M interactions to improve the performance of the sugarcane industry. Another step of this thesis, before applying APSIM-Sugar, was to evaluate gridded weather datasets (NASA/POWER and other developed for Brazil referred to 'XAVIER') as alternative climate inputs in the model. The results indicated these data sources should be employed with caution when the purpose is to simulate sugarcane yield because of the poor performance of gridded rainfall, at least for Center-South Brazil. Lastly, a climate change impact assessment was performed with APSIM-Sugar considering new features and traits for 10 Brazilian sites, being six under rainfed and four under fully-irrigated conditions. Five global climate models were selected to represent basic classes of climate changes: relatively cool/wet; cool/dry; middle; hot/wet; and hot/dry, for four future scenarios. These c...

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T‐FACE studies reveal that increased temperature exerts an effect opposite to that of elevated CO₂ on nutrient concentration and bioavailability in rice and wheat grains

Guo

Huang

Zhang

et al. 2021

Food and Energy Security

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Fluctuations of CO2 in Free-Air CO2 Enrichment (FACE) depress plant photosynthesis, growth, and yield

Cited by 67 publications

References 71 publications

Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

Sugarcane variety trait modelling: evaluating and improving the APSIM-Sugar model for simulating crop performance under current and future climates across Brazil

T‐FACE studies reveal that increased temperature exerts an effect opposite to that of elevated CO₂ on nutrient concentration and bioavailability in rice and wheat grains

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Fluctuations of CO2 in Free-Air CO2 Enrichment (FACE) depress plant photosynthesis, growth, and yield

Cited by 67 publications

References 71 publications

Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

Sunlit, controlled‐environment chambers are essential for comparing plant responses to various climates

Sugarcane variety trait modelling: evaluating and improving the APSIM-Sugar model for simulating crop performance under current and future climates across Brazil

T‐FACE studies reveal that increased temperature exerts an effect opposite to that of elevated CO2 on nutrient concentration and bioavailability in rice and wheat grains

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T‐FACE studies reveal that increased temperature exerts an effect opposite to that of elevated CO₂ on nutrient concentration and bioavailability in rice and wheat grains