Cycads show no stomatal-density and index response to elevated carbon dioxide and subambient oxygen

2011 ◽  
Vol 59 (7) ◽  
pp. 630 ◽  
Author(s):  
Matthew Haworth ◽  
Annmarie Fitzgerald ◽  
Jennifer C. McElwain
Keyword(s):  
Inverse Relationship ◽  
Stomatal Density ◽  
Atmospheric Oxygen ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Atmospheric Conditions ◽  
Fossil Plants ◽  
Atmospheric Co2 Concentration ◽  
Pore Length ◽  
Cycas Revoluta

The stomatal density (SD) and index (SI) of fossil plants are widely used in reconstructing palaeo-atmospheric CO2 concentration (palaeo-[CO2]). These stomatal reconstructions depend on the inverse relationship between atmospheric CO2 concentration ([CO2]) and SD and/or SI. Atmospheric oxygen concentration ([O2]) has also varied throughout earth history, influencing photosynthesis via the atmospheric CO2 : O2 ratio, and possibly affecting both SD and SI. Cycads formed a major component of Mesozoic floras, and may serve as suitable proxies of palaeo-[CO2]. However, little is known regarding SD and SI responses of modern cycads to [CO2] and [O2]. SD, SI and pore length were measured in six cycad species (Cycas revoluta, Dioon merolae, Lepidozamia hopei, Lepidozamia peroffskyana, Macrozamia miquelii and Zamia integrifolia) grown under elevated [CO2] (1500 ppm) and subambient [O2] (13.0%) in combination and separately, and compared with SD, SI and pore length under control atmospheric conditions of 380 ppm [CO2] and 20.9% [O2]. The cycad species analysed showed no significant SD, SI or pore-length response to changes in [CO2] or [O2].

Stomatal Density as an Indicator of Atmospheric CO2 Concentration

The Holocene ◽  
1992 ◽  
Vol 2 (1) ◽  
pp. 71-78 ◽  
Author(s):  
David J. Beerling ◽  
William G. Chaloner
Keyword(s):  
Stomatal Density ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Atmospheric Co2 Concentration

scholarly journals The <i>p</i>CO<sub>2</sub> estimates of the late Eocene in South China based on stomatal density of <i>Nageia</i> Gaertner leaves

2015 ◽  
Vol 11 (4) ◽  
pp. 2615-2647 ◽  
Author(s):  
X.-Y. Liu ◽  
Q. Gao ◽  
M. Han ◽  
J.-H. Jin
Keyword(s):  
South China ◽  
Stomatal Density ◽  
Co2 Concentration ◽  
Late Eocene ◽  
Atmospheric Co2 ◽  
Stomatal Index ◽  
Atmospheric Co2 Concentration ◽  
Fossil Leaves ◽  
The Mean ◽  
Carbon Dioxide Levels

Abstract. late Eocene pCO2 concentration is estimated based on the species of Nageia maomingensis Jin et Liu from the late Eocene of Maoming Basin, Guangdong Province. This is the first paleoatmospheric estimates for the late Eocene of South China using stomatal data. Studies of stomatal density (SD) and stomatal index (SI) with N. motleyi (Parl.) De Laub., the nearest living equivalent species of the fossil, indicate that the SD inversely responds to atmospheric CO2 concentration, while SI has almost no relationships with atmospheric CO2 concentration. Therefore, the pCO2 concentration is reconstructed based on the SD of the fossil leaves in comparison with N. motleyi. Results suggest that the mean CO2 concentration was 391.0 ± 41.1 ppmv or 386.5 ± 27.8 ppmv during the late Eocene, which is significantly higher than the CO2 concentrations documented from 1968 to 1955 but similar to the values for current atmosphere indicating that the Carbon Dioxide levels during that the late Eocene at that time may have been similar to today.

scholarly journals Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

2019 ◽  
Vol 16 (19) ◽  
pp. 3883-3910 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Co2 Concentration ◽  
Fire Regimes ◽  
Atmospheric Co2 ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Fire Models ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2 concentration, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric CO2 concentration. The effects of changes in atmospheric CO2 concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.

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