Dataset Information

Global CO2 rise leads to reduced maximum stomatal conductance in Florida vegetation.

ABSTRACT: A principle response of C3 plants to increasing concentrations of atmospheric CO(2) (CO(2)) is to reduce transpirational water loss by decreasing stomatal conductance (g(s)) and simultaneously increase assimilation rates. Via this adaptation, vegetation has the ability to alter hydrology and climate. Therefore, it is important to determine the adaptation of vegetation to the expected anthropogenic rise in CO(2). Short-term stomatal opening-closing responses of vegetation to increasing CO(2) are described by free-air carbon enrichments growth experiments, and evolutionary adaptations are known from the geological record. However, to date the effects of decadal to centennial CO(2) perturbations on stomatal conductance are still largely unknown. Here we reconstruct a 34% (±12%) reduction in maximum stomatal conductance (g(smax)) per 100 ppm CO(2) increase as a result of the adaptation in stomatal density (D) and pore size at maximal stomatal opening (a(max)) of nine common species from Florida over the past 150 y. The species-specific g(smax) values are determined by different evolutionary development, whereby the angiosperms sampled generally have numerous small stomata and high g(smax), and the conifers and fern have few large stomata and lower g(smax). Although angiosperms and conifers use different D and a(max) adaptation strategies, our data show a coherent response in g(smax) to CO(2) rise of the past century. Understanding these adaptations of C3 plants to rising CO(2) after decadal to centennial environmental changes is essential for quantification of plant physiological forcing at timescales relevant for global warming, and they are likely to continue until the limits of their phenotypic plasticity are reached.

SUBMITTER: Lammertsma EI

PROVIDER: S-EPMC3054011 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Global CO2 rise leads to reduced maximum stomatal conductance in Florida vegetation.

Lammertsma Emmy I EI de Boer Hugo Jan HJ Dekker Stefan C SC Dilcher David L DL Lotter André F AF Wagner-Cremer Friederike F

Proceedings of the National Academy of Sciences of the United States of America 20110217 10

A principle response of C3 plants to increasing concentrations of atmospheric CO(2) (CO(2)) is to reduce transpirational water loss by decreasing stomatal conductance (g(s)) and simultaneously increase assimilation rates. Via this adaptation, vegetation has the ability to alter hydrology and climate. Therefore, it is important to determine the adaptation of vegetation to the expected anthropogenic rise in CO(2). Short-term stomatal opening-closing responses of vegetation to increasing CO(2) are ...[more]

PMID: 21330552

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Project description:Stomatal conductance (g s) in terrestrial vegetation regulates the uptake of atmospheric carbon dioxide for photosynthesis and water loss through transpiration, closely linking the biosphere and atmosphere and influencing climate. Yet, the range and pattern of g s in plants from natural ecosystems across broad geographic, climatic, and taxonomic ranges remains poorly quantified. Furthermore, attempts to characterize g s on such scales have predominantly relied upon meta-analyses compiling data from many different studies. This approach may be inherently problematic as it combines data collected using unstandardized protocols, sometimes over decadal time spans, and from different habitat groups. Using a standardized protocol, we measured leaf-level g s using porometry in 218 C3 woody angiosperm species in natural ecosystems representing seven bioclimatic zones. The resulting dataset of 4273 g s measurements, which we call STraits (Stomatal Traits), was used to determine patterns in maximum g s (g smax) across bioclimatic zones and whether there was similarity in the mean g smax of C3 woody angiosperms across ecosystem types. We also tested for differential g smax in two broadly defined habitat groups - open-canopy and understory-subcanopy - within and across bioclimatic zones. We found strong convergence in mean g smax of C3 woody angiosperms in the understory-subcanopy habitats across six bioclimatic zones, but not in open-canopy habitats. Mean g smax in open-canopy habitats (266 ± 100 mmol m-2 s-1) was significantly higher than in understory-subcanopy habitats (233 ± 86 mmol m-2 s-1). There was also a central tendency in the overall dataset to operate toward a g smax of ∼250 mmol m-2 s-1. We suggest that the observed convergence in mean g smax of C3 woody angiosperms in the understory-subcanopy is due to a buffering of g smax against macroclimate effects which will lead to differential response of C3 woody angiosperm vegetation in these two habitats to future global change. Therefore, it will be important for future studies of g smax to categorize vegetation according to habitat group.

Project description:Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO2 flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO2 fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO2 exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate's temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE.

Dataset Information

Global CO2 rise leads to reduced maximum stomatal conductance in Florida vegetation.

Publications

Global CO2 rise leads to reduced maximum stomatal conductance in Florida vegetation.

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