Dataset Information

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production.

ABSTRACT: Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO₂ concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5180184 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production.

Zhang Yao Y Xiao Xiangming X Guanter Luis L Zhou Sha S Ciais Philippe P Joiner Joanna J Sitch Stephen S Wu Xiaocui X Nabel Julia J Dong Jinwei J Kato Etsushi E Jain Atul K AK Wiltshire Andy A Stocker Benjamin D BD

Scientific reports 20161223

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO<sub>2</sub> concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and ele ...[more]

PMID: 28008960

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Project description:Carbon isotope discrimination (Δ13 C) in C3 woody plants is a key variable for the study of photosynthesis. Yet how Δ13 C varies at decadal scales, and across regions, and how it is related to gross primary production (GPP), are still incompletely understood. Here we address these questions by implementing a new Δ13 C modelling capability in the land-surface model JULES incorporating both photorespiratory and mesophyll-conductance fractionations. We test the ability of four leaf-internal CO2 concentration models embedded in JULES to reproduce leaf and tree-ring (TR) carbon isotopic data. We show that all the tested models tend to overestimate average Δ13 C values, and to underestimate interannual variability in Δ13 C. This is likely because they ignore the effects of soil water stress on stomatal behavior. Variations in post-photosynthetic isotopic fractionations across species, sites and years, may also partly explain the discrepancies between predicted and TR-derived Δ13 C values. Nonetheless, the "least-cost" (Prentice) model shows the lowest biases with the isotopic measurements, and lead to improved predictions of canopy-level carbon and water fluxes. Overall, modelled Δ13 C trends vary strongly between regions during the recent (1979-2016) historical period but stay nearly constant when averaged over the globe. Photorespiratory and mesophyll effects modulate the simulated global Δ13 C trend by 0.0015 ± 0.005‰ and -0.0006 ± 0.001‰ ppm-1 , respectively. These predictions contrast with previous findings based on atmospheric carbon isotope measurements. Predicted Δ13 C and GPP tend to be negatively correlated in wet-humid and cold regions, and in tropical African forests, but positively related elsewhere. The negative correlation between Δ13 C and GPP is partly due to the strong dominant influences of temperature on GPP and vapor pressure deficit on Δ13 C in those forests. Our results demonstrate that the combined analysis of Δ13 C and GPP can help understand the drivers of photosynthesis changes in different climatic regions.

Dataset Information

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production.

Publications

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production.

Similar Datasets

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