Elsevier

Journal of Arid Environments

Volume 121, October 2015, Pages 43-51
Journal of Arid Environments

Upscaling CO2 fluxes using leaf, soil and chamber measurements across successional growth stages in a sagebrush steppe ecosystem

https://doi.org/10.1016/j.jaridenv.2015.05.013Get rights and content

Highlights

  • We measured carbon fluxes at four stages after disturbance in big sagebrush steppe.

  • Plant phenology drove seasonal fluxes more predictably than abiotic measurements.

  • We scaled leaf and soil fluxes to whole ecosystem chamber fluxes to compare methods.

  • Leaf respiration improved relationships between component and whole-ecosystem fluxes.

Abstract

Understanding and upscaling CO2 flux drivers from components (leaf and soil) to net ecosystem exchange (NEE) is critical to modeling exchange of terrestrial ecosystems. Our main objectives were to determine abiotic and biotic drivers of NEE, upscale CO2 fluxes from component measurements and validate the upscaling method using independent ecosystem scale (chamber) measurements. We measured four big sagebrush successional stages Wyoming, USA: recent growth (2 years since disturbance, ysd), establishment (9 ysd), expansion (20 ysd), and mature (38 ysd). Leaf biomass correlated with NEE (p < 0.01) and month of the growing season (p < 0.01), but not with soil dryness (p = 0.26) or with ysd (p = 0.99). Upscaled component measurements correlated to chamber measurements better when all stages were combined for both GPP (p = 0.01, slope 0.29, intercept −6.8) and ecosystem respiration (RE). RE correlated without leaf respiration (RL) added to soil respiration (RS, p = 0.01, slope 1.2, intercept 1.44) and with RL added to RS (p < 0.01, slope 1.2, intercept −0.30). Temporal changes in leaf biomass both in the short term (growing season) and long-term (ysd) can be discriminated to improve CO2 flux estimates when upscaling.

Introduction

Understanding drivers of CO2 fluxes and upscaling them from components (leaf and soil) to net ecosystem exchange (NEE) is critical for modeling biosphere-atmosphere exchange of terrestrial ecosystems. Acquiring field data at multiple scales can greatly improve carbon (C) cycle modeling. This is especially true when partitioning NEE into gross primary production (GPP) and ecosystem respiration (RE), which is the most challenging issue in upscaling CO2 fluxes (Reichstein et al., 2012, Reichstein et al., 2005). The dynamic disequilibrium of CO2 sources and sinks during disturbance and succession are an important component of global change needing additional research (Luo and Weng, 2011). Therefore, testing upscaling methodology across a gradient of disturbance, as we do in this study, is critical to improve spatio-temporal dynamics of terrestrial biosphere-atmosphere modeling.

Burning high elevation sagebrush steppe results in predictable succession within 40 years after fire (Anderson and Inouye, 2001, Cleary et al., 2010, Ewers and Pendall, 2008, Harniss and Murray, 1973, Lesica et al., 2007, Wambolt et al., 2001). Disturbance in lower elevation sagebrush ecosystems, in contrast, can result in Bromus tectorum L. (cheatgrass) invasion and consequential transition of ecosystem state (Booth et al., 2003, Bradley et al., 2006, Young and Allen, 1997). During succession in higher elevations, the plant community shifts from initial graminoid dominance to co-dominance of graminoids and shrubs at middle-age to dominance by sagebrush shrubs at maturity (Cleary, 2007, Ewers and Pendall, 2008). Total aboveground biomass increases during succession due to the increase of sagebrush stem accumulation; total leaf biomass does not change significantly (Cleary et al., 2010).

Although biomass changes have been described during succession, there is limited information about CO2 fluxes and net C changes in sagebrush ecosystems during succession despite their widespread area and ecological importance (Gilmanov et al., 2004, Gilmanov et al., 2003, Kwon et al., 2008). Forest CO2 fluxes respond to successional plant community changes by gradually shifting from net loss to gains, and then back to neutral over several decades (Bond-Lamberty et al., 2004, Goulden et al., 2011, Law et al., 2003, Litvak et al., 2003). Studies in rangeland and grassland ecosystems, however, have focused on initial flux responses to disturbances (Prater et al., 2006). It is unclear if shrub-dominated areas follow the same pattern as forested areas with regards to net CO2 fluxes despite a similar pattern in C accumulation in aboveground biomass.

Chamber measurements capture various levels and types of gaseous fluxes and are used to partition and validate tower-scale fluxes. There are few reported studies comparing up-scaled leaf-cuvette and sub-meter scale soil respiration chamber measurements to whole ecosystem scale chamber measurements to validate this practice. Angell et al. (2001) compared large-scale Bowen ratio/energy balance fluxes (tower method) to 1-m2 chamber measurements in two sagebrush ecosystems in Idaho and Oregon, USA and found a positive correlation between the two methods (r = 0.82, n = 190). Smith et al. (2003) compared leaf cuvette, 1-m2 chamber, to eddy covariance (ground based and remotely sensed) measurements and found measurements taken several days apart caused more deviation between fluxes than the systematic differences between the methods. While chamber methods can be temporally limited because they do not produce continuous data, they are cost effective and provide means to partition respiration and assimilation in short-stature ecosystems like sagebrush. Our main objectives, therefore, were to: (1) determine abiotic and biotic drivers of NEE, (2) upscale CO2 fluxes from component measurements (leaf and soil) to GPP and RE, and (3) validate the upscaling method using independent ecosystem scale (chamber) CO2 flux measurements at four sites representing different successional stages.

Section snippets

Study area

This study utilized a mountain big sagebrush (Artemisia tridentata Nutt. spp. vaseyana (Rydb.) Beetle) succession sequence in south-central Wyoming, USA. The sequence included four growth stages: recent growth (2 ysd, prescribed burn in 2003), establishment (6 ysd, prescribed burn in 1999), expansion (20 ysd, prescribed burn in 1985), and mature (38 ysd, herbicide spray in 1967). The stages were within 3 km of each other and had similar topographic characteristics (elevation 2280–2310 m and <1%

Abiotic and biotic drivers of NEE

Total leaf biomass was not significantly different between successional stages (p < 0.01, Fig. 2), but there was significantly more (p = 0.01) mean (reported with standard error) herbaceous biomass at the recent growth 98 (12) g m−2, establishment 110 (17) g m−2, and expansion 120 (24) g m−2 stages than at the mature stage 40 (4.9) g m−2 (Fig. 2). At all growth stages except the mature stage, herbaceous biomass was relatively high and did not statistically change between May and July

Abiotic and biotic drivers of NEE

This study found leaf biomass to be the best predictor of NEE regardless of the growth stage after fire, which may be predominantly due to the importance of phenology in this high desert ecosystem. The difference in phenology between different growth stages represents seasonal differences between herbs and shrubs, similar to what Barron-Gafford et al. (2011) and Potts et al. (2006) have found. This study adds to increasing evidence pointing to seasonal photosynthetic variability due to changing

Conclusion

Upscaling terrestrial CO2 fluxes from component fluxes (leaf and soil) to NEE is challenging. Our results provide insight into short-term (seasonal) and long-term (ysd) differences in C uptake and loss in semi-arid ecosystems, and provides a framework for understanding the relationships between different scales of measurement of CO2 fluxes in these systems. Testing the upscaling methodology across a gradient of disturbance is critical to improve spatio-temporal dynamics of terrestrial

Author contributions

EP and BEE designed the study. EP, BEE, and MBC established the exact locations of the field sites. MBC, KJN, EP, and BEE installed and implemented field-based measurements. MBC performed the statistical analysis and MBC and KJN wrote the paper. All authors discussed results and assisted in the revisions.

Acknowledgments

This project was supported by the National Research Initiative of the USDA Cooperative State Research Education and Extension Service, Grant number #2003-35101-13652 and a Graduate Student Fellowship from the Wyoming Space Grant Consortium. Partial funding was also provided by the Agricultural Experiment Station Competitive Grants program, project #WYO-401-06. We thank S. Adelman, J. Adelman, I. Abernathy, M. Bell, B. Cline, C. Miller, D. Sackett, and A. Schulstad for assistance with site

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    1

    Current address: Department of Biological Sciences, University of Arkansas, Fayetteville, AR 72701, USA.

    2

    Current address: Hawkesbury Institute for the Environment, University of Western Sydney, Locked Bag 1797, Penrith, New South Wales, Australia.

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