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United States Department of Agriculture

Agricultural Research Service

Research Project: IMPACTS OF GLOBAL CHANGES AND BIOLOGICAL CONTROL OF INVASIVE WEEDS ON WESTERN RANGELANDS

Location: Grassland, Soil and Water Research Laboratory

Title: Interannual variability in carbon dioxide fluxes and flux-climate relationships on grazed and ungrazed northern mixed-grass prairie

Authors
item Polley, Wayne
item Frank, Albert
item Sanabria, Joaquin - TEXAS AGRIC EXPT STN
item Phillips, Beckie

Submitted to: Global Change Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 28, 2007
Publication Date: June 12, 2008
Citation: Polley, H.W., Frank, A.B., Sanabria, J., Phillips, R.L. 2008. Interannual variability in carbon dioxide fluxes and flux-climate relationships on grazed and ungrazed northern mixed-grass prairie. Global Change Biology. 14:1620-1632.

Interpretive Summary: Air temperature may increase as carbon dioxide (CO2) and other greenhouse gases accumulate in the atmosphere. Plants grow by converting CO2 from air into carbon compounds in plant tissues, suggesting that the accumulation of plant material in ecosystems could slow the rise in atmospheric CO2 and any accompanying increase in temperature. The amount of plant-derived carbon that is retained in ecosystems is highly sensitive to variability in climate, however. In order to determine effects of climatic variability on grassland carbon balance, we measured climatic factors like temperature and precipitation and the exchange of CO2 between the atmosphere and grazed and ungrazed prairie in North Dakota, USA for 5 years. Inter-annual variability in climate explained about 20% of total variation in net CO2 exchange. Climatic variability affected CO2 exchange both directly and indirectly. Indirect effects of climate variability were evidenced by year-to-year differences in relationships between CO2 exchange and climatic regulators. Grazing reduced inter-annual variability in CO2 fluxes, but did not alter the impact of climatic variability on CO2 exchange. The carbon balance of these grasslands cannot be predicted without knowledge of year-to-year variation in both climate and CO2 exchange-climate relationships.

Technical Abstract: The annual carbon (C) budget of grasslands is highly dynamic, dependent on grazing history and on direct and indirect effects of interannual variability (IAV) in climate on carbon dioxide (CO2) fluxes. We measured net ecosystem exchange of CO2 (NEE) and its diurnal components, daytime ecosystem CO2 exchange (PD) and nighttime respiration (RE), on grazed and ungrazed mixed-grass prairie in North Dakota, USA for five growing seasons. Our primary objective was to determine how climatic anomalies influence variability in CO2 exchange. We used regression analysis to distinguish direct and indirect effects of IAV in climate on fluxes. Indirect effects of climatic variability result from changes in biological processes that regulate photosynthesis and respiration (functional change). Functional change was quantified as the improvement in regression on fitting a model in which slopes of flux-climate relationships vary among years rather than remain invariant. Functional change and direct effects of climatic variation together explained about 20% of variance in weekly means of NEE, PD, and RE. Functional change accounted for more than twice the variance in fluxes of direct effects of climatic variability. Grazing did not consistently influence the contribution of functional change to flux variability, but altered which environmental variable best explained year-to-year differences in flux-climate slopes, reduced IAV in seasonal means of fluxes, lessened the strength of flux-climate correlations, and increased NEE by reducing RE relatively more than PD. Most of these trends are consistent with the interpretation that grazing reduced the influence of plants on ecosystem fluxes. Because relationships between weekly values of fluxes and climatic regulators changed annually, year-to-year differences in the C balance of these ecosystems cannot be predicted from knowledge of IAV in climate alone.

Last Modified: 4/16/2014
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