Climatic controls and ecosystem responses drive the inter-annual variability of the net ecosystem exchange of an alpine meadow

Marcolla, Barbara; Cescatti, Alessandro; Manca, Giovanni; Zorer, R.; Cavagna, M.; Fiora, Alessandro; Gianelle, Damiano; Rodeghiero, Mirco; Sottocornola, Matteo; Zampedri, Roberto

doi:10.1016/j.agrformet.2011.04.015

Cited by 124 publications

(97 citation statements)

References 58 publications

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“…The IAV in NEE is a phenomenon observed at almost all eddy-flux sites around the world (Baldocchi, 2008). The factors driving the IAV in NEE include (1) climate, (2) physiological processes, (3) phenology, (4) ecosystem structure, (5) nutrient cycling in ecosystems, and (6) disturbance (Hui et al, 2003;Marcolla et al, 2011;Polley et al, 2008;Richardson et al, 2007). Among these, the changes in climatic variables and physiological processes can directly affect the IAV in NEE.…”

Section: Introductionmentioning

confidence: 99%

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Shao

Zhou

Luo

et al. 2015

Agricultural and Forest Meteorology

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a b s t r a c tInterannual variability (IAV, represented by standard deviation) in net ecosystem exchange of CO 2 (NEE) is mainly driven by climatic drivers and biotic variations (i.e., the changes in photosynthetic and respiratory responses to climate), the effects of which are referred to as climatic (CE) and biotic effects (BE), respectively. Evaluating the relative contributions of CE and BE to the IAV in carbon (C) fluxes and understanding their controlling mechanisms are critical in projecting ecosystem changes in the future climate. In this study, we applied statistical methods with flux data from 65 sites located in the Northern Hemisphere to address this issue. Our results showed that the relative contribution of BE (CnBE) and CE (CnCE) to the IAV in NEE was 57% ± 14% and 43% ± 14%, respectively. The discrepancy in the CnBE among sites could be largely explained by water balance index (WBI). Across water-stressed ecosystems, the CnBE decreased with increasing aridity (slope = 0.18% mm −1 ). In addition, the CnBE tended to increase and the uncertainty reduced as timespan of available data increased from 5 to 15 years. Inter-site variation of the IAV in NEE mainly resulted from the IAV in BE (72%) compared to that in CE (37%). Interestingly, positive correlations between BE and CE occurred in grasslands and dry ecosystems (r > 0.45, P < 0.05) but not in other ecosystems. These results highlighted the importance of BE in determining the IAV in NEE and the ability of ecosystems to regulate C fluxes under climate change might decline when the ecosystems experience more severe water stress in the future.

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Section: Introductionmentioning

confidence: 99%

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Shao

Zhou

Luo

et al. 2015

Agricultural and Forest Meteorology

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“…2.5e) shows an abrupt increase in DStDev at the onset of the growing season indicating that this period has an important role in the IAV definition. Marcolla et al 2011 concluded that climatic conditions and snow cover in late spring largely influence the interannual variability of NEE of this alpine grassland, and that the first half of the growing season at IT-MBo mitigates the IAV thanks to the negative correlation (R = −0.77) between the timing of snowmelt and the rate of carbon uptake at the beginning of the growing season. A second peak of DStDev due to the variable timing of the meadow cut has been observed, emphasizing the important role of management in controlling the inter annual variability.…”

Section: Analysis Of the Relationship Between Annual Nee And Climate mentioning

confidence: 99%

“…across sites) of annual NEE, and phenology, which is one of the main factors controlling the temporal variability of NEE at site level (e.g. Marcolla et al 2011).…”

Section: Analysis Of the Relationship Between Annual Nee And Climate mentioning

confidence: 99%

“…In the third analysis, the inter-annual variability has been analyzed defining for each site with more than 3 years of data, the phenological period that mostly contribute to annual NEE variability. Following Marcolla et al (2011), for each site-year the time series of cumulative monthly NEE and its standard deviation have been computed. According to Marcolla et al (2011), variations of standard deviation from one month to the preceeding one (DStDev) quantifies the contribution of each month to the observed interannual variability (IAV).…”

Section: Analysis Of the Relationship Between Annual Nee And Climate mentioning

confidence: 99%

“…Following Marcolla et al (2011), for each site-year the time series of cumulative monthly NEE and its standard deviation have been computed. According to Marcolla et al (2011), variations of standard deviation from one month to the preceeding one (DStDev) quantifies the contribution of each month to the observed interannual variability (IAV). The analysis has been conducted also at weekly time scale with comparable results (data not shown).…”

Section: Analysis Of the Relationship Between Annual Nee And Climate mentioning

confidence: 99%

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In this chapter the Eddy Covariance network of Italy is presented, with a short introduction to each of the 29 sites that were active during the CarboItaly project. These sites provided a unique dataset for a better study and understanding of the carbon cycle of terrestrial ecosystems and the links between carbon sink capacity and the main environmental factors. After a number of examples of Eddy Covariance time series where it is possible to see the effect of interannual climate variability and disturbances and managements practices, an analysis of the role of

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et al. 2013

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[1] It is well established that warming leads to longer growing seasons in seasonally cold ecosystems. Whether this goes along with an increase in the net ecosystem carbon dioxide (CO2) uptake is much more controversial. We studied the effects of warming on the start of the carbon uptake period (CUP) of three mountain grasslands situated along an elevational gradient in the Alps. To this end, we used a simple empirical model of the net ecosystem CO2 exchange, calibrated, and forced with multiyear empirical data from each site. We show that reductions in the quantity and duration of daylight associated with earlier snowmelts were responsible for diminishing returns, in terms of carbon gain, from longer growing seasons caused by reductions in daytime photosynthetic uptake and increases in nighttime losses of CO2. This effect was less pronounced at high, compared to low, elevations, where the start of the CUP occurred closer to the summer solstice when changes in day length and incident radiation are minimal.

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Climatic controls and ecosystem responses drive the inter-annual variability of the net ecosystem exchange of an alpine meadow

Cited by 124 publications

References 58 publications

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Carbon, Water and Energy Fluxes of Terrestrial Ecosystems in Italy

Trade‐offs between global warming and day length on the start of the carbon uptake period in seasonally cold ecosystems

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