Biosphere-atmosphere exchange of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; in relation to climate: a cross-biome analysis across multiple time scales

P C Stoy,M Williams,J H Mccaughey,K T Paw U,M Detto,J Campos,G G Katul,J Stanovick,M Reichstein,B E Law,S Sevanto,N Arriga,D D Baldocchi,M D Mahecha,L Montagnani,A D Richardson,G Wohlfahrt

doi:10.5194/bg-6-2297-2009

Abstract

Abstract. The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the relationship between flux and climate at multiple time scales is necessary for a comprehensive understanding of the role of climate in the terrestrial carbon cycle. Orthonormal wavelet transformation (OWT) can quantify the strength of the interactions between gappy eddy covariance flux and micrometeorological measurements at multiple frequencies while expressing time series variance in few energetic wavelet coefficients, offering a low-dimensional view of the response of terrestrial carbon flux to climatic variability. The variability of NEE, GEP and RE, and their co-variability with dominant climatic drivers, are explored with nearly one thousand site-years of data from the FLUXNET global dataset consisting of 253 eddy covariance research sites. The NEE and GEP wavelet spectra were similar among plant functional types (PFT) at weekly and shorter time scales, but significant divergence appeared among PFT at the biweekly and longer time scales, at which NEE and GEP were relatively less variable than climate. The RE spectra rarely differed among PFT across time scales as expected. On average, RE spectra had greater low frequency (monthly to interannual) variability than NEE, GEP and climate. CANOAK ecosystem model simulations demonstrate that "multi-annual" spectral peaks in flux may emerge at low (4+ years) time scales. Biological responses to climate and other internal system dynamics, rather than direct ecosystem response to climate, provide the likely explanation for observed multi-annual variability, but data records must be lengthened and measurements of ecosystem state must be made, and made available, to disentangle the mechanisms responsible for low frequency patterns in ecosystem CO2 exchange.

Highlights

Variability in the global carbon cycle is dominated by terrestrial ecosystem metabolism (Houghton, 2000; Canadell et al, 2007) and it is critical to understand how and why the terrestrial carbon cycle varies to advance in our knowledge of the Earth system
The net ecosystem exchange of CO2 (NEE) between the biosphere and atmosphere is determined by the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE) to physical and biological drivers which vary at multiple time scales
Abbreviations (“hourly”, “daily”, “annual”, etc.) are used to approximate the discrete time scales for simplicity; for example, the annual coefficients represent variability at 0.935 years, daily coefficients represent 16 h variability as 24 is not a power of 2, and “multi-day” represents 1.33 day and 2.67 day variability because these time scales are longer than 1 day yet shorter than 1 week (Fig. 2, see Table 2)

Summary

Introduction

Variability in the global carbon cycle is dominated by terrestrial ecosystem metabolism (Houghton, 2000; Canadell et al, 2007) and it is critical to understand how and why the terrestrial carbon cycle varies to advance in our knowledge of the Earth system. Models synthesize our knowledge of terrestrial carbon exchange and represent an explicit hypothesis about how ecosystem function transfers variability in climatic forcing to an ecological response, namely the flux of mass or energy. These ecosystem transfer properties can be explored using long-term meteorological and carbon flux measurements from the international FLUXNET project, which consists of eddy covariance tower flux measurements from regional networks [CarboeuropeIP, AmeriFlux, Fluxnet-Canada, LBA, Asiaflux, Chinaflux, USCCC, Ozflux, Carboafrica, Koflux, NECC, TCOS-Siberia, (e.g., Aubinet et al, 2000; Baldocchi et al, 2001a; Baldocchi, 2008)]. The FLUXNET project offers the unprecedented opportunity to relate directly the measured variability in mass and energy flux to the measured meteorological variability at time scales from hours to years, and in some cases over a decade (Grunwald and Bernhofer, 2007; Urbanski et al, 2007; Granier et al, 2008)

Objectives

Methods

Results

Discussion

Conclusion