Soil Respiration Across Scales: the Importance of a Model-Data
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344 DOI: 10.1002/jpln.200700075 J. Plant Nutr. Soil Sci. 2008, 171, 344–354 Soil respiration across scales: The importance of a model–data integration framework for data interpretation§ Markus Reichstein1* and Christian Beer1 1 Max-Planck Institute for Biogeochemistry, Biogeochemical Model-Data Integration Group, Hans-Knöll-Str. 10, 07745 Jena, Germany Abstract Soil respiration represents the second largest CO2 flux of the terrestrial biosphere and amounts 10 times higher than the current rate of fossil-fuel combustion. Thus, even a small change in soil respiration could significantly intensify—or mitigate—current atmospheric increases of CO2, with potential feedbacks to climate change. Consequently, to understand future dynamics of the earth system, it is mandatory to precisely understand the response of soil respiration to chan- ging environmental factors. Among those changing factors, temperature is the one with clearest and most certain future trend. The relationship of soil respiration to environmental factors and particular temperature has been tackled at a variety of scales—from laboratory via field scale to global, with each of the approaches having its particular problems, where results from different scales are sometimes contradictory. Here, we give an overview of modeling approaches to soil respiration, discuss the dependencies of soil respiration on various environmental factors, and summarize the most important pitfalls to consider when analyzing soil respiration at the respec- tive scale. We then introduce a model–data synthesis framework that should be able to reconcile and finally integrate apparently contradictory results from the various scales. Key words: soil respiration / modeling / upscaling / Bayesian / temperature dependence Accepted January 26, 2008 1 Introduction With globally 68–120 Pg C y–1 soil respiration represents the In this study, methods and problems analyzing soil-respira- second largest C flux between ecosystems and the atmo- tion data from different scales are reviewed and jointly inter- sphere (Schimel et al., 1996). This is more than 10 times the preted with emphasis on the temperature and moisture de- current rate of fossil-fuel combustion and indicates that each pendence of soil respiration. The application of an ecosystem year approx. 10% of the atmosphere’s CO2 cycles through model–data integration framework which is developed in a the soil. Thus, even a small change in soil respiration could cascade from fine scale to landscape scale, and parameter- significantly intensify—or mitigate—current atmospheric ized by using observations across these scales, is proposed increases of CO2, with potential feedbacks to climate change. to provide additional insights into the factors controlling tem- Despite this global significance as well as considerable scien- poral and across-ecosystem variability of soil respiration and tific commitment to its study over the last decades, there is C content. still limited understanding of the factors controlling temporal and across-ecosystem variability of soil respiration. 2 Environmental factors controlling soil This understanding is largely hampered by the fact that stud- respiration ies are often conducted and compared at different temporal and spatial scales that are not compatible. Since particularly 2.1 Abiotic factors in large-scale studies factors influencing soil respiration often correlate with each other, responses of soil respiration to Temperature is virtually influencing all biological and physico- those factors are confounded by other factors, and only chemical processes. This has been empirically observed in apparent relationships are obtained. the 19th century (van’t Hoff, 1898) and later formalized by * Correspondence: Dr. M. Reichstein; e-mail: [email protected] § Paper presented at the Workshop “Upscaling – Soil organisms and soil ecological processes up to the landscape scale”, February 23–24, 2006 at the University of Vechta, Germany. The workshop was organized by the Soil Ecology Working Groups of the German Soil Science Society (DBG) and the Ecological Society of Germany, Austria, and Switzerland (GfÖ), convenor Gabriele Broll and co-con- venors Volkmar Wolters and Anton Hartmann. 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.plant-soil.com J. Plant Nutr. Soil Sci. 2008, 171, 344–354 Soil respiration across scales 345 Arrhenius (1889). Not surprisingly, temperature has also perature. Since enzymes act in a certain temperature inter- been the most obvious and most often studied factor influen- val, all biological processes exhibit optimum temperatures. cing soil respiration, one of the first studies dating back to the Hence, the optimum function (Kirschbaum, 1995) may be 1920s (Waksman and Gerretsen, 1931). All studies confirm a considered as the most appropriate description. However, nonlinear positive direct relationship between temperature soil temperatures rarely reach such high values, so that with- and soil respiration. A number of shapes have been pro- in the normal range of temperatures, the monotonic exponen- posed, but the most commonly used are reviewed by Kätterer tial function may be as valid. et al. (1998), Kirschbaum (1995) as well as by Lloyd and Tay- lor (1994). The simplest, but theoretically not justified function The effect of soil water status on soil respiration has been de- is the so-called exponential Q10 relationship (Tab. 1), where scribed empirically via absolute or relative measures of volu- the parameter Q10 is the factor by which soil respiration in- metric water content and soil water potential as reviewed by creases with a 10°C temperature increase. The Arrhenius Rodrigo et al. (1997) (see examples in Tab. 2). It is usually function is theoretically justified from first physicochemical assumed, that both very low and very high water contents principles of the underlying biochemical reactions and pre- reduce soil respiration, via direct inhibition of biological activ- dicts an increasing Q10 towards lower temperatures. How- ity or inhibition of O2 diffusion, respectively. The relationship ever, the validity of a simple transfer from physicochemical between soil water status and soil-respiratory processes is reactions to complex processes controlling soil respiration complex, since many individual processes vary with soil has not been proved yet. Instead, more flexible exponential water content, in particular gas and solute diffusion, enzyme relationships have been derived from empirical field data, activities, and growth and mortality of microorganisms (Kill- which imply an even stronger variation of the Q10 with tem- ham, 1994; Marshall and Holmes, 1988). Soil water potential Table 1: Typical functions used for describing soil respiration in relation to temperature. Author Function Background Properties dfa À = van't Hoff (1898) Á T Tref 10 emprical always above 0 2 f T a Q10 2 Ratkowsky et al. (1982) f T a Á T À Tmin empirical studies on zero respiration at T = Tmin 2 microbial growth ÀE0= RÁT Arrhenius (1989) f T a Á e physical chemistry always >0, very similar to Q10, 2 ÀEa = T ÀTmin Lloyd and Taylor (1994) f T a Á e Arrhenius + study on zero respiration at T = Tmin,no 3 field respiration optimum Á À : = O'Connell (1990); f T a Á eb T 1 0 5T Topt empirical studies on optimum function 3 Kirschbaum (1995) soil respiration in lab a degrees of freedom (i.e., number of free parameters) Table 2: Typical model formulations used for soil-drought effects on soil respiration. Formulationa References Dependency on volumetric soil moisture f a Á b (plain linear) Stanford and Epstein (1974) À f a Á b (scaled linear) Myers et al. (1982) opt Àb f (hyperbolic) Bunnell et al. (1977) a1 Dependency on soil water potential É É Á log ÀÉ f m 10 c Sommers et al. (1981); Orchard and Cook (1983); Andrén and Paustian log ÀÉÀlog ÀÉ (log-linear) (1987) É 10 10 min f log ÀÉ Àlog ÀÉ 10 opt 10 min f Éa Á ebÁÉ (exponential) Davidson et al. (1998) Dependency on proportion of water-holding capacity P À À 2 f Pe a P Pref b P Pref (exponential) Howard and Howard (1993) a symbols a, b, hopt, hb, a1, m, c, Wmin, Wopt, Pref are model parameters determining the shape and scale of the functions. 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.plant-soil.com 346 Reichstein, Beer J. Plant Nutr. Soil Sci. 2008, 171, 344–354 has often been considered the physiologically more appropri- optimally under neutral conditions while fungi prefer slightly ate predictor of activities in soil, because it expresses the acidic soil pH. A recent study has shown that such optimum actual availability of water independent of texture (Davidson curve can be found through analysis of field data of respira- et al., 1998; Miller and Johnson, 1964). However, plausible tion (Reth et al., 2005), although confounding factors have to arguments for soil water content as a predictor have also be considered. been presented, based on the reasoning that the number and extent of microenvironments where microbial activity may Also in the temporal domain, processes from various time- take place is a function of the volume of the water in the soil scales overlap and superimpose on the resulting soil biologi- (Fang and Moncrieff, 1999; Orchard and Cook, 1983). cal activity and soil respiration (Fig. 1). Consequently, a cur- Furthermore, nutrient and O2 diffusion seem to be better de- rently observed soil respiration can be the result of processes scribed as dependent on soil water content (Skopp et al., that have occurred a long time