New Modeling Approach to Describe and Predict Carbon Sequestration Dynamics in Agricultural Soils

Stefano Mazzoleni, Giuliano Bonanomi, Francesco Giannino, Guido Incerti, Daniela Piermatteo, Riccardo Spaccini, and Alessandro Piccolo

Abstract The contribution of agro-ecosystems to carbon sequestration in the form of soil organic matter (SOM) is increasingly considered as a mitigating factor for climate change. The ecosystem carbon storage depends on the balance between C inputs and outflows due to SOM breakdown. SOM decomposition has been reported as mostly affected by temperature and water availability, at global and regional scale, and by C quality at local scale, where climate can be considered relatively uniform. In this work, a new model of SOM decomposition is presented. The SOMDY model is based on an advanced description of SOM chemical quality by 13C-CPMAS NMR instead of traditional C/N ratio. The model includes also the effects of physical aggregation of organic matter. SOMDY was calibrated on CO2 emission data from extensive field experimental measurements. The simulation results showed the model capability to predict SOM changes during decomposition processes, including the effects of addition of organic amendments (e.g., compost applications, crop residual burial), as well as the impact of different tillage practices on the physical structure of soil aggregation.

S. Mazzoleni (*) • G. Bonanomi • G. Incerti • D. Piermatteo

Dipartimento di Arboricoltura, Botanica e Patologia Vegetale, Universita di Napoli "Federico II",

Via Universita 100, Portici, Naples, Italy e-mail: [email protected]

F. Giannino

Dipartimento di Ingegneria Agraria, Agronomia e Territorio, Universita di Napoli "Federico II", Via Universita 100, Portici, Naples, Italy

Dipartimento di Scienze del Suolo, della Pianta, dell'Ambiente e delle Produzioni Animali, Universitá di Napoli "Federico II", Via Universita 100, Portici, Naples, Italy

A. Piccolo (ed.), Carbon Sequestration in Agricultural Soils,

DOI 10.1007/978-3-642-23385-2_11, © Springer-Verlag Berlin Heidelberg 2012

11.1 Introduction

The potential of agro-ecosystems to absorb large quantities of atmospheric carbon dioxide through carbon sequestration in the form of soil organic matter (SOM) is widely being put forward as one of the mitigating options for climate change (Post et al. 2004). In these man-controlled ecosystems, only a limited fraction of net primary production is yearly delivered to soil as dead organic matter, while a significant amount of organic C enters the soil from external inputs as organic amendments (cover crop, manure, compost, etc.).

However, the ecosystem carbon storage depends not only on C inputs, but also on its outflows, which are controlled by decomposition and mineralization processes. Organic matter decomposition rates are affected by climatic variables, litter quality, and soil disturbance and they change according to the level of incorporation of organic materials into the soil system. Temperature and water availability are considered the most important factors acting at global and regional scale (Aerts 1997; Incerti et al. 2011), while at local scale, when climate can be considered uniform, organic matter decay rate is mostly affected by C quality, i.e., the susceptibility of the substrate to be transformed by decomposers (Meentemeyer 1978).

The definition of organic matter quality in terms of organic chemical composition (Swift et al. 1979) is operationally difficult because litter contains several organic compounds with different susceptibility to decomposition (e.g., lignin, tannins, cellulose, organic acids, amino acids, simple sugars, humic substances) and several inorganic elements (e.g., N, P, S) whose relative fractions vary with decay stage (Rovira and Vallejo 2007). During the last decades, a substantial effort has been made to search effective indicators of organic matter quality, capable to provide reliable predictions of decay rate. The traditional approach has been based on the assessment of selected characteristics to identify parameters or indexes correlated with decay rates, and thus useful for predictive purposes (Meentemeyer 1978; Melillo et al. 1982). Several works reported consistent negative correlations with organic matter decay rate for carbon to nitrogen content ratio (C/N) (Taylor et al. 1989) and, limitedly to litter, for lignin to nitrogen content ratio (Lignin/N) (Melillo et al. 1982). Consequently, C/N and lignin/N ratios are extensively used in most C-cycle models, as descriptors of SOM and litter quality to control mass loss rate (Burke et al. 2003; Adair et al. 2008).

However, a more complex system develops as organic matter enters into soil, due to its interactions with the soil mineral fraction (Piccolo 1996). Consequently, a reliable description of SOM dynamics cannot be based only on organic matter quality indicators, but it should include OM interactions with soil mineral constituents (i.e., sand, silt, and clay fractions).

Moreover, it is widely known that soil disturbance by tillage practices greatly affects SOM stocks, due to their accelerated decomposition. Intensive tillage is widespread in modern agro-ecosystems to prepare seedbed, to incorporate mineral fertilizers, organic amendments and crop residues into soil, to reduce compaction, and effectively control weeds (Conant et al. 2007). Nevertheless, the diffusion of mechanical tillage is believed to be a primary cause of the historical SOM loss in agro-ecosystems, following the conversion of natural soil to agriculture (Drinkwater et al. 1998). Intensive soil tillage increases soil gas exchanges and distribution of organic residues through the soil profile. However, while the release of mineral nutrients is favored by an enhanced SOM decomposition caused by deep tillage, the stock SOM is in turn progressively depleted. As opposite to traditional tillage, the practice of conservative tillage is indicated by many studies to be likely to increase C sequestration in soil (Reicosky 2003). However, the evidence that reduced tillage promotes C sequestration are highly variable (Baker et al. 2007). Recently, Bonanomi et al. (2011a) reported a large decrease of C stock (—24%) from soils under intensive cultivation (more than six tillage treatments per year), as compared to low-input tree orchards (less than two yearly treatments).

In this regard, a considerable modeling effort has been done in last decades to mathematically describe SOM decomposition processes (for an extensive review, see Shibu et al. 2006), which are invariably included in most biogeochemical models simulating carbon dynamics and other ecosystem processes from annual to millennium scale. The main examples are CENTURY (Parton et al. 1994), ROTHAMSTED (RothC) (Coleman and Jenkinson 1996), LPJ (Sitch et al. 2003), and the Biome- (Hunt et al. 1996) and Forest- (Running and Gower 1991) BGC (Bio Geochemical Cycles) models. These detailed models are often used for simulations at regional or global level (e.g., Gholz et al. 2000), whereas their application at lower scale, particularly in Mediterranean agro-ecosystems, is much less reported (e.g., Hoff et al. 2002). For instance, models of SOM, such as CENTURY and RothC, have been developed and are now worldwide applied to evaluate the effects of various agricultural management practices on soil C stock.

In these models, litter and soil organic matter are usually divided in different compartments (early model in Hunt 1977; Jenkinson and Rayner 1977; Minderman 1968). In particular, litter is classified using three different criteria: chemical, kinetic, and functional. The chemical approach defines pools by difference in litter chemical components (e.g., Minderman 1968). This approach has the advantage that chemical compounds (i.e., water-soluble carbohydrates, holocellulose, and lignin) can be analytically determined (Allen 1989; Rowland and Roberts 1994). The kinetic approach defines pools according to their decomposition rate. For example, the Roth-C model (Jenkinson and Rayner 1977) distinguishes two kineti-cally defined pools of plant litter: decomposable (DPM) and resistant plant materials (RPM). The functional approach describes plant litter as composed by metabolic (labile) and structural (i.e., resistant) pools. According to this method, cell components degrade somewhat independently from the physical structure of plant material. Examples of this type of litter characterization are found in CENTURY (Parton et al. 1987, 1988) and GRAZPLAN (Hunt 1977) models.

Different models represent SOM as distributed in two or more pools with different turnover rates. In this way, litter inputs are assigned to SOM pools according to the initial quality of either structural or metabolic litter components. Generally, current approaches are either box models, in which organic matter compounds with similar dynamics are pooled (e.g., Century; Parton et al. 1987)

or continuum models, which track degradation of litter quality during decomposition of substrates which steadily decompose (e.g., Agren and Bosatta 1996). Recycling of C from older pools through microbial biomass is allowed in both model types.

In contrast, models specifically designed for application to agro-ecosystems tend to be used for single season simulations, using daily changes in nutrient and water availability to constrain crop growth and development (DNDC: Li et al. 2003; DayCent: Del Grosso et al. 2001; CANDY: Franko et al. 1995). In general, whether they are from an agricultural or ecological viewpoint, models developed primarily for estimating SOM storage include SOM quality indicators based on the C/N ratio. In spite of research efforts, the reliability of such indicator is not free of uncertainty. For instance, Berg and McClaugherty (2008) suggest that using C/N ratio to predict decay rate throughout the decomposition process should be avoided, because, irrespectively of its initial value, C/N progressively decreases as C is lost through respiration, while N is immobilized in microbial biomass (Bonanomi et al. 2010).

In the last decade, chemical throughput methods as pyrolysis-gas chromatogra-phy/mass spectrometry (Huang et al. 1998), near infrared reflectance spectroscopy (Gillon et al. 1999), and solid-state 13C nuclear magnetic resonance (NMR) spectroscopy either as such (Piccolo et al. 1990; Kogel-Knabner 2002) or in combination with chemometry (Smejkalova et al. 2008) have been applied to characterize organic matter at molecular level. In particular, 13C-CPMAS NMR has been proven useful to provide an overview of the total organic chemical composition of complex matrices, such as soil organic matter (Kogel-Knabner 2002; Preston et al. 2009; Bonanomi et al. 2011b). However, such novel experimental applications have not yet been exploited by current modeling implementation for an improved description of SOM quality.

In this work, a new model of SOM decomposition is developed, calibrated and validated. The model is based on a novel implementation of SOM quality by 13C-CPMAS NMR, to purposely overcome the limitations of C/N as single SOM quality indicator and to explore the effects of SOM interactions with soil mineral constituents.

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