HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Paul, E. A. Articles by Plante, A. F. Search for Related Content PubMed Articles by Paul, E. A. Articles by Plante, A. F. Agricola Articles by Paul, E. A. Articles by Plante, A. F. Related Collections Biogeochemical Processes Carbon Sequestration Isotopes Soil Organic Matter Soil Analysis

Symposium: Meaningful Pools in Determining Soil C and N Dynamics

Does the Acid Hydrolysis–Incubation Method Measure Meaningful Soil Organic Carbon Pools?

^a Natural Resource Ecology Lab., Colorado State Univ., Fort Collins, CO 80523-1499
^b Dep. of Biology, Bradley Univ., Peoria, IL 61625

^* Corresponding author (eldor{at}nrel.colostate.edu)

	ABSTRACT

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
The literature was reviewed and analyzed to determine the feasibility of using a combination of acid hydrolysis and CO₂–C release during long-term incubation to determine soil organic carbon (SOC) pool sizes and mean residence times (MRTs). Analysis of 1100 data points showed the SOC remaining after hydrolysis with 6 M HCl ranged from 30 to 80% of the total SOC depending on soil type, depth, texture, and management. Nonhydrolyzable carbon (NHC) in conventional till soils represented 48% of SOC; no-till averaged 56%, forest 55%, and grassland 56%. Carbon dates showed an average of 1200 yr greater MRT for the NHC fraction than total SOC. Long-term incubation, involving measurement of CO₂ evolution and curve fitting, measured active and slow pools. Active-pool C comprised 2 to 8% of the SOC with MRTs of days to months; the slow pool comprised 45 to 65% of the SOC and had MRTs of 10 to 80 yr. Comparison of field ¹⁴C and ¹³C data with hydrolysis–incubation data showed a high correlation between independent techniques across soil types and experiments. There were large differences in MRTs depending on the length of the experiment. Insertion of hydrolysis–incubation derived estimates of active (C_a), slow (C_s), and resistant pools (C_r) into the DAYCENT model provided estimates of daily field CO₂ evolution rates. These were well correlated with field CO₂ measurements. Although not without some interpretation problems, acid hydrolysis–laboratory incubation is useful for determining SOC pools and fluxes especially when used in combination with associated measurements.

Abbreviations: KBS–LTER, Kellogg Biological Station–Long Term Ecological Research • MRT, mean residence time • NHC, nonhydrolyzable carbon • SOC, soil organic carbon • SOM, soil organic matter

	INTRODUCTION

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
SOIL ORGANIC MATTER (SOM) is a complex mixture of plant- and microbiologically-derived compounds (Stevenson, 1994). Fractionation schemes have been employed to (i) isolate meaningful pools that provide information on C and nutrient cycling; (ii) test hypotheses on soil formation and ecosystem functioning; (iii) relate SOM characteristics to soil management and global change; and (iv) aid in developing models describing SOM dynamics. Observed differences in MRTs from months to centuries to millennia for different SOM fractions prompted the development of models with multiple soil C pools with differing MRTs (Jenkinson and Rayner, 1977; Van Veen and Paul, 1981; Parton et al., 1987). To date, no single biological, physical, or chemical fractionation technique has been developed that adequately describes the continuum of SOC that exists in nature. Mismatches between measurements of ¹⁴C-labeled plant materials using three size-density fractions and model outputs have been identified (Magid et al., 1996). Motavalli et al. (1994) and Smith et al. (2002) were not successful in their attempts to equate the active pool to microbial biomass plus soluble C fraction or the light fraction. Similar problems were found when attempts were made to equate the size of the slow pool in models with the particulate organic matter fraction (Metherell et al., 1995). However, more recent work investigating free and aggregate-associated SOC has produced more promising results (Kong et al., 2005; Sohi et al., 2005)

This paper reviews the degree to which a combination of acid hydrolysis and long-term laboratory incubation can be used to define SOC dynamics. Three pool models, with first order kinetics, have most often been found to best describe SOC dynamics (Paustian et al., 1992) with the general equation

[1]

where C_TSOC = the soil organic carbon released as CO₂ at time t, a = active, s = slow, r = resistant, k = decomposition rate constant (1/MRT), and t = time (days).

The coupling of long-term incubation with chemical digestion of SOC by acid hydrolysis has been reported by Collins et al. (2000), Haile-Mariam et al. (2000), Fortuna et al. (2003), and Paul et al. (2001a, 2001b). Resistant soil C (C_r) was measured by chemical fractionation using acid hydrolysis; its decomposition rate factor (k_r) was measured by ¹⁴C-dating the NHC. Long-term incubation enabled endogenous soil microorganisms to biologically fractionate the SOC with their enzymes with a resultant release of CO₂ under aerobic conditions. Statistical analysis of the rate of CO₂ evolution during long-term incubation (curve fitting) estimated the pool size and turnover time for the active fraction (C_a). This corresponded to the rapid, initial release of CO₂–C during the initial phases of the incubation. The turnover time for the slow fraction (k_s) was estimated by statistical analysis from the slope of the CO₂–C release curves during extended incubation. The size of the slow fraction (C_s) was determined by the difference between the total SOC and the sum of C_a and C_r.

In this literature review, which is part of a series on the determination of meaningful pools of C and N in soil, we evaluate the degree to which acid hydrolysis and C mineralization during incubation can be used to describe SOC dynamics. This involves a description of the analytical procedures used and the rationale for selecting them. The efficacy of this approach has been determined using three approaches: (i) by assessing how well data obtained by hydrolysis–incubation help interpret SOC dynamics under a range of management scenarios across time; (ii) by testing how well a combination of independent tracer and hydrolysis–incubation analyses on the same soil samples compare in their description of SOC dynamics; and (iii) a review of a paper that discusses how well the DAYCENT model (Parton et al., 1998) portrayed CO₂ evolution in the field when the parameters analytically determined by acid hydrolysis–incubation were inserted into the model.

	REVIEW OF THE METHODS

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
Acid Hydrolysis
Feller (1997) reports that in 1804, De Saussure used boiling HCl to fractionate humus. De Saussure determined that humus contained more C and less O and H than the original plant residues from which it was thought to be derived. Acid hydrolysis, involving refluxing in 6 M HCl at 116°C, has been extensively used to characterize soil N with 65 to 80% of the N being solubilized (Bremner, 1967). The hydrolysis reaction, through the process of protonation and hydration, solubilizes compounds with O- and N-containing functional side-groups (Barriuso et al., 1987). Fatty acids, proteins, and polysaccharides are susceptible to acid hydrolysis treatment, while long-chain alkyls, waxes, lignin, and other aromatics are resistant to hydrolysis.

The size of the resistant pool (C_r of Eq. [1]) is measured by acid hydrolysis as NHC and its decomposition rate constant (k_r) is measured by ¹⁴C-dating. Where carbon dates are unavailable, in most agricultural soils it is possible to substitute a value of 1000 yr for the MRT (1/k) without significantly altering the outcome of the curve fitting for the active and slow pools (Paul et al., 2001a). The hydrolyzability of samples is often expressed as % NHC, and calculated (Plante et al., 2006) using the following equation that corrects for mass loss of the mineral portion of the sample during hydrolysis:

[2]

where the terms represent the organic C concentrations and masses of the sample before and after acid hydrolysis. Significant sample mass loss has been observed during the hydrolysis procedure. This could not be accounted for by the mass loss of the hydrolyzed organic matter and is likely attributable to the solubilization of inorganic constituents such as carbonates, metal oxides, and some clay minerals.

Incubation
Waksman (1932) reported that as far back as 1891, the CO₂ evolution rate was used as a measure of SOC oxidation taking place in soils. By 1896, moisture and temperature controls had been recognized. In 1924, Lemmerans and Weissman (see Waksman, 1932) stated that under aerobic and constant environmental conditions, CO₂ formation proceeded according to the equation

[3]

where x is the amount of CO₂ produced in time (t), a is the initial C content of the soil, and k and m are constants. Löhnis and Fred (1923) and Lundegärdh (1927) pointed out that CO₂ is produced by soil microorganisms, and related rates of soil CO₂ evolution to plant growth and SOC changes. Mathematical analysis of long-term incubation data were first conducted by Stanford and Smith (1972) in their analysis of N-mineralization curves.

Early incubation methodology for SOC mineralization was described by Minderman and Vulto (1973) and Stotsky (1965). The CO₂ evolution rate during the initial incubation period is indicative of the size and decomposition rate constant (1/MRT) of the active pool. Methods for analysis of CO₂ data are presented by Paul et al. (2001a), Robertson et al. (1999), and Zibilske (1994). The parameters C_a, k_a, and k_s are determined using nonlinear regression (NonLIN, Systat Inc., Evanston, IL; or PROC NLIN, SAS Institute, Cary, NC) of the CO₂ incubation data (Paul et al., 2001a). After measurement of C_a and C_r, the C_s is determined by difference:

where C_SOC is the total soil C at the time soil is removed from the field. It is possible to determine soil C dynamics for both labeled and unlabeled C where the evolved CO₂ contains a useable ¹³C signal. This can occur in soils with crops that have had a plant switch between C₃ and C₄ photosynthesis types, such as when continuous corn (C₄) is grown after a previously mixed cropping system on soils that were developed under trees (C₃) or when wheat (C₃ plant) is grown on warm-season, grassland (C₄ plants) derived soils. Similar possibilities exist where fossil-fuel derived CO₂ with a specific label is added during plant growth such as in an elevated-CO₂ study (Haile-Mariam et al., 2000).

The moisture and temperature at which the incubation is conducted affects the CO₂ release rates. Incubation conditions using a temperature of 25°C and a water content of 60% of water holding capacity (Elliott et al., 1994) have most often been used (Paul et al., 2001a). Other temperatures and moisture contents could be used depending on the hypothesis being investigated. The MRTs determined in the laboratory have generally been corrected to reflect the measured mean annual temperature of field sites by assuming a Q₁₀ of 2 (Collins et al., 2000). Soils are best incubated immediately after collection. Where dried samples are necessary, a preincubation period can be used to minimize the flush of SOC mineralization attributable to drying and rewetting. Publications have reported incubation times of 200 to 800 d depending on the soil type and incubation temperature (Haile-Mariam et al., 2000; Collins et al., 2000). In general, incubations should be performed until the CO₂ evolution rate is low and rate curves have declined to approach an asymptote.

	RESULTS OBTAINED WITH HYDROLYSIS–INCUBATION

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
Acid Hydrolysis
Our review of the literature and analysis of available data consisted of approximately 1100 data points on NHC contents or %NHC across a range of soil textures, climates, land use histories, and methods of analyses. The most commonly used method was to reflux with 6 M HCl at 116°C for 16 h (Campbell et al., 1967; Collins et al., 2000; Follett et al., 1997; Haile-Mariam et al., 2000; Jenkinson and Rayner, 1977; Martel and Paul 1974a, 1974b; Martel and LaSalle, 1977; McLauchlan and Hobbie, 2004; Paul et al., 1997, 2001a). Some studies used 6 M HCl at 96°C (Plante et al., 2006) or 100°C (Tan et al., 2004), while one study refluxed soil in 2 M H₂SO₄ at 116°C (Vlassak et al., 1969). Consistent differences were observed based on the method used (P < 0.001), but in all cases, the amount of NHC was strongly correlated to the amount of total SOC (Fig. 1 ). The most frequently used method (6 M HCl at 116°C for 16 h) had a regression slope of 0.51, while the use of 6 M HCl at 96 and 100°C resulted in a regression slope of 0.58, and the use of 2 M H₂SO₄ at 116°C resulted in a regression slope of 0.75 between NHC and SOC.

View larger version (23K): [in this window] [in a new window]   Fig. 1. Nonhydrolyzable soil C as a function of total soil C for each of four different methods of acid hydrolysis: (a) standard method, 6 M HCl for 16 h at 116°C (data from Campbell et al., 1967; Collins et al., 2000; Follett et al., 1997; Haile-Mariam et al., 2000; Jenkinson and Rayner, 1977; Martel and Paul, 1974a, 1974b; Martel and LaSalle, 1977; McLauchlan and Hobbie, 2004; Morris et al., 2006, unpublished data; Paul et al., 1997, 2001a, 2001b); (b) 6 M HCl for 18 h at 96°C (Plante et al., 2006); (c) 6 M HCl for 18 h at 100°C (Tan et al., 2004); and (d) 2 M H2SO4 for 4 h (Vlassak et al., 1969).

View larger version (26K): [in this window] [in a new window]   Fig. 2. Proportion of nonhydrolyzable C as a function of depth for (a) cultivated conventional till, (b) cultivated no-till, (c) forest, and (d) grassland samples. Median values are represented by the solid line in each box, mean values by the dotted line, 25th and 75th percentiles by the upper and lower bounds of the box, 10th and 90th percentiles by the upper and lower whiskers, and fifth and 95th percentiles by dots above and below boxes, where available. The number of data points within each depth–management combination is indicated in parentheses above the x axis. Data obtained with other methods were normalized to those obtained with 6 M HCl at 116°C for 16 h using data from Fig. 1.

View larger version (22K): [in this window] [in a new window]   Fig. 3. Nonhydrolyzable soil C as a function of total soil C for samples from four different land-use types: (a) cultivated conventional till, (b) cultivated no-till, (c) native forest, and (d) native grassland (data from Campbell et al., 1967; Collins et al., 2000; Follett et al., 1997; Haile-Mariam et al., 2000; Jenkinson and Rayner, 1977; Martel and LaSalle, 1977; Martel and Paul, 1974a, 1974b; McLauchlan and Hobbie, 2004; Morris et al., 2006, unpublished data, Paul et al., 1997, 2001b; Plante et al., 2006).

An analysis of the MRT of three depths of seven corn-belt soils under various management practices (Paul et al., 2001b) produced negative regressions between the ¹⁴C MRT of the total soil with its sand contents at depth (Table 1). Clay content had a positive effect on the MRT values. As with the effect of sand contents, there was greater statistical significance with depth with clay contents. The silt content had no statistically significant effect on the MRT of the SOC. Silt contents also were not associated with MRTs of the NHC at the surface of the seven sites, but silt affected the MRT of the NHC at depth. The intercepts show the general increase in MRT with depth. The great ages (high MRTs) of the NHC fraction are indicated by the intercepts, with silt having generally higher values than clays (Table 1).

View larger version (24K): [in this window] [in a new window]   Fig. 4. Proportion of nonhydrolyzable C (%NHC) in silt- and clay-sized fractions isolated from 53- to 250-µm microaggregates (data from Plante et al., 2006).

Incubations in which CO₂ evolution rates approached an asymptote have been used to identify treatment effects on C dynamics in management studies involving crop rotations and composting (Fortuna et al., 2003). Paul et al. (2003) analyzed the effect of management on the SOC dynamics of six long-term Canadian Prairie sites, and found rates of CO₂ evolution to be very useful in interpreting SOC dynamics, especially during the early stages of management when it is difficult to obtain statistical differences in total SOC levels. This was especially the case when differences in CO₂ evolution rates were expressed relative to differences in total C accumulation rates at a particular site. This approach normalized soil type effects and showed a high correlation of CO₂ evolution with particulate organic matter measured on the various treatments.

In a long-term incubation of corn-belt soils, Collins et al. (2000) found that 4.0 to 9.4% of the SOC was evolved during 800 d of incubation with little effect of depth when the CO₂ was expressed as a percentage of the SOC. Haile-Mariam et al. (2000) analyzed CO₂ evolution from ponderosa pine (Pinus ponderosa C. Lawson) soils subjected to increased levels of atmospheric CO₂ containing an identifiable ¹³C label. They found that 4% of the surface horizon SOC was evolved in soils incubated at 37°C for 150 d. Three percent of the SOC was evolved from samples at depth. They measured the ¹³C content of the evolved CO₂ and of the soil after incubation to determine the fraction derived from the labeling during growth in an enhanced CO₂ environment. In this soil, the ¹³C-label associated with the clay-sized fraction decreased less (2.9% decrease) during incubation than did the ¹³C-label associated with the silt-sized fraction (9.7% decrease). The particulate organic matter plus sand fraction lost 10.7% of the label whereas the most active pool, the light fraction, lost 35.6% of its label-induced ¹³C during incubation.

The general shape of incubation curves, when expressed as a rate function, is exemplified by the data from the Kellogg Biological Station–Long Term Ecological Research (KBS–LTER) site in Hickory Corners, MI (Fig. 5 ). The shoulder at approximately Day 100 has been found in many of the curves analyzed and could be an indication of a change in the soil biota responsible for decomposition during this period. Soil fauna have been shown to develop slowly during incubation (Coleman et al., 2004) and changes in bacterial to fungal ratios during incubation have been found (McGill and Paul, 1976; McMahon et al., 2005). Another explanation for the CO₂ shoulder could be a change in substrate availability at this time. The CO₂ evolved from the slow pool is measured as the gradual drop to the asymptote. Atypical CO₂ evolution curves, where the evolution is better expressed as zero order than first order kinetics, have been occasionally found, especially in tundra soils (Weintraub and Schimel, 2003).

View larger version (17K): [in this window] [in a new window]   Fig. 5. Carbon dioxide evolution rate curves (µg C g soil–1 d–1) for three depths (0–20, 25–50, and 50–100 cm) from a Michigan corn-belt soil (from Collins et al., 2000).

View this table: [in this window] [in a new window]   Table 2. Pool sizes and soil organic C mineralization kinetics (mean resident time, MRT) determined using acid hydrolysis and long-term incubations of samples from five different sites for the 0- to 20-, 25- to 50-, and 50- to 100-cm depths.

The curve fitting used to determine the best fit relates C_a and C_s with k_a and k_s. Solving for C_s and k_s by this method dictates that they are inversely related to C_r. The data in Fig. 1 and 3 show a high correlation between NHC and SOC with approximately 48 to 56% of the SOC being hydrolyzed. The primary effect of the %NHC in the curve-fitting calculations is to change the value for C_s.

Collins et al. (2000) related the pool sizes of the C₃ (noncorn) derived SOC measured directly from soil samples to their MRTs, which were measured with hydrolysis–incubation, in plots where corn (C₄) had been grown for the last 10 to 30 yr (Fig. 6 ). This diagram does not differentiate whether the MRT or the size of the pool is the factor controlling the relationships. It does, however, show that the corn-belt soils derived from forested soils (Hoytville, OH; Hickory Corners, MI; and Wooster, OH) had larger pool sizes relative to their MRTs than those derived from the prairie soils (Lamberton, MN, and Arlington, WI). Both curvilinear plots of Fig. 6 show that this approach separates out original vegetation type with a high correlation between size of the pool and its MRT. Fortuna et al. (2003) utilized the hydrolysis–incubation method to investigate the effects of fertilization, green manure, crop rotations, and compost on pool sizes and MRTs of both C and N at a KBS–LTER site. They found that compost derived from oak leaves and cattle manure resulted in the largest changes during a 6-yr field experiment. Compost additions increased total soil C by 14% relative to the fertilizer N treatment. The proportion of NHC (C_r) increased by 30% and the slow pool by 10%. Both the size and MRT of the active pool decreased with oak–manure compost additions, showing the recalcitrant nature of the compost. This was reflected in N availability: compost additions did not supply enough N for the crop except in first-year corn following wheat–fallow cover crop treatments.

View larger version (22K): [in this window] [in a new window]   Fig. 6. Size of the slow soil C pool (Cs) determined using the hydrolysis–incubation method as a function of mean residence time (MRT) determined using 13C content of soil for Corn Belt and Northern Prairie soils (from Collins et al., 2000).

The use of ¹³C studies (Collins et al., 1999), ¹⁴C dating (Paul et al., 2001b), and hydrolysis–incubation experiments (Collins et al., 2000) on the same soil samples made it possible to compare the results from three independent analyses on the same soil samples. Paul et al. (2001b) compared ¹³C MRT data with data obtained using ¹⁴C carbon dating on the same site with 30 yr of continuous corn (Collins et al., 1999). Their data (Fig. 7 ) demonstrates that the ¹⁴C MRTs were related to the ¹³C measurements by the equation

[4]

They suggested that the curvilinear equation reflected the thousands of years of exposure time for the ¹⁴C MRTs relative to the 10 to 30 yr exposure for the¹³C MRTs measured during C₄C₃ replacement in the continuous corn plots. Given sufficient time, the two tracers should provide similar data. On the same plots, Collins et al. (2000) observed a linear relationship with a high degree of correlation between the sizes of the C₃ soil MRT as determined in the field with the C₄C₃ plant switch and that measured by an 800-d incubation and curve fitting with the equation

[5]

View larger version (14K): [in this window] [in a new window]   Fig. 7. Mean residence time (MRT) of total soil organic C by 14C-dating vs. 13C after a C3C4 plant switch to continuous corn for soils from three depths (adopted from Paul et al., 2001b).

The validity of the hydrolysis–incubation method was tested by Paul et al. (1999) by incorporating the analytically derived-pools and fluxes, as described in Table 2, into the DAYCENT model (Parton et al., 1998). Crop residue inputs and abiotic data required by the model were obtained from the KBS–LTER web site (http://lter.kbs.msu.edu/; verified 10 Feb. 2006). Model output was related to CO₂ values measured in the field at the KBS–LTER site (Fig. 8 ). As previously noted, the high CO₂ evolution rates of subsurface soils in the laboratory, together with the decrease in NHC of the subsurface horizons of this site, resulted in an increased size of the C_s and C_a pools, and a decrease in MRT of both pools with depth. Paul et al. (1999) reduced subsurface decomposition rate constants, determined by laboratory incubation, by 20% to account for the possibility that the subsurface soils may have given artificially high CO₂ values in the laboratory. This could have been because of changes in temperature or breakdown of aggregates and mixing during sampling. The 20% decrease in decomposition rates was based on the observation that burial of cellulose strips at depth resulted in 20% lower decomposition than at the surface (Coleman et al., 1980). A possible difference in field temperature for the subsurface horizons was not incorporated into the model, but may already be partially incorporated into the 20% lower decomposition rates observed at depth by Coleman et al. (1980).

View larger version (25K): [in this window] [in a new window]   Fig. 8. CO2 fluxes generated using DAYCENT modeling parameterized with hydrolysis–incubation data (solid line) compared with CO2 fluxes measured in the field (dots represent means with standard error) for the conventional tillage plots at the Kellogg Biological Station–Long Term Ecological Research site (from Paul et al., 1999).

	DISCUSSION

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
Our review and analysis of the literature show that NHC measurements are simple and repeatable, have a high signal to noise ratio, and isolate a fraction that is much older than whole-soil C. The rapid changes in the size of this fraction in response to changes in management do not fit with the concepts of a passive fraction in many present SOC models. This also is not consistent with the generally held concept that resistant fractions should only undergo slow changes during SOC loss or accrual. Several possible explanations that we propose for the differences between the measurable NHC and a conceptual resistant pool are (i) acid hydrolysis does not remove all the modern plant residues, particularly lignin; (ii) more than just biochemical complexity is involved in forming resistant C; (iii) NHC, although much older than the SOC, does not adequately represent the resistant C pool; (iv) our understanding of SOM dynamics is incomplete; or (v) the models are not correct. The possibility of contamination by recent plant residue inputs is minimized in ¹⁴C-dating techniques by removal of all plant residues by flotation and hand picking under a microscope (Martel and Paul, 1974a). This operation is not possible in the many analyses often associated with fractionation of the large number of samples in soil-management studies. However, the differences in %NHC of isolated silt and clay fractions observed by Plante et al. (2006), as shown in Fig. 4, should not be affected by recent plant residues, indicating that plant residue contamination is not a major factor in the interpretation of hydrolysis results.

It is difficult to determine the amount of SOC that is biochemically recalcitrant relative to that which is difficult to decompose because of physical protection and association with silt and clay minerals (Paul and Van Veen, 1978). López-Ulloa et al. (2005) found that SOC stabilized in Andisols was associated with metal–humate complexes and the mineral allophone. Long-term stabilization in Inceptisols was associated with sorption to clay minerals and noncrystalline (hydr-) oxides. The loss of soil C on tillage can be due to the altered physical protection in soils that may allow resistant C to be released. Land-use change can also increase rates of erosion which will remove soil C (Lal et al., 1998). Changes in the composition of the crop residues, rooting type, and depth also play a role, as do the effects of the incorporation of plant residues. The results with no tillage show enhanced buildup of SOC and the proportion of NHC with no changes in the type of crop grown or the amount of residue added (Lal et al., 1998). A two-stage hydrolysis procedure with a weak acid pretreatment has been used in the past to ensure that soil sugars do not caramelize during the 6 M HCl exposure to high temperatures (Martel and Paul, 1974a; Persson, 1967). This should especially be considered where the NHC is to be used for further chemical characterization.

A number of authors (Schmidt et al., 1999; Skjemstad et al., 1996, 2002) have suggested that materials identified as charcoal, black carbon, or char could account for a substantial portion of recalcitrant SOC in agricultural soils. These materials were most often measured by UV irradiation (Skjemstad et al., 1993) or preferential extraction (Kuhlbusch et al., 1995). In Ponomarenko and Anderson's (2001) examination of North American soils similar to those reviewed in this study (Collins et al., 2000; Follett et al., 1997), they concluded that char was found in agricultural soils formed under both grassland and forested vegetation and on different parent materials. Char was present in all particle-size fractions, but was especially prevalent in the silt-sized fraction where it often had clay coatings or inclusions. The resistance to UV irradiation and the strong aromatic peak at 130 ppm in CP mass ¹³C NMR lead them to conclude that up to 60% of the SOC of these soils could be char. The presence of char could help explain some of the NHC results in this review. The high MRT and the high proportion of NHC in silt-sized fractions are consistent with the presence of char. Char cannot be related to the 30% increase in NHC in agricultural soils where oak leaf–cattle manure compost was added for 6 yr (Fortuna et al., 2003). It also cannot explain the doubling of both SOC and NHC in the afforested soils during a 50-yr period with no fires (Morris, 2006, unpublished data) that formed a significant part of this literature analysis. As is so often the case with SOC studies, the interaction of multitude processes and controls makes it difficult to assign one explanation such as char to SOC recalcitrance.

The rapid increase in NHC during short periods of afforestation or return of land to grassland vegetation is difficult to interpret. Morris (2006, unpublished data) showed that changes in NHC were highly correlated to two-fold gains or losses of SOC after approximately 50 yr of afforestation. This suggests that the NHC is a dynamic pool sensitive to management changes, and should not be considered strictly a passive pool. The increased age that comes with depth is likely a consequence of decreased inputs, lower temperature, and possibly lower microbial activity resulting in reduced degradation. The possibility of geological C (e.g., that brought in with the parent materials) must also be considered on some sites.

Earlier reviews of SOC dynamics (Paul and Van Veen, 1978) recognized that persistence in soil is not due to chemical recalcitrance or biochemical complexity alone, but is also attributable to an interaction of biochemical complexity with soil particles and aggregates. The model of Van Veen and Paul (1981) utilized a physical protection factor to account for the decomposition rate changes attributable to aggregation and interaction of SOC with soil silt and clay. The high correlations between different methodologies based on tracers and analytical methods that give different MRTs can best be explained by the hypothesis that young SOC does not differ greatly in composition from older SOC. This leads to the corollary that SOC does not necessarily change with age once it is formed. Biochemical resistance (as measured by acid hydrolysis), physical protection within aggregates (especially microaggregates), and silt and clay interactions all play an important role in SOC stabilization. Incubation that allows the microorganisms through their enzymes to fractionate SOC is not a direct measure, but does reflect these controlling factors.

The use of three SOC pools with first order reaction kinetics has no specific scientific validation, but does give meaningful estimates that cannot be obtained when dynamics are analyzed on the basis of one or two pools. Use of a two-pool unconstrained model that does not consider the size of the resistant C pool leads to pool sizes that differ considerably from the hydrolysis–incubation data. Paul et al. (2001a) showed that the size of C_s was underestimated by 75% and the MRT by 29 yr when a two-pool unconstrained model was used.

The temperature sensitivity of different pools of SOC is very important in predicting the effects of global warming on SOC dynamics and sequestration. Zogg et al. (1997) found that the size of the C pool available for rapid decomposition (Ca) varied with incubation temperature. Knor et al. (2005) suggest that nonlabile C is more sensitive to temperature changes than labile C. Fang et al. (2005) found that temperature sensitivity of the resistant organic matter was not different from that of labile pools. Reanalysis of a large number of soils between 1978 and 2003 across England and Wales (Bellamy et al., 2005) showed a very large loss during that period. The loss, irrespective of land use, was said to suggest a link to climate change. The possibility of loss from different pools, however, was not investigated.

The hydrolysis–incubation methodology relies on the assumption that differences in estimates of C_a, whether induced by incubation conditions or by climate or management in the field, will be reflected in the values for k_a, C_s, and k_s. Comparisons between soils or field treatments will be valid, and C_a variation induced by incubation will not be a problem for parallel incubations with uniform conditions. However, more information is required as to whether different pools of SOC have different temperature responses (e.g., Q₁₀ values). At present, models tend to assign the same Q₁₀ coefficients to all fractions (Jenkinson and Rayner, 1977; Parton et al., 1987).

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 
This review and analysis of the literature indicates that the answer to the question, "do acid hydrolysis and incubation measure meaningful soil organic matter pools?" is a qualified yes. The hydrolysis–incubation method measures reproducible, sensitive pools. It can analytically determine the pool sizes and turnover rates of the continuum of related SOC that ranges from days to months to centuries and even to millennia. This was validated by comparing results determined using ¹³C and ¹⁴C, and by comparison of modeled data, using analytically determined pools and fluxes, with CO₂ evolution rates measured under field conditions.

The method works because SOC pools are best measured by techniques that take into account the various controls involved in SOC dynamics. Long-term laboratory incubation is a biological fractionation that allows soil enzymes and microbes to fractionate SOC into meaningful pools while implicitly accounting for differing degrees of substrate availability due to various protection mechanisms. Incubation data are, however, insufficient for estimating the size and turnover rate of resistant C because of their short time spans relative to the long MRTs of resistant C. Therefore, complementary information is required to estimate the size of the resistant pool.

There are a number of points that must be considered in utilizing and interpreting results using the hydrolysis–incubation method. In ¹⁴C dating, NHC is on average 1200 to 1400 yr older than total SOC in surface soils, and even more so at depth. It is the oldest fraction determined in analysis of humates and SOC associated with silt and clay (Paul and Van Veen, 1978). In spite of this age, NHC is correlated with total SOC contents and can be rapidly lost or gained after changes in soil management, such as afforestation or cultivation. It must be interpreted then that persistence in soil is not due to biochemical recalcitrance alone.

There is a strong correlation between pools and fluxes measured by hydrolysis–incubation and those measured by ¹³C incorporation due to a C₃C₄ vegetation change, as well as by ¹⁴C dating. Large differences in the age of SOC determined with different methods suggest that results must be related to the length of the experiment. Tracer and even hydrolysis–incubation data need to be reported relative to the time of the experiment and tracer exposure.

The use of the combined hydrolysis–incubation method highlights that SOC is a continuum of closely related materials that are affected by multiple controls and can change rapidly under changing environments or management. All components of SOC (the active, slow, and resistant pools) are essential to the formation and stabilization of SOC. It should not be surprising that SOC cannot be formed or sequestered without the participation of all pools. The resistant fraction as defined by acid hydrolysis is a useful component of the hydrolysis–incubation method. The fact that it does not necessarily infer recalcitrance as defined in models indicates that the models may have to be updated to recognize the possibilities for fairly rapid changes in all components of the continuum of SOM on changes in management.

	ACKNOWLEDGMENTS

 
This research was supported by the Office of Science (BER), U.S. Department of Energy, Grant No. DE-FG02-04ER63890 and the National Science Foundation, Contract No. DEB-0444880.

Received for publication March 31, 2005.

	REFERENCES

TOP ABSTRACT INTRODUCTION REVIEW OF THE METHODS RESULTS OBTAINED WITH HYDROLYSIS... DISCUSSION CONCLUSIONS REFERENCES

 

• Alvarez, R., and C.R. Alvarez. 2000. Soil organic matter pools and their associations with carbon mineralization kinetics. Soil Sci. Soc. Am. J. 164:184–189.
• Anderson, D.W., and E.A. Paul. 1984. Organo-mineral complexes and their study by radiocarbon dating. Soil Sci. Soc. Am. J. 48:198–201.
• Barriuso, E., J.M. Portal, and F. Andreux. 1987. Kinetics and acid hydrolysis of organic matter in humic–rich mountain soil. Can. J. Soil Sci. 67:647–658.
• Bellamy, P.H., P.J. Loveland, R.I. Bradley, R.M. Lark, and G.D.H. Kirk. 2005. Carbon losses from all soils across England and Wales. Nature (London) 437:245–248.[CrossRef][Medline]
• Bremner, J.M. 1967. Nitrogenous compounds in soil. p. 19–66. In A.D. McLaren and G.H. Peterson (ed.) Soil biochemistry. Marcel Dekker, New York.
• Campbell, C.A., E.A. Paul, D.A. Rennie, and R.J. McCallum. 1967. Applicability of the carbon dating method of analysis to soil humus studies. Soil Sci. 104:217–224.
• Campbell, C.A., R.P. Zentner, B.C. Liang, G. Roloff, E.G. Gregorich, and S. Blomert. 2000. Organic C accumulation in soil over 30 years on semiarid southwestern Saskatchewan. Effect of crops and fertilizers. Can. J. Soil Sci. 80:179–192.
• Coleman, D.C., A.I. Breymeyer, M.C. Dash, Y. Dommergues, H.W. Hunt, E.A. Paul, A. Sasson, R. Scheafer, B. Ulova, and R. Zlotin. 1980. Decomposer subsystems. p. 609–658. In A.I. Breymeyer and G.M. van Dyne (ed.) Grasslands system analysis and man. Cambridge Univ. Press, Cambridge, UK.
• Coleman, D.C., D.A. Crossley, and P.F. Hendrix. 2004. Fundamentals of soil ecology. Elsevier, San Diego, CA.
• Collins, H.P., R.L. Blevins, L.G. Bundy, D.R. Christenson, W.A. Dick, D.R. Huggins, and E.A. Paul. 1999. Soil carbon dynamics in corn-based agroecosystems: Results from carbon¹³ natural abundance. Soil Sci. Soc. Am. J. 63:584–591.[Abstract/Free Full Text]
• Collins, H.P., E.T. Elliott, K. Paustian, L.G. Bundy, W.A. Dick, D.R. Huggins, A.J.M. Smucker, and E.A. Paul. 2000. Soil carbon pools and fluxes in long-term corn belt agroecosystems. Soil Biol. Biochem. 32:157–168.
• Elliott, E.T., I.C. Burke, C.A. Monz, S.D. Frey, K.H. Paustian, H.P. Collins, E.A. Paul, C.V. Cole, R.L. Blevins, W.W. Frye, D.W. Lyon, A.D. Halvorson, D.R. Huggins, R.F. Turco, and M.V. Hickman. 1994. Terrestrial carbon pools: Preliminary data from Corn Belt and Great Plains regions. p. 179–191. In J.W. Doran et al (ed.) Defining soil quality for a sustainable environment. SSSA Spec. Publ. 35. SSSA and ASA, Madison, WI.
• Falloon, P.D., and P. Smith. 2000. Modeling refractory soil organic matter. Biol. Fert. Soils 30:388–398.
• Fang, C., P. Smith, J. Moncrief, and J.U. Smith. 2005. Similar response of labile and resistant soil organic matter to changes in temperature. Nature (London) 433:57–59.[CrossRef][Medline]
• Feller, C. 1997. The concept of soil humus in the past three centuries. p. 15–46. In D.H. Yaalon and S. Berkowitz (ed.) History of soil science. Catena Verlag GMBH, Reiskirchen, Germany.
• Follett, R.A., E.A. Paul, S.W. Leavitt, A. Halvorson, D. Lyon, and G.A. Peterson. 1997. Carbon isotope ratios of Great Plains soils and in wheat-fallow systems. Soil Sci. Soc. Am. J. 61:1068–1077.[Abstract/Free Full Text]
• Fortuna, A., R.R. Harwood, and E.A. Paul. 2003. The effects of compost and crop rotations on carbon turnover and the particulate organic matter fraction. Soil Sci. 168:434–444.[CrossRef]
• Haile-Mariam, S., W. Cheng, D.W. Johnson, J.T. Ball, and E.A. Paul. 2000. Use of carbon¹³ and carbon¹⁴ to measure the effects of carbon dioxide and nitrogen fertilization on carbon dynamics in ponderosa pine. Soil Sci. Soc. Am. J. 64:1984–1993.[Abstract/Free Full Text]
• Jenkinson, D.S., and J.H. Rayner. 1977. The turnover of soil organic matter in some of the Rothamsted classical experiments. Soil Sci. 123:298–305.
• Kong, A.Y.Y., J. Six, D.C. Bryant, R.F. Denison, and C. van Kessel. 2005. The relationship between carbon input, aggregation and soil carbon stabilization in sustainable cropping systems. Soil Sci. Soc. Am. J. 69:1078–1095.[Abstract/Free Full Text]
• Kuhlbusch, T.A.J. 1995. Method for determining black carbon in residues of vegetation fires. Environ. Sci. Technol. 29:2695–2702.
• Lal, R., J.M. Kimble, R.F. Follett, and C.V. Cole. 1998. The potential of U.S. cropland to sequester carbon and mitigate the greenhouse effect. Ann Arbor Press, Chelsea, MI.
• Law, B.E., P.E. Thornton, J. Irvine, P.M. Anthoni, and S.Van Tuyl. 2001. Carbon storage and fluxes in ponderosa pine forests at different development stages. Global Change Biol. 7:755–777.[CrossRef]
• Leavitt, S.W., R.F. Follett and E.A. Paul. 1997. Estimation of slow and fast cycling soil organic carbon pools from 6 N HCl hydrolysis. Radiocarbon 38:231–239.
• Löhnis, F., and E.B. Fred. 1923. Textbook of agricultural bacteriology. McGraw-Hill, New York.
• López-Ulloa, M., E. Veldkamp, and G.H. Koning. 2005. Soil carbon stabilization in converted tropical pastures and forests depends on soil type. Soil Sci. Soc. Am. J. 69:1110–1117.[Abstract/Free Full Text]
• Lundegärdh, L. 1927. Carbon dioxide evolution of soil and crop growth. Soil Sci. 23:417–453.
• Magid, J., A. Gorissen, and K.E. Giller. 1996. In search of the elusive "active" fraction of soil organic matter: Three size-density fractionation methods for tracing the fate of homogeneously ¹⁴C-labelled plant materials. Soil Biol. Biochem. 28:89–99.[CrossRef]
• Martel, Y.A., and P. LaSalle. 1977. Radiocarbon dating of soil organic matter from a cultivated topsoil in Eastern Canada. Can. J. Soil Sci. 57:375–377.
• Martel, Y.A., and E.A. Paul. 1974a. Effects of cultivation on organic-matter of grassland soils as determined by fractionation and radiocarbon dating. Can. J. Soil Sci. 54:419–426.
• Martel, Y.A., and E.A. Paul. 1974b. The use of radiocarbon dating of organic matter in the study of soil genesis. Soil Sci. Soc. Am. J. 38:501–506.[Abstract/Free Full Text]
• McGill, W.B., and E.A. Paul. 1976. Fractionation of soil and ¹⁵N nitrogen to separate the organic and clay interaction of immobilized N. Can. J. Soil Sci. 56:203–212.
• McLauchlan, K.K., and S.A. Hobbie. 2004. Comparison of labile soil organic matter fractionation techniques. Soil Sci. Soc. Am. J. 68:1616–1625.[Abstract/Free Full Text]
• McMahon, S.K., M.A. Williams, P. Bottomley, and D. Myrold. 2005. Dynamics of microbial communities during decomposition of labeled ryegrass fractions in soil. Soil Sci Soc. Am. J. 69:1238–1247.[Abstract/Free Full Text]
• Metherell, A.K., C.A. Cambardella, W.J. Parton, G.A. Peterson, L.A. Harding, and C.V. Cole. 1995. Simulation of soil organic matter dynamics in dryland wheat-fallow cropping systems. p. 259–270. In R. Lal et al. (ed.) Soil management and greenhouse effect. Advances in soil science. CRC Press, Boca Raton, FL.
• Minderman, G., and J.C. Vulto. 1973. Comparison of techniques for the measurement of carbon dioxide evolution from soil. Pedobiologia 13:73–80.
• Motavalli, P.P., C.A. Palm, W.J. Parton, E.T. Elliott, and S.D. Frey. 1994. Comparison of laboratory and modeling simulation methods for estimating soil carbon pools in tropical forest soils. Soil Biol. Biochem. 26:935–944.[CrossRef]
• Parton, W.J., M.D. Hartman, D.S. Ojima, and D.S. Schimel. 1998. DAYCENT: Its land surface submodel: Description and testing. Global Planet. Change 19:35–48.
• Parton, W.J., D.S. Schimel, C.V. Cole, and D.S. Ojima. 1987. Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Sci. Soc. Am. J. 51:1173–1179.[Abstract/Free Full Text]
• Paul, E.A., H.P. Collins, and S.W. Leavitt. 2001b. Dynamics of resistant soil carbon of midwestern agricultural soils measured by naturally-occurring ¹⁴C abundance. Geoderma 104:239–256.[CrossRef][ISI]
• Paul, E.A., R.F. Follett, S.W. Leavitt, A. Halvorson, G.A. Peterson, and D.J. Lyon. 1997. Radiocarbon dating for determination of soil organic matter pool sizes and dynamics. Soil Sci. Soc. Am. J. 61:1058–1067.[Abstract/Free Full Text]
• Paul, E.A., D. Harris, H.P. Collins, U. Schulthess, and G.P. Robertson. 1999. Evolution of CO₂ and soil carbon dynamics in biologically managed, row-crop agroecosystems. Appl. Soil Ecol. 11:53–65.[CrossRef]
• Paul, E.A., S.J. Morris, and S. Böhm. 2001a. The determination of soil C pool sizes and turnover rates: Biophysical fractionation and tracers. p. 193–205. In R. Lal et al (ed.) Assessment methods for soil carbon. Lewis Publ., Boca Raton, FL.
• Paul, E.A., S.J. Morris, J. Six, K. Paustian, and E.G. Gregorich. 2003. Interpretation of soil carbon and nitrogen dynamics in agricultural and afforested soils. Soil Sci. Soc. Am. J. 67:1620–1628.[Abstract/Free Full Text]
• Paul, E.A., and J.A. Van Veen. 1978. The use of tracers to determine the dynamic nature of organic matter. p. 61–202. In Proc. 11th Int. Congr. Soil Sci., Edmonton, AB. Int. Soil Sci. Soc.
• Paustian, K., W.J. Parton, and J. Persson. 1992. Modeling soil organic matter in organic amended and N-fertilized, long-term plots. Soil Sci. Soc. Am. J. 56:476–488.[Abstract/Free Full Text]
• Persson, J. 1967. A biological-chemical study of soil organic matter fractionation. Aberdeen, Trans. Int. Soc. Soil Sci. Comm. II and IV:59–64.
• Plante, A.F., R.T. Conant, E.A. Paul, K. Paustian, and J. Six. 2006. Acid hydrolysis of easily dispersed and microaggregate-derived silt- and clay-sized fractions to isolate a resistant fraction of soil organic matter. Eur. J. Soil Sci. (in press).
• Poirier, N., S. Derenne, J. Balesdent, C. Chenu, G. Bardoux, A. Mariotti, and C. Largeau. 2005. Dynamics and origin of the non-hydrolyzable organic fraction in a forest and cultivated temperate soil, as determined by isotopic and microscopic studies. Eurasian Soil Sci. 56:1–11.
• Ponomarenko, E.V., and D.W. Anderson. 2001. Importance of charred organic matter in Black Chernozemic soils of Saskatchewan. Can J. Soil Sci. 81:285–297.
• Robertson, G.P., D. Wedin, P.M. Groffman. J.M. Blair, E.A. Holland, K. Nadelhoffer, and D. Harris. 1999. Soil carbon and nitrogen availability. p. 258–271. In G.P. Robertson et al (ed.) Standard soil methods for long-term ecological research. Oxford Univ. Press, New York.
• Schmidt, M.W., J.O. Skjemstad, E. Gehrt, and I. Koegel-Knaber. 1999. Charred organic carbon in Germany chernozemic soils. Eurasian Soil Sci. 50:351–365.
• Skjemstad, J.O., P. Clark, J.A. Taylor, J.M. Oades, and S.C. McClure. 1996. The chemistry and nature of protected carbon in soil. Aust. J. Soil Res. 34:251–271.[CrossRef]
• Skjemstad, J.O., L.J. Janik, J.A. Head, and S.C. McClure. 1993. High energy UV-oxidation: A novel technique for studying physically protected organic matter in clay and silt-sized aggregates. J. Soil Sci. 44:485–489.
• Skjemstad, J.O., D.C. Reicosky, A.R. Wilts, and J.A. McGowan. 2002. Charcoal carbon in U.S. agricultural soils. Soil Sci. Soc. Am. J. 66:1249–1255.[Abstract/Free Full Text]
• Smith, J.U., P. Smith, R. Monaghan, and J. MacDonald. 2002. When is a measured soil organic matter fraction equivalent to a model pool? Eurasian Soil Sci. 53:405–416.[CrossRef]
• Sohi, S.P., N. Mahieu, D.S. Powlson, B. Madari, R.H. Smittenberg, and J.L. Gaunt. 2005. Investigating chemical characteristics of soil organic matter fractions suitable for modeling. Soil Sci. Soc. Am. J. 69:1248–1255.[Abstract/Free Full Text]
• Stanford, G., and S.J. Smith. 1972. Nitrogen mineralization potentials of soils. Soil Sci. Soc. Am. Proc. 36:465–472.
• Stevenson, F.J. 1994. Humus chemistry. 2nd ed. John Wiley & Sons, New York.
• Stotsky, G. 1965. Microbial respiration. p. 1550–1572. In C.A. Black (ed.) Methods of soil analysis, Part 2. Agron. Monogr. 9. ASA, Madison, WI.
• Stout, J.D., K.M. Goh, and T.A. Rafter. 1981. Chemistry and turnover of naturally occurring resistant organic compounds in soil. p. 1–74. In E.A. Paul and J.N. Ladd (ed.) Soil biochemistry. Vol. 5. Marcel Dekker, New York.
• Tan, Z.X., R. Lal, R.C. Izaurralde, and W.M. Post. 2004. Biochemically protected soil organic carbon at the North Appalachian experimental watershed. Soil Sci. 169:423–433.[CrossRef]
• Trumbore, S.E. 1993. Comparison of carbon dynamics in tropical and temperate soils using radiocarbon measurements. Global Biogeochem. Cycles 7:275–290.
• Van Veen, J.A., and E.A. Paul. 1981. Organic carbon dynamics in grassland soil. Background simulation and model verification. Can. J. Soil Sci. 61:185–201.
• Vlassak, K., L.M.J. Verstraeten, and J. Livens. 1969. Distribution of forms of nitrogen and carbon in some soil profiles. I. Composition of soil hydrolysates. Soil Sci. 108:127–131.
• Waksman, S.A. 1932. Principles of soil microbiology. The Williams and Wilkins Co., Baltimore, MD.
• Warembourg, F.R., and E.A. Paul. 1973. The use of ¹⁴CO₂ canopy techniques for measuring carbon transfer through the plant–soil system. Plant Soil 38:331–345.
• Weintraub, M.N., and J. Schimel. 2003. Interactions between carbon and nitrogen mineralization and soil organic matter chemistry in Arctic Tundra soils. Ecosystems 6:129–143.
• Zibilske, L.M. 1994. Carbon mineralization. p. 835–863. In R.W. Weaver et al (ed.) Methods of soil analysis: Part 2—Microbiological and biochemical properties. SSSA Book Ser. No. 5. SSSA, Madison, WI.
• Zogg, G.P., D.R. Zak, D.B. Ringelberg, N.W. MacDonald, K.S. Pregitzer, and D.C. White. 1997. Compositional and functional shifts in microbial communities due to soil warming. Soil Sci. Soc. Am. J. 61:475–481.[Abstract/Free Full Text]

This article has been cited by other articles:

G. L. Vourlitis, G. Zorba, S. C. Pasquini, and R. Mustard Chronic Nitrogen Deposition Enhances Nitrogen Mineralization Potential of Semiarid Shrubland Soils Soil Sci. Soc. Am. J., April 5, 2007; 71(3): 836 - 842. [Abstract] [Full Text] [PDF]