Samples are tropical soils originating from the Albertine rift valley in Uganda. They consist of profiles from 3 cultivated sites receiving no external inputs such as fertilizer or phytosanitary products. These samples were chosen to represent a large spectrum of mineralogy. Preliminary analyses showed that site 1 was least weathered and richest in primary silicates (feldspars). Site 2 showed signs of more advanced weathering with a high content of secondary clays such as kaolinite and a relative enrichment in quartz. Site 3 was highly weathered with signs of desilicification and residual accumulation of iron oxides and oxyhydroxides. Site 3 contained an extremely high total iron concentration (34%, expressed as Fe2O3 oxide) due to the presence of plinthic material (iron-rich induration51,52). For each profile, two horizons were sampled: topsoil (A) and subsoil (B). CSDF was performed on these 6 samples in four replicates.
The first step in evaluating the effectiveness of the fractionation procedure is to look at recovery rates, (i.e., whether the initial material is quantitatively retrieved at the end of the experiment). We assessed recovery rates based on the whole soil and SOC contents.
Overall, whole soil recovery rates were considered to be very good, with 16 out of 20 replicates having recovery rates of more than 90% and 4 replicates showing recovery rates between 85-90% (Table 4). The cause of incomplete recovery was most likely a loss of dissolved and colloidal substances during rinsing. Two replicates showed a slight gain of mass (in the order of 1%) that could possibly be caused by SPT residues or weighing imprecisions. It should be noted that reasonable mass imbalances (<10-15%) are common and do not generally compromise the validity of the fractionation.
SOC recovery was generally within the range of reports from other studies53,54 and remarkably constant considering the large variation in initial SOC content (Table 5). Most samples showed a SOC recovery rate of 80-85%. Losses are attributable to the flushing of soluble C, which is an unavoidable feature of the method; however, soluble organic C can easily be quantified using a separate extraction in water, salt or chemical dispersant55. A small loss of dispersed organic colloids during fractionation is also likely. One site showed a slight gain of carbon which can probably be attributed to analytical error, as the absolute value for the difference was small (3 mg).
The method reproducibility may be verified by analyzing dispersion between replicates. We assessed the standard error of the mean (SEM) as well as the coefficient of variation (CV) of fraction mass between replicates.
Standard errors of the mean were small (Table 6), being generally 1 to 2 orders of magnitude smaller than mean values. This shows that working in 4 replicates allowed us to reliably estimate the central tendency for distribution of materials between fractions.
Coefficients of variation ranged from 2 to 70% (Table 7). All CVs greater than 35% occurred for fractions with small amounts of material (<0.25 g). These high values are simply due to the fact that division by a small mean yields high CVs. A few hF1 and hF3 fractions (coarse and fine silicates) showed relatively high CVs, between 20-35%, yet comprised large amounts of materials (1 - 4 g). This may reflect the high potential for human errors during several sensitive steps (i.e., (1) the separation of floating and suspended materials from the pellet in dense solutions, (2) sedimentation to isolate particle size fractions, (3) sample rinsing and recovery). This result confirms the need to work in several replicates to obtain robust results. It is also recommended that the whole process be handled by the same person, who becomes an expert in performing manipulations in a reproducible way and will acutely notice any details that might be different from previous batches.
The distribution of material mass between fractions showed strong differences between sites, as could be expected given the initial differences in mineralogy (Figure 2). At site 1, dominated by primary silicates such as quartz and feldspars, most of the material was recovered in hF1 (designed to concentrate coarse silicates). Site 2 showed a greater percentage of phyllosilicates (mostly kaolinite) during mineralogical analysis; accordingly, hF3 (designed to concentrate fine silicates) had more materials than at site 1. Finally, site 3 was the richest in oxides and also showed the greatest amount of material in hF2, designed to concentrate coarse oxides. This indicates that the method was successful in physically fractionating bulk samples into their main mineralogical components.
The amount of materials recovered in coarse (hF1 + hF2) versus fine (hF3 + hF4) fractions was compared to what was expected based on particle-size distribution determined by laser granulometry (Table 8). Agreement was good (< 10%) for three samples. The three other samples showed an excess of material in the order of 20% in the coarse fractions. The large amount of oxides in the soils (particularly at site 3) may be partially responsible for this difference. Oxide grains have a greater density compared to silicates and will sediment faster. Other factors could include incomplete dispersion or partial flocculation of samples during sedimentation, since we did not use chemical dispersion, and removal of some fine materials in the light fractions (fLF and oLF). Finally, laser granulometry is based on volume estimates under the assumption of particle sphericity, while sedimentation yields mass-based estimates. These contrasting principles of measurement are likely to give somewhat diverging results.
CSDF isolates fractions of relative mineralogical homogeneity and their associated organic matter (organo-mineral complexes). It is most useful as a preparation step prior to subsequent geochemical, biochemical and mineralogical analyses. Arguably, the most powerful experiments will aim to characterize both the organic matter and the minerals in each fraction. This will provide direct evidence for the nature of organo-mineral association in soils.
Sample analyses could include determination of SOM quantity (e.g., elemental analysis of organic C and total nitrogen) and quality (e.g., differential Fourier-transform infrared spectroscopy, pyrolysis gas chromatography mass spectrometry, or thermal analysis such as Rock-Eval pyrolysis56,57,58). When looking at the mineral partner, useful analyses could include particle size analysis, quantification of reactive aluminum and iron phases59, X-ray diffraction (XRD) on powdered samples for bulk mineralogy or on oriented slides for clay mineralogy60.
Techniques able to yield simultaneous information on both the organic and inorganic components could be of particular interest. Elemental mapping by secondary ion mass spectrometry (SIMS) or electron microscopy coupled with X-ray microanalysis (WDS or EDS, wavelength or energy dispersive X-ray spectroscopy) can allow for the co-localization of C, N and elements associated with reactive mineral phases such as Fe, Al, Mn or Ca. X-ray photoelectron spectroscopy (XPS) can reveal the chemical composition of SOM and the surface elemental composition of each fraction61.

Figure 1: Flowchart. Fractionation steps and cut-offs used in the method are presented here. Please click here to view a larger version of this figure.

Figure 2: Distribution of materials between fractions as a function of soil mineralogy for two horizons (A and B) at three sites. (A) Bar chart showing the repartition of materials between fractions. Bars represent the mean and error bars represent the standard error of the mean of four replicates. For each sample, the five bars sum to 100%. (B) Bulk sample mineralogy as assessed by powder X-ray diffraction. Please click here to view a larger version of this figure.
| Soil component | Class | Density [g cm-3] | Size distribution | Source |
| Organic | Organic matter | 1.00-1.50 | Variable | Multiple sources. See Rühlmann et al. (2006)25 for a review |
| Imogolite | Poorly crystalline phase | 1.70-2.33 | Clay | Wada and Wada (1977)26 |
| Allophane | Poorly crystalline phase | 1.84-2.35 | Clay | Wada and Wada (1977)26 ; Wilson (2013)27 |
| Opal | Poorly crystalline phase | 1.90-2.30 | Variable | Hudson Institute of Mineralogy (2017)28 |
| Montmorillonite | Clay mineral | 2.30-2.35 | Clay | Wada and Wada (1977)26; Wilson (2013)27 |
| Vermiculite | Clay mineral | 2.30-2.50 | Clay | Wilson (2013)27 |
| Gibbsite | Al oxide | 2.34-2.42 | Variable | Hudson Institute of Mineralogy (2017)28 |
| K-feldspars | Primary Si-rich silicates | 2.54-2.57 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Albite | Primary Si-rich silicates | 2.60-2.62 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Kaolinite | Clay mineral | 2.60-2.68 | Clay and silt | Klein and Philpotts (2017)29; Wilson (2013)27 |
| Quartz | Primary Si-rich silicates | 2.63-2.66 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Calcite | Carbonate | 2.71 | Variable | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Anorthite | Primary Si-rich silicates | 2.74-2.76 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Illite | Fine-grained mica | 2.75-2.80 | Clay | Wilson (2013)27; Hudson Institute of Mineralogy (2017)28 |
| Muscovite | Mica | 2.77-2.88 | Variable | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Biotite | Mica | 2.78-3.20 | Variable | Klein and Philpotts (2017)29; Skopp (2000)30 |
| Dolomite | Carbonate | 2.84-2.86 | Variable | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Amphiboles | Primary ferromagnesian silicates | 3.00-3.40 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Pyroxenes | Primary ferromagnesian silicates | 3.20-3.60 | Silt and sand | Klein and Philpotts (2017)29; Hudson Institute of Mineralogy (2017)28 |
| Goethite | Fe oxide | 3.30-4.37 | Variable | Hiemstra and van Riemskijk (2009)31; Klein and Philpotts (2017)29 |
| Ferrihydrite | Fe oxide | 3.50-3.90 | Clay | Hiemstra and van Riemskijk (2009)31 |
| Lepidocrocite | Fe oxide | 4.00-4.13 | Variable | Hiemstra and van Riemskijk (2009)31; Hudson Institute of Mineralogy (2017)28 |
| Hematite | Fe oxide | 4.80-5.30 | Variable | Klein and Philpotts (2017)29; Skopp (2000)30 |
Table 1: Main soil components in order of increasing density. Their prevalence in the main textural classes (clay fraction, 0-2 µm; silt fraction, 2-50 µm; sand fraction, 50-2000 µm) for moderately weathered soils is also indicated.
| Name of fraction | Abbreviation | Cut-offs |
| Free organics | fLF | < 1.62 g cm-3 (before sonication) |
| Occluded organics | oLF | < 1.62 g cm-3 (after sonication) |
| Coarse silicates | hF1 | > 8 µm, 1.62 g cm-3< hF1 < 2.78 g cm-3 |
| Coarse oxides | hF2 | > 8 µm, > 2.78 g cm-3 |
| Fine silicates | hF3 | < 8 µm, 1.62 g cm-3< hF3 < 2.78 g cm-3 |
| Fine oxides | hF4 | < 8 µm, > 2.78 g cm-3 |
Table 2: List of fractions resulting from CSDF using one sonication, two density and one size separation steps.
| Solution volume [mL] | Desired density [g cm-3] | Mass SPT [g] | Volume H2O [mL] |
| 1000 | 1.6 | 741 | 856 |
| 1000 | 1.8 | 990 | 810 |
| 1000 | 2 | 1250 | 750 |
| 1000 | 2.2 | 1490 | 715 |
| 1000 | 2.4 | 1803 | 595 |
| 1000 | 2.6 | 2052 | 545 |
| 1000 | 2.8 | 2297 | 504 |
| 1000 | 3 | 2552 | 450 |
Table 3: Guide to the preparation of common SPT solutions.
| Site | Horizon | Replicate | Starting mass
[g] | Final mass
[g] | Difference
[g] | Difference
[%] |
| 1 | A | 1 | 10.110 | 9.531 | 0.579 | 5.73 |
| 2 | 10.057 | 9.354 | 0.703 | 6.99 |
| 3 | 10.010 | 8.589 | 1.421 | 14.19 |
| 4 | 10.043 | 10.197 | -0.154 | -1.53 |
| B | 1 | 10.054 | 9.891 | 0.163 | 1.62 |
| 2 | 10.069 | 9.746 | 0.323 | 3.21 |
| 3 | 10.058 | 9.699 | 0.359 | 3.57 |
| 4 | 10.059 | 9.782 | 0.277 | 2.76 |
| 2 | A | 1 | 10.130 | 9.252 | 0.878 | 8.67 |
| 2 | 10.182 | 9.246 | 0.936 | 9.20 |
| 3 | 10.053 | 9.372 | 0.681 | 6.77 |
| 4 | 10.031 | 9.577 | 0.454 | 4.53 |
| B | 1 | 10.123 | 8.824 | 1.299 | 12.83 |
| 2 | 10.052 | 8.938 | 1.114 | 11.08 |
| 3 | 10.029 | 9.006 | 1.023 | 10.20 |
| 4 | 10.086 | 9.118 | 0.968 | 9.60 |
| 3 | A | 1 | 10.020 | 9.187 | 0.833 | 8.32 |
| 2 | 10.060 | 9.139 | 0.921 | 9.15 |
| 3 | 10.069 | 9.386 | 0.683 | 6.79 |
| 4 | 10.049 | 9.638 | 0.411 | 4.09 |
| B | 1 | 10.071 | 9.207 | 0.864 | 8.58 |
| 2 | 10.065 | 9.314 | 0.751 | 7.46 |
| 3 | 10.155 | 10.241 | -0.086 | -0.85 |
| 4 | 10.046 | 9.549 | 0.497 | 4.95 |
Table 4: Recovery rate of whole soil, showing the starting mass at the beginning of the fractionation procedure and final mass calculated as the sum of all fractions. Differences are expressed as % starting mass.
| Site | Horizon | Starting SOC mass | Final SOC mass | Difference | Difference |
| [g] | [g] | [g] | [%] |
| 1 | A | 0.50 | 0.41 | 0.09 | 18.07 |
| B | 0.026 | 0.029 | -0.003 | -10.63 |
| 2 | A | 0.34 | 0.27 | 0.07 | 20.19 |
| B | 0.07 | 0.06 | 0.01 | 12.33 |
| 3 | A | 1.08 | 0.94 | 0.14 | 12.56 |
| B | 0.31 | 0.27 | 0.05 | 14.51 |
Table 5: Recovery rate of soil organic carbon. Initial SOC content was calculated as the product of organic C concentration measured by elemental analysis and initial sample mass. Final SOC content was calculated as the product of organic C concentration and each fraction mass, summed for all fractions. Differences are expressed as % starting mass.
| Site | Horizon | fLF
1.62 g cm-3 | oLF
1.62 g cm-3 | hF1
> 8 µm
< 2.78 g cm-3 | hF2
> 8 µm
> 2.78 g cm-3 | hF3
< 8 µm
< 2.78 g cm-3 | hF4
< 8 µm
> 2.78 g cm-3 |
| 1 | A | 0.0794 ± 0.0052 | 0.1093 ± 0.0076 | 5.2188 ± 0.3079 | 0.3925 ± 0.0416 | 3.3699 ± 0.1504 | 0.2478 ± 0.0689 |
| B | 0.0044 ± 0.0005 | 0.0074 ± 0.0011 | 8.4351 ± 0.16 | 0.2569 ± 0.0301 | 0.9528 ± 0.1013 | 0.1226 ± 0.0124 |
| 2 | A | 0.066 ± 0.011 | 0.1353 ± 0.0152 | 5.722 ± 0.1033 | 0.2575 ± 0.008 | 3.0761 ± 0.1464 | 0.1047 ± 0.0364 |
| B | 0.0024 ± 0.0002 | 0.0165 ± 0.0022 | 4.5416 ± 0.0387 | 0.3082 ± 0.0072 | 4.0005 ± 0.0547 | 0.1025 ± 0.0268 |
| 3 | A | 0.2107 ± 0.0099 | 0.1489 ± 0.0223 | 3.8507 ± 0.6801 | 1.762 ± 0.0923 | 3.2862 ± 0.4892 | 0.0792 ± 0.0165 |
| B | 0.0305 ± 0.0035 | 0.0433 ± 0.0065 | 2.5929 ± 0.376 | 4.1277 ± 0.1025 | 2.6909 ± 0.13 | 0.0927 ± 0.0087 |
Table 6: Mean value and SEM for fraction mass (g). Each cell represents a mean of 4 replicates.
| Site | Horizon | fLF
< 1.62 g cm-3 | oLF
< 1.62 g cm-3 | hF1
> 8 µm
< 2.78 g cm-3 | hF2
> 8 µm
> 2.78 g cm-3 | hF3
< 8 µm
< 2.78 g cm-3 | hF4
< 8 µm
> 2.78 g cm-3 |
| 1 | A | 0.13 | 0.14 | 0.12 | 0.21 | 0.09 | 0.56 |
| B | 0.22 | 0.29 | 0.04 | 0.23 | 0.21 | 0.20 |
| 2 | A | 0.33 | 0.22 | 0.04 | 0.06 | 0.10 | 0.70 |
| B | 0.17 | 0.26 | 0.02 | 0.05 | 0.03 | 0.52 |
| 3 | A | 0.09 | 0.30 | 0.35 | 0.10 | 0.30 | 0.42 |
| B | 0.23 | 0.30 | 0.29 | 0.05 | 0.10 | 0.19 |
Table 7: Coefficients of variation of fraction mass for 4 replicates.
| Site | Horizon | Texture
< 8 µm
% | Texture
> 8 µm
% | Materials in fine fractions
(hF3 + hF4)
% | Materials in coarse fractions
(hF1 + hF2)
% | Coarse fraction
'excess'
% |
| 1 | A | 48 | 52 | 39 | 61 | 9 |
| B | 31 | 69 | 11 | 89 | 20 |
| 2 | A | 43 | 57 | 35 | 65 | 8 |
| B | 46 | 54 | 46 | 54 | 1 |
| 3 | A | 58 | 42 | 37 | 63 | 21 |
| B | 52 | 48 | 29 | 71 | 23 |
Table 8: Comparison between soil's texture determined by laser granulometry and the distribution of particles in size fractions. The last column shows the excess of materials in the coarse fractions compared to what was expected based on textural analysis.