soil properties controlling the adsorption of dissolved

soilsci_08-0254 Kothawala.inddSSSAJ: Volume 73: Number 6 • November–December 2009 1831
Soil Sci. Soc. Am. J. 73:1831-1842 doi:10.2136/sssaj2008.0254 Received 4 Aug. 2008. *Corresponding author ([email protected]). © Soil Science Society of America 677 S. Segoe Rd. Madison WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
Dissolved organic C represents the most mobile, dynamic, and reactive component of the soil C pool. Th e rapid ki-
netics of sorption processes between the mineral soils and DOC allows steady-state conditions to occur within minutes, even during rapid percolation ( Jardine et al., 1989; Dahlgren and Marrett, 1991; Qualls and Haines, 1991). Consequently, DOC retention within mineral soils is largely a result of the abiotic processes of adsorption and desorption, followed by slow biodegradation (Qualls et al., 2002). Identifying and understanding controls on the adsorption, stabilization, and degradation of organic matter within mineral soils is particularly relevant to the cycling of soil C, and can allow better prediction of C inputs to aquatic systems (see von Lützow et al., 2006).
Some studies have attempted to link mineral and chemical soil properties to adsorption characteristics derived from adsorption isotherms, using a range of soil types (e.g., Moore et al., 1992; Kaiser et al., 1996) and for a particular soil type (e.g., Vance and
David, 1989). Previous studies have found that Fe and Al oxides and oxyhydroxides are strongly related to DOC adsorption. Gu et al. (1994) proposed ligand exchange for reactive surface hydroxyls as the dominant mechanism of DOC adsorption to Fe oxides, and found the association to be largely irreversible. A number of other possible mechanisms of interaction between the mineral soils and DOC have been proposed including cation bridging and anion exchange (Inoue and Wada, 1968; Tipping, 1981; Sposito, 2004). Organic–organic associations between DOC and soil C, such as H bonding and van der Waal’s forces, may occur at high concentrations, but the mechanisms of retention are poorly understood (Qualls, 2000; Tan 2003).
Clay content has also been reported to infl uence DOC adsorption in some studies (e.g., Jardine et al., 1989; Shen, 1999), while in others it had a relatively weak infl uence on DOC adsorption compared with Fe and Al oxides and oxyhydroxides (Kaiser and Zech, 2000). Soil C has been shown to have a negative infl u- ence on further DOC adsorption by potentially blocking active binding sites on the soil particle surfaces ( Jardine et al., 1989; Moore et al., 1992; Kaiser et al., 1996; Kaiser and Zech, 2000), although its role remains uncertain (Loft s et al., 2001).
Th e linear initial mass (IM) isotherm has been the most common isotherm approach used to describe DOC adsorption to and desorption from mineral soils (Nodvin et al., 1986). Recent studies have shown that a modifi ed Langmuir isotherm can provide a better fi t to experimental data than the linear IM isotherm when using a broad initial DOC concentration range (>500 mg kg−1, see Vandenbruwane et al., 2007; Kothawala et al., 2008). Th e Langmuir approach holds the advantage of providing
D. N. Kothawala* T. R. Moore Dep. of Geography and Global Environmental & Climate Change Center (GEC3) McGill Univ. 805 Sherbrooke St. West
Montréal, QC, H3A 2K6 Canada
W. H. Hendershot Dep. of Natural Resource Sciences Macdonald Campus McGill Univ. 21, 111 Lakeshore Rd. Ste-Anne-de-Bellevue Montréal, QC, Canada
SO IL C
Soil Properties Controlling the Adsorption of Dissolved Organic Carbon to Mineral Soils
Dissolved organic C (DOC) is the most reactive and mobile component of soil C and can be retained within mineral soils by adsorption. We determined the adsorption characteristics for 52 mineral soil samples from 17 temperate and boreal soil profi les, using a modifi ed Langmuir equation. Th e DOC solution used for batch experiments was derived from the organic horizons of a Spodosol. We analyzed the extent to which soil properties, such as the sum of poorly crystalline Fe and Al (Fepc + Alpc), texture, and soil C, are related to DOC adsorption to mineral soils. Sorption characteristics including the maximum adsorption capacity (Qmax), and the null point (np), where adsorption equals desorption, were best explained by Fepc + Alpc (R2 = 0.55 and 0.28, respectively). Th e Alpc exerted a stronger infl uence than Fepc on Qmax. A simple method for estimating Qmax was developed whereby the change in pOH aft er treatment with NaF is well correlated to Fepc + Alpc (R2 = 0.71, P < 0.0001) and Qmax (R2 = 0.50, P < 0.0001). Th e infl uence of clay content on Qmax was of secondary importance and was largely masked by the dominant infl uence of Fepc + Alpc. Soil C did not have any infl uence on Qmax, but a slight negative infl uence on np. Th e B horizons of Spodosols and volcanic soils had the greatest Qmax, while large levels of soil C in Spodosols produced a high desorption potential. Results from this study emphasize the importance of considering the adsorption potential in conjunction with the desorption potential for better prediction of changes to the size of mineral soil C pools and DOC export to aquatic systems.
Abbreviations: Alo, oxalate-extractable aluminum; Alp, pyrophosphate-extractable aluminum; Alpc, poorly crystalline aluminum; Cp, pyrophosphate-extractable carbon; DOC, dissolved organic carbon; ECEC, eff ective cation exchange capacity; Fecry, crystalline iron; Fed, dithionite-extractable iron; Feo, oxalate-extractable iron; Fep, pyrophosphate-extractable iron; Fepc, poorly crystalline iron; IM, initial mass; SMR, stepwise multiple regression.
1832 SSSAJ: Volume 73: Number 6 • November–December 2009
an estimate of the maximum adsorption capacity (Qmax) of DOC to soil horizons. Gu et al. (1995) has suggested that Fe oxides may have a limited number of adsorption sites available. Likewise, the surface area of mineral soils has been proposed as the factor limit- ing the amount of organic matter able to accumulate on mineral soils (Kaiser and Guggenberger, 2003). Consequently, it is use- ful to identify the Qmax of DOC to mineral soils and, further, to identify key soil properties related to the Qmax. A modifi ed version of the Langmuir isotherm has been used previously to describe DOC partitioning to minerals soils (Lilienfein et al., 2004; Vandenbruwane et al., 2007). To estimate the desorption potential (b), a modifi ed version of the Langmuir isotherm, using the initial solution concentration (Xi), is used. A modifi ed version of the Langmuir isotherm using the fi nal solution concentration (Xf ) is used to predict the Qmax, as well as the null point (np), which is the Xf where adsorption and desorption are equal.
We related DOC adsorption characteristics derived from the modifi ed Langmuir isotherm (b, np, and Qmax) to a broad range of mineral soil properties. We used 52 mineral soil samples, with varying mineral and chemical properties, collected from 17 profi les across Canada, including Spodosols, Andisols, Inceptisols, Alfi sols, and a Histosol (Podzols, Brunisols [including volcanic], Gleysols, Luvisols, and an organic soil; Soil Classifi cation Working Group, 1998), which are typical of temperate and boreal forests. We determined DOC sorption characteristics, including b, np, and Qmax, by applying a modifi ed Langmuir isotherm using a series of initial solutions varying in DOC concentration from 0 to 1200 mg kg−1. Th e DOC solution used for our sorption experiments was derived from the organic horizons of a Spodosol. Our objectives were to analyze the extent to which soil properties, such as texture, the amount of Fe and Al associated with poorly crystalline phases, and soil C, are related to the sorption characteristics derived from the modifi ed Langmuir isotherm. We tested the eff ectiveness of a simple experimental technique to measure the F− reactivity of mineral soils and relate it to the Qmax. We also examined the extent to which soil type and soil horizon can capture generalized patterns of sorption characteristics.
MATERIALS AND METHODS Study Sites
Fift y-two soil samples, including nine horizon types, were collected from 17 soil profi les and represent fi ve soil orders (Tables 1 and 2).
Campbell River sites are located on Vancouver Island and developed on volcanic ash, with thin organic horizons (≤5-cm depth) and thin (<1 cm) or no Ah horizon. Saskatchewan Waskesiu sites (BS, JP, AS) are located on the southern edge of the boreal forest. Black spruce (BS), jack pine (JP) and aspen (AS) sites are covered with 21, 8, and 7 cm of organic soil, respectively. Th e Waskesiu Lake region has clay deposits, as found at AS and BS sites, as well as sandy deposits, found at the JP site. Groundhog River is located in northern Ontario on heavily mottled clayey soils. Organic horizons overlying Orthic and Humic Gleysols are 6 to 13 and 30 cm thick, respectively. Mineral horizons from the organic soil were collected from a conifer swamp with a 1.2-m-thick organic horizon. Turkey Point sites are developed on lacustrine sand plains (Peichl et al., 2007) on the northern shore of Lake Erie, and are overlain by organic horizons 5 to 7 cm thick. Plastic Lake watershed soils are developed on basal tills, with a bedrock of mainly granitized biotite
and hornblende gneiss (Watmough and Dillon, 2003), with an organic horizon 15 cm thick. Hermine watershed soils developed on shallow till with anorthositic bedrock with an organic layer 10 cm thick (Courchesne et al., 2005). Lac Lafl amme watershed soils had an overlying organic horizon 8 cm thick. Lac Tirrase soils are developed on thick undiff erentiated till, with parent material originat- ing from sedimentary rocks, shales, sandstone, conglomerates, and volcanites (Tremblay et al., 2006). Th e overlying organic horizon at Lac Tirrase was 16 cm deep.
Soil Properties Soils were sieved to <2 mm, air dried, and stored at 4°C.
Clay soils were air dried and gently crushed before sieving. Soil pH (pHCaCl2) was measured in 0.01 mol L−1 CaCl2 using a soil/solution ratio of 1:2. Total soil C and N were determined by an elemental analyzer (Carlo Erba NC2500, Milan, Italy). Eff ective cation exchange capacity (ECEC) was determined by the method of Hendershot et al. (2007), and cations were analyzed by fl ame atomic absorption spectroscopy (Perkin Elmer 2380, Perkin Elmer Corp., Norwalk, CT). Particle size analysis for sand, silt, and clay was performed by the sieve pipette method, aft er the removal of organic C by H2O2, with dispersion using sodium metaphosphate and NaO3 (Sheldrick and Wang, 1993).
Th ree extractions (Ross and Wang, 1993) were used to estimate the amount of Fe and Al associated with various chemical forms within soils (e.g., associated with crystalline and poorly crystalline phases and organic material). Th e extractions included: dithionite–citrate (Fed) (pH 7, USDA Soil Conservation Service, 1972), 0.2 mol L−1 acid ammonium oxalate (Feo and Alo) (pH 3, McKeague and Day, 1966), and 0.1 mol L−1 sodium pyrophosphate (Fep and Alp) (McKeague, 1967). Th e pyrophosphate extract was cleared by adding 0.5 mL of a 0.1% solution of Superfl oc N-100 (Cytec Canada, Niagara Falls, ON), centrifuged at ~510 × g for 10 min, and decanted. We measured the amount of pyrophosphate-extractable soil C (Cp) with a TOC analyzer (Shimadzu 5050, Shimadzu Corp., Kyoto, Japan). Th e amount of Fe associated with crystalline forms (Fecry) was estimated by taking the difference between Fed and Feo. Th e amount of Fe and Al associated with poorly crystalline phases (Fepc and Alpc) was estimated by taking the diff erence between the oxalate and pyrophosphate extractions (Feo − Fep and Alo − Alp). We recognize that each of the extraction methods is limited in the specifi city of targeting Fe and Al associated with the crystalline, poorly crystalline, amorphous, or organic phases. Th e oxalate extraction has been found to dissolve Fe and Al from poorly crystalline, amorphous, and organic material with little removal from the crystalline oxides (McKeague and Day, 1966). Th e sodium pyrophosphate method has been found to primarily extract organically complexed Fe and Al, with slight removal of Fe and Al from amorphous materials and only slight dis- solution of crystalline forms of Fe and Al (McKeague, 1967). Th e sum of Fepc + Alpc is thus an estimated value. Analysis of Fe and Al was performed by fl ame atomic absorption spectroscopy (Perkin Elmer AAnalyst 100). All extractions and ECEC cations included a minimum of fi ve samples done in triplicate, three sample blanks, and secondary standards to ensure method reproducibility, test for contamination, and ensure accuracy.
Th e change in solution pOH due to the addition of NaF (ΔpOHNaF) was measured to estimate the F− reactivity of soils (Fields and Perrott, 1966; Perrott et al., 1976). A solution of
SSSAJ: Volume 73: Number 6 • November –December 2009 1833
Ta bl
e 1.
D es
cr ip
ti on
Ta bl
e 2.
K ey
s oi
0.1 mol L−1 NaF in a soil (g) to solution (mL) ratio of 1:40 was shaken and allowed to equilibrate for 20 min prior taking the fi - nal solution pH. Th e method was repeated using deionized water (dH2O). Th e diff erence in OH− concentration, calculated from the pH in dH2O and NaF, was used to measure the ΔpOHNaF. Th e ΔpOHNaF analysis was performed in triplicate for all soil samples.
Dissolved Organic Carbon Dissolved organic C was extracted from the forest fl oor and
Oi, Oe, and Oa horizons of a Spodosol (LFH horizons of a Podzol; Soil Classifi cation Working Group, 1998) collected from Mt. Saint Hilaire, Quebec (45°33 N, 73°08 W). Th e intact LFH horizon (50 by 50 by 20 cm) was soaked in deionized water overnight. Th e soil solution was poured off and fi ltered with 0.45-μm glass fi ber fi l- ters (Rose Scientifi c, Edmonton, AB, Canada). Th e procedure was repeated for ~5 d until enough volume of leachate was collected. Th e combined original solution of leachate had a concentration of ~200 mg L−1, a pH of 4.8, and conductivity of 100 μS cm−1. Seven initial DOC solutions ranging from 0 to ~120 mg L−1 were created by diluting the original extract into a 0 mg L−1 solution of with similar ionic strength and pH. Th e 0 mg L−1 DOC solution consisted of 10 mg L−1 NaCl, 20 mg L−1 CaCl2·2H2O, and 24 mg L−1 K2SO4 for a total ionic strength of 0.001 mol L−1. Fresh initial DOC solutions were created for every batch of approximately six isotherms, and initial solution concentrations were determined with every batch of isotherms. Th e pH of the solutions before and aft er equilibration to mineral soils was measured to determine the change in solution pH on reaction of DOC with the mineral soils.
Sorption Isotherms Th irty milliliters of initial DOC solution was added to 3 g of
soil in 50-mL centrifuge vials, which were shaken by hand and laid fl at on a horizontal shaker for 24 h at 4°C. Th e vials were placed upright to settle for ~30 min before fi ltration with 0.45-μm glass fi ber fi lters (Rose Scientifi c). Th e fi ltrate was acidifi ed to pH 3 with dropwise addition of 2 mol L−1 HCl, and analyzed for total non- purgeable organic C, operationally defi ned as DOC here, using a Shimadzu TOC 5050 total C analyzer.
Th e Langmuir isotherm was modifi ed by adding a b term (Eq. [1]), allowing an adjustable y intercept. Th e Langmuir equation expresses a relationship between the amount of substance adsorbed or desorbed (RE) (in mg kg−1), and the fi nal equilibrium solution concentration (Xf ) (mg kg−1), the binding affi nity (k) (kg solution kg−1 soil), and the maximum adsorption capacity (Qmax) (in mg kg−1). Th e null point (np) is calculated as the Xf (in mg kg−1) where no net exchange of DOC between the soil and solution occurs, when RE is equal to 0 mg kg−1. Th e Qmax was estimated with with Eq. [1]:
max f
kX = -
+ [1]
Th e potential desorption (b) was derived from the Langmuir isotherm using the initial solution concentration (Xi) rather than the Xf:
max i
kX = -
+ [2]
Consequently, the b term was derived from Eq. [2], and provides an estimate of the amount of DOC desorbed from the mineral soil surface when the initial DOC concentration is 0 mg L−1.
Statistical Analysis All soil properties and sorption characteristics were log10 trans-
formed, with the exception of pH and ΔpOHNaF. Linear regression was performed between sorption characteristics and soil properties. Regression models for sorption characteristics, log Qmax, log np, and log b, were developed using stepwise multiple regression (SMR), with forward selection using JMP 7 (SAS Institute, Cary, NC). Due to common soil formation factors, several soil properties were related (Table 3). Th e SMR analysis considers key relationships. We combined Fepc and Alpc into one predictor (Σ(Fepc + Alpc)) since the chemical forms of these elements are strongly correlated (R2 = 0.60), and subsequently tested the relative infl uence of Fepc and Alpc. Th e same was done for Feo and Alo. Rather than include all soil properties in SMR analysis, we sequentially tested the infl uence of related soil extractions. For instance, Fep + Alp was not a strong predictor of Qmax, thus during SMR analysis this soil property was not included due to relationship with Fepc + Alpc. In addition, SMR was performed with only one of: Fepc + Alpc, Feo + Alo, or ΔpOHNaF, rather than including all three strongly related soil properties. A comparison of the means of individual soil horizons and horizon groups was performed with the Tukey–Kramer honestly signifi cant test, performed at a signifi cance threshold of P < 0.05.
RESULTS Soil Characteristics
A broad range of soil characteristics were represented across the eight sampling locations, fi ve soil orders, and nine mineral soil horizons (Table 2). Soil properties including soil pH, soil C, sand content, and Fepc + Alpc (Fig. 1) were compared across four major horizon groupings, including A horizons (Ah, Ahe, and Ae), B horizons (Bm, Bt, and Bg), Podzol B horizons (Bf, Bfj , Bfh , and Bcc) and volcanic B horizons (Bfj and Bf ).
Soil pHCaCl2 ranged from 3.4 to 7.6. Based on the bulk horizon groups, the Fe-enriched Podzol B horizons were signifi cantly more acidic (4.4 ± 0.4) than other groups (Fig. 1a). Soil C content across all soils ranged from 0.5 to 84.8 g kg−1, with the highest levels observed in the Bfh horizons of the Podzols (Table 2). Th is resulted in signifi cantly higher soil C for the Podzol B horizons (Fig. 1b) than other bulk horizon groups. Th ere was no signifi cant diff erence in sand or clay contents between the bulk soil horizon groups (Fig. 1c). Th e Fepc + Alpc was signifi cantly higher for the two Fe-enriched B horizon groups (Podzol and volcanic) compared with the other horizon groups (Fig. 1d). Likewise, the ΔpOHNaF was signifi cantly lower for the Fe-enriched B horizons soils (not shown, Tukey–Kramer, P < 0.05), corresponding to a greater increase in OH− on the addition of NaF. Th e reproducibility (mean ± standard deviation) of extractions was as follows: Fed, 1 ± 33%; Feo, 6 ± 25%; Alo, 5 ± 10%; Fep, 8 ± 20%; Alp, 20 ± 41%. When isotherms from the 52 mineral soils were separated into four groups, each group had a visibly distinct shape (Fig. 2), with corresponding sorption characteristics.
Sorption Characteristics and Their Controls Th e Qmax ranged from 60 to 5500 mg kg−1, with an average
of 851 ± 1076 mg kg−1 (Fig. 3a). Th ree extremely high Qmax estimates (3555–5500 mg kg−1) were derived for three Fe-enriched
Podzol horizons. While there was very little distinction between the Qmax of individual soil horizons, the four horizon groupings did show distinct patterns (Fig. 3a). Iron-enriched B horizons from Podzols (1867 ± 1750 mg kg−1) and volcanic soils (966 ± 448 mg kg−1) had signifi cantly higher Qmax values than
the B horizons without Fe enrichment (351 ± 152 mg kg−1) and the A horizons (172 ± 115 mg kg−1) (Fig. 3a).
Th e log Qmax was most strongly related to log Σ(Fepc + Alpc), log Σ(Feo + Alo), and ΔpOHNaF, which explained 55, 53, and 50% of the variability, respectively (Table 4). A strong relation-
Fig. 1. Soil properties (a) soil pH, (b) soil C, (c) sand content, and (d) the sum of poorly crystalline Fe and Al, by major horizon groups: A horizons (Ah, Ae, and Ahe), B horizons (Bg, Bm, and Bt), Fe-enriched Podzol B horizons (Bf, Bfh, Bcc, and Bfj), and Fe-enriched B horizons of volcanic soils (Bfj and Bf). The line in the middle of the boxes represents the median, with the lower and upper parts of the box representing 25 and 75% of the distribution, respectively, while the lower and upper whiskers represent 10 and 90% of the distribution, respectively. Horizon groups not sharing the same lowercase letter are signifi cantly different from each other based on the Tukey–Kramer honestly signifi cant difference comparison of means (P < 0.05). Sample sizes for A, B, Podzol B, and volcanic B groups were 9, 17, 11, and 9, respectively. Two C horizons were excluded from this analysis.).
Table 3. Individual coeffi cients of determination (R2) between soil properties and sorption characteristics† (n = 52). Italic values indicate a negative relationship.
pH(CaCl2) Log soil C Log clay content
Log ECEC Log Fecry Log Σ
(Feo + Alo) Log Σ
Log clay content 0.05 0.01 –
Log ECEC 0.15* 0.14* 0.40*** –
Log Fecry 0.00 0.12* 0.12* 0.09* –
Log Σ(Feo + Alo) 0.18* 0.35*** 0.02 0.03 0.29* –
Log Σ(Fepc + Alpc) 0.08* 0.13* 0.07 0.12* 0.19** 0.87*** –
pOHNaF 0.04 0.13* 0.10* 0.15* 0.13* 0.69*** 0.71*** –
Log Qmax 0.00 0.12* 0.00 0.01 0.29*** 0.53*** 0.55*** 0.50*** –
Log np 0.03 0.00 0.05 0.16* 0.02 0.15* 0.28** 0.15* 0.12* – Log b 0.13* 0.35*** 0.12* 0.14 0.05 0.13* 0.02 0.00 0.05 0.13* – * Signifi cant at the 0.05 level. ** Signifi cant at the 0.01 level. *** Signifi cant at the 0.001 level. † ECEC, effective cation exchange capacity; Fecry, crystalline Fe; Feo and Alo, oxalate-extractable Fe and Al, respectively; Fepc and Alpc, poorly crystalline Fe and Al, respectively; pOHNaF, change in pOH due to addition of NaF; Qmax, maximum adsorption capacity; np, null point; b, desorption capacity.
ship was observed between the ΔpOHNaF method and log Σ(Fepc + Alpc) (R2 = 0.71) as well as log Σ(Feo + Alo) (R2 = 0.69) (Fig. 4, Table 3). Multiple regression with log Σ(Fepc + Alpc) showed that log(clay content) was of secondary importance, along with Fecry, which raised the R2 to 0.57 and 0.60, respectively, and lowered the RMSE (Table 4). Likewise, the incorporation of log Fecry and log(clay content) as secondary predictors in the multiple regression analysis with ΔpOHNaF improved the R2 to 0.64 and 0.57, respectively (Table 4).
Th e average np for all soils was 161 ± 174 mg kg−1 and ranged from 12 to 875 mg kg−1 (Table 2). No distinction could be made based on individual horizon type or horizon group (Fig. 3b). Th e np for three Ae soil horizons was never achieved, since they contin- ued to release DOC within the experimental range, and these three were thus excluded from the SMR analysis.
Th e strongest predictor of log np was log Σ(Fepc + Alpc), which explained 28% of the variability (Table 4), whereas a higher amount of Alpc and Fepc resulted in a lower np concentration, thus resulting in a negative relationship. Th e log Σ(Feo + Alo) could predict 15% of the variability in log np. Th e additional infl uence of soil C and log Σ(Fepc + Alpc) improved the regression with np to explain 32% of the variability (Table 4). Secondary predictors of log np also included the ECEC, which improved the multiple regression to R2 = 0.33 (Table 4). Among the cations, exchangeable K+ contributed the greatest amount of variability (Table 4). Th e remaining cations produced relationships with low levels of signifi cance at P > 0.20. Th e regression between
log np and ΔpOHNaF was signifi cant (R2 = 0.15, P = 0.008) but weaker than the regression with Σ(Fepc + Alpc).
We distinguished the relative infl uence of strongly related soil properties, Fepc and Alpc (R2 = 0.60), on the sorption characteristics log Qmax and log np (Table 5). Multiple regression analysis between sorption properties and Alpc and Fepc (in mol kg−1) showed that Alpc had a stronger eff ect than Fepc for the prediction of log Qmax, and to a lesser extent for log np. For the prediction of log Qmax, Alpc had a lower associated P value and higher t ratio (P = 0.005, t = 2.92) than Fepc (P = 0.04, t = 2.16) (Table 5). Similar but weaker relationships were observed for log np (Table 5). Th e relative infl uence of Feo and Alo on the prediction of log Qmax was tested and we found Alo had a stronger infl uence than Feo (Table 5).
Th e average desorption (b) for all soils was 76 ± 52 mg kg−1 and ranged from 4 to 256 mg kg−1. No distinction could be made of b based on individual horizon type. When the horizons were grouped, the Podzol B horizons had signifi cantly greater desorption (120 ± 63 mg kg−1) than the three other groups, volcanic B horizons (62 ± 45 mg kg−1), A horizons (67 ± 43 mg kg−1), and B horizons without Fe enrichment (50 ± 28 mg kg−1) (Fig. 3c).
Dissolved organic C desorption (b) was most strongly related to log(soil C content) (R2 = 0.24, Table 4) and Cp (R2 = 0.26), with a strong correlation between soil C and Cp (R2 = 0.75). No other soil properties contributed signifi cantly to a multiple regression of b.
Th e solution-phase pH of Podzol B horizons decreased by a mean of 0.28 ± 0.23 during the equilibration, while volcanic B horizons had an increase in solution pH by 0.12 ± 0.15 (Fig. 5).
Fig. 2. Comparison of average dissolved organic C (DOC) isotherms for the (a) A horizons, (b) B horizons, (c) Fe-enriched Podzol B horizons, and (d) Fe-enriched B horizons of volcanic soils. The light gray circles represent individual isotherm data points.
Th e pH values of the other B horizons increased by 0.41 ± 0.11, and the mean change for solution pH of the A horizons was 0.01 ± 0.16 (Fig. 5).
DISCUSSION Th e 52 mineral soil samples used in this study represent a
diversity of mineral and chemical soil characteristics typical of temperate and boreal forested ecosystems. Th us, key relationships identifi ed between soil properties and DOC sorption characteristics should be generally applicable to these regions. Th e DOC leachate used for the batch experiments was derived from the bulk organic (L, F, and H) horizons of a Podzol. Th e nature of the DOC can infl uence adsorption characteristics such as the np, which was found to vary between 20 and 67 mg L−1 when DOC leachates from diff erent sources were used on the same mineral soil (Moore and Matos, 1999). We used one DOC source to place focus on identifying the soil properties controlling sorption characteristics. As the soil solution pH and ionic strength can have a strong infl uence of DOC retention and release (Vance and David, 1989), we maintained a constant solution pH and ionic strength across all initial DOC solutions used to create the isotherms.
Iron and Aluminum Associated with Poorly Crystalline Phases
Th e Qmax could be predicted almost equivalently based on the Fe and Al associated with poorly crystalline phases (Fepc and Alpc) or based on oxalate-extractable Fe and Al (Feo and Alo) (Table 4). We estimated the sum of Fepc + Alpc based on the diff erence between the oxalate and pyrophosphate extractions. Th e diff erence between oxalate- and pyrophosphate-extractable Fe has been suggested to provide an estimate of the amount of Fe derived largely from amorphous materials plus some crystalline material, without incorporation of the organically associated Fe (McKeague et al., 1971). Th e same has been noted to hold approximately true for Al (Courchesne and Turmel, 2007); however, there are concerns about the specifi city of the pyrophosphate extraction, particularly for organically associated Al. Kaiser and Zech (1996) found that the pyrophosphate extraction dissolved Al from the hydroxide phases, and in some cases found that more Al was removed by the pyrophosphate extraction than the oxalate (and dithionite–citrate) extraction of il- luvial podzolic horizons. We found that the amount of Fe and Al derived from the pyrophosphate extraction was always lower than that derived from the oxalate extractions, including the illuviated podzolic horizons (mean ± standard deviation for horizons in Table 2). Th e pyrophosphate extraction did target organically associated Fe and Al since we found a strong relationship between soil C and Cp (R2 = 0.74). We have not, however, examined the mineralogy of the Al and Fe complexes removed by oxalate or pyrophosphate extractions and thus cannot be sure of the amount of poorly crystalline Fe and Al removed by the pyrophosphate method. Th e oxalate extraction has been noted to dissolve poorly ordered phases like allophane and imogolite, which are typical of volcanic soils. Since our study did not target one specifi c soil type, we aimed to identify the best general predictor(s) of sorption characteristics (Qmax and np) across a range of soils, including those based on volcanic ash. In general, we consider the pyrophosphate extraction to have primarily removed organically complexed Fe and Al, with relatively small amounts of poorly crystalline structures. It would appear that the Fepc + Alpc approach may be sound for the estimation of poorly crystalline structures with the exclusion of organically associated material; however, we also present results from Feo + Alo (Table 4 and 5). As expected, we found a strong relationship between Fepc + Alpc and Feo + Alo (R2 = 0.87). Both measurements were found to predict the Qmax
Fig. 3. Comparison of dissolved organic C (DOC) adsorption isotherm characteristics of four soil horizon groups: A horizons (Ah, Ae, and Ahe), B horizons (Bg, Bm, and Bt), Fe-enriched Podzol B horizons (Bf, Bfh, Bcc, and Bfj), and Fe-enriched B horizons of volcanic soils (Bfj and Bf). Sorption characteristics include (a) the maximum sorption capacity, Qmax, (b) the null point, np, both derived from the Langmuir isotherm using fi nal concentration, and (c) the desorption term, b, derived from the Langmuir isotherm using the initial concentration. The line in the middle of the boxes represents the median, with lower and upper parts of the box representing 25 and 75% of the distribution, respectively, while the lower and upper whiskers represent 10 and 90% of the distribution, respectively. Horizon groups not sharing the same lowercase letter are signifi cantly different from each other based on the Tukey–Kramer honestly signifi cant difference comparison of means (P < 0.05), which is a conservative comparison for uneven sample sizes. Sample sizes for A, B, Podzol B, and volcanic B groups were 9, 17, 11, and 9, respectively. Two C horizons were excluded from analysis.
equally well; however, the np concentration was better predicted by Fepc + Alpc than Feo + Alo. Previous studies have found that soil C can have a negative infl uence on further adsorption at the np concentration (Jardine et al., 1989; Moore et al., 1992; Kaiser et al., 1996; Kaiser and Zech, 2000). Likewise, we found that the regression with Fepc + Alpc increased when the negative infl uence of soil C was incorporated into the stepwise multiple regression of np. Th is suggests that the np concentration could be predicted based on both the amount of poorly crystalline structures available for adsorption processes and the negative infl uence of soil C that could be desorbed into solution. Th e Fep + Alp was a relatively poor predictor of the Qmax (R2 = 0.39) and np (R2 = 0.07) compared with poorly crystalline forms of Fe and Al, suggesting that organically complexed forms of Fe and Al are less eff ective in the adsorption of DOC. Using Fepc and Alpc to predict the Qmax and np may have an advantage over using the Feo and Alo, since the infl uence of organically associated Fe and Al is reduced. Other studies using the linear IM isotherm have found Alo and Fed to be strong predictors of the np (Moore et al., 1992) and binding affi nity (m for the IM isotherm) (Moore et al., 1992; Kaiser et al., 1996). Th ese previous studies did distinguish the relative infl uence of Feo and Alo from the organically associated Fep and Alp.
We found that the relative infl uence of Alpc was stronger than Fepc at the np concentration (Table 5), suggesting that the dominant mechanisms controlling adsorption at the np concentration involved Alpc. Moore et al. (1992) also found that Alo had a stronger infl uence on the np concentration than Fed based on partial regression analysis. By using the Langmuir isotherm approach along with a wide range of soil types, we found that Alpc had a much stronger infl uence on DOC adsorption than Fepc at the high equilibrium concentrations of Qmax. It should be noted that nine of the 52 soils included in our set of soil samples are of volcanic ori- gin, and thus are expected to contain high levels of Al-containing poorly crystalline minerals such as allophane.
Change in pOH Due to Addition of Sodium Fluoride Th e traditional methods of extracting Fe and Al from min-
eral soils, such as dithionite–citrate, acid ammonium oxalate, and sodium pyrophosphate, are lengthy and labor intensive and can have poor reproducibility. In contrast, measuring the F− reactivity (ΔpOHNaF) simply involves taking the diff erence in pH before and aft er addition of NaF. Th e ΔpOHNaF method was performed in triplicate in a fraction of the time required for extractions. Th e ΔpOHNaF proved to be a good surrogate measure for Fepc + Alpc (Table 4), and was also well correlated to Qmax (Table 3). A poor- er correlation with the np may be due to the fact that desorption along with adsorption processes controls the np concentration. Th e ΔpOHNaF is a measure of the diff erence in solution pOH due to
the displacement of soil surface OH− by the added F−. Th e addition of NaF has been shown to release OH− associated with noncrystalline and poorly ordered inorganic materials, particularly allophane (Perrott et al., 1976). A limitation to the ΔpOHNaF method is the excessive reaction with Al hydrous phases relative to the Fe hydrous phases. Consequently, the strong relationship we observed between Fepc + Alpc and ΔpOHNaF may be due in part to our observation of a stronger infl uence from Alpc (or Alo) than Fepc (or Feo) on the Qmax. Strong relationships do generally exist, however, between Fepc and Alpc, as observed in this study (R2 = 0.60). A previous study found that stable soil C was signifi cantly related to the number of mineral surface hydroxyls released by NaF reactivity (Kleber et al.,
Fig. 4. Relationship between the change in pOH resulting from the addition of NaF (pOHNaF) and the logarithm of the sum of poorly crystalline Al and Fe [log Σ (Fepc + Alpc)]. Dark fi lled circles are the Podzol B horizons, asterisks are the volcanic B horizons, and open circles are A and B horizons.
Table 4. Stepwise multiple regression analysis identifying key relationships between dissolved organic C sorption characteristics including the maximum adsorption capacity (Qmax), the null point (np), and the desorption capacity (b), and with soil properties. All regressions were signifi cant at P < 0.001, with the exception of np using Σ (Fepc + Alpc) + soil C, which was signifi cant at P = 0.006.
Sorption characteristic and soil properties†
Equation R2 RMSE
Log Qmax Σ(Fepc + Alpc) log Qmax = 0.55 log Σ(Fepc + Alpc) + 5.7 0.55 0.6703
Σ(Fepc + Alpc) + Fecry log Qmax = 0.42 log Σ(Fepc + Alpc) + 0.18 log Fecry + 5.50.57 0.5930
Σ(Fepc + Alpc) + clay log Qmax = 0.60 log Σ(Fepc + Alpc) + 0.41 log clay + 4.7 0.60 0.6388
Σ(Feo + Alo) log Qmax = 0.27 log Σ(Feo + Alo) + 7.4 0.53 0.6776
pOHNaF log Qmax = −0.89 pOHNaF + 9.1 0.50 0.7103
pOHNaF + Fecry log Qmax = −0.73 pOHNaF + 0.20 log Fecry + 8.3 0.64 0.4359
pOHNaF + clay log Qmax = −1.00 pOHNaF + 0.50 log clay + 8.3 0.57 0.6655
Log np
Σ(Fepc + Alpc) log np = −0.44 log Σ(Fepc + Alpc) + 2.7 0.28 0.9316
Σ(Fepc + Alpc) + soil C log np = −0.52 log Σ(Fepc + Alpc) + 0.21 log soil C + 2.3 0.33 0.9098
Σ(Fepc + Alpc) + ECEC log np = −0.37 log Σ(Fepc + Alpc) + 0.23 log ECEC + 2.4 0.33 0.9079
Σ(Fepc + Alpc) + K+ log np = −0.36 log Σ(Fepc + Alpc)]+ 0.40 log K+ + 3.6 0.35 0.8984
Σ(Feo + Alo) log np = −0.22 log Σ(Feo + Alo) + 1.4 0.15 0.9365
Log b Soil C log b = 0.32 log soil C + 3.3 0.24 0.6967 † Fepc and Alpc, poorly crystalline Fe and Al, respectively; Fecry, crystalline Fe; Feo and Alo, oxalate- extractable Fe and Al, respectively; pOHNaF, change in pOH due to addition of NaF; ECEC, effective cation exchange capacity.
2005). Th e fi ndings of Kleber et al. (2005), along with this study, suggest that there is good potential for using the simple and cost- eff ective ΔpOHNaF method not only to estimate the Qmax of DOC but also to assess the stability of soil C. Several soil surface complexation models attempting to model the partitioning of organic acids between the solid and solution phases (Tipping, 1994; Loft s et al., 2001; Lumsdon et al., 2005) may be able to incorporate an easy-to- measure soil property, such as F− reactivity, to predict the Qmax for DOC across a vast range of mineral soil horizons.
Clay Content Clay content and Fecry emerged as secondary predictors
for Qmax aft er Fepc + Alpc, suggesting that clay structures have a mechanistic contribution to DOC adsorption, but the infl uence was largely masked by Fepc and Alpc. In fact, sandy soils (>80%) oft en comprised those horizons identifi ed to have high Qmax values. Shen (1999) reported a strong positive correlation between the Qmax and clay content (ranging from 18 to 62%) for four Taiwanese soils. Strong DOC adsorption has also been reported on kaolinite ( Jardine et al., 1989) and montmorillonite (Inoue et al., 1990). Th e large surface area of clays is thought to provide charged surfaces, particularly if coated with Fepc and Alpc, yet Kaiser and Zech (2000) found that DOC adsorption decreased up to 94% with the removal of poorly crystalline Fe and Al and suggested that DOC adsorption for nonexpanding layer silicate clays was almost
entirely due to surface coatings of Fe and Al. Our results suggest that interactions between DOC and nonexpandable clay minerals were limited, which is in line with previous studies ( Jardine et al., 1989), and we agree that the Fepc and Alpc are the most dominant reactive sites for DOC complexation.
Soil Organic Carbon Soil C had no infl uence on the Qmax, yet could explain some of
the variability observed at the np concentration. Based on the linear IM isotherm, similar studies have found a strong positive relationship between np and organic C (Moore et al., 1992; Kaiser et al., 1996). Jardine et al. (1989) reported a fourfold increase in DOC adsorption to mineral soils aft er the removal of organic matter with H2O2. Since the np concentration is the point on an isotherm where desorption of organic C is balanced by adsorption, it is not surprising that this study, along with others, found a relationship between the main driv- er for desorption (soil C) and the np. Th e fact that soil C does not appear to have any infl uence on the Qmax implies that, at concentrations greater than the np, the level of soil C is mechanistically less relevant to the further adsorption of DOC.
Desorption Capacity To estimate the desorption potential, b, we used the Langmuir
isotherm with Xi (Eq. [2]) rather than Xf (Eq. [1]). Since natural soils generally have some level of soil C capable of undergoing desorption, a fi nal equilibrium concentration (Xf ) of 0 mg L−1 is theoretically meaningless, and the b term (of Eq. [1]) is simply a require- ment of the equation to fi t the experimental data (see Kothawala et al., 2008).
Th e desorption estimates produced in this study were within a lower range (4–255 mg kg−1) than estimates from previous studies of 30 to 520 mg kg−1 (Moore et al., 1992) and 30 to 520 mg kg−1 (Kaiser et al., 1996). Th e strongest predictor of desorption potential was the soil C, which is consistent with the fi ndings of other studies (Moore et al., 1992; Kaiser et al.,1996). We discuss the greater desorption potential observed from Podzol B horizons relative to other horizons below.
Soil Horizon Groups Soils were clustered into four distinct groups based on com-
mon soil properties (Fig. 1). Th ese groups were characterized based on isotherms of similar shape, and thus common adsorption characteristics (b, np, and Qmax, Fig. 2). Soil horizons were cat- egorized into the following: A horizons, B horizons, Fe-enriched Podzol B horizons, and Fe-enriched volcanic B horizons. Sorption characteristics derived from this study provide a basis for predict- ing DOC soil–solution partitioning with other mineral soils cat-
Table 5. Differentiation of the relative contribution of Fe and Al associated with the poorly crystalline phases of Fe and Al (Fepc and Alpc) and oxalate-extractable Fe and Al (Feo and Alo) toward explaining the variability in the maximum adsorption capacity (log Qmax) and the null point (log np), based on least squares linear regression models. The strength of the full regression (R2), along with the level of signifi cance (P value) and test statistic (t-ratio) for the individual contribution of Fe and Al are provided.
Sorption characteristic Equation R2 Log Fepc Log Alpc
RMSE P value t ratio P value t ratio
Fepc and Alpc Log Qmax log Qmax = 0.25 log Fepc + 0.28 log Alpc)+ 8.1 0.55 0.04 2.16 0.005 2.92 0.6844
Log np log np = −0.16 log Fepc −0.26 log Alpc + 0.85 0.28 0.33 −0.98 0.06 −1.96 0.9358
Feo and Alo Log Qmax log Qmax = (0.19 log Feo) + 0.36 log Alo + 6.9 0.53 0.27 1.13 0.02 2.53 0.9973 Log np log np = −0.13 log Feo −0.20 log Alo + 1.8 0.28 0.62 −0.50 0.36 −0.92 1.0313
Fig. 5. Comparison of the change in solution pH during equilibration of batch experiments for A horizons (Ah, Ae, and Ahe), B horizons (Bg, Bm, and Bt), Podzol B horizons (Bf, Bfh, Bcc, and Bfj), and B horizons of volcanic soils (Bfj and Bf). The original solution pH was 4.6. The line in the middle of the boxes represents the median, with the lower and upper part of the box representing 25 and 75% of the distribution, respectively, while the lower and upper whiskers represent 10 and 90% of the distribution, respectively. Horizon groups not sharing the same lowercase letter are signifi cantly different from each other based on the Tukey–Kramer honestly signifi cant difference comparison of means (P < 0.05).
egorized into these four groups. Soil groups with high levels of Fepc and Alpc had the largest adsorption capacity, including the B horizons of Podzols and volcanic soils, while A horizons and the B horizons of Gleysols and Luvisols had weak sorption maxima.
Th e Podzol B horizons had a unique capacity to both adsorb and desorb large quantities of DOC. Th is trait can be attributed to several related soil properties that are characteristic of Podzols, including high levels of Fepc and Alpc, high levels of soil C, and low soil pH. Th e high desorption capacity of Podzols was strongly correlated to high amounts of soil C. A study examining changes to the soil surface area with the adsorption of DOC to mineral soils revealed that the initial adsorption of DOC occurs in, or at the mouth of, micropores, forming strong associations due to multiple sites for ligand exchange, while subsequent adsorption may be limited to less reactive sites (Kaiser and Guggenberger, 2003). Th e fraction of DOC desorbed into the solution phase was probably released from weaker surface sites of Podzol B horizons. Regardless of the high amount of soil C and the high desorption capacity, the capacity for Podzol B horizons to adsorb DOC was among the highest measured values. In fact, the average adsorption capacity (Qmax = 1867 ± 1750 mg kg−1) dwarfed the desorption capacity (b = 120 ± 63 mg kg−1) of Podzol B horizons by ~15 times. Th is suggests that a large fraction of the potentially reactive surface sites of Podzol B horizons have not been occupied, despite the large amount of soil C. Major mechanisms involved in the development of Podzols are largely a consequence of the acidic nature of Podzols. Th e low soil pH contributes to the accumulation of soil C due to reduced microbial activity (Lundström et al., 2000). Th e combined eff ect of low pH and accumulated soil C contributes to mineral weathering, resulting in higher levels of illuviated poorly crystalline forms of Fe and Al within the mineral B horizons (Lundström et al., 2000). Th is combination of soil properties, including low pH, high amounts of Fepc and Alpc, and high soil C, probably contributed to the unique shape of sorption isotherms with high desorption capacity (b) and high adsorption capacity (Qmax).
In contrast, volcanic B horizons had high adsorption capacity but lower desorption potential. Th e low desorption potential was probably due to lower amounts of soil C strongly associated with soil particle surfaces than observed for Podzols. Another explana- tion may be due to the nature of soil C associated with volcanic soils located on Vancouver Island. We expect the soil C associated with these volcanic soils to be more hydrophobic since these soils typically receive high levels of precipitation (1,697 mm) relative to the other soils (450–1,430 mm). Consequently, soil C with hydro- philic properties may have been readily leached. Like the Podzol B horizons, the volcanic B horizons had high Qmax estimates. Volcanic soils are known to have high levels of noncrystalline minerals such as allophane, as well as imogolite and ferrihydrite (Torn et al., 1997). Th ese noncrystalline minerals provide ideal sites for the formation of strong multidentate ligand exchange sites.
Th e change in solution pH with equilibration to mineral soils diff ered for volcanic and podzolic B horizons (Fig. 5a). We found a general increase in pH for volcanic B horizons, which suggests that the dominant mechanism of adsorption may have been ligand exchange, whereby surface OH− groups were displaced by the car- boxyl groups of DOC. Th is type of specifi c adsorption is commonly regarded as the strongest type of soil–solution interaction between organic C and mineral soils (Tipping, 1981; Gu et al., 1994; Kaiser and Guggenberger, 2000). Ligand exchange is considered largely
irreversible for DOC adsorption to pure Fe oxides, whereby maximum sorption occurs within the acid dissociation constant, pKa, range of carboxylic acids, a pH between 4.3 and 4.7 (Gu et al., 1994). In contrast to the volcanic B horizons, Podzol B horizons observed a decline in solution pH aft er equilibration (<4.6). Th is decline does not rule out the possibility that ligand exchange occurred. Due to the large exchangeable acidity of Podzols, we cannot rule out the possibility that the overall decline in the fi nal solution pH may have simply been due to a greater release of H+ (replaced by cations in solution phase) relative to OH− released from surface complexation. Studies proposing mechanisms for DOC adsorption on mineral soils have been noted to be hypothetical (Jardine et al., 1989). Since the change we observed in pH is an average of many interactions resulting in a change in the solution-phase H+ and OH− concentrations, the primary mechanism(s) responsible for adsorption cannot be determined based exclusively on the results of this study. While the mechanisms responsible for the adsorption of Podzol and volcanic B horizons may be similar, we know the exchange reactions for volcanic B horizons are mostly irreversible, while a fraction of the DOC adsorbed to Podzol B horizons is more easily reversible.
CONCLUSIONS Th e Qmax of DOC was highly variable across mineral soils
and horizons. Th e amount of Fe and Al associated with poorly crystalline phases (Fepc + Alpc) was the strongest predictor of Qmax. An alternative and eff ective means of estimating the Qmax was determined, which is a simple measurement of the F− reactivity (ΔpOHNaF) rather than lengthy extractions. While a limitation to the ΔpOHNaF technique is some potential for bias to the OH− groups associated with Al hydroxides over Fe hydroxides, the amount of Alpc within mineral soils is generally strongly related to Fepc due to common soil formation factors. Within the soils included in this study, we found that the Alpc explained more of the variability in the prediction of Qmax, and to a lesser degree the np, than Fepc. Th e texture of mineral soils included in this study was largely irrelevant to the prediction of the adsorption characteristics. While sandy soils were among the strongly adsorbing soils, we did fi nd a positive infl uence of clay masked under the strong dominant infl uence of Fepc and Alpc. Soil C did not have a signifi cant infl uence on the Qmax but was the primary soil property able to predict the desorption capacity. Since the np is theoretically repre- sentative of adsorption and desorption processes, it is logical that Fepc + Alpc, along with the presence of soil C, infl uenced the np.
Th e general shape of isotherms along with adsorption and desorption characteristics could be broadly predicted based not only on soil properties but also soil type and horizon. In general, weak adsorption and desorption capacity was observed for A horizons and the B horizons derived from Gleysols, Luvisols, and organic soils. Th e B horizons from Podzols and volcanic soils had the largest Qmax. A unique characteristic of Podzol B horizons was the high desorption capacity. As also determined by Gu et al. (1994), we found that a strong hysteresis can be expected for the adsorption and desorption dynamics for DOC and the mineral horizons of Podzols. Th e same was not true of other soil horizons. Consequently, the hysteresis of DOC–soil interactions should be considered for better modeling of natural organic matter transport. While the adsorption capacity (Qmax) of a mineral soil may have strong implica- tions on DOC transport and fl uxes to aquatic systems, it is critical to assess in-soil controls on the adsorption capacity in conjunction
with desorption potential, from the perspective of understanding controls on the size of the mineral soil C stocks. Th is study has provided estimates of the adsorption and desorption capacity (Qmax and b) for a range of mineral soils; however, we have not addressed questions related to the short-term or long-term fate of organic C aft er adsorption to mineral soils. Further research needs to be di- rected at relating estimates of Qmax to the stability and turnaround time of newly adsorbed soil C relative to indigenous soil C.
ACKNOWLEDGMENTS Th is study was funded by the Natural Sciences and Engineering Research Council of Canada and BIOCAP Canada, and funding was provided to D.N. Kothawala by the Global Environmental and Climate Change Centre. We thank Isabelle Gagnon, Mike Dalva, Hélène Lalande, and Glenna Keating for help with experimental work and Julie Turgeon, Jim McLaughlin, and Tony Trofymow for sample collection. We also thank Sami Ullah and Martyn Futter for insightful suggestions and help with data analysis. We thank reviewers for comments that contributedto an improved manuscript.
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