The dynamic exchange of dissolved organic matter percolating through six diverse soils

Soil Biology & Biochemistry 69 (2014) 83e92

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The dynamic exchange of dissolved organic matter percolating through six diverse soils Emily E. Scott*, David E. Rothstein 126 Natural Resources, 480 Wilson Road, Michigan State University, East Lansing, MI 48824, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 29 July 2013 Received in revised form 8 October 2013 Accepted 26 October 2013 Available online 15 November 2013

The movement of dissolved organic matter (DOM) through forest soils is regulated by a suite of physicochemical and biological processes that retain, transform, and release DOM. While sorptive processes are known to limit DOM losses, there are still uncertainties about what regulates DOM composition. This study examined DOM dynamics in waters percolating through ex-situ soil cores from six diverse forest soils to determine if DOM leaching losses reflected dynamic exchange processes between fresh DOM inputs and soil surfaces or the continual stripping of surface-reactive compounds from recent DOM inputs. There was a net desorption of hydrophilic compounds into soil solutions after 10 cm soil depth that coincided with an increase in DOM biodegradability as solutions percolated to depth. There was also a limited net retention of dissolved organic nitrogen (DON) in surface soils. Taken together, these results support a dynamic exchange model of DOM dynamics where highly sorptive, hydrophobic compounds displace previously sorbed, N-rich hydrophilic compounds from soil surfaces. These soils also demonstrated fairly consistent leaching losses of dissolved organic carbon (DOC) and DON despite their variation in texture, hydraulic conductivity, and Fe and Al mineralogy, removing 72e85% of the DOC added by 50 cm depth. The strong sorption capacity of these soils may be one reason for the fairly uniform DOM chemistry leaching from these soil cores. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Dissolved organic carbon Dissolved organic nitrogen Sorption Biodegradability Dynamic exchange Dissolved organic matter

1. Introduction Dissolved organic matter (DOM) is a crucial component of terrestrial biogeochemical cycles due to its ability to transport nutrients and carbon (C) through forest ecosystems to aquatic environments. This transport is mediated by both physicochemical and biological processes that serve to retain, transform, and release DOM from different soil compartments. Because DOM is central to questions of C sequestration in soils and nutrient availability to microorganisms and plants, it is critical that we have a solid understanding of the processes that regulate DOM movement in terrestrial environments. Forest soils are widely recognized for their strong ability to impact DOM movement and chemistry as water percolates from surface to deep soils (Seely et al., 1998; Qualls et al., 2002; Möller et al., 2005). While sorption between DOM compounds and soil surfaces is paramount in constraining DOM losses (McDowell and Likens, 1988; Qualls et al., 2002), it is still unclear whether DOM composition in subsoils reflects surface litter inputs or is primarily

* Corresponding author. Tel.: þ1 517 827 1738. E-mail addresses: [email protected], [email protected] (E.E. Scott). 0038-0717/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.soilbio.2013.10.052

composed of mature, soil-based C sources. In the former scenario, DOM composition is largely driven by physicochemical processes that retain highly surface-reactive, complex DOM compounds from litter inputs onto soil surfaces, while more soluble compounds continue into subsoils (Guggenberger and Kaiser, 2003; Kaiser and Kalbitz, 2012). In the latter scenario, DOM composition results from exchange reactions between highly sorptive, surface litter-derived compounds with previously sorbed, microbially-altered compounds that have a lower affinity for soil surfaces (Sanderman et al., 2008; Kaiser and Kalbitz, 2012). These compounds redissolve and migrate deeper into soils, causing subsoil DOM to more closely resemble older soil organic matter and microbial residues. The key difference between these models lies in the soluble fraction chemistry at depth; does it reflect surface DOM inputs or previously degraded soil organic matter? One way to examine how DOM chemistry changes as it percolates through soils is by fractionating DOM into operationallydefined hydrophobic and hydrophilic pools. Hydrophobic compounds represent plant-derived compounds with some microbial alterations (Guggenberger et al., 1994) and readily sorb to mineral soil because of their high molecular weights, polymeric/aromatic structure, and low ratio of carboxyl functional groups to C content (Kaiser and Zech, 1998; Qualls and Haines, 1991; Gu et al., 1995).

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Hydrophilic compounds are largely microbial-derived by-products (Guggenberger et al., 1994) that remain in solution due to their low molecular weights, aliphatic configurations, and high carboxyl-to-C ratios (Qualls and Haines, 1991; Kaiser and Zech, 1998); they also tend to be N-rich (Lajtha et al., 2005). Hydrophobic compounds in percolating waters are preferentially removed over hydrophilic substances, with some indication that they displace previously sorbed hydrophilic substances (Kaiser and Zech, 1998), resulting in their proportionate decrease with increasing soil depth (Yano et al., 2004; Lajtha et al., 2005; Möller et al., 2005). Hydrophobic and hydrophilic DOM fractions are chemically complex and only capture a coarse view of DOM dynamics. Biodegradability assays provide an additional tool for evaluating DOM chemistry with the added benefit of also describing the energetic and nutritive potential of DOM for microorganisms. Interestingly, there are contradictory expectations surrounding how soil sorption processes will impact DOM biodegradability. The preferential removal of hydrophobic compounds that degrade slowly in favor of hydrophilic, more rapidly-biodegradable compounds suggests the overall biodegradability of DOM will increase as solutions percolate to depth (Michaelson et al., 1998; Kaushal and Lewis, 2005). However, Schwesig et al. (2003) found DOM to be less biodegradable in deep versus surface horizons, leading Kaiser and Kalbitz (2012) to state that subsoil DOM would be “hardly decomposable.” This latter idea agrees with the concept of dissolved organic nitrogen (DON) “leaking” from terrestrial ecosystems due to its overall low biodegradability (Hedin et al., 1995; Perakis and Hedin, 2002; Neff et al., 2003). Clearly further study is warranted to investigate this inconsistency. The ability of a soil to sorb DOM is contingent upon the summative influences of its texture (Seely et al., 1998), structure (Asano et al., 2006), organic matter content (Lilienfein et al., 2004), and mineral composition (i.e., Fe and Al oxides; Qualls, 2000; Lilienfein et al., 2004; Yano et al., 2004), which can individually either augment or restrict DOM sorption. For example, high soil organic matter concentrations can inhibit DOM sorption by limiting available binding sites on soil colloids (Kaiser and Zech, 1998; Lilienfein et al., 2004), while high concentrations of Fe and Al oxides can facilitate sorption (Qualls, 2000; Lilienfein et al., 2004). Therefore, DOM sorption dynamics are likely highly dependent on individual soil environments and will vary across the landscape as soil conditions change. We predict that soils with relatively few free sorption sites (e.g., coarse-textured, low amorphous mineral content) will retain less DOM compared to soils with abundant free sorption sites. Additionally, we expect these soils to retain more hydrophobic DOM compounds as they outcompete hydrophilic compounds for the limited number of sorption sites (Kaiser and Zech, 1998). This would also translate into an increasing biodegradability of DOM solutions as they percolate to depth (Cleveland et al., 2004). In this study, we investigated DOM sorption dynamics and its biodegradability in leachate from soil cores collected in six diverse northern hardwood forests. We posed the following questions: i) Do DOM leaching losses reflect dynamic exchange processes or the continual stripping of the most surface-reactive compounds from recent DOM inputs? ii) Does the biodegradability of DOM increase or decrease with soil depth? and iii) How do differences in soil characteristics impact the quantity and quality of DOM in soil leachates?

ecosystem units by Host et al. (1988). The forest stands range from low N availability, white oak (Quercus alba)-black oak (Q. velutina)dominated outwash plains to N-rich, sugar maple (Acer saccharum)-dominated moraines (Host et al., 1988; Zak et al., 1989). The least developed soil is classified as a Typic Udipsamment, followed by a slightly more developed Entic Haplorthod. The next three forest soils have progressively higher N-availability and represent a spodic developmental sequence. All are classified as Typic Haplorthods, with the two most N-rich soils having clay lamellae at depth. The last soil is an Alfisol with substrata of sandy clay loam and is classified as a Typic Hapludalf (Cleland et al., 1993). All soils are within 32 km of each other and experience consistent precipitation throughout the year (annual average of roughly 81 cm) with a mean annual temperature of 7.2  C (Albert, 1995). Elevation ranges from 213 to 369 m above sea level. 2.2. Soil core collection On June 19, 2007, we collected a “cluster” of soil cores at 3 randomly selected positions along a 10 m transect in each forest stand. Each cluster contained a soil core of 0e10, 0e25, and 0e 50 cm depth for a total of 9 soil cores per stand. After first removing the O horizon, sharpened polyvinyl chloride (PVC) pipes approximately 11 cm in diameter were pounded into the soil and carefully removed to maintain the integrity of the soil column. Cheesecloth was affixed to the bottom of the core and covered in plastic for transport to the lab. Cores were refrigerated for 2e4 weeks after collection to equilibrate after the disturbance of removing the cores from the sites. 2.3. Soil core leaching The hydraulic conductivity (Ksat) was determined on intact cores by the constant head method (Klute and Dirksen, 1986) prior to soil core leaching, in part to remove post-disturbance effects that may have resulted from extracting cores from the field. Next, the soil cores were flushed with 1 pore volume of a manufactured O horizon solution to displace the reverse osmosis water in soil pores used to determine Ksat. Because DOM represents a diverse collection of compounds that span a gradient of molecular sizes, reactivities, and solubilities (Qualls and Haines, 1991; Kaiser and Zech, 1998) that vary in their affinity for soil (Kleber et al., 2007), the cores were supplied with a common organic matter solution to isolate the effects of soil characteristics on leachate chemistry. The hardwood forests from which the soils cores were collected have relatively rapid litter decomposition and therefore do not develop stratified litter layers; organic horizons are primarily classified as Oi and are indicative of freshly fallen litter. As a result, a concentrated O horizon solution was generated by extracting equal parts of ground leaf litter collected during fall senescence from all forest stands in E-pure deionized (DI) water for 24 h. Working solutions were made daily during the experiment and averaged 138.2 mg L1 (SE 2.7) of DOC and 1.0 mg L1 (SE 0.1) of DON. After flushing the cores, the O horizon solution was reapplied in 100 mL increments until at least 200 mL of soil solution leached from the core bottom. Leaching volumes were recorded, and solutions were immediately filtered through 0.2 mm Whatman Nuclepore Track-Etch membrane filters, and frozen.

2. Methods 2.4. Soil solution fractionation 2.1. Study area Soil cores were collected in the Manistee National Forest in the northwestern Lower Peninsula of Michigan, USA (44 480 N, 85 480 W) from six forest stands previously classified into

Soil solutions were fractionated into humic acids, fulvic acids, hydrophilic acids, and hydrophobic organic neutral matter in batches using DAX-8 exchange resins (Supelco, Bellefonte, PA) following a modified procedure of Van Zomeren and Comans

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(2007). To begin the fractionation procedure, soil solutions from each core were thawed and analyzed by oxidative combustionchemiluminescence and oxidative combustion-infrared analysis for their initial DOC and TN concentrations, respectively (TOC/TN analyzer; Shimadzu Corp., Kyoto, Japan). We also determined their initial ammonium (NHþ 4 ) concentration after Sinsabaugh et al. (2000) and initial nitrate (NO 3 ) concentrations after Doane and Horwath (2003). DON was calculated by subtracting the NHþ 4 and NO 3 concentrations from the TN concentration. Forty-mL aliquots of each solution were next acidified to a pH of <1 with 6 M HCl, allowed to sit overnight to precipitate dissolved humic acids, and then centrifuged for 10 min at 3000 g. Solutions were decanted into new tubes, and a subsample was removed for DOC analysis (the difference between the initial DOC concentrations and this one is the humic acid content of the sample). Approximately 10 g of DAX-8 resins were added to each sample before continuous tumbling on a rotary shaker for 1 h. Solutions were filtered through monopolyester mesh (#86, Ernst Dorn Co, Santa Clara, CA) fitted to test tube lids to prevent loss of resins and saved for DOC analysis (to provide a measure of hydrophilic content). To desorb fulvic acids on the resins, 20 mL of 0.1 M potassium hydroxide (KOH) was poured through the mesh, washing resins back into solution, and equilibrated for 1 h (pH > 11) before refiltration through the mesh. This extraction procedure was repeated 3 additional times, and the eluents from each extraction were saved and combined for DOC analysis (to determine the fulvic acid composition of the sample). The hydrophobic organic neutral matter composition was determined as the difference between the DOC content of the soil solution prior to the addition of DAX-8 resins and the summed DOC concentrations of fulvic and hydrophilic acids. The concentration of fulvic acids in all samples was low (<0.01 mg L1), so we combined this fraction with the hydrophobic organic neutral fraction for one “hydrophobic” fraction. Humic acids were also negligible and not included in subsequent analyses. As a result, the data analyses contained only the hydrophobic fraction, composed of fulvic acids þ hydrophobic organic neutral matter, and a hydrophilic fraction. As a blank, a vial of 0.1 M HCl was subjected to the same steps as soil leachate and used to adjust sample values for any C bleeding from the resins. The moisture content of the resins was determined to be 71%. The summed DOC concentration of both fractions for each sample was within an average of 5% of the prefractionated DOC concentration. 2.5. Soil characteristics Soil was removed from the cores 24 h after the leaching experiment in 0e10, 10e25, and 25e50 cm depth increments as appropriate (i.e., only 50 cm cores had all three segments) and passed through a 4-mm mesh sieve. Particle size distributions of each soil segment were determined by the pipette method (McKeague, 1978; Gee and Bauder, 1986) after first removing organic matter with 30% hydrogen peroxide. The bulk density, total porosity, microbial biomass (chloroform-fumigation extraction), and soil pH (measured in DI water at a soil:water ratio of 1:2 (w/v)) of soils were also measured. The C and N contents were determined by flash combustion/chromatographic separation using a Costech Elemental Combustion System 4010 elemental analyzer (Costech Analytical Technologies, Inc., Valencia, CA) on soil that had been oven dried at 105  C for 24 h and ground to a fine powder. The content of iron hydrous oxides (Fed) was measured by the citratedithionite method and the amount of noncrystalline (amorphous) aluminosilicates and hydrous oxides of iron and aluminum (Feo, Alo) with the acid ammonium oxalate dark reaction (McKeague, 1978; Jackson et al., 1986). Solutions were analyzed with inductively coupled plasma-optical emission spectrometry (ICP-OES)

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using an Optima 2100DV optical emission spectrometer (PerkinElmer, Inc., Shelton, CT). The soil characteristics listed in Table 1 represent the amounts found within a core segment (i.e., 0e10, 10e25, 25e50 cm) in order to illustrate how characteristics changed with depth. Because all cores had 0e10 cm segments, we averaged all of these values when calculating the values in this core increment for a total of 9 soil core increments per soil type. For the 10e25 cm core increment, we averaged the increment values in 0e25 and 0e50 cm cores for a total of 6 core increments per soil type. The 25e50 cm core increment was found only in 0e50 cm cores for a total of 3 core increments per soil type. 2.6. Biodegradability assay The biodegradability of soil leachate was analyzed by inoculating soil solutions with a standard inoculum and incubating the samples for up to 14 days (McDowell et al., 2006). Soil leachate was first filtered through a 0.22 mm Millex GS syringe filter (Millipore, Carrigtwohill, Ireland) to remove microbial cells already present in the solution. Additionally, each solution was diluted with varying amounts of DI water so that all samples had similar initial C concentrations in order to more accurately compare the biodegradability of solutions from different soil types and depths. The final volume of soil solution and water was approximately 10 mL. We then added 6 mL of a nutrient solution containing 0.1% ammonium nitrate (NH4NO3) and 0.1% potassium phosphate (K2HPO4) to ensure that only C quality limited microbial metabolism of DOM. The final C concentration of solutions averaged 8.1 mg L1 (range: 7.3e10.4 mg L1). One 6 mm disc punched from a Whatman GF/A glass microfiber filter was added to each vial as a physical substrate for microbial growth. We pipetted 0.2 mL of a standard inoculum (BI-CHEM BOD Seed, Novozymes Biologicals, Inc., Salem, VA) into each vial, agitated the samples, and placed them in an incubator at 25  C; time 0 samples were not inoculated. Every other day after inoculation, samples were inverted 5 times, uncapped, and vented for 1.5 min to prevent the build up of excessive amounts of carbon dioxide. Vials were harvested at 0, 2, and 14 days after inoculation. Harvesting involved mixing the samples thoroughly before filtering the solutions through 0.22 mm Millex GS syringe filters and immediately analyzing them for DOC as stated above. While filtering solutions post incubation has the potential to overestimate the amount of DOC consumed if particulate carbon that formed during the incubation process is retained on the filter (Marschner and Kalbitz, 2003), the alternative method of using CO2 evolution to measure biodegradability fails to attribute microbiallyincorporated C to the biodegradable pool. We were interested in estimating both biodegradable and microbially-incorporated C so opted for filtering our solutions post incubation after the methods of McDowell et al. (2006) and Schnabel et al. (2002). Inoculated DI water plus the nutrient solution was used as a blank to account for any DOC contributed by the microbes during the assay. The %C consumed was calculated as:


%C consumed ¼ 1  Adjusted CTfinal =Adjusted CTinitial *100 where adjusted CTfinal is the difference between the DOC of the soil leachate at a particular harvest time and the DOC of the water blank, and adjusted CTinitial is the DOC concentration at time ¼ 0. 2.7. Statistical analyses Differences in DOC and DON in soil core leachate across soils and at different soil depths were evaluated with mixed-effects analysis

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Table 1 Soil characteristics for individual core segments (depth ranges in cm) except for hydraulic conductivity, which was measured for the entire, intact core. Data in italics are 1 SE. Ksat (cm s1) Typic Udipsamment 0e10 1.5 0.1 10e25 1.4 0.1 25e50 1.3 0.2 Entic Haplorthod 0e10 0.9 0.1 10e25 1.3 0.1 25e50 0.8 0.1 Typic Haplorthod (1) 0e10 0.4 0.1 10e25 0.7 0.0 25e50 0.5 0.1 Typic Haplorthod (2) 0e10 0.8 0.3 10e25 0.6 0.2 25e50 0.9 0.2 Typic Haplorthod (3) 0e10 1.0 0.4 10e25 0.6 0.2 25e50 0.6 0.2 Typic Hapludalf 0e10 1.3 0.3 10e25 0.6 0.2 25e50 0.3 0.1 pH 5.0 5.6 5.8 5.0 5.2 5.4 4.5 4.8 5.1 5.2 5.4 5.5 4.8 5.1 5.4 5.5 5.8 6.0

0.2 0.4 0.6 0.1 0.1 0.1 0.2 0.1 0.2 0.2 0.2 0.3 0.2 0.2 0.3 0.2 0.2 0.2

% Clay (<0.002 mm)

Bulk density (g cm3)

Porosity (%)

0.3 0.5 0.7

3.6 1.2 0.7

0.2 0.5 0.0

0.8 1.4 1.5

0.1 0.0 0.0

70.7 46.0 42.6

3.6 1.8 1.5

10.8 10.4 10.9

0.6 0.3 0.6

2.0 1.0 0.1

0.6 0.3 0.1

0.8 1.3 1.6

0.1 0.1 0.1

71.2 51.9 38.4

3.4 2.0 4.8

2.2 2.4 4.4

8.9 8.8 6.4

0.8 1.1 1.8

2.1 1.1 0.5

0.3 0.4 0.2

0.8 1.4 1.4

0.1 0.0 0.0

69.4 48.3 46.4

2.0 1.0 0.6

44.8 49.6 53.4

1.3 1.5 2.4

7.9 7.4 4.7

0.5 0.9 1.6

3.0 1.3 0.6

0.4 0.5 0.3

0.7 1.2 1.5

0.1 0.2 0.0

73.9 54.3 43.5

2.6 6.8 0.9

1.4 1.7 1.7

36.4 41.8 45.3

1.4 1.4 2.6

10.1 9.5 10.7

0.3 0.5 0.4

2.9 1.7 0.5

0.5 0.3 0.5

0.9 1.4 1.5

0.1 0.0 0.1

67.2 47.0 42.9

4.5 1.7 2.0

0.7 0.7 2.2

31.6 34.2 37.3

0.3 0.5 0.1

26.9 27.1 24.8

0.8 1.1 2.0

5.2 3.3 0.4

0.4 0.6 0.2

0.8 1.2 1.6

0.1 0.1 0.2

68.6 54.1 39.7

3.2 2.7 7.0

% Coarse sand (2.0e0.25 mm)

% Fine sand (0.25e0.05 mm)

65.7 59.6 59.2

1.7 2.6 3.6

25.0 33.5 35.3

1.6 2.4 3.2

5.7 6.0 4.7

67.0 63.8 63.3

1.3 1.5 2.8

20.2 24.9 26.5

1.1 1.2 2.1

39.0 37.4 37.0

3.0 3.5 6.0

50.0 53.0 56.1

44.3 41.9 41.3

1.3 0.9 0.7

50.6 47.0 44.5 36.4 35.5 37.5

Soil C (g kg1)

Soil N (g kg1)

C:N

22.8 6.6 2.3 19.6 6.9 2.3 24.7 7.3 6.3 21.8 5.5 4.2 23.6 4.5 4.7 25.2 6.9 3.4

0.3 0.1 0.2 0.8 0.1 0.2 1.2 0.1 0.4 1.5 0.3 0.3 1.8 0.5 0.4 1.4 0.6 0.3

79.6 72.1 10.1 33.8 63.7 9.7 20.1 63.4 14.6 14.8 34.4 12.3 12.3 9.0 11.7 28.6 10.9 9.7

2.1 0.6 0.3 3.1 0.5 0.7 4.8 0.7 0.4 3.4 0.8 0.8 5.1 0.3 0.3 4.7 1.0 1.1

0.1 0.0 0.0 0.2 0.0 0.0 0.2 0.0 0.0 0.2 0.1 0.0 0.3 0.0 0.0 0.3 0.0 0.1

8.7 7.0 0.5 8.6 2.4 1.6 1.5 3.2 0.3 0.6 10.7 1.1 0.6 0.4 0.8 6.7 0.8 1.7

% Silt (0.05e0.002 mm)

Fed (g kg1)

Feo þ Alo (g kg1)

Microbial C (mg g1)

Microbial N (mg g1)

8.9 11.6 10.6 5.0 10.6 10.0 2.9 5.1 7.9 3.6 5.2 6.7 4.7 6.5 9.7 4.9 9.6 8.3

4.9 7.5 6.3 2.9 9.1 6.8 1.4 3.6 7.8 2.2 4.0 6.1 2.0 3.4 6.8 2.7 6.6 6.0

16.8 4.5 4.3 16.0 5.8 3.6 13.8 6.4 5.8 16.3 4.9 4.4 18.3 4.5 5.3 20.5 8.1 5.3

1.5 0.2 0.0 1.7 0.4 0.0 1.2 0.3 0.2 1.9 0.3 0.1 1.7 0.2 0.1 2.2 0.5 0.1

of variance (ANOVA) models. DOC or DON was the dependent variable and soil type and depth were the fixed effects. “Soil core cluster” was included as a random effect in each model to account for correlations that occurred within each cluster. DON concentration was log transformed to meet assumptions of normality. An interaction term between soil type and depth was tested, but this was never significant so was excluded from the models. To evaluate differences in hydrophobic and hydrophilic DOC, generalized least squares analysis of covariance (ANCOVA) models were used. Total DOC was included as the covariate, soil type and depth were fixedeffects, and “soil core cluster” was modeled using a compound symmetry correlation structure. Mixed-effects ANCOVA models were used to compare C consumption in the biodegradability assay. The C concentration at either day 2 or 14 was the dependent variable while the initial C concentration was the covariate. The remaining model terms were soil type and depth as fixed-effects, and soil cluster as a random effect. Tukey contrasts were used for post-hoc comparisons of all models to evaluate the significant model terms. We also used step-wise regression analyses with forward selection to explore how soil parameters influence total DOC and DON chemistry. However, these analyses had limited success and will not be discussed (the final models are provided in

0.5 0.7 1.4 0.5 0.8 0.6 0.4 0.7 1.4 0.5 0.5 0.8 0.3 0.8 1.0 0.4 0.4 1.5

0.3 0.4 1.0 0.4 0.7 0.8 0.3 0.7 2.3 0.5 0.6 0.6 0.4 0.9 0.2 0.3 0.6 2.0

1.6 0.7 0.3 1.7 0.8 0.2 1.4 0.5 0.2 2.0 0.3 0.2 2.3 0.3 0.7 2.5 0.9 0.5

0.3 0.0 0.0 0.3 0.1 0.0 0.2 0.1 0.1 0.3 0.1 0.0 0.3 0.1 0.0 0.4 0.1 0.0

Appendix A). In all of the statistical models, Type III sums of squares were used so that all terms were considered simultaneously during the analyses. All analyses were conducted using R statistical software (R Development Core Team, 2013), and results were accepted as significant at a ¼ 0.05. Non-metric multidimensional scaling (NMDS) was used to explore how multiple soil characteristics simultaneously influenced DOC and DON patterns across soil types. Individual soil cores from all six soil types were first ordinated by their soil characteristics, then the DON and DOC in core leachate was overlaid on the ordination. Separate analyses were conducted for 0e10, 0e25, and 0e50 cm cores to prevent the geochemical influences from being confounded by the increasing core volume with depth. For 25 and 50 cm cores, we calculated weighted averages for each variable, except hydraulic conductivity, based on measurements taken on the 0e10, 10e25, and 25e50 cm core segments (the latter segment for 50 cm core only) to generate total core values. Each soil type had 3 replicate cores per depth that were included in the analyses. Prior to analysis, the soil variables were transformed with Wisconsin double standardization. A distance matrix was calculated using a BrayeCurtis distance measure, and NMDS was run from random starts. These analyses were conducted using the metaMDS function

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in the vegan library of R statistical software (R Development Core Team, 2013). 3. Results 3.1. Soil characteristics Soils became increasingly fine-textured along the gradient we examined, as expected (Table 1). The coarse sand content decreased from roughly 60% in the Typic Udipsamment to roughly 45% in the two most developed Typic Haplorthods, while the amount of fine sand, clay, and silt generally increased in cores from least to most developed. Notably, the Typic Hapludalf had over 2 times more silt in all soil core increments compared to the remaining soil types. Correspondingly, Ksat was generally highest in the Typic Udipsamment and lowest in the Typic Hapludalf. However, the two most developed Typic Haplorthods (2, 3) had some of the fastest hydraulic conductivities in 0e50 cm cores despite having some of the finest textures. The bulk density of soils increased from surface to deeper soils, while % porosity decreased with depth. Soil pH in 0e10 cm cores ranged from 4.5 in the least developed Typic Haplorthod (1) to 5.5 in the Typic Hapludalf, with surface soils always slightly more acidic compared to deeper soils. The least developed Typic Haplorthod (1) had some of the highest soil C in all cores; however, this was not the case for soil N, which was consistently higher in the more developed Typic Haplorthods (2, 3) and the Typic Hapludalf compared to the other soils. Therefore, these soils generally had lower C:N (by mass) ratios compared to the Typic Udipsamment, Entic Haplorthod, and least developed Typic Haplorthod (1). In most soils, the concentration of iron hydrous oxides (Fed) and noncrystalline aluminosilicates and hydrous oxides of iron and aluminum (Feo, Alo) increased from surface to deeper soils, with the Typic Udipsamment having the highest concentrations of both forms. Microbial biomass C and N generally increased from the least to most developed soil in 0e10 cm cores (17e21 mgC g1 and 1.5 to 2.2 mgN g1).

Fig. 1. The (a) DOC and (b) DON of leachate from 0 to 10, 0e25, and 0e50 cm soil cores for six different soil types (1 SE). The dashed lines indicate the input organic matter values. Soil types are: 1 ¼ Typic Udipsamment, 2 ¼ Entic Haplorthod, 3 ¼ Typic Haplorthod (1), 4 ¼ Typic Haplorthod (2), 5 ¼ Typic Haplorthod (3), 6 ¼ Typic Hapludalf.

3.2. Soil solution chemistry DOC demonstrated a high net retention in all soils as solutions percolated to depth (mixed-effects ANOVA; soil depth, F2,44 ¼ 12.57, p < 0.001; Fig. 1a). By the time percolating waters reached 50 cm depth, 72e85% of DOC had been removed from solution, with the majority retained within the top 10 cm of soil (i.e., 60e68%). Between 10 and 25 cm, only an insignificant amount of DOC was removed from solution (i.e., 4% on average; Tukey contrasts: 10 and 25, z ¼ 1.50, p ¼ 0.29), but this increased significantly between 25 and 50 cm depths where on average an additional 10% of DOC was removed (25 and 50, z ¼ 3.39, p ¼ 0.002). There was no significant effect of soil type on DOC losses (mixed-effects ANOVA; F5,44 ¼ 0.93, p ¼ 0.47), suggesting DOC retention patterns were consistent across all soils. Like DOC, DON in soil core leachate decreased significantly with increasing soil depth (ANOVA; F2,44 ¼ 18.79, p < 0.001); however, overall DON retention was more variable than DOC (29e70% reduction by 50 cm) and there was not the same large decrease in the upper 10 cm of soil as seen with DOC (Fig. 1b). Indeed, DON in 10 cm solutions was often similar to, or greater than, DON in the input solution. DON only decreased significantly from soil solutions after 25 cm (10 and 25: z ¼ 2.31, p ¼ 0.06; 10 and 50: z ¼ 6.07, p < 0.001; 25 and 50: z ¼ 3.77, p < 0.001). Unlike DOC, there were significant differences in DON retention across soil types (F5,44 ¼ 3.22, p ¼ 0.02), with the two most developed Typic Haplorthods (2, 3) losing significantly more DON compared to the Typic Hapludalf (Typic Haplorthod (2) and Typic Hapludalf: z ¼ 3.26,

p ¼ 0.01; Typic Haplorthod (3) and Typic Hapludalf: z ¼ 3.30, p ¼ 0.01); otherwise, the soil types had similar net DON retention. The hydrophobic and hydrophilic DOC fractions were strongly correlated with total DOC in soil solutions (ANCOVA; hydrophobic: F1,44 ¼ 654.82, p < 0.001; hydrophilic: F1,44 ¼ 224.62, p < 0.001), and also demonstrated high net retention as soil solutions percolated to depth, especially within the top 10 cm of soil (Fig. 2). Hydrophobic compounds comprised the majority of total DOC inputs (w60%), and were reduced by 75e89% across soils by the time solutions reached 50 cm, 60e69% of which occurred in the top 10 cm. There continued to be a significant removal of hydrophobic compounds from soil solution with increasing depth (mixed-effects ANCOVA; F2,44 ¼ 6.24, p ¼ 0.004), but only between 10 and 25 cm (10 and 25: z ¼ 2.83, p ¼ 0.01; 10 and 50: z ¼ 3.27, p ¼ 0.003; 25 and 50: z ¼ 1.10, p ¼ 0.51). The hydrophobic fraction was the only one to exhibit retention differences among soil types (hydrophobic: F5,44 ¼ 2.79, p ¼ 0.03; hydrophilic: F5,44 ¼ 1.18, p ¼ 0.34), with the Typic Udipsamment and Typic Haplorthod (3) on average retaining significantly more hydrophobic compounds from solution than the Typic Hapludalf (Typic Hapludalf and Typic Udipsamment: z ¼ 3.25, p ¼ 0.01; Typic Hapludalf and Typic Haplorthod (3): z ¼ 3.00, p ¼ 0.03). While hydrophilic compounds also demonstrated a strong net retention in the top 10 cm of soil (53e62% across soils), they tended to increase significantly in soil solutions from subsequent depths (F2,44 ¼ 18.96, p < 0.001), both in absolute and relative terms (Fig. 2b and c). The absolute amount of hydrophilic DOC in

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days: F2,43 ¼ 31.27, p < 0.001; Fig. 3). While the amount of C consumed in leachate from 25 to 50 cm depths was statistically indistinguishable at both 2 (25 and 50: z ¼ 1.11, p ¼ 0.51) and 14 days (25 and 50: z ¼ 1.24, p ¼ 0.43), 10 cm leachate always exhibited significantly less C consumed than subsoils; after 2 days of incubation, 19e32% of C compounds had been consumed in 10 cm leachate, while between 30 and 45% had been consumed in 50 cm leachate (10 and 25: z ¼ 4.03, p < 0.001; 10 and 50: z ¼ 5.16, p < 0.001). By 14 days of incubation, the %C consumed in 10 cm leachate had increased to 45e55% while between 61 and 69% of C compounds had been consumed in deep soil leachate (10 and 25: z ¼ 6.13, p < 0.001; 10 and 50: z ¼ 7.41, p < 0.001). Across soil types, C consumption differed only at 2 days of incubation (F5,43 ¼ 3.99, p ¼ 0.005), with significantly more C consumed in leachate from Typic Haplorthods 2, 3 and the Typic Hapludalf compared to Typic Haplorthod 1 (Tukey contrasts: Typic Haplorthods 2 and 1, z ¼ 2.95, p ¼ 0.04; Typic Haplorthods 3 and 1, z ¼ 3.15, p ¼ 0.02; Typic Hapludalf and Typic Haplorthod 1, z ¼ 3.83, p ¼ 0.002). By 14 days of incubation, these differences had disappeared (F5,43 ¼ 0.13, p ¼ 0.99). When compared to the input organic matter solution, soil leachate was almost always more biodegradable. These differences were most pronounced after 2 days of incubation where 2e4 times more C was consumed in 10 cm leachate compared to the input solution and up to 5 times more C was consumed in 50 cm leachate. Over time, the amount of C consumed in the input solution and in 10 cm leachate converged; however, subsoil leachate was

Fig. 2. The (a) hydrophobic and (b) hydrophilic DOC fractions, and (c) the proportion of hydrophilic DOC of leachate from 0 to 10, 0e25, and 0e50 cm soil cores for six different soil types (1 SE). The dashed lines indicate the input organic matter values. Soil types are as in Fig. 1.

leachate from both 25 and 50 cm cores was higher than 10 cm cores, with 25 cm leachate having the maximal values (10 and 25: z ¼ 5.81, p < 0.001; 10 and 50: z ¼ 4.73, p < 0.001; 25 and 50: z ¼ 0.005, p ¼ 0.95). Proportionally, hydrophilic DOC steadily occupied a greater percentage of total DOC with increasing soil depth. 3.3. Biodegradability Soil leachate from 50 cm cores had significantly higher biodegradability than surface soils regardless of soil type and incubation time (mixed-effects ANCOVA; 2 days: F2,43 ¼ 14.65, p < 0.001; 14

Fig. 3. The % C consumed by microbes in leachate from 0 to 10, 0e25, and 0e50 cm cores across six soil types after (a) 2 and (b) 14 days incubation. The dashed lines indicate the input organic matter values. Soil types are as in Fig. 1.

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consistently more biodegradable than the input solution for the length of the incubation experiment. 3.4. Multivariate analyses Multivariate analyses were used to link soil characteristics with the DOC and DON leaching from soil cores of three depth increments. The analysis of 0e10 cm soil cores produced the most defined grouping structure of soil types, with the grouping of soils becoming more indistinct with increasing depth. Therefore we will focus our analysis on the 0e10 cm core results (ordinations for 0e 25 and 0e50 cm cores are provided in Appendix B). The analysis of 0e10 cm soil cores produced a 3-axis solution with a final stress of 8.90; subsequent axes minimally reduced stress. Based on Clarke’s rule of thumb, a final stress of 5e10 has “no real risk of drawing false inferences” (McCune and Grace, 2002). Two convergent solutions were found after one run with these data. While there were 4 noticeable groupings of soil types in the ordination produced by the first two axes, there was no clear grouping structure of soil types on the ordination of axes 2 and 3. Therefore, only patterns on the first two axes will be discussed. The replicates from the Typic Udipsamment, Entic Haplorthod, and Typic Hapludalf formed three distinct groups, while the three Typic Haplorthods overlapped, suggesting they should be grouped together (Fig. 4). All soil characteristics examined were significantly correlated with the ordination produced by the first two axes except microbial C, soil C, bulk density, and % porosity (Table 2). The soil characteristics most strongly related to axis 1 were the Feo þ Alo content, the Fed content, pH, and soil N content of soils, suggesting this axis predominantly described differences among soil types in their geochemistry. The Fed and Feo þ Alo contents of soils had the highest negative scores with axis 1 of any variable examined (¼0.999 and 0.996, respectively), which corresponded to soils with relatively high soil Fe and Al contents (Table 1). The pH of 0e 10 cm soils also had a high negative score with axis 1 (0.997), although the reason for this is less certain as there was no clear pattern of pH across soil types. Soil N had the highest positive score (0.918) with axis 1, which was reflected in fairly high soil N contents in soils positively related to axis 1 (i.e., the three Typic Haplorthods) and low soil N contents in soils negatively associated with axis 1 (i.e., Typic Udipsamment, Entic Haplorthod). Soil types were separated along axis 2 based primarily on soil texture, due to the

Fig. 4. Non-metric multidimensional scaling (NMDS) ordination of the first two axes for 0e10 cm cores. Numbers represent 3 core replicates from each soil type. Soil types are as in Fig. 1. Arrows are significant vectors of soil characteristics overlain on the ordination.

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Table 2 Fits of soil characteristic vectors with axes 1 and 2 on non-metric multidimensional scaling (NMDS) ordinations for 0e10 cm cores. Numbers in bold are significant. Soil characteristics

r2

P

Microbial C Microbial N pH Feo þ Alo Fed Soil N Soil C Bulk density % porosity Ksat Coarse sand Fine sand Clay Silt

0.34 0.63 0.61 0.76 0.80 0.57 0.11 0.05 0.05 0.47 0.51 0.70 0.63 0.79

0.060 0.001 0.001 0.001 0.001 0.003 0.422 0.685 0.684 0.013 0.003 0.001 0.001 0.001

high silt (0.994), clay (0.932), and fine sand (0.644) scores with this axis. The Typic Hapludalf had the highest silt and clay contents of any soil while the Typic Haplorthods all tended to have high fine sand contents. When we overlaid the DOC and DON leaching from 10 cm cores on the ordination of soil characteristics, neither was significantly correlated with either axis (DOC: r2 ¼ 0.06, p ¼ 0.63; DON: r2 ¼ 0.08, p ¼ 0.55). 4. Discussion 4.1. DOM leaching chemistry We evaluated DOM dynamics in soil waters as they percolated through soil cores in order to determine if DOM chemistry reflected dynamic exchange processes between incoming DOM and soil organic matter or the continual stripping of the most surfacereactive compounds from recent DOM inputs. While both models predict a strong decrease in DOC that is dominated by the preferential sorption of hydrophobic compounds as waters percolate to depth, they differ in their expectations of the chemistry of the weaker-binding fraction (i.e, hydrophilic compounds) along the same path: in the dynamic exchange model, the chemistry of the hydrophilic fraction should become progressively more distinct from that of fresh inputs as organic compounds are desorbed off soil surfaces, whereas in the chemical stripping model it should remain fairly consistent with fresh inputs. In this study, DOM dynamics in leachate from cores of six diverse soil types was consistent with the idea of dynamic exchange between incoming DOM and previously sorbed organic matter for several reasons. First, there was a net desorption of hydrophilic compounds in soil core solutions between 10 and 25 cm (Fig. 2b). This increase in hydrophilic compounds could only have originated from soil sources, suggesting previously sorbed hydrophilic compounds were displaced by incoming DOM compounds from the input solution. Second, the biodegradability assay demonstrated a shift in the quality of the hydrophilic fraction as solutions percolated through 0e10 cm cores. Solutions leaving 10 cm soil depth were more biodegradable compared to the input organic matter solution (i.e., 19e32% versus 8%, respectively) despite having similar proportions of hydrophilic compounds, indicating that the differences were attributed to quality changes within the hydrophilic fraction rather than overall DOM quality by the removal of hydrophobic compounds from solution (Figs. 2c and 3a). These biodegradability differences disappeared by 14 days, emphasizing that it was the labile fraction of the C pool (i.e., hydrophilic compounds) that was primarily responsible for the biodegradability differences (Michaelson et al., 1998; Qualls, 2004). Finally, there was limited

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net retention of DON in 0e10 cm soil cores, with significant decreases in DON not occurring until after 25 cm depth (Fig. 1b). This is consistent with the idea that high C:N ratio plant inputs displace low C:N ratio microbial by-products which then migrate into deeper soils. The idea of dynamic exchange processes structuring DOM dynamics can also explain why we observed a high retention of DOC in the 0e10 cm depth increment (on average 65%) despite this depth increment having an order of magnitude more soil C (g kg1) than the other increments we investigated (Table 1). High soil C concentrations can inhibit DOC sorption by limiting the number of available reactive binding sites on mineral surfaces (Kothawala et al., 2009). Under these conditions, DOC sorption is dominated by the net removal of stronger-binding hydrophobic compounds from solution, resulting in a proportional increase in hydrophilic compounds as solutions percolate to depth (Kaiser and Zech, 1998). Our results mimic this pattern, demonstrating both a strong retention of hydrophobic compounds in surface soils and a proportional increase in the hydrophilic composition of subsoil solutions. As previously argued, the proportional increase in hydrophilic compounds is at least partly due to the release of previously sorbed compounds that were exchanged off of soil surfaces. These processes could also explain why there was limited retention of DON in surface soils. N is contained in greater proportions in hydrophilic versus hydrophobic compounds (Lajtha et al., 2005; Möller et al., 2005). The fact that surface soils were also high in soil N suggests there was a potential reservoir of soluble N that was mobilized when soil cores were leached (Table 1). This was particularly evident for the most developed Typic Haplorthod (3), which lost more DON at 10 cm than was added to the soil core in the input solution. Also, the relatively high microbial C and N concentrations in surface soils indicates this depth increment likely contains a greater proportion of N-rich, microbial byproducts compared to deeper soils. This high retention in surface soils is most likely due to abiotic sorption to mineral soil rather than biological decomposition, despite surface soils having noticeably more microbial C and N than subsoils, for several reasons. First, this experiment measured DOM dynamics in soil cores under saturated conditions, which would have favored preferential flow of soil waters and limited the opportunities for microorganisms to interact with percolating DOC. Second, the input organic matter solution was dominated by hydrophobic compounds (w60%), which can be highly resistant to biotic decomposition (Qualls et al., 2002; Qualls, 2004), especially given the short time frame of this experiment which measured DOM dynamics over the course of minutes to hours. Yano et al. (2005) similarly concluded that abiotic rather than biotic mechanisms were primarily responsible for DOM retention on their soils due to the low presence of biodegradable hydrophilic compounds (<2%) in their solutions. Finally, favorable entropy changes occur when hydrophobic compounds are removed from solution (Qualls, 2000), which facilitates their exposure to soil surfaces where ligand exchange between their acidic functional groups and the hydroxyl groups of Fe and Al hydrous oxides can bind hydrophobic compounds to soil surfaces (Yano et al., 2004). These soils were all low in clay content, supporting the idea that hydrous oxides played a more significant role in DOM retention. 4.2. Leachate biodegradability with depth In their models describing DOM dynamics as waters percolate into deep soils, Sanderman et al. (2008) and Kaiser and Kalbitz (2012) both predict that the biodegradability of DOC will decrease with increasing depth as compounds become either more recalcitrant in nature (i.e., Sanderman et al., 2008) or “hardly

decomposable” despite being nutrient rich (i.e., Kaiser and Kalbitz, 2012). Our results contradict their predictions; all of the leachate solutions we examined became more biodegradable with increasing soil depth. These differences occurred despite the addition of nutrients to incubation solutions, emphasizing that these differences were related to C quality rather than changes in nutrient availability as solutions percolated to depth. This increase in biodegradability occurred concomitantly with an increase in the proportion of hydrophilic compounds in core leachate, which tend to be highly biodegradable (Cleveland et al., 2004; Kaushal and Lewis, 2005). Qualls and Haines (1992) found similar results as ours in a field experiment where they examined the biodegradability of DOC from various strata in oak-hickory forests of North Carolina, USA. The amount of C remaining after 134 days of incubation was lower in soil leachate from subsoil horizons compared to that from the A horizon. However, the relatively low microbial C and N in the subsoils of this study brings into question whether or not microorganisms in the field actually use DOM percolating at this depth to any great extent, even if its potential biodegradability is fairly high (upwards of 70% in 50 cm leachate at 14 days). Therefore, it may be less true that “subsoil DOM, having the signature of highly degraded organic material, seems to be rather the left over of decomposition than an energy and nutrient source,” (Kaiser and Kalbitz, 2012) and more that the opportunities for biodegradation are fewer because of lower microbial populations (Toosi et al., 2012). The relatively high biodegradability of DOM at depth provides further support for the idea that abiotic versus biotic mechanisms are primarily responsible for DOM retention in soils. The idea that DOM leaching losses are a function of exchange reactions between stronger-binding compounds that displace previously sorbed, more highly degraded compounds, and that these desorbed, N-rich compounds are potentially biodegradable, brings into question our understanding of the controls over DON leaching losses from forest ecosystems. Previously, DON leaching losses have been described as an “N leak” from temperate forests (Hedin et al., 1995; Perakis and Hedin, 2002; Neff et al., 2003). As a part of the “leak” hypothesis, DON losses were expected to consist of relatively refractory compounds that resisted biotic decomposition over the time scale of leaching. However, the steady removal of hydrophobic, biotically-unavailable compounds from percolating solutions in favor of labile, hydrophilic compounds, coupled with the potential for over half of the DOM in deep soils to be readily degraded by microbes, calls this assumption into question. Instead, the tendency for terrestrial ecosystems to “leak” DON is likely due to the chemistry of DON compounds which only weakly sorb to mineral soils and are easily displaced by fresh inputs of strongerbinding DOM chemicals rather than the inability of biota to process relatively recalcitrant compounds before they percolate to deep soils. Indeed, the formation of complex N-containing compounds has been implicated as one mechanism contributing to soil organic matter stabilization (Swanston et al., 2004), providing further evidence that these complex molecules are more likely to remain in soils rather than leach out of the ecosystem. Multiple studies have cited soil sorption dynamics as the primary mechanism regulating DOM chemistry over biotic controls (Qualls et al., 2002; Yano et al., 2005). This is in contrast to our understanding of inorganic N cycling, which is tightly controlled by microbial mineralization and immobilization (Schimel and Bennett, 2004). The rate of water movement through soil influences the exposure time of percolating DOM to both soil sorption and biotic uptake processes (Asano et al., 2006; Castellano and Kaye, 2009). Therefore, when fast water movement occurs, as is the case in saturated water flow, these retentive processes are constrained and DOM is expected to experience less of a shift in chemistry as it

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percolates to depth (Kaiser and Zech, 1998). Because this experiment was conducted under saturated flow, the shift in DOC chemistry between the input solution and 50 cm depth, as indicated by the proportion of hydrophilic compounds in soil core leachate and the biodegradability of solutions, represents the minimum amount of chemical changes expected to occur as DOC percolates through these soils. Unsaturated flow could facilitate greater exchange between incoming compounds and those sorbed to the soil (Qualls, 2000), greater overall DOC retention, and/or increased biotic consumption, resulting in even greater chemical and biodegradability differences between incoming DOM and subsoil solutions, although the exact nature of these differences is difficult to predict. 4.3. DOM quantity and quality as a function of soil characteristics We examined DOC and DON leaching from cores of six different soil types that varied in physicochemical properties to identify how soil parameters constrained these leaching losses. We expected leaching losses to be lowest from the soil types that had more available free binding sites due to being finer textured or having higher quantities of amorphous minerals. Instead, there were no significant differences in DOC leaching losses, while only three soil comparisons differed in DON leaching losses: Typic Haplorthods 2 and 3 lost significantly more DON than the Typic Hapludalf. This result was surprising given that these soils varied in key characteristics expected to impact DOM leaching dynamics, such as texture, hydraulic conductivity, and Fe and Al mineralogy. Indeed, the multivariate analyses identified distinct soil groups based on multiple soil parameters, emphasizing the variable nature of soil types we investigated. Regardless, all the soils demonstrated a strong capacity to retain DOC, removing 72e85% of the DOC added from the input solution by the time solutions reached 50 cm depth. They were also fairly consistent in DOC quality, with few differences in the hydrophobic and hydrophilic contents of leaching DOC or the in the degree of biodegradability. Distortion of the hydrophobic to hydrophilic ratio would only occur if there were substantial differences in the amount of free binding sites across the soils we examined, causing a gradient in the level of competition for free binding sites between hydrophobic and hydrophilic compounds (Kaiser and Zech, 1998). 4.4. Conclusions We investigated DOM dynamics in leachate from soil cores representing six diverse forest soils to better understand how soils regulate DOM leaching losses in terrestrial environments. The results of this study supported a dynamic exchange model for DOM movement through soil where highly sorptive, hydrophobic compounds from fresh inputs displace previously-sorbed, weakerbinding hydrophilic compounds that are N-rich byproducts of microbial degradation. These hydrophilic compounds migrate into deeper soils and may contribute to the increasing biodegradability of soil leachate with depth found in this study. This increase in biodegradability with depth has ramifications for our understanding of DON losses from temperate forests, which have previously been described as “leaks” because they occur despite Nlimitation by biota. Our results suggest these “leaks” occur not because N is contained in biotically-unavailable compounds, but because most DON compounds only sorb weakly to mineral soils and are easily displaced by stronger-binding compounds. It will be important to examine DON chemistry in a field setting to verify these laboratory results. All the soil types examined in this study retained DOC and DON at similar levels when supplied with a common organic matter

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solution despite varying in key soil characteristics known to impact DOM leaching dynamics. Although this result may be an artifact of our using a common input solution, it is more likely that the overall strong sorption capacity of all the soils we examined drove the DOM chemistry towards uniformity. In the field, where these soils experience non-uniform DOM inputs reflective of their unique forest conditions under unsaturated conditions, DOM leaching losses may demonstrate greater variability in both chemistry and quantity.

Acknowledgments We thank Dr. Phu Nguyen for laboratory assistance with soil Fe and Al contents, and J. Darling, G. Smith, A. Esper, and J. Berlin for helping with sample collection and processing. The USDA Forest Service graciously provided access to field sites. This project was conducted in agreement with the laws of the United States and was funded by NSF grant DEB 0448058 to D. E. Rothstein and by the Michigan Agricultural Experiment Station.

Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.soilbio.2013.10.052.

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