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Soil Biology & Biochemistry 42 (2010) 1743e1750

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Soil Biology & Biochemistry

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Effects of amino-acid chemistry and soil properties on the behaviorof free amino acids in acidic forest soils

David E. Rothstein*

Department of Forestry, Michigan State University, East Lansing, MI 48824-1222, USA

a r t i c l e i n f o

Article history:Received 2 April 2010Received in revised form1 June 2010Accepted 16 June 2010Available online 30 June 2010

Keywords:Soil amino acidsOrganic nitrogenMineralizationMicrobial assimilationSorptionTemperate forest soils

* Tel.: þ1 517 432 3353; fax: þ1 517 432 1143.E-mail address: rothste2@msu.edu

0038-0717/$ e see front matter � 2010 Elsevier Ltd.doi:10.1016/j.soilbio.2010.06.011

a b s t r a c t

Free amino acids (FAAs) in soil solution are increasingly recognized as a potentially important source ofnitrogen (N) for plants, yet we are just beginning to understand the behavior of FAAs in soil. I investigatedthe effects of amino-acid chemistry and soil properties on mineralization, microbial assimilation andsorption of amino-acid N in soils from three ecosystems representing the two endpoints and mid point ofa temperate forest fertility gradient ranging from low mineral N availability/high FAA oak forests to highmineral N availability/low FAA maple-basswood forests. Soils were amended with six 15N-labeled amino-acid substrates that ranged widely in chemical properties, including molecular weight, C:N ratio, averagenet charge, hydrophobicity, and polarity: Arginine (Arg), Glutamine (Gln), Glutamate (Glu), Serine(Ser), Glycine (Gly) and Leucine (Leu). Mineralization of amino-acid N accounted for 7e45% (18% avg.) ofthe added label and was most strongly affected by soil characteristics, withmineralization increasing withincreasing soil fertility. Mineralization of amino-acid N was unrelated to amino-acid C:N ratio, rather,I observed greater N mineralization from polar FAAs compared to non-polar ones. Assimilation of amino-acid N intomicrobial biomass accounted for 6e48% (29% avg.) of the added label, andwas poorly predictedby either intrinsic amino-acid properties or soil properties, but instead appeared to be explicable in termsof compound-specific demand by soilmicoorganisms. Sorption of amino-acid N to soil solids accounted for4e15% (7% avg.) of the added label andwas largely controlled by charge characteristics of individual aminoacids. The fact that both positively- and negatively-charged amino acids were more strongly sorbed thanneutral ones suggests that cation and anion exchange sites are an important factor controlling sorption ofFAAs in these acid forest soils. Together, the findings from this study suggest that there may be importantdifferences in the behavior of free amino acids in sandy, acidic forest soils compared to generalizationsdrawn from finer-textured grassland soils, which, in turn, might affect the availability of some FAAs in soilsolution.

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1. Introduction

Free amino acids (FAAs) in soil solution are increasingly recog-nized as a potentially important source of nitrogen (N) for plants.The capacity for uptake of FAAs by plants is widespread amongtaxonomic groupings and biomes (Lipson and Näsholm, 2001;Näsholm et al., 2009), and N in FAA pools in soil solution havebeen shown to rival or exceed that ofmineral N, particularly in cold-temperate forests (Finzi and Berthrong, 2005; Rothstein, 2009),boreal forests (Nordin et al., 2001; Kielland et al., 2007), and arcticand alpine tundra (Chapin et al., 1993; Raab et al., 1996). Whereassoil biogeochemists have a well-developed understanding ofcontrols over the production, consumption and transformation of

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mineral forms of N in soil, and how these affect availability of N forplant uptake, we are just beginning to understand the behaviorof FAAs in soil. Much of our knowledge comes from studies thatmeasure standing pools of bulk FAAs,with no discrimination amongdifferent amino acids. Because the 20 common amino acids varygreatly in intrinsic properties, and because plants have the capacityto take up a variety of FAAs (Kielland, 1994; Öhlund and Näsholm,2001; Persson and Näsholm, 2001; Weigelt et al., 2005), it isimportant that we develop a better understanding of variabilityamong amino acids in their behavior in soil. Whereas plants mayhave the physiological capacity to take up a wide suite of aminoacids, the pool of amino-acid species available to contribute to plantnutrition may be constrained by differences among amino acids intheir potential for mineralization, microbial assimilation and sorp-tion to soil solids.

Several intrinsic properties of amino acids have been proposedto affect their behavior in soils, including molecular weight

Table 1Soluble N pools and background soil characteristics (0e15 cm) of the three studysites.

Site 1 Site 3 Site 5

Soluble N Pools (mg N m�2)a

Free amino acids 94 41 3NH4

þ 104 190 100NO3

� 32 63 233

Soil CharacteristicsSoil pH (H2O) 4.5 4.6 5.0Clay (%) 7.8 5.7 8.1Silt (%) 2.0 5.7 6.7Fine Sand (%) 22.3 49.5 33.1Coarse Sand (%) 67.9 39.1 52.2Soil C (mg/g) 15.4 10.3 19.0Soil N (mg/g) 0.7 0.7 1.4Soil C:N Ratio 22.5 15.2 13.7Microbial Biomass C (ug/g)b 400 671 1169

a Calculated from Rothstein (2009); soils extracted in 4 mM CaCl2 (1:2 ratio);averaged across 6 monthly sample dates.

b From Rothstein (2009).

Table 2Properties of amino acids used in the labeling experiment.

Arginine Glutamate Glutamine Serine Glycine Leucine

Polarity Polar Polar Polar Polar Non-Polar

Non-Polar

Side-chainChemistry

Basic Acidic Neutral Neutral Neutral Neutral

Iso-electric Pointa 10.8. 3.2. 5.7. 5.7. 6.0. 6.0.Average Net Chargeb

Site 1 1.003. �0.725. 0.005. 0.005. 0.007. 0.007.Site 3 1.002 �0.769 0.004 0.005 0.006 0.005Site 5 1.001 �0.894 0.001 0.002 0.002 0.002

Hydropathy Indexc �4.5 �3.5 �3.5 �0.8 �0.4 3.8Molecular Weight 174 147 146 105 75 131Molar C:N Ratio 1.5 5 2.5 3 2 6N in Side Chains. Yes. No. Yes. No. No. No.

a McMurry 1988.b Estimated using the HendersoneHasselbach equation based on pKa’s of indi-

vidual amino acids and pH in water for each site.c Ranges from �4.5 (most hydrophyllic; Arginine) to þ4.5 (most hydrophobic;

Isoleucine); Kyte and Doolittle (1982).

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e17501744

(Kumari et al., 1987; Kielland,1994; Harrison et al., 2007), N content(Lipson et al., 1999; Bonde et al., 2001) and charge characteristics(Kumari et al., 1987; Jones and Hodge, 1999; Gonod et al., 2006).Amino acids vary greatly in molecular weight from a low of 75 forglycine to a high of 204 for tryptophan (McMurry, 1988). Lowmolecular weight amino acids are thought to be more available forplant uptake (Kielland, 1994), and potentially a poor substratefor microbial growth due to lower C content (Lipson et al., 1999).Kumari et al. (1987) identified molecular weight as an importantfactor controlling adsorption to soil solids with larger amino acidsexperiencing lower adsorption due to greater steric interference.Molar N content has been hypothesized as a potential driver of Nmineralization from FAAs, with the expectation that N from lowerC:N ratio amino acids is more likely to be mineralized than N fromhigh C:N ratio amino acids (Bonde et al., 2001; Roberts et al., 2009).However, Roberts et al. (2009) found that C:N ratio was a poorpredictor of amino-acid mineralization in soil from a UK grassland,and argued instead that the relative position of amino acids withinbiosynthetic pathways may be more important in determiningpatterns of microbial assimilation and mineralization. Becauseof their diversity of functional groups FAAs can vary widely in netcharge at soil pH, which, in turn, affects their interactions withsoil solids. Several studies have shown that positively-chargedamino acids (lysine and histidine) are strongly sorbed to soil solids;whereas neutral and negatively-charged amino acids are not(Kumari et al., 1987; Jones and Hodge, 1999; Gonod et al., 2006).

Many of the detailed studies of amino-acid behavior in soil havecome from grassland or agricultural soils (e.g. Jones andHodge,1999;Gonodet al., 2006; Roberts et al., 2009),with a relative paucity of datafrom forest soils. More detailed information on amino-acid dynamicsin northern forests is important because FAAs are thought to makean important contribution to N cycling in these systems, and becausetheir generally coarser texture and greater acidity may result inimportant differences compared to grassland and agricultural soils. Inthis study, I investigated the effects of amino-acid chemistry andsoil properties onmineralization,microbial assimilation and sorptionof amino-acid N in soils from three ecosystems shown previouslyto vary widely in soluble pools of total FAAs (Rothstein, 2009).I hypothesized that mineralization of amino-acid N would increasewith decreasing amino-acid C:N ratio and would increase withincreasing site fertility. I further hypothesized that microbial assim-ilation of amino-acid N would be greater for amino acids thathad highmolar C:N ratios, and that assimilationwould increasewithincreasing site fertility (due to higher microbial biomass). Finally,I hypothesized that abiotic sorption of amino-acid N would decreasefrompositively-charged to neutral to negatively-charged compoundsand would increasewith increasing site fertility (due to higher levelsof soil organic matter and finer texture).

2. Materials and methods

2.1. Study sites and amino-acid substrate selection

I selected three of the five sites studied by Rothstein (2009), tospan the range of soluble FAAs found in soil (Table 1). These sites arelocated along a well-studied N-mineralization/forest productivitygradient in the northwestern Lower Peninsula of Michigan, USA(Zak et al., 1986, 1989), and are representative of associationsbetween soil properties, species composition,mineral N availability,and productivity throughout the northeastern US (Pastor et al.,1984; Reich et al., 1997; Morris and Boerner, 1998; Finzi andBerthrong, 2005). A previous study demonstrated that standingpools of FAAs followed an opposing pattern to that of mineral N(Rothstein, 2009). Site 1 is an oak (Quercus)-dominated forestgrowing on soils developed in coarse, sandy outwash sediments

that had the highest standing pools of FAA’s and the lowest standingpools ofmineral N. Site 3 is amixed oak/maple (Acer) forest growingon soils developed in fine, sandy till that had intermediate pools ofFAAs and mineral N. Site 5 is a maple-dominated forest growing onsoils developed in fine, sandy till that had the lowest standing poolsof FAAs and highest standing pools of mineral N.

I selected 6 amino-acid substrates that ranged widely in chem-ical properties: Arginine (Arg), Glutamine (Gln), Glutamate (Glu),Serine (Ser), Glycine (Gly) and Leucine (Leu) (Table 2). Previousresearch on 14C-labeled amino-acid mineralization has suggestedthat charge characteristics have a large influence on amino-acidsorption/mineralization dynamics (Kumari et al., 1987; Jones andHodge, 1999; Vinolas et al., 2001; Gonod et al., 2006). Therefore Ispecifically chose an amino acid that would carry a positive chargeat soil pH (Arg) and one that would carry a negative charge (Glu).I also selected amino acids to span a wide gradient from veryhydrophilic to very hydrophobic (Table 2), reasoning that hydro-phobicity might influence solubility, microbial uptake and reac-tivity with soil organic matter. I chose amino acids that would spana wide range of molecular weights and molar C:N ratios, as well asamino acids with N-containing side chains vs. those without N intheir side chains. I acquired amino acid substrates that wereuniversally-labeled with 98e99 at% 15N from Cambridge IsotopeLaboratories, Inc. (Andover, MA), and made up labeling solutions of

Fig. 1. Schematic representation of the pools of 15N tracer recovered and their use inestimating mineralization, sorption and microbial assimilation of labeled amino acids.Mineralized label was calculated as the recovery of extractable inorganic 15N in live soil,sorption was calculated as the residual 15N in sterile soil following K2SO4 extraction, andmicrobial assimilationwas calculated as residual 15N in live less residual 15N in sterile soil.

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e1750 1745

each amino acid in deionized water (DI) to achieve equivalentconcentrations of N (30 mg N mL�1).

2.2. Field sampling and laboratory analyses

Within each site, I located a 100-m � 40-m sampling plot on anarea of uniform terrain, with no evidence of recent disturbance, andas far as possible from roads or other boundaries. On July 7, 2008 Icollected 5 soil samples per plot, with one sampling point locatedrandomly within each 20-m interval along the long axis of theplot. At each sampling point, I collected two soil cores (5.08 cmdiameter � 15 cm depth) which were composited in a single bag,immediately packed on ice and transported to the laboratory. On themorning following collection, each soil sample was passed througha 4-mmsieve to remove rocks, roots andother debris and thoroughlyhomogenized. A 10-g fresh weight subsample was removed fromeach sample and oven-dried overnight at 105 �C to determinemoisture content, and two, 125 g fresh weight subsamples wereplaced in beakers, coveredwith plastic wrap and stored overnight at5 �C. On the morning of the third day, I added enough deionizedwater (DI) to each subsample to achieve 20% gravimetric moisturecontent (fresh soil basis). One subsample from each sample,designated as the “sterilized” treatment, was placed uncovered ina dessicator and fumigated with CHCl3 for 24 h in order to kill activemicroorganisms. The other subsample, designated the “control,”wasplaced in a closed dessicator,without CHCl3 for 24 h. FollowingCHCl3fumigation and venting, the sterilized subsamples were coveredtightly with aluminum foil and heat treated (105 �C) at ambientpressure for 30min in order to denature any exoenzymes remainingin soil.

Following fumigation and heat treatment of soils I weighed outseven, 10-g dry-weight-equivalent subsamples of each control andfumigated soil into 50 mL polypropylene centrifuge tubes. Six of thesubsamples were injected with 1-mL of the Arg, Gln, Glu, Gly, Leuor Ser labeling solutions to achieve a target enrichment of 3 mg15N gd w�1, whereas the seventh was injected with 1 mL of DI toserve as a control for background 15N enrichment. Labeling solutionsand DI were injected into the soil using a 1-mL syringe in five 0.2-mlaliquots, with solution dispensed evenly as the needle was removedfrom the soil. Soils were incubated for 4 h at 25 �C, after which theywere extracted with 0.5 M K2SO4 in a two-stage process. In the firststep, 25 ml of K2SO4 was added to each tube; the tubes were cappedand shaken for 20 min on an end-over-end rotisserie shaker, andthen centrifuged at 182 g for 5 min. This was repeated with a second25-ml aliquot of K2SO4 and the two supernatants were combinedand filtered through a pre-leached Whatman #42 filter. Residualsoil remaining in the tubeswas combinedwith soil particles trappedon the filter and oven dried at 65 �C for 48 h. Weighing, labeling,incubating and extracting of samples was organized in blocks bywithin-site replicate in order to avoid confusing effects due to delaysin processing with effects of site and/or amino-acid substrate.

Potassium sulfate extracts from sterilized and control treatmentswere analyzed for NH4

þ and NO3� using colorimetric reactions in

96-well microplates (Sinsabaugh et al., 2000; Doane and Horwath,2003) and then an aliquot containing 25e50 mg N was diffusedonto acid traps following a modified method of Brooks et al. (1989).Both NH4

þ andNO3�were diffused together in a capped specimen cup

for 12 d by adding MgO and Devarda’s alloy simultaneously to eachaliquot. Acid traps were then dried over sulfuric acid, rolled in tincapsules, and analyzed for atom % 15N on a PDZ Europa ANCA-GSLelemental analyzer interfaced to a PDZ Europa 20e20 isotope ratiomass spectrometer (Sercon Ltd., Cheshire, UK) at the University ofCalifornia, Davis Stable Isotope Facility. The entire sample of eachdried soil remaining following extraction was pulverized in a ballmill and a 20e30 mg subsample was weighed into tin capsules and

analyzed for total N and atom %N at the UC Davis Stable IsotopeFacility. Samples from the DI treatment were processed in parallelwith the 15N-tracer labeled samples and used to correct for back-ground 15N in both K2SO4 extracts and residual soils.

2.3. Calculations and statistical analyses

I used isotopic data to calculate the percent recovery of the 15Ntracer in the following pools: mineralized N, N sorbed to soil solidsvia abiotic processes, and N assimilated by microbial cells (Fig. 1).Mineralized N was expressed simply as the percent recovery oftracer 15N in the mineral N pool in the control treatment. Abioti-cally-sorbed N was expressed as the percent recovery of tracer 15Nin the residual soil pool in the sterilized treatment. Microbialassimilation was calculated as the difference between residual soil15N in the control and sterilized treatments. I first used two-wayanalysis of variance (ANOVA) to test for main effects of site andamino-acid species on recovery in these pools. This initial ANOVAanalysis was followed by Bonferroni tests of all pairwise compari-sons among sites, within each amino-acid treatment, in order toexamine differences in amino-acid behavior among sites.

I took two approaches to analyze variation in mineralization,sorption and assimilation among amino acids. First, I regressedsite-level means of recovery in the various pools against severalcontinuous indices of amino-acid chemistry (Table 2) as anexploratory tool to identify chemical properties of amino acidsimportant in determining their fate in soil. These indices includedhydropathy (an index of the hydrophobic vs. hydrophilic natureof an amino acid based on its side-chain properties; Kyte andDoolittle, 1982), C:N ratio, molecular weight, iso-electric pointand average net charge estimated for each site based on soil pH.Prior to conducting regression analyses, I first conducted analysesof covariance (ANCOVA) to test for significant interactions betweensite and each index of amino-acid chemistry. In cases wherea significant interaction occurred, I conducted separate regressionanalyses for each site (n ¼ 6); otherwise data from all sites weregrouped for analysis (n ¼ 18). Next, I explored alternative groupingfactors for the amino-acid effect in two-way ANOVAs with site asthe second main effect. These grouping factors included: polar vs.non-polar, acidic and basic side chains vs. neutral side chains(hereafter referred to as side-chain chemistry) and N-containingside chains vs. N-free side chains. Values for mineralized N andabiotically-sorbed N were log-transformed to improve normality

Fig. 2. Mineralized 15N as a function of amino-acid substrate and site for live (a) and sterilized (b) soil samples. Values are means � 1 standard error. Bars with the same letter,within each amino-acid substrate do not differ significantly.

Table 3Results for simple linear regressions of mineralization, abiotic sorption and micro-bial assimilation against amino-acid properties. For independent variables whereAnalysis of Covariance indicated a significant interactionwith site, regression resultsare reported individually for each site. Bold font indicates a significant regression atP < 0.05.

Dependent Independent adjR2 P

Mineralized N Hydropathy e Site 1 0.032 0.734Hydropathy e Site 3 0.439 0.091Hydropathy e Site 5 0.279 0.162C:N Ratio e Site 1 <0.001 0.846C:N Ratio e Site 3 0.079 0.298C:N Ratio e Site 5 0.296 0.153Isoelectric Point <0.001 0.735Average Net Charge <0.001 0.666Molecular Weight <0.001 0.626

Abiotic Sorption Hydropathy 0.277 0.014C:N Ratio <0.001 0.699Isoelectric Point 0.100 0.109Average Net Charge 0.018 0.269Molecular Weight 0.502 0.001

Assimilation Hydropathy 0.130 0.078C:N Ratio <0.001 0.661Isoelectric Point 0.118 0.089Average Net Charge 0.157 0.058Molecular Weight <0.001 0.930

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e17501746

and homogeneity of variances. All statistical analyses wereperformed using SYSTAT for personal computers.

3. Results

Mineral 15N recoveries in the sterilized treatment were nearzero for all amino acids except Gln (Fig. 2b), indicating that Iwas largely successful in eliminating microbial activity in thistreatment. Mineralization of Gln in the sterilized treatment wasapparently a real phenomenon, and not an artifact of interferencewith the colorimetric determination of NH4

þ (Herrmann et al.,2005), because it arose from an increase in the atom% enrich-ment of the mineral N pool (4.5 at% vs. 0.8 at% for all other aminoacids) rather than an increase in the inorganic pool size (65 mg N vs78 mg N for all other amino acids). Frankenberger and Tabatabai(1991) showed that residual glutaminase activity, ranging from3.5 to 7 mg NH4

þeN g�1 h�1, remained in soils following heatsterilization, suggesting that residual exoenzyme activity mayexplain the relatively high mineralization of this amino acid in thesterilized treatment.

Mineralization of amino-acid N in the live soil treatmentaccounted for 18% of the added label averaged across all sites andamino acids, with an absolute range from 7 to 45%. There wasan overall pattern of increasing mineralization with increasingsite fertility (P < 0.001 for site main effect), although patterns ofmineralization among sites varied among individual amino acids(Fig. 2a). Arginine, Glu, Ser and Gly showed the only statistically-significant increases in mineralization with increasing fertility.Mineralization of N from Arg was noteworthy in that variationamong sites for this single amino acid spanned the entire range ofmineralization rates found across all 6 FAAs. This variability inthe strength of the site effect on mineralization resulted in manysignificant interactions between indices of amino-acid chemistryand site in ANCOVA analyses. This, in turn, resulted in reduceddegrees of freedom for the regressions of mineralization againstamino-acid chemical properties. Nevertheless, none of the indicesof amino-acid chemistry were a significant predictor of minerali-zation (Table 3). Hydropathy index came the closest with a P-valueof 0.091 at site 3; however, it yielded poor fits for the other twosites. In contrast, grouping amino acids by polarity and presencevs. absence of side-chain N, yielded significant effects in two-wayANOVAs (Table 4). Nitrogen from polar amino acids was mineral-ized at a significantly greater rate than N from non-polar aminoacids, with a stronger polarity effect at sites 3 and 5 comparedto site 1 (Table 4; Fig. 4). Similarly, 15N from amino acids withN-containing side chains was mineralized at a greater rate thanfrom those with N-free side chains (Table 4; Fig. 4).

Assimilation of tracer 15N into microbial biomass averaged 29%across all sites and substrates, with an absolute range from 6 to48% (Fig. 3b). There was not a significant overall effect of site onmicrobial assimilation (P ¼ 0.225), although there were significantdifferences among amino acids (P < 0.001). Arginine, Ser andLeu appeared to form a groupwith lower 15N assimilation (20e24%)than the group composed of Gln, Glu and Gly (35e37%). Thesedifferences in tracer assimilation among amino-acid substrateswere not explicable by any of the indices of amino-acid chemistry Iselected. None of the continuous indices were significant predictorsof assimilation in regression analysis, nor were any of the groupingfactors significant in ANOVA (Tables 3 and 4). Hydropathy indexand average net charge were both close to significant as continuouspredictors at P ¼ 0.078 and P ¼ 0.058, respectively. The trends herewere toward lower assimilation of more hydrophobic aminoacids and lower assimilation of more electronegative amino acids(data not shown).

Recovery of tracer 15N in the abiotically-sorbed pool averaged 7%across all sites and substrates, with an absolute range from 4 to 15%(Fig. 3a). Therewas an overall pattern of decreasing abiotic sorptionwith increasing site fertility (P < 0.001 for site main effect),although this was only statistically significant for Glu, Ser and Gly.

Table 4Analysis of variance results for effects of amino-acid grouping factors on minerali-zation, abiotic sorption and microbial assimilation. Bold font indicates a significanteffect at P < 0.05.

Parameter Grouping Factor F1,84 P maina P interactionb

Mineralized N Polarity 47.010 <0.001 0.001Side Chain Chemistryc 0.123 0.727 0.029Side-chain N 5.562 0.021 0.197

Abiotic Sorption Polarity 11.372 0.001 0.858Side-chain Chemistry 152.777 <0.001 0.805Side-chain N 16.164 0.000 0.331

Assimilation Polarity 0.598 0.442 0.887Side-chain Chemistry 1.354 0.248 0.308Side-chain N 1.138 0.289 0.842

a F-score and P-value for main effect of amino-acid grouping factor.b P-value for site � grouping factor interaction term.c Amino acids placed into two groups: those with acidic or basic side chains

(Arg, Glu) and those with neutral side chains (Gln, Ser, Gly, Leu).

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e1750 1747

In contrast to mineralized 15N, there were no significant interac-tions between site and any of the continuous indices of amino-acidchemistry in ANCOVA. Pooled across all sites, hydropathy andmolecular weight were the only significant predictors of abioticsorption (Table 3; Fig. 5), with sorption increasing with decreasinghydrophobicity and increasing molecular weight (Fig. 4). Groupingamino acids by polarity, side-chain chemistry and side-chain N allyielded significant effects in two-way ANOVAs with site (Table 4;Fig. 5). Side-chain chemistry was the grouping factor with the mostpronounced effect, with 15N tracer from acidic Glu and basic Arghaving nearly twice the recovery in this pool than tracer from any ofthe neutral amino acids (Table 4; Fig. 5e).

4. Discussion

Variability among compounds and ecosystems in the fate ofamino-acid N added to these acid forest soils was largely explicableby a combination of intrinsic chemical properties of the amino acidsthemselves, their relative importance to microbial metabolism andphysical and chemical properties of the study soils. Mineralizationof amino-acid N appeared to be most strongly affected by soilcharacteristics, with mineralization increasing with increasing soilfertility. Variability in microbial assimilation was poorly predictedby either intrinsic amino-acid properties or soil properties, butinstead appeared to be explicable in terms of compound-specificdemand by soil micoorganisms. As hypothesized, sorption to soilsolids was largely controlled by charge characteristics of individualamino acids; surprisingly, however, both positively and negatively-

Fig. 3. Tracer 15N recovery in the abiotically sorbed (a) and microbial biomass (b) pools aswith the same letter, within each amino-acid substrate do not differ significantly. Sites are

charged amino acids were more strongly sorbed than neutral ones.My findings suggest that there may be important differences in thebehavior of free amino acids in sandy, acidic forest soils compared togeneralizations drawn from finer-textured grassland soils, which, inturn, might affect the availability of some FAAs in soil solution.

As hypothesized, mineralization of amino-acid N increased withincreasing site fertility. These findings are consistent with a similar15N-Leu labeling experiment with live soils from these same sites(Rothstein, 2009) and a 15N-Gly labeling experiment along a similarforest soil fertility gradient in Conneticut, USA (Finzi and Berthrong,2005). In all three studies, it appears that the N status of the soilexerts a strong influence over the mineralization of N from FAAs,with mineralization rates increasing with decreasing C:N ratio ofsoil organic matter. This pattern suggests that microorganisms areutilizing FAAs primarily as a C source at high fertility vs. utilizationas a source of both C and N at low fertility, that amidohydrolaseexoenzyme activity increases with site fertility, or some combina-tion of the two. Rapidmineralization of N from FAAs at high fertilitymay, in turn, contribute to observations of decreasing abundance ofFAAs in soil solution and greater reliance on mineral N by plantswith increasing forest soil fertility (Nordin et al., 2001; Finzi andBerthrong, 2005; Gallet-Budynek et al., 2009; Rothstein, 2009).

Contrary to my original hypothesis, there was no relationshipbetween amino-acid C:N ratio and N mineralization. This finding isconsistent with the results of Roberts et al. (2009) who found norelationship between amino-acid C:N ratio and net Nmineralizationin a study where 19 unlabeled amino acids were incubated ina grassland soil. Instead, polarity and the presence of side-chain Nwere the only intrinsic chemical properties associated with greatermineralization (Table 4; Fig. 3). The fact that polarity explained a fargreater proportion of the variation in mineralization (Table 4) thandid side-chain N, combined with the fact that the only amino acidswith N-containing side chains were both polar (Table 2), suggeststhat the statistically-significant effect of side-chain N is likelyspurious and driven by covariation with polarity. Further evidencefor this conclusion comes from the fact that the amino acid with thegreatest rates of N mineralization was Ser, a polar amino acid withan N-free side chain. Polarity is plausible as a potential driver ofmineralization in that polar amino acids may be more soluble,and thusmore available formicrobial uptake andmineralization (e.g.Barraclough, 1997) or reaction with extracellular amidohydrolases.However, it is unclear how biologically important the polarityeffect is compared to the effects of compound-specific differences inmicrobial metabolism as proposed by Roberts et al. (2009). Theseauthors also observed rapid rates of N mineralization from Arg, butattributed this to its positioning at the endpoint of a biosyntheticpathway, rather than its polarity or C:N ratio. Conversely, Glu is

a function of amino-acid substrate and site. Values are means � 1 standard error. Barsdenoted by bar colors as in Fig. 2.

Fig. 4. Mineralized 15N recovery as a function of site and amino-acid polarity (a) or side-chain N (b). Values are means � 1 standard error. Sites are denoted by bar colors as in Fig. 2.

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e17501748

a polar amino acid that had very low rates of mineralization inthis study (Fig. 2a), but very high rates of microbial assimilation(Fig. 3b), perhaps reflecting its central role in metabolic pathways ofN assimilation (Paul and Clark, 1996). In summary, these findingssuggest that polarity may generally influence the accessibility ofFAAs tomicrobial uptake or enzymatic cleavage, but that compound-specific metabolic properties may ultimately drive differences inmineralization potential among amino acids.

There was significant variation in microbial N assimilationamong the 6 amino acids studied; however, contrary to my originalhypothesis, microbial assimilationwas unrelated to amino-acid C:Nratio or any other intrinsic chemical property. Instead, microbialassimilation appears to be driven by compound-specific patterns ofmicrobial utilization (as suggested above). Amino acids formed twodistinct groups in terms of N assimilation potential with N fromGln,Glu and Gly being assimilated at nearly twice the rate of N from Arg,

Fig. 5. Abiotic sorption of 15N as a function of hydropathy index (a), molecular weight (b), avacid substrates. Values are means � 1 standard error. Sites are denoted by bar colors as in

Ser and Leu (Fig. 3b). These results are consistent with findings foramino-acid composition of soil microbial biomass across a diversearray of soils (Friedel and Scheller, 2002), in which Glu and Gly arefound at 2e3 times the concentration of Ser, Arg and Leu. Furtherevidence for compound-specific metabolic demand as a driverof microbial assimilation comes from the significant decline in Serassimilation with increasing site fertility (Fig. 3b). Serine occurs athigh concentrations in fungal cell walls (Wagner and Mutatkar,1968) and Friedel and Scheller (2002) found an increase in theSer content of microbial biomass in more acidic soils, which theyinterpreted as reflecting a shift in biomass composition frombacteria to fungi. Thus the decrease in Ser-N assimilation from site 1to site 5 is likely explained by the decline in fungal:bacterial ratiopreviously described for this fertility gradient (Myers et al., 2001).Although it was not statistically significant, mineralization of Nfrom Ser trended in the opposite direction as Ser-N assimilation,

erage net charge (c), polarity (d), side-chain chemistry (e) or side-chain N (f) of amino-Fig. 2. Lines in panels a and b represent best-fit linear regressions.

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e1750 1749

suggesting that microbial uptake of Ser may be similar amongecosystems, but the proportion of this substrate that is mineralizedmay increase with increasing bacterial dominance.

Several intrinsic chemical properties of the amino acids studied(both categorical and continuous) had significant associations withabiotic sorption of amino-acid N (Tables 3 and 4). Examination ofthe data (Fig. 5), however, suggests that several of these associa-tions are spurious and that side-chain chemistry is likely the keyfactor determining amino-acid sorption potential in these soils.Evidence for this comes first from the fact that side-chain chemistry(charged vs. neutral) by far explained the most variation of anyparameter. Furthermore, significant relationships between sorptionand hydrophobicity (Fig. 5a) and molecular weight (Fig. 5b) areclearly driven by the two charged amino acids (Glu and Arg), withno apparent effect of hydrophobicity or molecular weight amongthe remaining four uncharged compounds. Several previous studieshave shown that adsorption to soil solids is greatest for positively-charged amino acids, much less for neutral amino acids and lowestfor negatively-charged amino acids (Kumari et al., 1987; Jones andHodge, 1999; Vinolas et al., 2001; Gonod et al., 2006). Surprisingly, Ifound that N from the negatively-charged Glu was sorbed asstrongly as the positively-charged Arg, particularly at site 1 (Figs. 3aand 5c). The most parsimonious mechanism to explain this result isthat these acidic forest soils contain a significant anion exchangecapacity (e.g. Bellini et al., 1996) and thus are capable of sorbingboth positively- and negatively-charged amino acids. This inter-pretation is supported by the fact that previous studies indicatinglittle or no sorption of negatively-charged amino acids have beenconducted in neutral to basic soils with pHs of 6.8 (Gonod et al.,2006), 7.5 (Jones and Hodge, 1999), 7.9 (Vinolas et al., 2001) and8.4 (Kumari et al., 1987).

Comparison of abiotic sorption of amino acids in these sandy,acid forest soils with similar studies in agricultural and grasslandsoils points to some potentially important differences in amino-acid behavior. Previous studies have concluded that negatively-charged FAAs should bemost available for microbial assimilation ormineralization, whereas abiotic sorption provides strong competi-tion for positively-charged amino acids e potentially limiting theirbioavailability (Jones and Hodge, 1999; Gonod et al., 2006). Find-ings from this study suggest that abiotic sorption may be equallystrong for positively- and negatively-charged FAAs in spodic forestsoils. Another key distinction between this study and previousstudies is that the overall magnitude of sorption was much lowerthan what has been observed for finer-textured grassland soils. Forexample, Gonod et al. (2006) added 14C-labeled lysine to gammaray-sterilized soil from a silteloam Ap horizon (2e40 mg C g soil�1)and observed 90% of the label adsorbed to the solid phase after 2 h.In contrast, sterilized soils in this study adsorbed an average of 7%(15% maximum) of the 15N tracer added as charged amino acids.While it is possible that this difference could arise because ofdifferences in the specific compounds studied (i.e. lysine vs. Arg), orbecause of differences in isotopic labeling (14C vs. 15N), the mostparsimonious explanation is that the higher clay content in thegrassland soil (50%; Gonod et al., 2006) results in far greatersorption capacity. Whereas previous studies have concluded thatabiotic sorption is an important factor constraining the bioavail-ability of positively-charged amino acids, data from this studysuggest that sorption provides little competition for plant andmicrobial uptake of positively-charged amino acids in sandy forestsoils. Previously it has been hypothesized that slower diffusionof basic amino acids through soil might constrain uptake ratesby boreal forest plants relative to neutral or acidic amino acids(Näsholm and Persson, 2001); however, data from this studysuggests that diffusion of positively-charged amino acids throughsandy forest soils should be relatively unimpeded by interactions

with soil solids. These findings may be particularly significantfor the potential role of Arg in plant nutrition in acid forest soils.Arginine is positively charged at soil pH, has a very high N content,is abundant in soil (Näsholm and Persson, 2001) and has beenshown to be rapidly taken up by boreal and temperate forest trees(Öhlund and Näsholm, 2001; Persson and Näsholm, 2001; Scottand Rothstein unpublished data). Note that at the low fertility sitein this study, sorption, mineralization and microbial assimilationtogether accounted for only approximately 40% of the 15N added asArg e suggesting that the residence time of this amino acid in soilsolution may be high relative to others.

Several important caveats arising from methodological choicesshould be considered in evaluating the strength of the conclusionsdrawn above. First, it is conceivable that heat treatment in thesterile soils may have affected soil organic matter (SOM) properties,or SOM-clay associations, in ways that could alter sorption of FAAs.Thus it could be argued that the low sorption potentials observedhere relative to those from finer-textured grassland soils could, inpart, be an artifact of heating. However, comparison of resultsfrom this study with results from the literature suggests that thispossibility is unlikely. First, as noted above Gonod et al. (2006)found very high sorption rates of positively-charged lysine ingamma ray-sterilized grassland soil. In contrast, they found thatonly 7.5% of neutral leucine was sorbed to soil solids, which isalmost identical to the 5% sorption found in this study (Fig. 3a).Rothstein (2009) conducted a 15N-Leu labeling experiment on livesoils from the same sites as in this study and found that recovery of15N in the residual soil pool averaged approximately 12%, which isagain consistent with findings from this study considering that hisresidual soil pool included chloroform-resistant microbial biomassin addition to abiotically-sorbed 15N.

A second important caveat arises from the fact that amino acidswith only the N labeled were used as substrates Thus it is possiblethat some amount of the 15N label recovered inmicrobial biomass orsorbed to soil solids was first mineralized to NH4

þ or NO3�, meaning I

would be misinterpreting the uptake or sorption of inorganic Nas uptake or sorption of amino-acid N. While some portion of thesorbed and assimilated 15N was likely to have come throughmineralization, several lines of evidence suggest that the overallpatterns in Fig. 3 are driven by the dynamics of intact amino acids.First, if abiotic sorption of NH4

þwere responsible for the residual 15Nrecovered in the sterilized treatment, then we would expect to seethe greatest sorption for Gln. This is clearly not the case and, in fact,the amino acids which yielded the highest recoveries in the sorbedpool showed no appreciable mineralization in the sterilized treat-ment. Second, the patterns of microbial assimilation that I observedare consistent with estimates of amino-acid assimilation inferredfrom similar studies using 14C-labeled FAAs. For example, Jones andHodge (1999) added 14C-labeled lysine, Gly and Glu to live soil andfound 20e30% recovery in microbial biomass after 3 h of incubation(estimated from Fig. 2 therein). This compares well with the20e40% recovery of amino-acid N I found after 4 h of incubation inmy study. In addition, as discussed above, patterns of 15N assimi-lation by microbial biomass among amino-acid substrates matcheswell with the relative abundances of amino acids in microbialbiomass (Friedel and Scheller, 2002).

Several aspects of the methods used in this study are likely toinflate the rates of all processes examined relative to what wouldoccur in situ. For example, mineralization, assimilation and sorptionare all concentration-dependent and amounts of amino acids addedas a tracer (3 mg N g soil�1) greatly exceed background amino-acidconcentrations in soil solution (0.1e1 mg N g soil�1; Rothstein, 2009).Similarly, because amino acids were added singly, rather than asa cocktail of different amino acids, rates of microbial assimilationmay be elevated compared to a situation where there was

D.E. Rothstein / Soil Biology & Biochemistry 42 (2010) 1743e17501750

competition for uptake among different amino-acid compounds.The labeling assay was conducted in the lab under optimaltemperature and moisture conditions, whereas in the field, rates ofmineralization and assimilationwould undoubtedly be reduced dueto colder temperatures and/or suboptimalmoisture. Therefore, ratesof mineralization, assimilation and sorption reported herein shouldbe viewed as potentials with an excess of available substrate underoptimal temperature and moisture. While these caveats need to beconsidered in terms of extrapolating lab results to field conditionsthey should not affect comparison of these results with results fromthe literature as labeling rates and other experimental conditionswere comparable to similar studies (Jones and Hodge, 1999; Vinolaset al., 2001; Gonod et al., 2006). A final caveat of note is that I didnot have true replication of sites with multiple locations at eachfertility level, thus inference is limited to the three specific sitesstudied. However, as noted above, results from these three sitesvarying in soil N fertility were consistent with similar studiesrepresenting other forest fertility gradients, suggesting that findingspresented herein may be more broadly generalizable.

In conclusion, this study has demonstrated strong variation inthe fate of FAAs added to acid forest soils, both among differentamino-acid compounds, and among sites along a fertility gradient.Variability among sites was most pronounced for mineralizationof N from FAAs, where I found that mineralization increased withincreasing site fertility. This finding is consistent with literatureobservations that FAA pools decline, mineral N pools increase andplant reliance on mineral N increases along similar forest fertilitygradients (Nordin et al., 2001; Finzi and Berthrong, 2005; Gallet-Budynek et al., 2009; Rothstein, 2009). In contrast, there wasmuch less variation among sites in microbial assimilation or sorp-tion of amino-acid N. Microbial assimilation of amino-acid N waspoorly described by any intrinsic chemical properties, but insteadappeared to be explicable based on compound-specific microbialdemand, as hypothesized by Roberts et al. (2009). Abioticsorption potential was greatest for FAAs carrying a net charge, but,surprisingly, positively- and negatively-charged FAAs were sorbedat equivalent rates. The overall weak sorption potential of thesesandy soils suggests that bioavailability and diffusivity of basic FAAswill be greater in forest soils than inmore heavy-textured grasslandsoils. This may have important implications for plant N nutrition innorthern forests because the basic amino acids all contain multipleN atoms (Arg ¼ 4; histidine ¼ 3; lysine ¼ 2).

Acknowledgements

This project would not have been possible without the advice,assistance and hard work of Stephen LeDuc. Jamie Berlin, AllisonEsper, Sue Spaulding, Emily Scott and Jason Darling also providedvaluable assistance with laboratory analysis. I gratefully acknowl-edge the USDA

Forest Service for providing access to field sites. This projectwas funded by NSF grant 0448058 to D. E. Rothstein and by theMichigan Agricultural Experiment Station.

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