REGULAR ARTICLE

Rhizosphere priming and plant-mediated covercrop decomposition

Steven T. Rosenzweig & Meagan E. Schipanski &Jason P. Kaye

Received: 9 September 2016 /Accepted: 30 March 2017# Springer International Publishing Switzerland 2017

AbstractBackground and aims Rhizosphere priming occurswhen plant belowground carbon (C) allocation influ-ences the rate of soil organic matter (SOM) decomposi-tion. We investigated the effects of priming and plant-mediated cover crop decomposition on agroecosystemC and nitrogen (N) dynamics.Methods Using C stable isotopes, we tracked C and Nfrom corn, clover (Trifolium pratense) and rye (Secalecereale) cover crop litter, and background SOM in plotsfollowing clover, rye, or no cover crop (fallow) in 2013and 2014.Results Corn enhanced the decomposition of N-richclover cover crop litter in 2013, but there was littleevidence of priming of bulk SOM decomposition.There was no corn effect on litterbag decomposition in2014, likely due to greater soil moisture and temperaturein no-corn plots. Corn N uptake per unit of corn-derivedCO2 respiration was consistently lower following ryethan clover and fallow, suggesting a higher C cost forcorn to access N following a rye cover crop.Conclusions This is one of the first field-based studiesto provide evidence that plant-mediated litter

decomposition potentially provides an important sourceof plant-available N. Climate and residue quality influ-ence the extent to which corn mediates its own N supplywith implications for agroecosystem C and N cycling.

Keywords Litter decomposition . Belowgroundcarbon . Nitrogenmineralization . Soil organic matter .

Soil respiration . Natural abundance

Introduction

As a large reservoir of organic carbon (C) and nutrients,soil organic matter (SOM) plays an important role inplant growth and ecosystem functioning. Microbiallymediated transformations of residues and SOM releasemineral nutrients for plant uptake, an action that plantsinfluence via rhizosphere processes. Rhizosphere prim-ing is one of the mechanisms by which labile C inputsfrom plant roots stimulate or suppress SOM decompo-sition (Kuzyakov 2002). Plant belowground C inputscan account for up to 50% of net primary productivity interrestrial ecosystems (Whipps 1990). Climatic changesand shifts in soil resource availability can influence plantbelowground C allocation (Bottner et al. 1999;Kuzyakov 2002; Dijkstra et al. 2013), affecting micro-bial activity and the rate of SOM decomposition(Hamilton and Frank 2001; Cheng and Kuzyakov2005; Allard et al. 2006; Cheng 2009). Priming ofSOM and plant-mediated litter decomposition are mech-anistically similar phenomena, but occur at differenttimescales and magnitudes (Cheng and Kuzyakov

Plant SoilDOI 10.1007/s11104-017-3246-5

Responsible Editor: Paul Bodelier.

S. T. Rosenzweig (*) :M. E. SchipanskiDepartment of Soil and Crop Sciences, Colorado State University,1170 Campus Delivery, Fort Collins, CO 80523, USAe-mail: steven.t.rosenzweig@gmail.com

J. P. KayeDepartment of Ecosystem Science and Management, ThePennsylvania State University, University Park, PA 16802, USA

2005), and in turn may differentially affect nutrientavailability (Dijkstra et al. 2013).

Management of SOM pools is a cornerstone of bothclimate change mitigation and adaptation strategies inagricultural systems. Climate change potentially alterspriming-induced decomposition of SOM (Phillips et al.2011; Cheng et al. 2013), highlighting a critical feed-back between the climate and the rhizosphere. In addi-tion to being a potential C sink, SOM also has manycascading effects relevant for adaptation to climate var-iability including improved drought tolerance, tempera-ture regulation, nutrient use efficiency and yield stability(Lal 2004; Pan et al. 2009). Cover cropping is one keymanagement practice that can contribute to soil C stor-age by extending the period of C fixation in croppingsystems. Cover crops also contribute to improved nitro-gen (N) retention (Dabney et al. 2010; Finney et al.2016) and legume cover crops reduce the need forsynthetic fertilizer inputs due to N inputs from biologi-cal N fixation (Tonitto et al. 2006). However, severalknowledge gaps remain in our understanding of howsoil-plant-microbe interactions regulate the fate of covercrop litter inputs and how these interactions influenceagroecosystem C and N cycling, including rhizospherepriming.

The rhizosphere priming effect on SOM decom-position has largely been investigated in non-agricultural ecosystems, yet it may be an important,overlooked mechanism that regulates N cycling inagricultural soils. Previous work suggests that prim-ing effects can increase SOM decomposition rates byseveral fold (Cheng and Kuzyakov 2005), with pos-sible implications for N mineralization and plantavailability (Dijkstra et al. 2013), but we lack anassessment of the relative importance of primingeffects on C and N cycling in agricultural systems.Many of the prior rhizosphere priming studies havebeen conducted in greenhouse pots (e.g. Cheng et al.2003; Zhu et al. 2014), and the majority of fieldstudies have been in the context of elevated CO2

conditions (e.g. Dijkstra et al. 2013) or in forest andother natural ecosystems (e.g. Drake et al. 2013).Priming results have varied widely based on theresearch context, so these data cannot be extrapolat-ed to estimate the effect of rhizosphere priming on Cand N cycling in agricultural soils. Field studies ofpriming have proven difficult because of differencesin soil moisture between planted and unplanted plots,confounding the plant effect on decomposition and

often leading to a negative rhizosphere priming ef-fect (Shields and Paul 1973; Jenkinson 1977). In oneof the few field studies of priming in an agriculturalsystem, Kumar et al. (2016) found evidence thatcorn stimulated SOM decomposition. Field studiesof priming remain rare and fewer still have exploredthe interactions of carbon and nitrogen cycling.There remains a need for further exploration of therhizosphere priming effect in agricultural soils underfield conditions.

While most studies have found evidence of posi-tive rhizosphere priming effects on litter and SOMdecomposition (Cheng and Kuzyakov 2005; Chengand Gershenson 2007), the link between rhizosphereC flows and plant N availability have been mixed.BPrimed^ increases in SOM decomposition oftenincrease gross nitrogen (N) mineralization, but con-current increases in microbial N immobilization maylimit the release of N for plant uptake (Cheng 2009;Dijkstra et al. 2013). Alternatively, increased micro-bial activity may increase soil N turnover rates(Allard et al. 2006), which can result in a netincrease in N availability to plants (de Graaff et al.2009; Phillips et al. 2011). In many N cycle models,microbial competition may limit plant N uptakewhen cover cropping increases SOM and microbialbiomass (Manzoni and Porporato 2009). However,cover crop litter quantity and quality may impactcrop belowground C allocation with varying effectson net N availability.

In this study, we assessed the importance of plant-mediated litter decomposition and rhizosphere primingin the context of a cover crop - corn (Zea mays) se-quence within an organic cropping system. Cover cropsgrew over winter and were killed and incorporated intothe soil prior to planting corn. We used the 13C naturalabundance method to differentiate between corn-derived and C3 cover crop- and SOM-derived sources.The objectives of this study were to: 1) Quantify theeffects of cover crop litter quality on corn rhizosphere Callocation, and 2) Determine the effect of corn rhizo-sphere C allocation on litter and SOM decompositionand plant N uptake. We expected that the presence ofcorn would increase cover crop litter decomposition andpriming of SOM relative to a no-corn control. We alsopredicted that litter quality would influence corn rhizo-sphere C allocation, and thus the magnitude of primingand litter decomposition would differ by cover croplitter type.

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Materials and methods

Study site

The experimental site is located at the Russell E. LarsonAgricultural Research Center near Rock Springs, PA.The dominant soil type at the experiment site is aMurrillchannery silt loam (Fine, mixed, semiactive, mesic,Typic Hapludalf). Soil texture in the experimental fieldsis predominantly silt loam with variability in silt (rangeof 34.3–48.5%), clay (range of 20.7–30.4%) and sand(21.3–45.0%), and the pH ranges from 6.3 to 6.8. Thehistorical mean annual precipitation in the area is975 mm with mean monthly temperatures ranging from3 degrees C (January) to 22 degrees C (July). Weatherdata was compiled from the NRCS SCAN site located inan adjacent field (NRCS 2014). The site received400 mm and 500 mm precipitation from May toSeptember of 2013 and 2014, respectively. The averagetemperature from May to September was 18.2 and 17.9degrees C in 2013 and 2014, respectively. The field hadpreviously been used for tomato breeding experimentsand, thus, had not had any corn or other C4 crops grownfor more than 10 years.

Experimental design

The experiment was conducted in each of theyears 2013 and 2014 during the corn phase of arotation of corn (Zea mays), soybean (Glycinemax), and wheat (Triticum aestivum). The covercrop treatments included monoculture red clover(Trifolium pratense) and cereal rye (Secale cereale)plots (27 m × 6 m) to represent a gradient of litterC to N ratios, as well as a no cover crop (fallow)treatment. The cover crops were planted in August2012 and 2013, and incorporated in May 2013 and2014 by moldboard plowing followed by severalpasses with a field cultivator. Three and two timesmore rye biomass C than clover biomass C wasincorporated prior to corn planting in 2013 and2014, respectively (Table 1). This large differencein incorporated biomass is typical of agronomicconditions in this region, and reflects a realisticproduction scenario. No fertilizer other than covercrop litter was applied to the experimental plots.For a more complete description of the larger fieldexperiment, see Murrell et al. (2017).

The experiment was established as a random-ized complete block design with four replications.Within each of the three whole-plot cover croptreatments, three microplots (3 m × 2 m) wereestablished as a split-plot design. After emergence,corn was removed from one of the microplots toestablish no-corn control plots. Immediately fol-lowing corn planting, two litter bags (8 cm × 22 cm)constructed of nylon mesh (2 mm mesh size) con-taining 8 g of dry cover crop litter were placed2 cm below the surface within each of the centertwo corn rows of each microplot. Clover litterbagswere buried in clover plots and rye litterbags wereburied in rye plots (Fig. 1). In fallow plots, bothclover and rye litterbags were buried (Fig. 1).Cover crops for litterbags were grown in thegreenhouse in soil-free media and litterbagscontained a representative mixture of root andshoot material. The use of litterbags allowed usto quantify litter decomposition rates within a fieldenvironment. There are limitations to the method,but it was the most appropriate and feasible meth-od for our questions. Shade cloths were installedin no-corn microplots when corn microplotsreached 50% cover to control soil temperatureand moisture.

Corn, litter, and soil C and N analysis

Destructive sampling occurred in corn microplots 8 and10 weeks after corn planting. Plant, litterbag, and soil Cand N pools were quantified at each sampling point(Fig. 2). The δ13C natural abundance stable isotopemethod was used to differentiate between C4 (corn)-derived and C3 cover crop and SOM sources.Aboveground corn biomass was sampled from 1 m inthe center two corn rows, dried and weighed, and ana-lyzed for total C and N on an elemental analyzer(LECO, St. Joseph, MI). Live corn roots were carefullyremoved from litterbags. In 2013, corn roots removedfrom litter bags were dried and analyzed for δ13C toensure there was no accidental litter removal whenremoving corn roots, and no significant differences(α = 0.05) were found in δ13C between corn rootsremoved from clover (mean = −13.9, SE = 0.46) andrye litterbags (mean = −13.2, SE = 0.33), and corn rootsgrown in the absence of a cover crop (mean = −13.2,SE = 0.30). After removing live roots, litterbags weredried and weighed. Litter was analyzed for C and N as

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with the corn shoots. To calculate and correct litter mass,C and N measurements for the portion of soil thatentered the litterbags, an ash correction was conductedfollowing the methods of Harmon et al. (1999). Toassess bulk density and gravimetric water content, four2-cm diameter cores (20-cm depth) each were collectedfrom the corn and no-corn plots. Fresh 10 g subsampleswere cleaned of rocks, then weighed, dried, andreweighed to determine gravimetric water content. Ateach of the two sampling time points, 10 soil samples to20-cm depth within 10 cm of the center two corn rowswere collected and composited. Total soil C and N weremeasured simultaneously with cover crop litter and cornshoot C and N using the same methods.

Extractable microbial C and DOC

From the same 20-cm depth soil samples, extractablemicrobial C, dissolved organic C (DOC), and δ13C weremeasured using a modification of the chloroform

fumigation-extraction method (Horwath and Paul1994). Soil samples (15 g) were sieved to 2 mm andshaken for 4 h at 150 rpm in 40 ml 0.5 M K2SO4 with orwithout 1 ml chloroform, centrifuged, and filteredthrough a 0.45 μm filter. Samples were lyophilizedand analyzed for total C and 13C using a using a contin-uous flow Isotope Ratio Mass Spectrometer (Costech,Valencia, CA). We did not apply a correction factor forincomplete microbial C recovery, and we refer to thisproperty as extractable microbial C. An isotope mixingmodel was used to quantify the C4 corn contributions toextractable microbial and dissolved organic C poolsrelative to C3 cover crop and SOM sources (Cheng1996).

Extractable microbial N, DON, and inorganic N

Extractable microbial N and dissolved organic N (DON)were measured simultaneously with extractable micro-bial C and DOC using the same methods described

Table 1 Corn Biomass, whole –plot cover C, whole –plot coverC:N, and starting cover litter bag litter C:N ratio in three cover croptreatments at 8 weeks (Sampling 1) and 10 weeks (Sampling 2)

after corn planting 2013 and 2014. Cover crop biomass C wasincorporated in May of both years before the start of experiment

Year Cover crop Corn biomass (g / m2)a Cover cropbiomass C (g / m2)b

Whole plotcover crop biomass C:N

Initial cover croplitter C:N Ratio

Inorganic N atcorn planting(mg / kg dry soil)Sampling 1 Sampling 2

2013 Clover 180 ± 14ac 528 ± 49a 85.9 ± 11.8a 16.1 ± 1.92 23 16.2 ± 2.9a

Fallow 135 ± 8a 434 ± 46ab – – 11.6 ± 2.1ab

Rye 60.1 ± 6.1b 239 ± 28b 249 ± 14b 40.9 ± 1.52 28 5.72 ± 1.22b

2014 Clover 134 ± 17A 450 ± 59A 44.1 ± 7.5A 9.9 ± 0.16 19 14.2 ± 3.9A

Fallow 104 ± 14A 432 ± 59A – – 11.2 ± 2.8A

Rye 95.7 ± 13.8A 317 ± 27A 100 ± 6B 41.2 ± 1.15 24 8.93 ± 1.63A

aCorn biomass values are means and standard error of 4 replicate blocks (n = 4)b Cover crop biomass C values are means and standard error of 4 replicate blocks (n = 4)c Lowercase and uppercase letters within a column represent significant differences between cover crop treatments in 2013 and 2014,respectively (α = 0.05)

Fig. 1 Plot layout and litterbagplacement

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above. Similar to above, we did not apply a correctionfactor for incomplete microbial N recovery, and we referto this property as extractable microbial N. Soil samplesextracted for DON analysis were also analyzed forammonium and nitrate using a microplate colorimetrictechnique (Sims et al. 1995) based on the Berthelotreaction for NH4

+ and the vanadium chloride methodfor NO3

− (Doane and Horwath 2003). At corn planting,20 g of fresh soil was extracted with 100 mL of 2 MKCl, and analyzed for inorganic N as described above.

Field soil respiration

Field soil respiration was measured 8 and 10 weeks aftercorn planting. A closed chamber approach was utilizedas in Ekblad and Högberg (2001). Chamber headspacewas sampled every 2 min for 10 min by withdrawing25 ml of gas. Samples were analyzed for CO2 concen-tration and δ13C using a cavity ring-down spectrometer(Picarro, Inc., Santa Clara, CA) with a small samplevolume manifold as in Berryman et al. (2011) in 2013,and an isotope ratio mass spectrometer in 2014 (UCDavis Stable Isotope Facility). To estimate the relativecontributions of recent C4 corn inputs to the total soilrespiration pool, the δ13C of respired CO2 was calculat-ed using Keeling plots, which define the δ13C of re-spired CO2 as the intercept of the linear relationshipbetween δ13C and 1/[CO2] (Keeling 1958). RelativeC4 and C3 contributions to soil respiration were deter-mined using the same mixing models as were used forextractable microbial C and DOC. C4-derived

respiration was normalized by corn biomass to quantifyrelative belowground C allocation.

Data analysis

Statistical analyses tested the relationship between covercrop litter type and 1) corn-derived CO2 and 2) corn Nuptake. Response variables (soil CO2 respiration, MBC,DOC, MBN, DON, litter decomposition) were analyzedusing linear mixed models, with cover crop type, sam-pling date, and covariates as fixed factors, and block as arandom factor. For the model of soil CO2 respiration,gravimetric soil water content and the amount of covercrop C incorporated prior to corn planting were includedas covariates.

To estimate what proportion of litter decompositionand N availability in the corn treatments may be attrib-utable to rhizosphere priming effects, we tested forstatistical differences in response variables (MBC,DOC, MBN, DON, soil C and N, soil CO2 respiration,and litter decomposition) within cover crop treatmentswith and without corn. Models were set up as a split-split plot design, with cover crop type, corn presence/absence, sampling date, and covariates as fixed factors,and block as a random factor. Whole-plot cover crophad no effect on litter decomposition (P = 0.22), and wasremoved from the model. Litterbag type was included asa fixed factor in the model of litter decomposition. Forthe model of soil CO2 respiration, gravimetric soil watercontent was included as a covariate. DOC and C3-derived soil respiration were log-transformed to meet

Fig. 2 Measured sources andsinks of carbon and nitrogen

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normality assumptions of the models. Analyses wereoriginally conducted across both years, but due to thestrong year effect, we present results separately by year.We used R for all data analyses (R Core Team 2013),and all models were generated and tested for signifi-cance using the packages lme4 (Bates et al. 2014),lsmeans (Lenth and Herve 2015), and lmerTest(Kuznetsova et al. 2014).

Results

Overall, we found little evidence of SOM priming bycorn, but we found evidence of corn-mediated decom-position of clover litter and greater corn N uptake fol-lowing a clover cover crop relative to rye or no covercrop. However, interannual variability prevents us fromgeneralizing these trends across years. Soil inorganic Nat corn planting and corn biomass were consistentlygreater in clover plots than in the rye plots, althoughthe differences were only significant in 2013 (Table 1).Soil temperature was similar between no-corn and cornplots in 2013, and was slightly warmer in no-corn plotsat sampling 1 in 2014 (p = 0.02, Table 2). Soil gravi-metric water content in no-corn plots was higher thancorn plots at sampling 2 in 2013 and at both samplingsin 2014 (p < 0.01, Table 2).

Litter decomposition

The rate of litter decomposition varied with litter typeand corn treatment. Litter type affected percent massloss of litterbag residue by sampling 2 in 2013(p < 0.01), but there were no significant differences indecomposition between litter types in 2014 (Fig. 3). In

corn plots in 2013, clover litter lost 11% more mass(p < 0.01), 19% more C (p < 0.001), and 20% more N(p < 0.05) by sampling 2 compared to rye litter (Fig. 3).There were no differences between percent mass or Nloss between rye and clover in no-corn plots. Resultswere similar at sampling 1, so only the cumulativeeffects at sampling 2 are shown in Fig. 3.

Corn stimulated the decomposition rate of clover, butnot rye litter. Compared to a no-corn control, cornstimulated mass, C, and N loss from litterbags of cloverresidue by 7% (p = 0.02), 7% (p = 0.07), and 19%(p = 0.02), respectively by Sampling 2 in 2013(Fig. 3). Corn did not stimulate decomposition of cloverlitter in 2014 (Fig. 3). Corn had no effect on rye decom-position in either year (Fig. 3).

Extractable microbial C and N and dissolved organic Cand N

We did not find an increased contribution of corn-derived C in dissolved organic C or extractable micro-bial C in any of the cover crop plots. However, thedissolved organic C:N ratio was greater in the presenceof corn across samplings and years (p < 0.001, Fig. 4).At sampling 2, dissolved organic N was approximately50% lower in corn compared to no-corn plots and therewas no effect of corn on dissolved organic C (Table 3).There were no significant differences in extractablemicrobial C or N (data not shown) or dissolved organicC or N between cover crop treatments.

Soil CO2 respiration

Compared to a no-corn control, corn plots had sig-nificantly higher δ13C values of soil CO2 respiration

Table 2 Soil gravimetric water content (GWC) and soil temperature in corn and no-corn plots at 8 weeks (Sampling 1) and 10 weeks(Sampling 2) after corn planting in 2013 and 2014

Year Corn treatment GWCa Soil temperature (°C)1

Sampling 1 Sampling 2 Sampling 1 Sampling 2

2013 No-Corn 0.186 ± 0.007ab 0.194 ± 0.006a 27.0 ± 0.5a 18.7 ± 0.3a

Corn 0.171 ± 0.008a 0.161 ± 0.009b 25.8 ± 0.3a 18.5 ± 0.3a

2014 No-Corn 0.181 ± 0.005A 0.186 ± 0.005A 21.7 ± 0.5A 17.8 ± 0.5A

Corn 0.166 ± 0.005B 0.156 ± 0.006B 20.1 ± 0.3B 17.8 ± 0.5A

aAll values are means and standard error of 3 plots in each of 4 blocks (n = 12)b Lowercase and uppercase letters within a column represent significant differences between corn treatments in 2013 and 2014, respectively(α = 0.05)

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indicative of the higher δ13C signature of C4-derivedC (Table 4). Additionally, the lower δ13C of cloverand rye plots reflects the larger recent C3 biomassinputs compared to fallow plots. Total respiration didnot differ by cover crop type in either year.

C3-derived soil respiration was greater in rye com-pared to clover plots, but only at sampling 1 in 2013

(Fig. 5). The presence of corn had no significant effecton C3-derived respiration for any cover crop treatment,although C3-derived respiration was consistently greaterin clover corn plots compared to no-corn plots acrosssamplings and years. At the first sampling of 2013,corn-derived soil respiration per g corn biomass in ryewas twice that in clover and fallow plots (p < 0.001,

Fig 3 Percent mass, C, and N loss of clover and rye litterbags incorn and no-corn plots at sampling 2 in 2013 and 2014. Barheights and error bars represent model-generated least squared

means ± standard errors (n = 4). Symbols indicate significanceof the difference between corn and no-corn plots (* p < 0.05, **p < 0.01)

Fig. 4 Corn effect on dissolved organic C:N ratio. Bar heights and error bars represent model-generated least squared means ± standarderrors (n = 12). Symbols indicate significance of the difference between corn and no-corn plots (** p < 0.01, *** p < 0.001)

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Fig. 6). However, total N in aboveground corn biomassper corn-derived CO2 respiration was consistentlyhigher in rye plots compared to clover and fallow(Fig. 7).

Discussion

Plant belowground C allocation

We expected that corn would increase relativebelowground C allocation following a rye covercrop as a result of greater root foraging activityin the presence of nutrient limitation. Corn below-ground C allocation as measured by corn-derivedsoil respiration per g corn biomass was either nodifferent or greater in soils with rye, as opposed tofallow and clover cover crop treatments (Fig. 6).Our results suggest that corn did increase relativebelowground C allocation in the presence of rye,but that nutrient limitation following rye covercrop treatments was severe enough to restrict total

plant photosynthesis and root respiration and exu-dation. For example, aboveground corn biomassand N content were lower following rye, particu-larly in 2013 (Table 1).

These results highlight the complex effects of soilN on plant belowground C allocation that are rarelyconsidered by current ecosystem and crop models(Bottner et al. 1999; Kuzyakov and Domanski2000). In particular, soil nutrient availability effectson belowground C allocation likely follow non-linearpattern. At sufficient or higher soil nutrient levels,plants will decrease C investment belowground(Kuzyakov 2002). While nutrient limitation can re-strict total plant photosynthesis and belowground Callocation, moderate nutrient limitation can stimulateincreased C allocation to roots (Hansson et al. 1991)and increased root proliferation, such as in the pres-ence of soil nutrient patches (Hodge 2004). Increasedunderstanding of these feedbacks, particularly rootforaging responses at moderate nutrient limitation,could improve our ability to estimate cropping sys-tem impacts on both N and C cycling.

Table 3 Dissolved organic C and N in three cover crop treatments and two corn treatments at 10 weeks after corn planting in 2013 and2014a

Year Cover crop DOC (mg C / g dry soil) DON (mg N / g dry soil)

Clover Fallow Rye Clover Fallow Rye

2013 No Corn 7.99 ± 1.23ab 9.04 ± 1.23a 7.40 ± 1.23a 1.77 ± 0.24b 1.49 ± 0.24b 1.13 ± 0.24b

Corn 9.51 ± 1.23a 8.13 ± 1.23a 8.39 ± 1.23a 0.71 ± 0.24a 0.70 ± 0.24a 0.66 ± 0.24a

2014 No Corn 6.05 ± 0.98A 6.95 ± 0.83A 4.65 ± 0.83A 2.70 ± 0.33B 1.85 ± 0.40A 2.12 ± 0.33A

Corn 6.29 ± 0.93A 5.86 ± 0.83A 4.69 ± 0.83A 1.15 ± 0.33A 0.95 ± 0.33A 1.53 ± 0.33A

aAll values represent least squares means and standard errors (n = 4)b Lowercase and uppercase letters within a column represent significant differences between corn treatments in 2013 and 2014, respectively(α = 0.05)

Table 4 The isotopic 13C signatures (δ13C) of soil CO2 respiration (per mil) at 8 weeks (Sampling 1) and 10 weeks (Sampling 2) after cornplanting in 2013 and 2014a

Year Corn treatment Clover Fallow Rye

Sampling 1 Sampling 2 Sampling 1 Sampling 2 Sampling 1 Sampling 2

2013 No Corn −24.4 ± 0.6ab −22.5 ± 0.6a −22.0 ± 1.1a −20.4 ± 1.1a −25.0 ± 1.3a −22.9 ± 1.3a

Corn −19.6 ± 0.6b −17.2 ± 0.6b −18.9 ± 1.1b −18.5 ± 1.1b −21.2 ± 1.3b −19.2 ± 1.3b

2014 No Corn -23.3 ± 0.7A -20.7 ± 0.7A -22.6 ± 1.3A -19.4 ± 1.3A -23.6 ± 1.4A -21.7 ± 1.4A

Corn -18.9 ± 0.7B -16.9 ± 0.7B -16.9 ± 1.3B -15.7 ± 1.3B -19.6 ± 1.4B -17.1 ± 1.4B

aAll values represent least squares means and standard errors (n = 4)b Lowercase and uppercase letters within a column represent significant differences between corn treatments in 2013 and 2014, respectively(α = 0.05)

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Litter decomposition and plant N acquisition

Trends in belowground C allocation did not mirror theplant effect on litter decomposition. Clover litterdecomposed more in the presence of a growing corncrop relative to a no plant control, though there was nocorn effect on rye decomposition (Fig. 3). While overallC mass loss was greater than N mass loss, corn stimu-lated levels of N loss in clover litter that were almost 3times greater than relative levels of corn-induced C loss(Fig. 3). These results suggest that N-rich compoundswere preferentially mineralized, adding to recent sup-port for the concept that priming is a distinct microbialN-mining response (Murphy et al. 2015).

Litter quality ultimately drove the availability ofplant N by influencing its accessibility. The amount ofN uptake for each unit of C expended by corn was 2 to 4times greater following a clover cover crop compared torye (Fig. 7), and the intensity of N limitation reducedcorn growth and root foraging following rye. The higherquality clover litter supported greater C-efficiency of Nuptake, which supported greater biomass and corn me-diation of clover decomposition in 2013. The concept ofBrhizoeconomics,^ where plant C is analogous to

currency in the acquisition of nutrients, has been appliedto plant phosphorus acquisition (Lynch and Ho 2005),but is also well suited to the C and N dynamics ofrhizosphere priming. Future assessments of the C costsof accessing different N forms could inform breedingefforts for improved N use efficiency and may helpproducers make decisions regarding their source of or-ganic N.

We observed the N-mining effect on fresh litter in-puts, but we did not quantify N mineralization fromSOM pools due to logistical constraints of N budgetingand separating N sources in the field. Several studieshave demonstrated the increase in N mineralizationassociated with the rhizosphere priming effect(Dijkstra et al. 2013; Zhu et al. 2014), and plants rapidlytake up N mineralized in the root zone. Even in agricul-tural systems with uncoupled C and N cycles, the ma-jority of plant N cycles through microbial and SOMpools (Gardner and Drinkwater 2009). Still, the primingeffect may be more important in agricultural systemswith recoupled C and N cycles. Applications of mineralN fertilizer reduce the priming effect by reducing soil Nlimitation and influencing plant rhizosphere C inputs assummarized by Kuzyakov (2002). Without fertilization,

Fig. 5 C3-derived soil CO2 respiration across corn and cover crop treatments. Bar heights represent model-generated least squared means(n = 4). Letters indicate significant differences in C3-derived soil CO2 respiration between corn and cover crop treatments (α = 0.05)

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N mineralization from SOM can increase by 40 to over100 kg N ha−1 compared to soil amended with N fertil-izer (Kuzyakov 2002). By sidestepping the need forrhizosphere-derived nitrogen, mineral N-dependent ag-ricultural systems suppress a potentially importantsource of natural fertility that has a lower risk of lossto the environment.

Labile C and N pools

We did not find an increased contribution of corn-derived C in dissolved organic C or extractable micro-bial C in any of the cover crop plots, likely because thesemeasures are temporally variable and are small in com-parison to the large pool of background C3-derived C. Inthe presence of corn, we observed a significant

reduction in the dissolved organic N pool, which maybe an important direct or indirect source of plant N. Thisreflects greater competition for N in the presence ofcorn.

Corn had no effect on extractable microbial C com-pared to no-corn plots, although previous studies haveshown increased priming-induced SOM decompositionwithout changes in microbial biomass (Cheng 2009).The turnover of the microbial biomass may be fasterwith priming, which lowers plant-microbe competitionfor mineral N because it is rapidly released once assim-ilated. In addition, soil microbial community carbon useefficiency may shift in response to nutrient availability,often decreasing relative soil respiration rates underhigher nitrogen availability (Blagodatskaya et al.2014). Soil microbial dynamics are difficult to measure

Fig. 6 C4-derived soil CO2 respiration across cover crop treatments. Bar heights represent model-generated least squared means (n = 4).Letters indicate significant differences in C4-derived soil CO2 respiration between cover crop treatments (α = 0.05)

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in the field with infrequent samplings of total biomassbecause of the temporally variable nature of microbialpools. While we focused on tracking the fate of plant-derived carbon into discrete pools of microbial biomassor fluxes such as respiration using isotopic approaches,an increasing body of research is linking these functionsto microbial community physiology using advancedmolecular tools and approaches (e.g. Blagodatskayaet al. 2014; Kallenbach et al. 2015). Increased applica-tion of these methods to field environments will provideimportant new mechanistic information.

Combined across two study years, our results suggestthat priming does influence decomposition along withenvironmental drivers. General trends emerged in soilrespiration measurements, in that C3-derived respirationwas consistently greater in clover corn plots comparedto no-corn plots, although the significance of the trendswas likely masked by the large background C3-C soilefflux. Also, the variability induced by the soil δ13Cnatural abundance may also mask priming-relatedtrends. Other studies using δ13C natural abundance todistinguish between C3 and C4 sources have used soilswith longer histories (>40 years) of C3 vegetation, thusallowing a clearer distinction between C3 and C4 sources(e.g. Cheng et al. 2003).

In 2014, we faced similar challenges as other fieldstudies of rhizosphere priming in controlling soil mois-ture and temperature between planted and unplantedplots. The difference in plant-mediated litter decompo-sition between the two years of the study illustrates theimportance of environmental drivers of decompositionrelative to plant effects.Warmer and wetter conditions inthe no-plant control likely increased decomposition rel-ative to the corn plots, making it difficult to distinguishany priming effects from these environmental drivers ofdecomposition. However, the fact that we saw evidenceof enhanced litter decomposition when these experi-mental artifacts were controlled in 2013 suggests thatplant belowground C is a part of the suite of drivers ofdecomposition that should be more broadly integratedinto our conceptual models of soil-plant-microbesystems.

Conclusions

Overall, we were able to detect plant belowgroundC allocation as a significant driver of litter decom-position under field conditions. This is one of thefirst field studies to demonstrate that the presenceof a plant can stimulate litter decomposition.

Fig. 7 Total N in aboveground corn biomass per unit of C4-derived soil CO2 respiration (n = 4). Bar heights representmodel-generated least squared means (n = 4). Lowercase lettersindicate significant differences between cover crop treatments at

sampling 1 within year (α = 0.05). Uppercase letters indicatesignificant differences between cover crop treatments at sampling2 within year (α = 0.05)

Plant Soil

Compared to small and labile C and N pools andsoil respiration, litter decomposition rates are amore easily detectable measure of plant effectson C and N cycling. The difficulty in measuringrelatively small and variable pools is one reasonwhy field studies of priming are rare. Still, wefound evidence of corn stimulating the decompo-sition of N-rich cover crop litter in the field. Plant-mediated decomposition of clover litter contributedto greater corn biomass and uptake of N comparedto corn grown in plots with legacies of fallow andrye cover crop treatments. Plant-mediated litter andSOM decomposition potentially provide an impor-tant source of plant-available N, but the extent towhich corn mediates its own N supply depends onthe quality of residue and interannual climate var-iability. Most models of C and N dynamics relymainly on environmental parameters such as tem-perature and moisture to predict decompositionpatterns, and do not incorporate microbial activityand labile C as drivers of C and N turnover. Theresults of this study suggest that plant-mediatedlitter decomposition is a significant process drivingC and N dynamics in agricultural systems withcoupled C and N cycles.

Acknowledgements Thank you to Brosi Bradley and CassandraSchnarr for providing technical expertise and to David Mortensenfor input on the project design. This project was supported byAFRI Grant no. 2012-67012-22889 from USDA NIFA.

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