Minor topography governing erosional distribution of SOCand temperature sensitivity of CO2 emissions: comparisonsbetween concave and convex toposequence

Yao He1 & Yaxian Hu1& Xin Gao1

& Rui Wang1& Shengli Guo1

& Xianwen Li2

Received: 15 October 2019 /Accepted: 27 January 2020 /Published online: 20 February 2020# Springer-Verlag GmbH Germany, part of Springer Nature 2020

AbstractPurpose: Erosion processes spatially redistribute soil particles and the associated carbon across landscapes. Their spatial redis-tribution pattern is governed by the transport distances of individual displaced soil particles, which is not only dependent on theirsettling velocity, but also affected by slope topography. However, the potential impacts of fine-scale variation of slope topographyon the erosion-induced lateral and carbon fluxes are often over-generalized by coarse digital elevation models.Material and methods: In this study, two topo-sequences, convex and concave, over a long gentle slope in the northeast Chinawere investigated. Surface soils were sampled at predetermined space intervals from upslope to downslope along the twotoposequences, and then fractionated by the settling velocity of individual fractions into four classes: > 250, 63 – 250, 20 –63 and < 20 μm. The soil organic carbon (SOC) and δ13 C of the unfractionated soils and all the settling classes were measured,and their CO2 emission rates were also determined at six temperature gradients: 5°C, 10°C, 15°C, 20°C, 25°C and 30°C.Results and disucssion: Our results show that: 1) The soil fractions along the upper lying convex segment showed a coarseningeffect toward the knee point and then a fining trend at the slope toe, whilst the soil compositions along the lower lying concavesegment stayed fairly comparable as the slope descended. 2) The net loss of surface soil along the eroding convex segmentresulted in depleted SOC and more positive δ13 C signatures than that along the depositional concave segment. 3) The CO2

emission rates of almost all the settling fractions were enhanced compared with that of the unfractionated soil, and the settlingclass-specific CO2 emission rates and their temperature sensitivity (Q10 ) also differed along the two topo-sequences.Conclusions: This demonstrates that fine scale topographic variations had a strong control over the lateral and vertical carbonfluxes, which has been often disguised by coarse grid size in digital elevation models or average sediment delivery ratios.Topography-dependency must be properly accounted for when calculating slope-scale carbon balances.

Keywords Slope topography . Erosional redistribution . CO2 emission rate .Q10

1 Introduction

Globally, about 80% land is under erosion threat (Oldeman1994), which laterally re-distributes 0.3–5 Gt soil carbon ev-ery year (Berhe et al. 2007; Chappell et al. 2005), and pro-foundly perturb global carbon cycling (Lal 2004). However,whether soil erosion contributes as a carbon source or sink isstill under intense debate due to the great uncertainties to ac-count for lateral and vertical carbon fluxes at different scales(Wilken et al. 2017).

During erosion processes, fine fractions are selectivelytransported downslope and further into rivers in suspension,while coarse fractions, due to their fast settling velocity, are

Responsible editor: Weixin Ding

* Yaxian Huhuyaxian@nwafu.edu.cn

* Xianwen Lilixianwen@nwafu.edu.cn

1 State Key Laboratory of Soil Erosion and Dryland Farming on theLoess Plateau, Institute of Soil and Water Conservation, NorthwestA&F University, Yangling 712100, Shaanxi, China

2 Key Laboratory of Agricultural Soil and Water Engineering in Aridand Semiarid Areas, Ministry of Education, Northwest A&FUniversity, Yangling 712100, Shaanxi, China

Journal of Soils and Sediments (2020) 20:1906–1919https://doi.org/10.1007/s11368-020-02575-6

SOILS, SEC 1 • SOIL ORGANIC MATTER DYNAMICS AND NUTRIENT CYCLING • RESEARCH

ARTICLE

often preferentially deposited nearby footslope after shorttransport distances (Hu et al. 2016; Hu and Kuhn 2016;Starr et al. 2000; Wainwright et al. 2008). This consequentlycreates spatially enriched or depleted soil organic carbon(SOC) at various slope positions (Li et al. 2018b; Schimelet al. 1985). At present, soil models predict sediment redistri-bution patterns mostly based on soil texture or selected parti-cle size classes (Fiener et al. 2008; Morgan et al. 1998; VanOost et al. 2004). However, sediments are mostly moving asaggregates (Beuselinck et al. 2000; Hu and Kuhn 2016;Walling 1988), and the transport distances of differently sizedaggregates are primarily depended on their settling velocities(Dietrich 1982; Tromp-van Meerveld et al. 2008). In additionto conventionally recognized particle diameter, the settlingvelocity of any particle is also affected by its inherent shapeand porosity, as well externally by water flow velocity(Dietrich 1982; Hu et al. 2013b; Kinnell and McLachlan1988; Loch 2001; Warrington et al. 2009). By incorporatingfine particles into coarser aggregates with faster settling ve-locity, the mobility or transportability of these fine particles islargely reduced, consequently increasing their likelihood to bedeposited within terrestrial systems than being transportedaway into aquatic systems (Alderson et al. 2016; Wilkenet al. 2017). Given the unequal distribution of SOCwithin soilfractions (Hu et al. 2013a; Puget et al. 2000; Schiettecatte et al.2008; Six et al. 2000), erosion processes must be examinedfrom the perspective of aggregate-specific transportability tofully understand the slope-scale spatial variations of SOC.

Previous studies on slope-scale SOC erosion were mostlyconducted by comparing carbon biochemical properties at as-sumed site of erosion and deposition (Berhe et al. 2007;Dlugoß et al. 2012; Doetterl et al. 2013; Nadeu et al. 2012;Stallard 1998; van Hemelryck et al. 2010; Van Oost et al.2012; Wang et al. 2014). However, erosion-induced lateralcarbon fluxes often have great spatial variability, as hillslopeheterogeneity and minor topography can result in differenterosion and deposition rates with various sediment and organ-ic compositions during individual erosion events (Darbouxet al. 2002; Fissore et al. 2017; Yoo et al. 2006; Zhao et al.2016; Zhu et al. 2014). Soil redistribution by tillage practicesis also highly controlled by terrain features by translocatingplowed soil over different distances (Heckrath et al. 2006).Moreover, vertical carbon fluxes are spatially variable too,as carbon concentration and stability, microbial community,and other microclimatic conditions (e.g., soil moisture, pH,aeration) can differ at any slope point, thus resulting in spa-tially different rates of carbon outgassing, dynamic replace-ment, or burial preservation (Alderson et al. 2016; Dlugoßet al. 2010; Doetterl et al. 2012; Helgason et al. 2014;Quijano et al. 2014; Wiaux et al. 2014; Yoo et al. 2006;Zimmermann et al. 2010). Therefore, to improve our currentunderstanding on erosion-induced soil-atmosphere carbon ex-change, topography-specific lateral and vertical carbon fluxes

among locally varying erosion-deposition settings must besystematically accounted for.

In this study, a long gentle slope in northeast China withparallelly lying concave and convex segments was investigat-ed. Soil compositions, SOC, δ13C, and CO2 emission ratewere compared among different settling fractions of the soilscollected along toposequences; we aimed to (1) identify theimpacts of microtopography on the spatially varying compo-sitions of soil particles and SOC and (2) compare the miner-alization potentials and the temperature sensitive of CO2 emis-sion rate of individual settling fractions so as to evaluate thetopography-dependency of carbon vertical fluxes.

2 Materials and methods

2.1 Study site and soil sampling

A long gentle slope in Hebei watershed (48°43′N, 124°56′W),located south of Heihe City, Heilongjiang province, northeast-ern China, was investigated in this study (Fig. 1a). The localannual precipitation ranges from 480 to 500 mm and 70–80%concentrates between June and September (meteo-data obtain-ed from the weather stations standing in the Hebei watershed).The soil was Mollisol (local people named it as black soil),featuring 6.1% of sand, 56.92% of silt, and 36.97% of clay.The SOC concentration of unfractionated soil was on average25 mg g−1, and soil pH was averaged at 5.75. Soybean andmaize are the main crops and planted in rotation. Tillage op-erations were conducted by large machinery up-and-downhill, resulting in significant rill and gully erosion on thecropped slope (Miao et al. 2008; Zhang et al. 2006) (Fig. 1b).

The studied slope was approximately 2000 m long, and theslope gradient was 3° (Fig. 1b). Soil samples were collected inOctober 2018 at predetermined space intervals along twotoposequences, the convex and concave segment. With theattempts to adequately capture the possible changes of soilcompositions along the two segments, especially the rapidchanges of soil compositions near the erosion hotspot(900m to 950m away from the slope top), the sampling pointswere not equally distant from each other but in predeterminedspaces: at 150 m, 650 m, 900 m, 950 m, and 1100 m along theconvex segment and at 150 m, 400 m, 650 m, 800 m, and900 m along the concave segment (Fig. 1c). Only topsoildirectly affected by soil erosion was collected, and the coor-dinates of all the sampling points were determined by the real-time kinematic equipment (RTK, i60, Huace, China).Therefore, the elevation of individual sampling points on theconvex segment was 396m, 380m, 368m, 365m, and 358m,while that of the sampling points on the concave segment was396 m, 386 m, 377 m, 372 m, and 367 m. At each samplingpoint, three subsamples were randomly collected within a ra-dius of 50 cm and mixed. The composite samples were then

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separated into two subgroups: one subgroup was air-dried tomeasure soil texture, SOC, and pH and the second subgroupwas preserved in a portable refrigerator to eliminate changesof soil structure and bioactivities, so as to be ready for settlingfractionation and incubation later in the laboratory .

2.2 Soil fractionation by settling velocity

In order to understand possible impacts of slope topog-raphy on the spatial patterns of soil compositions andSOC, all the soil samples from different slope positionswere fractionated according to the settling velocities ofindividual soil fractions (Fig. 2). The use of the settlingtube apparatus and the settling classification were de-scribed in Hu et al. (2013b). In brief, 200 g of each soilsample was prewetted for 15 min in a breaker by200 ml distilled water, and then introduced to the set-tling tube apparatus from the top injection chamber (Fig.2a). Following the Stokes’ law, soil fractions will fallthrough the static water column at different time inter-vals according to their settling velocities (Fig. 2b, c).Since the SOC is redistributed across the terrestrial andaquatic systems by the function of sediment aggregatesize (Starr et al. 2000), settling fractions of four equiv-alent quartz size (EQS), > 250, 63–250, 20–63, and <20 μm, were then collected at predetermined time inter-vals (Table 1) to represent the potential fate of soil frac-tions once they subject to erosion and transport. TheEQS was conceptualized to represent the diameter of anominal spherical quartz particle that has the same ve-locity with the aggregated fraction (Hu et al. 2013b;

Loch 2001). The 15 min prewetting before settling frac-tionation was to eliminate systematic variations uponfast-wetting and thus ensure comparable soil destructionacross all the EQS classes (Le Bissonnais 1996).

2.3 Measurement of SOC and δ13C

The concentration of SOC in all the unfractionated soilsamples and each settling fractions was determined byH2SO4-K2Cr2O7 oxidation (Nelson and Sommers 1996).The δ13C signatures of all the unfractionated bulk andfractionated samples were measured by ECS 4024 elemen-tal analyzer (Costech company, Italy). Since the inorganiccarbon content in the study soil was very limited under pHof 5.75, the signatures of δ13C of the total carbon wereused to represent the δ13C of the SOC. The δ notation (‰)represents stable isotopic compositions and was calculatedas follows (Dawson and Brooks 2001; Hu et al. 2016):

δ13C ¼ Rsample−Rstandard

Rstandard� 1000 ð1Þ

The Rsample represents the ratio of the heavy C (13C) tothe light C (12C) isotopes, and the Rstandard denotes theratio from a standard.

2.4 CO2 emission rate of settling fractions and theirtemperature sensitivity

After collected from the water tank at the bottom of the set-tling tube apparatus (Fig. 2b), each settling fraction was

Fig. 1 Location of study site and soil sampling scheme on the erodingslope. a The location of the study area in the Heilongjiang Province, b theorthoimage of the eroding slope, and c the digital elevation model of thesampling slope where the points represent the sampling positions. The

dataset of the study area is from the International Scientific & TechnicalData Mirror Site, Computer Network Information Center, ChineseAcademy of Sciences (http://www.gscloud.cn)

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introduced into a folded filter paper placing on a permeablestone to naturally drain away the surplus water until no morewater freely drained out of each sample (approximately halfan hour). The soil water content at that moment was thenassumed to be the field capacity for each settling class.According to previous studies, soil fractions of different sizestend to have various field capacity because of their unequalspecific surface areas (Hu et al. 2016; Rummel et al. 2014).Therefore, settling class specific field capacity, rather than ageneral field capacity referring to unfractionated soil core, wassimulated in this study. After free drainage, 15 g of moist soilwas placed into a 100-ml butyl lithium bottle and incubated atsix temperature gradients: 5 °C, 10 °C, 15 °C, 20 °C, 25 °C,

and 30 °C, to systematically measure the CO2 emissions rateof different settling fractions and their sensitivity totemperature changes. Adapted from the incubation methoddescribed in Lefebvre et al. (2014) and Ding et al. (2018), themoist samples were pre-incubated with lids open for 7 days at20 °C to stabilize biotic activities. As the formal incubationstarted, all the bottle lids were closed, first for 48 h at 5 °C,then each for 24 h at 10 °C, 15 °C, 20 °C, and 25 °C, and finallyfor 12 h at 30 °C. The prolonged incubation period at the lowesttemperature of 5 °C was to ensure adequate time to accumulatedetectable changes of CO2 concentration, while the shortenedincubation period at the highest temperature of 30 °C was toavoid invalid measurement once the CO2 concentration in thebottle reached saturation. The CO2 concentration in each bottlewas measured by portable infrared gas analytical apparatus(GXH-3010E1, Huayun, Beijing, China), and the dry weightof each incubated sample was determined at the end of the test.The soil CO2 emission rate (Rs) of each incubated sample wascalculated by the differences of CO2 concentration over a cer-tain period of time per unit of dry weight.

The relationship between temperature and CO2 emission ratewas described as following (Davidson et al. 1998; Xu and Qi2001):

Table 1 Equivalent quartz size (EQS) classes, settling velocities, andtime intervals to fall through the 1-m-long settling tube

EQS (μm) Settling velocity (m s−1) Settling time (min)

> 250 > 5.6 × 10−2 0.3

63–250 5.6 × 10−2–3.6 × 10−3 4.7

20–36 3.6 × 10−3–3.6 × 10−4 46.3

< 20 Suspension > 46.3

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Fig. 2 Settling tube apparatus. a The settling tube. b Soil fractions sitting in different samplers in the water tank. c Soil fractions after air-dried

Rs ¼ αeβT ð2ÞQ10¼e10β ð3ÞRS: CO2 emission rate (μg CO2 g

−1 dry soil h−1), T: tempera-ture (°C), Q10: temperature sensitivity of CO2 emission rate,α: fitting parameter, and β: temperature dependence of soilCO2 emission. Only the Q10 with the coefficient of determi-nation r2 greater than 0.90 was considered reliable.

The cumulative CO2 emission rate from each topographicposition was calculated by multiplying the CO2 emission ratewith weight distribution and interpolating them over the incu-bation intervals at each temperature. During incubation, all thesamples were re-moistened every 3 days to control their wetweight. All the regressions for Q10 were implemented byMicrosoft Excel 2016, and all the figures were plotted usingSigmaplot 12.5.

3 Results

3.1 Size distribution at different topographicpositions

The cumulative mass percentage of EQS distribution of thetopsoil noticeably differed between the two toposequences(Fig. 3). On the convex segment, the EQS distribution firstexperienced a coarsening effect toward eroding hotspot, andthen a fining pattern as the slope flattened out (Fig. 3a). Thefine fractions of EQS < 63 μm were comparable at 15% from150 m (elevation of 396 m) to 650 m (elevation of 380 m) andthen declined to only 6% at the position of 900 m, whereas thecoarse fractions of EQS > 250 μm noticeably increased tofrom 50% at 150 m to 68% at 900 m (elevation of 368 m)(Fig. 3a). Meanwhile, along the concave segment, the EQSdistribution was comparable among different positions, merely

with a slightly greater content of fractions of EQS < 250 μm atthe position of 900 m (elevation of 367 m) (Fig. 3b).

3.2 Soil SOC and δ13C along the slope

The SOC concentration was generally lower along the convexthan the concave segment, and the δ13C signatures of theconvex segment were also more positive than that of the con-cave segment (Fig. 4). Their spatial variations also differedconsiderably. Even though the SOC concentration of the twotoposequences both started from 24.73 mg g−1 at the upslope(position of 150 m with elevation of 396 m), it progressivelydeclined down to the lowest value of 7.39 mg g−1 as theconvex segment approached the erosion hotspot at the posi-tion of 900 m (elevation of 368 m) (Fig. 4a). Meanwhile, theSOC concentration of the concave segment peaked at36 mg g−1 around the position of 400 m (elevation of386 m), and then slightly decreased afterwards until the29.42 mg g−1 at the position of 900 m (elevation of 367 m).The δ13C signatures at the position of 150 m (elevation of396 m) of the two toposequences stayed together at −24.28‰ (Fig. 4b). As the slope descended, the δ13C signaturesalong the convex segment first increased and then decreased,peaking at 900 m (elevation of 368 m) with − 22.25‰ (Fig.4a), while the δ13C signatures along the concave segmentfluctuated between − 23.97‰ and − 22.42‰ (Fig. 4b).

3.3 SOC and δ13C across settling classes

The size-specific SOC distribution differed both among slopepositions and across EQS classes, and their variations weremuch more pronounced along the convex than that concavesegment (Fig. 5a, b). To be specific, the SOC concentrationsof each EQS along the convex segment (Fig. 5a) varied be-tween 3.39 and 27.04 mg g−1, which was overall lower than

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Fig. 3 Cumulative mass percentage of equivalent quartz size (EQS) of the topsoil collected at different distances (with elevations in brackets) along theconvex segment (a) and concave segment (b)

that along the concave segment (ranging from 22.15 to37.13 mg g−1, Fig. 5b). While consistent with the spatial pat-terns of unfractionated soils along the convex segment, theEQS classes derived from the position of 900 m (elevation

of 368 m) had the lowest SOC concentrations of3.39 mg g−1 and the highest δ13C signature of − 21.09‰among all the EQS classes (Fig. 5a, c). Among different set-tling classes along the convex slope, the SOC tended to be

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Fig. 4 Spatial variation of SOC concentration and δ13C of unfractionated soils along the convex segment (a) and concave segment (b)

Fig. 5 Variation of SOC concentration and δ13C across the four the equivalent quartz size classes fractionated from unfractionated bulk soils collected atdifferent topographic positions along the concave and convex segment

slightly enriched in the finest EQS class (< 20 μm). The δ13Csignatures of all the settling classes along the convex slopewere less positive as EQS reduced, with the most positiveδ13C of − 21.09‰ in the coarse fractions of EQS > 250 μmat 900 m (elevation of 368 m), and the most negative δ13C of− 24.79‰ in the fine fractions of EQS < 20 μm at 150 m(elevation of 396 m). As for all the EQS classes along theconcave segment, the δ13C signatures appeared to be slightlymore negative as the EQS decreased, ranging from − 24.00 to− 24.81‰ (Fig. 5c, d).

3.4 Fractions size-specific CO2 emissions rate

The CO2 emission rates of both unfractionated and fractionat-ed soil fractions typically increased with higher incubationtemperature (Fig. 6). Compared with the unfractionated soils(mostly under 1.5 μg CO2 g

−1 dry soil h−1), the CO2 emissionrates of the settling fractions (except for the EQS of 20–63 μm) were generally enhanced along the convex segment(Fig. 6). The most pronounced enhancement of CO2 emissionrate was observed in the settling fractions of EQS < 20 μm(e.g., with the CO2 emission rate of 3.14 μg CO2 g

−1 dry soilh−1 at 30 °C on the position of 950 m (elevation of 365 m)(Fig. 6e). Among the different topographic positions along theconvex segment (Fig. 6a–e), the CO2 emission rate was al-ways lowest at the position of 900 m (elevation of 368 m),both for the unfractionated soils (e.g., 0.68 μg CO2 g

−1 drysoil h−1 at 30 °C, Fig. 6a) and the fractionated settling classes(e.g., EQS < 20 μm with 1.08 μg CO2 g−1 dry soil h−1 at30 °C, Fig. 6e).

The cumulative CO2 emissions from different topo-graphic positions along the convex segment also showednoticeable variations (Fig. 7a–e), with the lowest emis-sions from the position of 900 m (elevation of 368 m)(in total 0.24 mg CO2) and the highest from the position1100 m (elevation of 358 m) (in total 1.34 mg CO2).Meanwhile, the cumulative CO2 emission rate along theconcave segment were rather comparable among differenttopographic positions, ranging from 0.57 to 0.98 mg h−1

(Fig. 7f–j). The cumulative CO2 emissions from bothtoposequences were predominantly contributed by coarsefractions of EQS > 63 μm, responsible for 74% to 84%total CO2 emissions at each position (Fig. 7).

3.5 Temperature sensitivity of CO2 emission rate

The Q10 of the unfractionated bulk soils along the convexsegment increased from 3.39 at the position of 150 m (el-evation of 396 m) to 4.87 at the position of 900 m (eleva-tion of 368 m), and then dropped to 2.23 at the position of1100 m (elevation of 358 m) (Table 2), evidencing morepronounced spatial variation than that on the concave seg-ment fluctuating between 2.50 and 2.94. The Q10 of the

fractionated EQS classes along the convex segment didnot show consistent patterns, only appearing to be greaterat the position of 900 m (elevation of 368 m) with Q10 of5.22 in the EQS > 250 μm and 7.19 in the EQS of 63–250 μm (Table 2). The Q10 of the fractionated classesalong the concave segment was comparable among topo-graphic positions but tended to increase as the EQS be-came finer (Table 2). While the Q10 of the EQS < 20 μmvaried between 3.35 and 5.33, that of the EQS > 250 μmranged from 2.85 to 3.51 (Table 2).

4 Discussion

4.1 Topography-specific spatial redistribution of soilcompositions and SOC

While the soil fractions along the convex segment showeda coarsening effect on the upper slope and a fining trendtoward the slope toe (Fig. 3a), the soil compositions alongthe concave segment were fairly comparable as slopedescended (Fig. 3b). Such inconsistent spatial variationsof soil compositions over the two toposequences were pri-marily caused by their divergent topographic features andthe thus induced differences in soil erosion and transportprocesses (Fig. 1). On the one hand, the runoff contribut-ing area along the convex segment gradually increased asthe slope descended, and the up-and-down hill furrowsfurther facilitated the within field connectivity (Fig. 1).This jointly led to concentrated and progressively acceler-ating runoff as slope descended, during which time thesurface soil experienced an increasingly coarsening effect(Fig. 3a) and forming an erosion hotspot at the steepestslope segment (approximately 900 m away from upslope)(Fig. 1b). On the other hand, every time a tillage tractorpassed the steepest point of the convex segment, the localplow layer was translocated (Heckrath et al. 2006; Zhaoet al. 2018), yet the translocation distance downward slopewas longer than that in the upward direction (Van Oostet al. 2000). This resulted in net surface soil loss at thesteepest point of the convex segment over repeated up-and-down hill tillage operations (Hu et al. 2016), whicheventually consumed all the fertile soil, exposed the sandysubsurface soil, and even formed gullies (Fig. 1b). At thesame time, although the concave segment was roughlyparallel to the convex segment, it was low-lying, gentler,and thus less affected by tillage translocation (Fig. 1).During water erosion events, the concave segment mainlyreceived surface runoff and selectively transported soilfractions from both the upper and the adjacent high-lyingslope, consequently accumulating SOC-rich fine soil frac-tions as a temporal depositional site (Fig. 3).

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4.2 Slope-scale heterogeneity of SOC redistribution

Topography variations also cause spatial differences in SOCconcentrations and δ13C signatures (Figs. 4 and 5), as the SOCof different stability was mobilized and preferentially depos-ited over the two toposequences with soil fractions of distinctsettling velocities (Fissore et al. 2017; Hu and Kuhn 2016,2014; Kuhn et al. 2012; Yoo et al. 2006). The comparableCO2 emission rates of the unfractionated soils collected fromthe convex and concave segments (Fig. 6) further point outthat the mineralization of SOC was not exclusively deter-mined by the inherent SOC concentration (Fig. 4) and theprecedent decomposition experiences (Fig. 5). The desirablesoil moisture at field capacity and stably controlled tempera-ture gradients simulated in this study (Sect. 2.4) may havestimulated the SOC mineralization of all the incubated soilsamples, which would not be equally favorable if otherwisein the field with complex erosion and deposition settings. Thelimited contributions of cumulative CO2 emissions from theerosion hotspot at the position of 900 m but the concentratedCO2 releases from the depositional position of 1100 m on theconvex segment (Fig. 6) further underline the concerns pro-posed by previous reports (Dialynas et al. 2016; Li et al.2018a) that topography variations have a strong control oversoil erosion processes and thus induced carbon sourcestrength. The varying Q10 among different positions alongthe convex segment (Table 2) also accentuate the erosionalperturbation of slope-scale carbon cycling by raising the tem-perature sensitivity of CO2 emission rates at erosion hotspot(at position of 900 m with elevation of 368 m) and reducingsuch sensitivity at depositional site at the far end of the slopetoe (at position of 1100 m with elevation of 358 m) (Table 2).However, such fine spatial scale variations are oftenovergeneralized by coarse grid sizes in digital elevationmodels (DEM) (Balaguer-Puig et al. 2018; Li et al. 2018b;Xu et al. 2019). Neither the sediment delivery ratio nor thesediment discharge measured by flow meter devices at fieldoutlet can truly reflect the net soil displacement and localerosion loss on hillslopes (Kirkby 2010; Walling 1983).Therefore, even for regions with low relief, slope-scale soilerosion risks should be not crudely estimated by averagingsediment discharged out of the field over the entire slope area.Topography-specific rather than indiscriminate measuresshould be integrated to effectively mitigate on-site soil lossand land degradation risks.

4.3 Topography-dependency of carbon vertical fluxes

The generally enhanced CO2 emission rates of fractionat-ed classes than the unfractionated soils (Fig. 6) suggestthat erosion was very likely to accelerate CO2 emissionsas soil aggregates breakdown upon raindrop impact or viatransport. This is in line with previous reports (Hu andKuhn 2014; Polyakov and Lal 2008, 2004), which ob-served that aggregate destruction during erosion processeswould expose SOC that was previously encapsulated with-in aggregates and introduce additional CO2 emissions. Inthis study, such enhancement of CO2 emission rate wasmore noticeable in the fine soil fractions of EQS <20 μm (Fig. 6e, j), which was probably fostered by therelatively rich SOC and less decomposed δ13C signatures(Fig. 5). The EQS-specific CO2 emission rates also dif-fered among different slope positions (Fig. 6), suggestingthat even for the same EQS class, its stability could bealtered after being mobilized, deposited and residing atdifferent slope positions. Presumably for a nominal 1 kgtopsoil on a prolong slope such as in this study (Table 3),it would be very likely to experience enhanced CO2 emis-sion rate after being fractionated and redistributed along aconvex segment, but undergo a slightly inhibited mineral-ization process over a concave segment. This further high-lights the demand to adequately account for the potentialimpacts of minor topographic features on slope-scale lat-eral and vertical carbon fluxes.

Despite that the Q10 of the EQS classes were noticeablyvaried among different slope positions on the convex seg-ment (Tables 1 and 2), no consistent patterns were ob-served (except for the enlarged Q10 of the fractionatedclasses at the position of 900 m). Such finding is differentfrom previous studies, out of which Chevallier et al.(2015) reported that there were not significant effects ofmacroaggregate crushing to soil Q10, and Plante et al.(2009) also reported that no differences in Q10 values weredetected between the intact and crushed macroaggregates.The discrepancies between previous reports and our find-ings are mainly because no erosional biochemical changesof SOC or topography-specific microclimate conditionswere involved in previous studies when carrying out soilaggregate destruction or wet-sieving fractionation undercontrolled experimental conditions. The spatial variationsof EQS-specific CO2 emission rates recorded in this studynot only underpin the impacts of soil settling velocity toslope-scale SOC redistributions, as reported by Hu et al.(2016) and Wilken et al. (2017), but also highlight that thestability of eroded SOC and its sensitivity to temperaturechanges are both dependent on topographic features andlocal microclimatic conditions (Berhe 2012; Fiener et al.2012; Li et al. 2018b). Furthermore, given the expansionof cropland in northeast China (Shi et al. 2013; Ye and

�Fig. 6 Changes of CO2 emission rate of unfractionated and fractionatedsoils at six temperature gradients. Subfigures a–e respectively representthe CO2 emission rate of unfractionated bulk soil, and EQS > 250 μm,63–250 μm, 20–63 μm, and < 20 μm along the convex segment, whereasthe subfigures f–j represent that along the concave segment. Thesampling distances are listed in the legend where the numbers in thebrackets indicate the elevation of each sampling point

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Fang 2011), the redistribution of soil fractions and SOCalong cropped slopes is likely to become more sensitive toheterogeneous topographic features over more concentrat-ed summer rainstorms (Li et al. 2018a; Shi et al. 2013;Wilken et al. 2017). The generally increasing temperatureprojected to the future can also introduce unknown effectson vertical carbon fluxes through crop production, carbondynamic replacement, and SOC decomposition at differenterosion and deposition settings along the slope (Aldersonet al. 2016; Harden et al. 1999). Therefore, topography-dependency and within-field connectivity must be proper-ly represented into soil-atmosphere carbon models(Billings et al. 2019; Dialynas et al. 2016).

5 Conclusions

This study examined the spatial variations of soil particles,SOC and CO2 emission rate over two toposequences (con-vex and concave segment) on a long gentle cropped slopein northeast China. Under the heterogeneous effects ofwater erosion and tillage operations at different topograph-ic positions, the convex segment displayed a sequence ofcoarsening and fining trend from upslope to erosionhotspot and further down to slope toe, while the soil

compositions along the concave segment were rather com-parable. The SOC, CO2 emission rate, and its sensitivityto temperature changes also differed among different topo-graphic positions, further accentuating the strong control offine spatial scale variations of slope heterogeneity to thelateral redistribution patterns and stability of SOC.Moreover, the biochemical properties of SOC in individualsoil fractions were also altered by being eroded, transport,deposited, and resided in different erosion-deposition set-tings, which would also pose diverse impacts on verticalcarbon fluxes. Therefore, topography-dependency must beproperly represented into soil-atmosphere carbon models.Even for regions with low relief, topography-specific rath-er than indiscriminate measures should be integrated toeffectively mitigate soil loss and land degradation risks.

Table 2 Variations of Q10 among the unfractionated soils and four equivalent quartz size (EQS) settling fractions at different topographic positionsalong the convex and concave segment

Toposequence Distance from upslope (m) and the elevation (m) Unfractionated soil Equivalent Quartz Size (μm)

> 250 63–250 20–63 < 20

Convex 150 (396) 3.39 (0.95) 2.51 (0.98) 2.72 (0.99) 4.09 (0.97) 2.92 (0.98)

650 (380) 3.01 (0.95) 7.48 (0.88) 3.69 (0.95) 4.81 (0.91) 3.14 (0.94)

900 (368) 4.87 (0.96) 5.22 (0.93) 7.19 (0.98) 2.88 (0.95) 3.73 (0.80)

950 (365) 1.99 (0.89) 3.75 (0.97) 2.65 (0.96) 3.09 (0.97) 3.42 (0.97)

1100 (358) 2.23 (0.94) 2.51 (0.99) 3.38 (0.99) 3.98 (0.84) 2.41 (0.97)

Concave 150 (396) 2.82 (0.96) 2.98 (0.98) 3.11 (0.98) 3.97 (0.96) 5.33 (0.91)

400 (386) 2.50 (0.94) 2.85 (0.99) 3.08 (0.99) 3.37 (0.98) 4.22 (0.94)

650 (377) 2.88 (0.98) 3.07 (0.98) 2.53 (0.97) 2.81 (0.98) 4.72 (0.91)

800 (372) 2.75 (0.97) 3.51 (0.97) 2.67 (0.96) 3.04 (0.97) 3.35 (0.96)

900 (367) 2.94 (0.99) 2.98 (0.99) 6.77 (0.85) 3.03 (0.98) 4.10 (0.90)

Numbers in the parentheses indicate the r2 of regression curves to calculate Q10. The Q10 values with r2 greater than 0.90 were italicized

Table 3 Normalized CO2 emission rate from nominal 1 kg ofunfractionated soil and fractionated classes with total weight of 1 kg

Toposequence Distancefromupslope(m) andthe eleva-tion (m)

CO2 emissionrate from 1 kgunfractionatedsoil (mg h−1)

CO2 emissionrate fromfractionatedclasses withtotal weight of1 kg (mg h−1)

Relativedifferences(%)

Convex 150 (396) 3.57 5.34 49.52650 (380) 3.71 2.94 − 20.81900 (368) 1.41 1.25 − 11.90950 (365) 2.38 2.55 7.021100 (358) 3.43 7.35 114.18

Concave 150 (396) 4.51 5.44 20.58400 (386) 4.32 4.41 2.25650 (377) 6.22 4.38 − 29.53800 (372) 4.60 2.92 − 36.47900 (367) 5.18 5.09 − 1.71

�Fig. 7 Cumulative CO2 emission rate over the incubation intervals ateach temperature along the two toposequences. Subfigures a–erespectively represent the cumulative CO2 emissions from the fiveslope positions along the convex segment, whereas the subfigures f–jrepresent that along the concave segment. The sampling distances arelisted in the legend where the numbers in the brackets indicate theelevation of each sampling point

1916 J Soils Sediments (2020) 20:1906–1919

Acknowledgments The authors also gratefully acknowledgeMs. BrigitteKuhn for her professional pilot of UAVover the study area. The contri-butions of Xiaojing Ou, Yan Zhang, Weijia Li, and Fangbin Hou in fieldwork and laboratory experiments are also thankfully appreciated.

Funding information The research was supported by the National KeyResearch and Development Project of China (2018YFC0507001) and theNational Natural Sciences Foundation of China (No. 41701318).

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