Soil carbon and nutrient sequestration linking to soil aggregate in a temperate fen in Northeast China

Ecological Indicators 98 (2019) 869–878

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Soil carbon and nutrient sequestration linking to soil aggregate in a temperate fen in Northeast China

T

Mingzhi Lua, , Mengyao Yangb, Yurong Yangc, Deli Wangc, , Lianxi Shengc ⁎

⁎

a

Institute of Grassland Science and School of Life Science, Northeast Normal University, and Key Laboratory of Vegetation Ecology, Ministry of Education, Changchun, Jilin 130024, China b Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China c School of Environment, Northeast Normal University, and State Environment Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Changchun, Jilin 130117, China

ARTICLE INFO

ABSTRACT

Keywords: Soil nutrient Soil aggregates Freshwater wetland Fen Stoichiometric characteristics

Soil carbon and nutrients play vital roles in ecosystem services. Many previous studies documented carbon or nutrient accumulation and the relevant impacting factors, and emphasized the soil physical structure, especially soil aggregates, that might play a key role in grasslands or farmlands. Unfortunately, there is little known about the relationship between soil aggregates and nutrient sequestration in fens and which soil aggregate type contributes most strongly to the soil nutrient cycle in fens. In this study, we collected 180 soil samples from 3 sites and then tested the changes in soil nutrient contents and carbon sequestration rates based on soil aggregate fractions from a fen that has critical implications for temperate wetland ecosystems in Northeast China. This fen soil is obviously characterized with macroaggregate and microaggregate structures. For this soil, the mean weight diameter (MWD) ranged from 0.42 to 0.61 mm and the geometric mean diameter (GMD) ranged from 0.82 to 0.90 mm, and there were fluctuations for both MWD and GMD along with soil depth. The correlation analysis showed that macroaggregates were more closely related to carbon sequestration (p < 0.01) and stable soil microaggregates were important for nutrient conservation (p < 0.01) in this fen. The sequestration rates of carbon, nitrogen and phosphorus were 87.64 ± 10.88 gC m−2 yr−1, 3.43 ± 0.54 gN m−2 yr−1, and 0.17 ± 0.02 gP m−2 yr−1, respectively. Additionally, the characteristic stoichiometric balance was related to the aggregate size and there were four distinct intervals for both the C/N ratio and C/P ratio; three intervals were located in similar ranges for the C/N ratio and C/P ratio (12–14 cm, 20–22 cm, and 28–30 cm) which means three of these areas coincided with the C/P ratio that characterizes the phosphorus conversion intensity index. The findings indicate that soil aggregates play key roles in soil carbon sequestration and nutrient cycling within wetlands.

1. Introduction Soil is the major “switching yard” for the global cycles of carbon, water and nutrients (Regnier et al., 2013). Carbon, nitrogen, phosphorus, and many other nutrients are stored, transformed, and cycled through soil (Quinton et al., 2010). Soil carbon plays vital roles in ecosystem services, such as maintaining biodiversity, regulating climate and adjusting water circulation (Nahlik and Fennessy, 2016). Despite occupying 5–8% of the land surface on Earth, wetlands contain a disproportionate 300–700 PgC of soil carbon, which constitutes between 20 and 30% of the estimated 1500 PgC of global soil carbon (Lal, 2008; Nahlik and Fennessy, 2016). Most wetlands are net carbon sinks, and many studies have attempted to estimate the annual carbon

⁎

accumulation rate (Armentano and Menges, 1986; Mitsch et al., 2013; Schillereff et al., 2016). Water loss, wetland management policy and some metal ions in soil may influence wetland carbon sequestration (Horvath et al., 2017; Lewis, 2016; Wang et al., 2017), but in some circumstances, the soil physical structure might play a key role (Bronick and Lal, 2005). Soil aggregates are the basic units of soil structure; they are sensitive to land use and can mediate many chemical and biological processes in soils (Post et al., 2004; Wang et al., 2015a). The formation mechanism of soil aggregates has been determined (Six et al., 2000; Uwe et al., 2018). The distribution and development of soil aggregates are highly related to the external environment (Mueller et al., 2007). Some studies have found that freeze-thaw processes and human activities can affect

Corresponding authors. E-mail addresses: [email protected] (M. Lu), [email protected] (D. Wang).

https://doi.org/10.1016/j.ecolind.2018.11.054 Received 23 August 2018; Received in revised form 20 November 2018; Accepted 21 November 2018 1470-160X/ © 2018 Elsevier Ltd. All rights reserved.

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the development of soil aggregates, which in turn affect nutrient cycling in soil (Alexandre Bogas et al., 2016; Medina et al., 2013; Six et al., 2000). In addition, variations in macroaggregates and microaggregates in cultivated land can affect the soil nutrient distribution and nutrient sequestration rates (Kasper et al., 2009). Soil aggregates can be divided into two types: macroaggregates and microaggregates. Macroaggregates and microaggregates have been considered to be crucial to the process influencing the stabilization of soil organic matter (SOM) (Oades, 1984; Six et al., 2004). Although most soil carbon is sequestered in macroaggregates, microaggregates provide a more stable sink of soil carbon (Jastrow, 1996). In addition, macroaggregates and microaggregates are believed to have different effects on soil nutrient distribution and sequestration rates in cultivated land (Kasper et al., 2009). Although we intuitively understand that soil aggregates can influence the nutrient input and carbon sequestration rate in tillage soil, these relationships have never been quantified from a wetland soil structure perspective (Wang et al., 2015a). This study quantitatively estimated the relationship between aggregates and nutrients in fen soil with different layers. The objective of this study was to identify the linkages between soil aggregates and changes of carbon and nutrients in fens. We hypothesized that the soil structure of wetland is similar to that of grassland and farmland, i.e., aggregates have a significant relationship with nutrient dynamics in fen. In addition, this study sought to determine which the aggregate type that contributes most strongly to the soil nutrient cycle in fens. We

tested the hypothesis and pursued our objectives by analyzing soil from a fen that has critical implications for temperate wetland ecosystems in Northeast China. 2. Materials and methods 2.1. Study area The study area, the Jinchuan wetland (42°16′–42°26′ N, 126°13′–126°32′ E), is located in the middle of the southwestern Changbai Mountains, Northeast China, with elevations ranging between 632.51 m and 640.51 m above sea level. There are many rivers in the study area; the Hou River flows through the southern portion of this wetland. The area is characterized by a continental monsoon climate with four distinct seasons. The mean annual temperature is 4.1 °C, and the accumulated temperature from May to September is 2500–2600 °C. The average annual precipitation in the study area is nearly 704.2 mm, most precipitation occurs during the summer and fall, and the average annual evaporation is approximately 1276.1 mm. This fen has a high species diversity, with sedges, cattails and reeds being the dominant species. Six main communities were observed in this wetland, including birch (Betula ovalifolia) + sedge (Carex schmidtii); C. schmidtii + typha (Thelypteris palustris); C. schmidtii + reed (Phragmites australis); C. schmidtii; C. tenuiflora; and Ph. australis + C. schmidtii (Fig. 1).

Heilongjiang province

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Liaoning province

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Sampling sites Administrative boundary River system

48°20'57"N 46°20'57"N

Jinchuan wetland H

0

124°21'31"E

Rice paddy 200 126°21'31"E

400 m 128°21'31"E

Fig. 1. Location of the Jinchuan wetland and our study site.

870

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Figure Legends

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Sample 1 Sample 2 Sample 3

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soil and continually decays into gaseous 226Rn, which in turn is distributed globally throughout the atmosphere and rapidly decays into several other short-lived isotopes. 210Pb is readily adsorbed by the soil matrix and sediment surface. To account for varying sedimentation throughout time, the constant rate of supply (CRS) model was selected to calculate sediment age as follows (Alvarez-Iglesias et al., 2007):

2.2. Sampling and measurement Nine intact soil cores (3 from each site) were collected from this fen, and the 3 sampling sites were chosen based on their accessibility and typical plant community. The sampling sites were oriented in a radial direction from the center of the wetland to the outer edge (Fig. 1, bottom). The corer liner was made from a clear polycarbonate pipe, which was easily detected from the difference in the level of the soil surface between the inside and outside of the liner. Once the core was discarded, sampling was repeated. After the soil core was extracted from the corer liner, to compensate for the loss fraction due to compaction, the length of the extruded core was compared with the length of the core liner, and the average correction was used to represent the entire core length. Three replicate cores, each 40 cm long and 7 cm in diameter and divided into 2 cm increments, were extracted from each sample site by the core method (Isaksson et al., 2001; Stark et al., 2006b). All of the increments were packed and stored at 4 °C until analysis. In this study, 65 samples were collected from the three sample sites, and each sample was divided into two portions for testing. The first portion was used in a series of measurements that included bulk density analysis and sieving soil aggregates, and the second portion was used for soil radiometric analysis. To obtain reliable bulk density estimates, 2-cm-thick air-dried soil segment samples were weighed, and the mass was used to estimate the bulk density. Then, the samples were placed on the top sieve of 5 nested sieves (1.000, 0.300, 0.250, 0.063 and 0.053 mm) in a container full of de-ionized water. After wetting the samples for 30 min by capillarity, the samples were gently wet-sieved with a vertical motion (5 cm amplitude and 25 S min−1) for 30 min (Kemper et al., 1985; Kemper and Rosenau, 1986). For the nutrient distribution and radiometric analyses, the samples were oven dried at 60 °C for 72 h to determine the dry weight. Total organic carbon (TOC) concentration was measured by subtracting the inorganic carbon (IC) from the total carbon (TC) using a Shimadzu Total Organic Carbon Analyzer (TOC-V series, SSM-5000A, Japan). TC (%) was determined via combustion at 900 °C in the analysis chamber. Samples used for the determination of IC (%) were pretreated with 10 mol L−1 H3PO4 and then combusted at 200 °C using standard procedures for wetland soils. The percent TOC was multiplied by 10 to calculate the carbon concentration in gC kg−1 in 2-cm sample intervals (Craft, 2012; Lyu et al., 2016). Total nitrogen (TN) and total phosphorus (TP) were measured by the Kjeldahl (Kjeltec 8400, Demark) and molybdenum-antimony anti-spectrophotometric methods, respectively (Bremner, 1996; Kuo, 1996). The second portions of the samples were sealed and labeled in individual plastic bags, which were then arranged according to depth from the surface to 40 cm. A radiometric detector was used to ascertain 137 Cs and 210Pb activity (pCi, 10–12 Ci) for the estimation of recent soil accretion rates. Composite subsamples with a mass of 10 g were analyzed by γ spectrometry for 20 h at 661.7 keV and 46.5 keV for 137Cs and 210Pb activity, respectively, using a high-efficiency germanium detector (ORTEC High-Purity Germanium (HPGe) Well Detectors, USA). Radio cesium (137Cs) is a man-made fallout radionuclide (30.1 yr halflife) that is distributed worldwide as a consequence of deposition from atmospheric nuclear weapon tests (Craft and Richardson, 1993). The sediment peak of 137Cs deposition worldwide appears to correspond to the year 1964. 137Cs binds with sediment and moves with it in soil, remaining unaltered; thus, the radionuclide is widely used as tracer in studies with many sites, such as wetlands and floodplains (Stark et al., 2006a). The activity peak layer (year 1964) in the soil profile which was used to estimate the sediment accumulated in the wetland. If the profile has not been disturbed by any activity, then the estimated accretion rate can be calculated assuming a constant sedimentation rate (Beilman et al., 2009; Bernal and Mitsch, 2012; Brenner et al., 2001). In cases where 137Cs (30.1 yr half-life) profiles cannot conclusively be used to determine the rate of soil accretion, 210Pb, a radioisotope in the 238U decay series, can be used. 238U is found naturally in the Earth’s

A d = A 0e

(1)

( t) 210

210

where Ad is the excess Pb activity at depth d, A0 is the Pb activity at depth zero, λ is the 210Pb decay constant (0.0311/yr), and t is the time (yr). Carbon sequestration and nutrient accumulation rates g m−2 yr−1were calculated by the following equation: (2)

Cseq = BD × Ccon × A d −3

where BD is the average bulk density (g cm ) throughout the dated portion of the soil core profile, and Ccon (g kg−1) is the average carbon concentration in the soil sample. Aggregate stability was estimated by the MWD and GMD. MWD is a comprehensive indicator for the evaluation of aggregate stability, and GMD is an index of the main grain size distribution of aggregates. Greater values of MWD and GMD indicate higher aggregate stability (Bavel, 1950; Bedini et al., 2009). MWD and GMD are calculated using the following formulas: n

MWD =

x i wi i=1

GMW =

n w lnx1 i=1 i n x i=1 i

(3)

(4)

where xi is the mean diameter of aggregate i (mm), wi is the percentage of aggregate i (%), and n is the number of aggregate fractions. 2.3. Statistical analysis All data were analyzed by SPSS Statistical Software version 23.0 (X64) for Windows 10 (IBM, Endicott, New York). The distribution normality of carbon sequestration, carbon content with respect to particle size, TOC, TN, and TP were tested using the Shapiro-Wilk test when necessary at a 95% significance level (Ghasemi and Zahediasl, 2012). One-way analyses of variance (ANOVA) was used to assess the relationship of soil depth and soil particle size with carbon content, TOC, TN, and TP in this wetland, followed by the Duncan test as a post hoc test. Principal component analysis (PCA) and redundancy analysis (RDA) were performed for each range of particle sizes to examine the relationship between the content of each of TOC, TN, and TP and the sediment accumulation rate (Klinger et al., 2015). Significant differences are indicated by p ≤ 0.05 and p ≤ 0.01 for 95% and 99% confidence, respectively. 3. Results 3.1. Proportion of soil aggregate fractions and nutrient content distribution In this study, soil aggregates were divided into two parts, and the proportions of each fraction are shown in Fig. 2. Generally, the proportion of the macroaggregate fraction was greater than that of the microaggregate fraction; the amount of macroaggregates was almost four times that of the microaggregates in all layers. Moreover, the mean weight diameter (MWD) ranged from 0.42 to 0.61 mm, while the geometric mean diameter (GMD) ranged from 0.82 to 0.90 mm; both the MWD and GMD fluctuated. The general trend of macroaggregate distribution decreased from the soil surface to the 12–14 cm layer, then increased in the 16–18 cm layer, and subsequently fluctuated in the remaining layers. In the 12–14 cm layer, the macroaggregate 871

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1.0 0.9 0.8

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Proportion of aggregate fraction (%)

100

Depth (cm)

>0.25

MWD

<0.25

GMD

Fig. 2. Proportion of aggregate fractions with different MWD and GMD values.

Depth (cm)

250 0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24 24-26 26-28 28-30 30-32 32-34 34-36 36-38 28-40

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* * Fig. 3. Soil nutrient content distribution between macroaggregates and microaggregates.

proportion, MWD and GMD all reached minimum values, with values of 60%, 0.42 mm, and 0.82 mm, respectively. However, the maximum values of all three parameters were reached in the 0–4 cm and 36–38 cm layers, with values of 80%, 0.61 mm, and 0.90 mm, respectively. The soil nutrient content distribution showed different trends for TOC, TN and TP (Fig. 3). The amount of TOC in both macroaggregates and microaggregates increased from the surface to the bottom layer. TN content decreased gradually from the soil surface to a certain depth and then increased to the bottom. The change in TP was approximately similar to that in TN, but the TP values fluctuated in the lower layer. TOC content of macroaggregates was higher than that of microaggregates. The lowest TOC contents occurred in the 6–8 cm layer with values of 319.09 ± 8.39 mg g−1 and 303.95 ± 41.72 mg g−1 for

macroaggregates and microaggregates, respectively, and TOC contents reached their highest values in the 36–38 cm layer with values of 447.59 ± 10.69 mg g−1 and 431.84 ± 17.63 mg g−1 for macroaggregates and microaggregates, respectively. The paired T-test was performed for the TOC between macroaggregates and microaggregates when the samples were divided into 0–20 cm and 20–40 cm ranges (Table S1). The results showed significant differences for the two intervals, and when the samples were divided into 8-cm layers (Table S2), some significant differences were found in the 0–8 cm, 8–16 cm (p = 0.045), 24–32 cm and 32–40 cm (P = 0.004) layers but not in the 16–24 cm layer. For the TN content, there were no significant differences between macroaggregates and microaggregates (Table S1 & S2). There was a reduction in the 12–16 cm layer for macroaggregates and 872

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87.64 ± 10.88 gC m−2 yr−1, ranged from 3.43 ± 0.54 gN m−2 yr−1, 0.17 ± 0.02 gP m−2 yr−1, respectively. Based on the reconstructed 210Pb chronology, we reconstructed the TOC, TN and TP sediment accumulation rates in the soil aggregates at different depths (Fig. 5). There were similar increasing trends for TOC, TN, and TP in sediment with the soil depth from the surface to the bottom layers, and there was no significant difference in sediment TP between macroaggregates and microaggregates, except for those in the 32–34 cm layer (p = 0.02). The rates of increase and the variations in TOC, TN and TP sequestration in the lower layers (0–24 cm) were much higher than those in the upper layers (24–40 cm). For sediment TOC, the average rate of increase in macroaggregates and microaggregates was 80.30 ± 6.13 gC m−2 yr−1 and 77.46 ± 12.32 gC m−2 yr−1, respectively. In addition, the nitrogen sequestration rate ranged from 0.42 to 10.53 gN m−2 yr−1, and the phosphorus sequestration rate ranged from 0.02 to 0.44 gP m−2 yr−1 There were two sediment peaks in the results, one appearing in the 24–26 cm layer (∼A.D. 1930 ± 3) and the other appearing in the 34–36 cm layer (∼A. D. 1900 ± 3).

microaggregates, and the TN reached minimum values of 12.05 ± 0.79 mg g−1 and 12.93 ± 1.27 mg g−1, respectively (Fig. 3), while the maximum values appeared at the surface and bottom for both macroaggregates and microaggregates (20.36 ± 1.58 mg g−1 –23.93 ± 5.39 mg g−1). In contrast, the TP content in macroaggregates was rarely higher than that in microaggregates (Fig. 3). The minimum TP contents in macroaggregates and microaggregates were found in different layers: the 20–22 cm (0.68 ± 0.02 mg g−1) layer for macroaggregates and the 20–22 cm layer (0.73 ± 0.02 mg g−1) and 28–30 cm layer (0.73 ± 0.01 mg g−1) for microaggregates. The maximum TP contents for macroaggregates and microaggregates occurred in the same layer, 32–34 cm (0.89 ± 0.01 mg g−1 and 0.95 ± 0.01 mg g−1, respectively). In the paired T-test of TP between macroaggregates and microaggregates, the samples were divided into two parts: 0–20 cm and 20–40 cm (Table S1), and the results showed significant differences for these two intervals. When dividing the samples into 8-cm layers (Table S2), some significant differences were found in the 8–16 cm (p = 0.046), 24–32 cm and 32–40 cm (p = 0.004) layers but not in the 0–8 cm and 16–24 cm layers. When performing the paired T-test with 2-cm layers, only the 34–36 cm (p = 0.02), 36–38 cm, and 38–40 cm layers showed differences between macroaggregates and microaggregates.

3.3. C, N and P stoichiometric characteristics in wetland soil The soil nutrient ratio is commonly used to understand the biogeochemical cycles of soil and determine whether a wetland is N-limited or P-limited. In this study, the C/N ratio, C/P ratio and N/P ratio were analyzed for different aggregate sizes and soil depths (Fig. 6). Although the soil profile was segmented into 2-cm intervals in this study, there were 4 distinct regions for the C/N ratio and C/P ratio but no clear regions for the N/P ratio. From a soil depth perspective, the minimum values for both the C/N ratio and C/P ratio appeared in the range from the surface to a 10-cm depth in the soil profiles. In contrast, for the N/P ratio, the minimum value was found near the 14–16 cm layer. There were four distinct intervals for both the C/N ratio and C/P ratio; three intervals were located in similar ranges for the C/N ratio and C/P ratio (12–14 cm, 20–22 cm, and 28–30 cm). However, the fourth distinct interval was found in different positions for the C/N ratio and C/P ratio (34–36 cm and 38–40 cm, respectively). The mean values of the C/N ratio and C/P ratio were 24.36 and 478.20, respectively. For the N/P ratio, the maximum values appeared in the surface layer (2–4 cm) and bottom layer (38–40 cm). Both the C/N ratio and C/P ratio in microaggregates were lower than those in macroaggregates in

3.2. Radioisotope chronology The 210Pb and 137Cs radioactivities were used for chronology establishment and verification in the vertical direction (Fig. 4), and the CRS model was used to reconstruct the chronology for each layer in this study. Unsupported 210Pb activity generally showed a decreasing trend as the depth from the surface of the peat cores increased and reached approximately stable values at a 12–14 cm depth (a cumulative dry mass of 8.32 g cm−2) in the soil samples; according to the CRS model, the sediment might have taken nearly 250 years to accumulate. The 137 Cs profiles reflect the historical atmospheric fallout of this compound, and the activity of 137Cs had the highest value near the surface layer at 2–4 cm (3.77 g cm−2). The peaks of both the 210Pb and 137Cs profiles appeared in a similar place (2–4 cm), which meant that this layer might correspond to the year 1963. These results implied that the chronology reconstructed by the 210Pb analysis was acceptable and reliable. The sequestration rates of carbon, nitrogen and phosphorus are

CRS Chronology 2015 0-2

1943

1920

1900

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1963 ± 3

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0

1000

2000 210

210

3000

0

4000

Pb (Bq kg ) 137

Fig. 4. Unsupported Pb and Cs activity (Bq kg 210 Pb CRS model with the 137Cs time marker.

200

400 137

-1

−1

) profiles plotted against cumulative mass depth (g cm

873

−1

600

800

1000

1200

Cs (Bq kg ) -1

) and a comparison of the chronology estimated by the

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TOC (g m-2yr-1) 50

Depth (cm)

0 0-2 2-4 4-6 6-8 8-10 10-12 12-14 14-16 16-18 18-20 20-22 22-24 24-26 26-28 28-30 30-32 32-34 34-36 36-38 28-40

100

TN (g m-2yr-1) 150

200

250

0

2

4

6

8

TP (g m-2yr-1) 10

12

14

0

0.1

0.2

0.3

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* >0.25 <0.25

Fig. 5. Soil nutrient sequestration distribution in macroaggregates and microaggregates.

Fig. 6. Different soil nutrient ratios with differing aggregate depth and size.

the 0–8 cm layer, but a similar trend was not obvious for the N/P ratio.

size and between TP and aggregate size were greater than that between TOC and TN (Fig. 9). Group I was more sensitive to TOC and TN, while group II was more sensitive to TN and TP. Group I had a closer relationship with aggregates with 0.25 mm and 0.053 mm sizes than the other groups. Both positive and negative relationships between soil nutrient content, nutrient ratio and nutrient increment rate were found among all soil aggregate sizes (Fig. 9). Given that the TN content showed a positive relationship with the TP content, there existed a positive correlation between C/N and C/P. The sequestration rates of all nutrients had highly significant correlations with each other. The TOC content was closely related to all soil nutrient sequestration rates. The TP content was only related to the sequestration rate for sizes of < 0.053 mm. C/N and C/P were also closely related to the sequestration rates of soil nutrient elements (TOC, TN, and TP) in the 0.3-mm aggregates, and C/P also had a correlation with the 0.25 mm and < 0.053 mm sizes.

3.4. Ordination analysis and Pearson correlation analysis with soil aggregates and nutrient content Both PCA and RDA are commonly used to find possibly correlated variables, and soil depth and soil aggregate sizes were subjected to PCA and RDA analyses in this study (Figs. 7, 8). The PCA explained 26.33% of the variance in the first axis and 64.51% of the variance in the second axis, and microaggregates and macroaggregates dominated the first axis and second axis, respectively. All the layers could be divided into three groups according to their interactions. The distances between the points in group II were closer than those in the other groups (I and III). Compared to the other groups (II and III), group I was closer to the microaggregate vectors, indicating that group I had a closer relationship with microaggregates. The results showed there were four groups with internal relationships in the soil profile distribution (Fig. 8). This RDA model explained 83.7% of the total variance with axes 1 and 2, which explained 80.13% and 3.57% of the constrained variance, respectively. The members with a close relationship were interdependent: TP was related to axis 1, and TN was related to axis 2. The relationships between TN and aggregate

4. Discussion MWD and GWD, as two indicators of soil condition and land use policy, are frequently used to indicate the status of soil onsite. In this study, these indicators showed that there are similarities in structure 874

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Fig. 7. Ordination analysis with different aggregate sizes and depths.

microaggregates, especially in the upper parts of the core samples (Table S1 & S2). In the paired t-test to detect differences in TN and TP between macroaggregates and microaggregates, significant differences were observed when dividing samples by the 8 cm layer or 20 cm layer. The TN and TP content distributions show that the microaggregates had higher values than did the macroaggregates, which appears to be the result of tillage (Denef et al., 2001). Some studies have shown strong positive correlations between the concentrations of C, N and to a lesser extent P in both macroaggregates and microaggregates (Mbagwu and Piccolo, 1990; Srivastava et al., 2016). Macroaggregates have a higher rate of organic carbon accumulation but are less stable than microaggregates (Coleman et al., 2004). Moreover, human activities influence the balance between macroaggregates and microaggregates in soil (Six et al., 2000). Human activity also changes the contents of nitrogen and phosphorus in soil (Wang et al., 2015b). The comparison of sequestration rates revealed that the rate in the deep layers (20–40 cm) was higher than that in the upper layers (0–20 cm), and differences according to grain size were not obvious. However, macroaggregates had a slightly higher carbon sequestration rate than did microaggregates in the 22–34 cm layer. The comparisons of carbon sequestration rate showed that the fen in this study performed a sink function in this area (Table 2). A previous study showed that macroaggregates have a higher rate of organic carbon accumulation than do microaggregates (Coleman et al., 2004). The dynamics of soil nutrients depend not only on the enhancement of soil physical structure but also on the increment of organic matter input (Kou et al., 2012; Zhang et al., 2016). On the basis of stoichiometry, differences in particle size affect C/N, C/P and N/P ratios. Differences were only observed in the C/N and C/P ratios of the different aggregates, but the N/P ratios fluctuated slightly

between fen soils and other upland soils. The MWD and GWD results at the sampling points revealed obvious differences in the distribution of soil nutrients between macroaggregates and microaggregates. For the fen soils, the MWD values were small and the GMD values were large, with mean values of 0.53 mm and 0.88 mm, respectively. This finding is similar to other findings in natural soil and croplands (Álvaro-Fuentes et al., 2008; Wei et al., 2013); the MWD in fen soil had a similar range as that reported for silt soil or sandy soil, whereas the GWD values were similar to those of tillage soils (Table 1). According to the mechanism of soil aggregate formation in upland soil (Six and Paustian, 2014) and studies performed in restored cropland or forest (Table 1), the values of MWD and GWD for upland, cropland and forest soils can be expected to be lower than those in the present study (Castro Filho et al., 2002; Jiao et al., 2006; Shukla, 2013). The results of the present study indicate that macroaggregates account for a relatively greater proportion of the soil compositional structure than do microaggregates and that the soil status is relatively new. The MWD and GMD results indicated that macroaggregates constituted the greater proportion in this case; some studies have indicated that the carbon accumulation capability of macroaggregates is higher than that of microaggregates (Six et al., 2000; Six et al., 1998). Furthermore, under different land use strategies, the proportions of soil aggregates have been found to change (Denef et al., 2001; Wei et al., 2013). Long-term N addition might be the only way to promote aggregate stability (Chen et al., 2017; Kong et al., 2013; Sun et al., 2018). In addition, the dynamics of soil aggregates can influence the soil bulk density, soil nutrient content distribution and soil nutrient sequestration (Askari and Holden, 2014; Denef et al., 2001). The soil nutrient content distribution in the lower half of the samples (20–40 cm) was greater than that in the upper half (0–20 cm), and the macroaggregates contained a higher carbon content than did the 875

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Fig. 8. Redundancy analysis (RDA) of different soil nutrient ratios with different aggregate depths, showing the relationship between soil aggregate distribution (in solid triangles) and soil nutrient content (solid lines) and between soil profile distribution (solid dots) and soil nutrient content. F1 F2 F3 F1 1.00 *** *** *** F2 1.00 1.00 F3 F4

1

F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 *** ** *** ** *** ** 1.00 *** F5 1.00 * * *** * F6 1.00 1.00 ** F7 * * * * F8 1.00 1.00 ** ** ** * ** F9 1.00 ** F10 ** *** F11 1.00 *** * F12 1.00 *** *** *** F13 1.00 *** * F14 1.00 *** F15 1.00 F16

F1 : TOC <0.053 F2 : TOC 0.063 F3 : TOC 0.25 F4 : TOC 0.3 F5 : TOC 1 F6 : TN <0.053 0 F7 : TN 0.063 F8 : TN 0.25 F9 : TN 0.3 F10 : TN 1 F11 : TP <0.053 F12 : TP 0.063 F13 : TP 0.25 F14 : TP 0.3 -1 F15 : TP 1

F16 : C/N < 0.053 F17 : C/N 0.063 F18 : C/N 0.25 F19 : C/N 0.3 F20 : C/N 1 F21 : C/P < 0.053 F22 : C/P 0.063 F23 : C/P 0.25 F24 : C/P 0.3 F25 : C/P 1 F26 : N/P < 0.053 F27 : N/P 0.063 F28 : N/P 0.25 F29 : N/P 0.3 F30 : N/P 1

F16 F17 F18 F19 F20 F21 F22 F23 F24 ** * * *** * ** *** * ** *** *** *** ** *** * ** * ** * *** *** ** ** * ** *** * * * ** ** *** * * * *** * ** ** * *** ** * ** ** * * * * *** *** * * * * ** *** ** *** * 1.00 * ** * *** *** ** ** * ** ** * F17 1.00 * * ** ** ** F18 1.00 * ** *** * *** F19 1.00 * < 0.053 F20 1.00 1.00 *** ** *** F21 0.063 F22 1.00 *** *** F23 1.00 *** 0.25 F24 1.00 0.3 F25

F31 : TOCseq F32 : TOCseq F33 : TOCseq F34 : TOCseq F35 : TOCseq 1 F36 : TNseq < 0.053 F37 : TNseq 0.063 F38 : TNseq 0.25 F39 : TNseq 0.3 F40 : TNseq 1 F41 : TPseq < 0.053 F42 : TPseq 0.063 F43 : TPseq 0.25 F44 : TPseq 0.3 F45 : TPseq 1

F25 F26 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 F37 F38 *** *** *** *** *** *** *** *** * ** ** ** ** ** ** * ** * *** *** *** *** *** *** *** *** ** ** ** ** ** ** * ** * ** ** ** ** ** * * * *** *** ** * *** * *** * * * *** * * * * * ** * ** * * *** ** ** *** ** * * * ** * *** ** * * * * * * * ** ** ** ** ** ** ** ** ** ** ** * ** * * * * * * 1.00 F26 1.00 F27 1.00 * F28 1.00 * ** ** ** ** ** ** ** ** F29 1.00 F30 1.00 *** *** *** *** *** *** *** F31 1.00 1.00 *** *** *** *** *** *** F32 F33 1.00 *** *** *** *** *** F34 1.00 *** *** *** *** F35 1.00 *** *** *** F36 1.00 *** *** F37 1.00 *** F38 1.00 F39

F39 *** * *** * *

F40 *** ** *** ** *

F41 *** ** *** ** *

F42 *** ** *** ** *

F43 *** ** *** ** *

F44 *** ** *** ** *

F45 *** ** *** ** *

* *

* * *

* **

* **

**

**

* **

** *

* ** *

* ** *

* ** *

* *

* **

* * ** *

** ** * * * * * *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** 1.00 *** *** *** *** *** *** F40 1.00 *** *** *** *** *** F41 1.00 *** *** *** *** F42 1.00 *** *** *** F43 1.00 *** *** F44 1.00 *** F45 1.00

Fig. 9. Pearson correlations between soil nutrient content, nutrient ratio and soil nutrient sequestration rate in different aggregate sizes (n = 20). TOC: TOC content; TN: TN content; TP: TP content; C/N: C/N ratio; C/P: C/P ratio; N/P: N/P ratio; TOCcon: TOC sequestration rate; TNcon: TN sequestration rate; TPcon: TP sequestration rate. *: significant at p < 0.05; **: significant at p < 0.01; ***: significant at p < 0.001.

in both macroaggregates and microaggregates. Nitrogen mineralization in soil has been proven to be positively related to the nitrogen content of unprotected carbon and negatively related to the C/N ratio of unprotected carbon (Six et al., 2002). Studies have found a negative correlation between soil C/N and the soil decomposition rate. In this study, in the surface layer of the soil (0–10 cm), both macroaggregates and microaggregates decomposed rapidly, while in the deeper layers,

there were four more obvious low-decomposition areas (Wang and Yu, 2008). Furthermore, three of these areas coincided with the C/P ratio that characterizes the phosphorus conversion intensity index. The mean value of C/N was 24.36, which is similar to previous results (10–35) (Bedford et al., 1999; Meng et al., 2015). The C/P ratio is an indicator of the availability of phosphorus (Wang and Yu, 2008). The C/P ratio in this fen ranged from 278.85 to 655.69 in three clear active areas and 876

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Table 1 MWD and GWD in different soil types. Region

Soil type

MWD (mm)

GWD (mm)

Reference

NE China SW China SE China Eastern India Ohio, USA Mid China East China

Peat soil Orthents Latosolic red soil Silt loam Hoytville series Chromic Cambisol Sandy loam

0.42–0.61 0.67–1.27 1.57–2.42 0.54–1.11 0.66–1.61 0.50–0.90 0.50–1.18

0.82–0.90 0.26–0.54 0.94–1.59 0.46–0.70 1.03–1.77 0.30–0.55 0.25–0.65

This study (Wang et al., 2015c) (Wang et al., 2015d) (Padbhushan et al., 2016) (Baker et al., 2004) (Chen et al., 2009) (Shu et al., 2015)

Table 2 Carbon sequestration rates in different wetlands. Region

Wetland type

Carbon sequestration rate (gC m−2 yr−1)

Reference

NE China NE China NE China Ohio, USA Ohio, USA Georgia, USA NE Costa Rica North Finland North America Ohio, USA California, USA

Fen Carex marsh Freshwater marsh Reed-bulrush Marsh Cattail marsh Tidal forest Rainforest swamp Boreal peatlands Peatland Constructed wetland Agricultural wetland

8.05–198.96 83.9–225.7 61.60–318.48 105 210 49 ± 6 222 ± 13 15–26 29 219 ± 15 0.02

This study (Bao et al., 2010) (Zhang et al., 2016) (Bernal and Mitsch, 2012) (Bernal and Mitsch, 2012) (Craft, 2012) (Bernal and Mitsch, 2013a) (Turunen et al., 2002) (Eville, 1991) (Bernal and Mitsch, 2013b) (Maynard et al., 2011)

Appendix A. Supplementary data

was related to aggregate size. Some microaggregates have a marked relation with carbon accumulation (Coan and Shoichet, 2008; Pathak et al., 2017). The results of the RDA and Pearson correlation analysis also indicated that a close positive correlation exists between carbon and microaggregates. Although macroaggregates have a higher carbon sequestration capacity than do microaggregates, the correlation of microaggregates with carbon in soil is higher than that of macroaggregates with soil carbon. This size-dependent relationship implies that microaggregates are important in characterizing the stability of soil carbon. The soil carbon anchoring effect in macroaggregates is stronger than that in small aggregates, but the stability of small aggregates in soil is more important for carbon stocks (Katie and Virginie, 2010; Liu et al., 2015). Moreover, PCA and RDA analyses revealed the relationship between soil aggregate size and carbon was higher than the corresponding relationships between soil aggregate size and other nutrients.

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5. Conclusion This study shows that in the examined fen, there exists a soil aggregate structure that plays a key role in soil nutrient cycling (C, N and P) and is similar to that found in upland soil. Although macroaggregates have a strong relation with carbon sequestration, stable soil microaggregates are important for C, N and P conservation in this fen. Furthermore, the characteristic stoichiometric balance is related to aggregate size. Further studies are needed to increase the stability of soil carbon pools in wetlands during wetland restoration. Acknowledgements We are grateful to Zhang Nannan from Harbin Normal University for the radiometric analysis of samples. This work was supported by the National Natural Science Foundation of China (41701096, 41801084), and the National Key Research and Development Program of China (2016YFC0500602), the Program for Introducing Talents to Universities (B16011), the Program for Innovative Research Team in University (IRT-16R11). 877

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