Background

The loss of phosphorus (P) from agricultural soils has been identified as one of the main causes of eutrophication of lakes in the lower reaches of the Yangtze River in southern China [1]. Statistics have shown that major lakes and reservoirs in this area were eutrophic and mesotrophic [2,3,4], and the Yangtze River Delta region accounted for 17% of the 10 Tg annual increase in soil P around the world [2]. In soil, colloidal P (Pcoll) is the P fraction bound to colloids [5]. Colloidal particles are highly mobile and are effective adsorbents of organic and inorganic contaminants and nutrient elements, such as P, owing to the high specific surface area and charge density [6, 7]. Colloid-facilitated P transport is an important pathway for the migration of P into water bodies [5, 8, 9]. One study has reported that more than 75% of P in cultivated soil solution is combined with fine particles smaller than 240 nm [10]; similarly, 40–58% of molybdate-reactive P, with a size less than 450 nm in the water extract of grassland soil, demonstrates fine-grained P with a size of 25–450 nm [9]. Other studies have suggested that Pcoll reached up to 50% of total P (TP) in surface runoff, rivers, and lakes [11], which may lead to environmental risks.

Soil aggregate stability plays a key role in controlling the erosion processes and the loss of soil nutrients [12,13,14]. Water-dispersible colloids in the soil adhere to soil aggregates, forming a stable system [15]. Colloids either can bind to soil aggregates, or be physically strained from water flowing through pores between aggregates [16, 17]. Some scholars determined the colloid content in 1–2 mm aggregates in 39 soils and revealed a significant positive correlation between the water-dispersible colloid content and clay content in soil aggregates [18]. Furthermore, they reported that water-dispersible colloid content was a function of total organic C and total clay. Other scholars modeled the release characteristics of colloids from soil aggregates, the attachment and detachment processes at the air–water interface, and flocculation and straining from interstitial water [19]. The release of colloids from aggregates may result in the disintegration of aggregates [20]. However, soil aggregation mainly depends on the availability of active mineral surfaces and the dispersion/flocculation behaviors of the colloidal components [21]. Meanwhile, the degree of clay colloid dispersion can be reduced by increasing the aggregate stability [18, 22, 23]. Therefore, the stability of soil aggregates directly affects the migration of soil colloids.

The retention of P in soil aggregates depends on the aggregate sizes and chemical properties [24, 25]. Notably, P has a relatively closed cycle, with most of the mineralized and dissolved P from microaggregates adsorbed onto unaggregated clay-sized particles (< 53 μm) or utilized by plants [26]. Reportedly, some studies have shown that the soil aggregate stability and size affect the soil P distribution [27,28,29]. Higher percentages of both water-extractable and Mehlich III-extractable P were observed in both the 0.50–0.25 and 0.25–0.125 mm aggregate fractions [30]. In contrast, reports have suggested that TP is the highest in small soil aggregates [31], or the TP content is uniform in soil aggregates of all sizes, whereas available P is higher in small soil aggregates [32]. Soil aggregation could reduce the loss of organic P in aggregates and increase the adsorption of inorganic P by silt and clay particles [26]. Meanwhile, the P forms in soil aggregates may vary with different particle sizes and land-use types [24, 33]. For example, a study has indicated that aluminum oxide bond P (Al–P) is mainly dominated by soil aggregates < 1 mm; those of 2–8 mm were mainly iron oxide bond P (Fe–P) and calcium oxide bond P (Ca–P) [34]. Other investigators have claimed that the labile P in macroaggregates was higher under native land-use than other land uses, further confirming that soils under native use contained more Ca-bound P in macroaggregates than the disturbed soils [35]. These studies provide the first basis for the better understanding the relationship between soil aggregates and P.

To date, information on the Pcoll content and its loss potential from aggregates remains limited. The impact of the aggregation process on the Pcoll content in soils remains unclear. Moreover, the composition and structure of soil aggregates vary under different land-use management [36, 37]. There are fewer large-sized aggregates present in rice soil than dryland due to long-term flooding and anaerobic conditions that cause the macroaggregates to be dispersed [36, 38]. In addition, alternation between dry and wet conditions generally destroys macroaggregates and enhances the decomposition of organic carbon in paddy soils [39]. Therefore, we suspected that the content of Pcoll in the macroaggregates of paddy soils was less than dryland soils, mainly existing in microaggregates and small particles, with a higher loss potential.

This study mainly aimed to understand the effect of soil aggregate stability on soil Pcoll content and its loss potential, and to assess the core environmental factors affecting Pcoll in soil aggregates. Hence, we collected soil samples from 15 sites and 6 land-use types in the Yangtze River Delta region, Zhejiang Province for aggregates and Pcoll analysis. Firstly, we isolated the different-sized aggregates in the soil samples. Secondly, we determined the Pcoll, total carbon (TC), TP, total nitrogen (TN), Al, Fe, and Ca content in each aggregate size fractions. We hypothesized that (1) larger sized aggregates have higher TP and Pcoll content; (2) aggregates with a higher TC content have lower loss potential of Pcoll, and (3) land-use management with single rice has a higher loss potential of Pcoll.

Materials and methods

Soil sampling and preparation

In total, soils with different land-use types (Fig. 1) were collected from 15 sites, which were almost evenly distributed in the Zhejiang Province (an area of 1,055,000 km2). Information on specific sampling points is presented in Table 1. The 15 sampling points covered six land-use types including orchards, single cropping rice, double-cropping rice, rice–rape rotation, rice–wheat rotation, and vegetables, generally established in the past 5 years.

Fig. 1
figure 1

Location of sampling sites. Location sites of S1–S15 correspond to Kaihua, Kecheng, Longquan, Zhuji, Lingxi, Changshan, Qiandaohu, Liandu, Tonglu, Zhoushan, Wuxing, Tiantai, Shengzhou, Mazhan, and Luqiao in Zhejiang Province, China, respectively

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Table 1 Basic chemical and physical properties of soil, and characterization of sites located in Zhejiang Province, China
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Soil samples of 0–20 cm were collected from typical fields (long-term farmland with conventional fertilization by local farmers) in May 2018 during the second season of rotation systems and in other land-use types. Two samples, with three replicates, were obtained at intervals of 1000 m at each site with the same land-use type. Next, the replicates were brought back to the laboratory and mixed. Then, the mixed soil samples from each site were divided into four equal parts by the diagonal quartering method and maintained for a follow-up test. All samples were air-dried and separated into two parts: one was finely milled and sieved through a 2-mm mesh to determine basic physical and chemical properties, and the other was carefully broken into small pieces manually and passed through an 8-mm sieve for aggregate separation and Pcoll determination.

Aggregate separation and determination

Aggregate size distribution was determined for each soil sample using a modified wet sieving method [40]. Briefly, 50 g of unground soil, passed through an 8-mm sieve, was carefully placed above a nest of three sieves (2 mm, 0.26 mm, and 0.053 mm). Then, the sieves were submerged for 20 min in 2.5 L deionized water at room temperature and oscillated 300 times for 10 min with a 30-mm amplitude to separate aggregate fractions. Thus, four aggregate fractions were obtained on each sieve: large macroaggregates (2–8 mm), small macroaggregates (0.26–2 mm), microaggregates (0.053–0.26 mm), and (silt + clay)-sized particles (< 0.053 mm) [41]. Aggregates of each size were carefully removed from the sieve and placed into a beaker. The water used for wet sieving was left to rest for 48 h, silt and clay particles were collected, and the supernatant was used to determine total dissolved P (TDP), truly soluble P (TSP), and Pcoll content. All aggregates were oven-dried at 65 °C for 48 h, weighed, and placed in a zip lock bag. To obtain water-stable aggregates, the sediment concentration was subtracted from that obtained by wet sieving as sand was not considered a component of water-dispersible aggregates [40]. The sand content was determined by the following process: 5 g of the dry aggregates obtained above were weighed, dispersed into 30 mL 5 g L−1 hexametaphosphate solution, placed into an ultrasonic cleaner, and dispersed for 30 min. The suspension was then poured through a nest of sieves. The residue left on the 0.053-mm sieve represented the sand content of each sized aggregate. After collection, sand was dried at 65 °C and weighed.

Soil pH was determined with a glass electrode pH meter (PHS-3C, Shanghai) using a soil-to-water ratio of 1:5. Soil cation exchange capacity was measured with ammonium acetate (12.5 mL 1 M NH4OAc, 2.5 g soil) [42]. Soil and aggregate-associated TP was determined by H2SO4–HClO4 digestion and evaluated using the molybdenum-blue colorimetric method [43]. Soil particle size distribution was determined by the hydrometric method according to an international soil texture classification standard. Soil- and aggregate-associated TC and TN were determined using an elemental analyzer (dry combustion with Vario MAX CNS, Elementar, Germany). Soil- and aggregate-associated Al, Fe, and Ca were determined by inductively coupled plasma mass spectrometry (ICP-MS) after digestion with 5 mL HNO3 (16 M), 1 mL HClO4 (12.4 M), and 1 mL HF (23 M) for 12 h. All reagents were acquired from Sinopharm Chemical Reagent Co., Ltd.

Colloidal P was determined as described by Ilg [44]. Briefly, 10 g of unground soil was placed into a 250-mL flask, 80 mL deionized water was added. The sample was shaken at 160 rpm and 25 °C for 24 h. The supernatant was pre-centrifuged at 3000g for 10 min to remove coarse particles. After pre-centrifugation, the supernatant was filtered with a 1-μm microporous membrane, 5 mL of the primary filtrate was discarded, and the total filtrate was collected (sample I). This suspension included the colloidal and dissolved components. The filtrate was ultracentrifuged at 300,000g for 2 h to remove colloids (Optima TL, Beckman, USA; Sample II), and the residue at the bottom of the ultracentrifuge tube demonstrated the water-dispersible colloids. The TDP in Sample I and TSP in Sample II, in the solution, were determined after digestion with acidic potassium persulfate. The concentration of Pcoll indicated the difference between TDP in Sample I and TSP in Sample II. Previous studies have shown that soil P through leaching and surface runoff was usually in the soluble form, that can pass through the 0.45–1 μm filter [45, 46]; therefore, in the present study, TDP including Pcoll and TSP in aggregates was defined as the potential loss P, and the Pcoll in TDP was defined as Pcoll loss potential. TDP in the supernatant after 10 min wet sieving was considered as easy loss P.

Calculation of water-stable aggregate (WSA) size fractions

The proportion of WSA in each size fraction was obtained from Eqs. (1) and (2), as described by Alvaro-Fuentes [47]:

$${\text{WSA}}_{i} = \frac{{{\text{DSA}}_{i} - {\text{Sand}}_{i} }}{{{\text{Total}}_{\text{Soil}} - \mathop \sum \nolimits_{i = 1}^{n} {\text{Sand}}_{i} }} ,$$
(1)
$$\left( {{\text{silt}} + {\text{clay}}} \right) {\text{sized}}\;{\text{fraction}} = 1 - \mathop \sum \limits_{i = 1}^{n} {\text{WSA}}_{i} ,$$
(2)

where i is the ith size fraction (2–8, 0.25–2, and 0.053–0.25 mm); dry soil aggregate (DSAi) is the oven-dried mass of total, non-dispersed aggregates collected on each sieve; sand is the oven-dried mass of sand collected after dispersal in the hexametaphosphate solution on the 0.053 mm sieve; TotalSoil is the oven-dried mass of soil (50 g) for aggregate separation.

Calculation of mean weight diameter (MWD) and geometric mean diameter (GMD)

The MWD and GMD of the aggregates were obtained by Eqs. (3) and (4) [48]:

$${\text{MWD}} = \mathop \sum \limits_{i = 1}^{n} d_{i} \times {\text{WSA}}_{i} ,$$
(3)
$${\text{GMD}} = {\text{EXP}}\left[ {\frac{{\mathop \sum \nolimits_{i = 1}^{n} {\text{WSA}}_{i} \log d_{i} }}{{\mathop \sum \nolimits_{i = 1}^{n} {\text{WSA}}_{i} }}} \right] ,$$
(4)

where i is the ith size fraction (2–8, 0.26–2, 0.053–0.26, and < 0.053 mm) and d is the mean diameter of each size (0.053–2 mm). WSAi include 2–8, 0.26–2, 0.053–0.25, and < 0.053 mm WSA and (silt + clay)-sized fractions.

Contribution of aggregate-associated Pcoll to TDP

The contribution rate (CR) was used to explore the impact of aggregate sizes on the Pcoll loss potential, calculated using Eq. (5):

$${\text{CR}}_{i} = \frac{{{\text{Agg}}\_{\text{CP}} \times {\text{WSA}}_{i} }}{{\mathop \sum \nolimits_{i = 1}^{n} {\text{TDP}}}} ,$$
(5)

where Agg_CP is the concentration of aggregate-associated Pcoll (mg kg−1), TDP is the concentration of total dissolved P (mg kg−1), and i is the ith size fraction (2–8, 0.26–2, 0.053–0.26, and < 0.053 mm).

Statistical analysis

Microsoft Excel 2016 and Origin 8.0 were used for data processing and cartography. Data were statistically analyzed using SPSS Statistics 22.0 (SPSS Inc. Chicago, USA) software. One-way ANOVA was performed using two samples from each site to examine differences of different variables as presented in Additional file 1: Tables S1, S2, and Figures S1, S2 and Table 3. Pearson correlation analysis was used to identify the relationship between aggregate-associated Pcoll and other soil parameters. Stepwise linear regression was performed to evaluate the relationships between P indicators (content and loss potential of Pcoll) and soil variables (pH, TP, TC, TN, C/N, Fe, Al, Ca, MWD, and GMD).

Results

Soil and aggregate characteristics

Within the 15 soils collected, ten were acidic soils, two were neutral soils, and three were alkaline soils (Table 1). There were six land-use types: orchard, single cropping rice, rice–rape rotation, vegetable, double-cropping rice, and rice–wheat rotation. The TC of the soils ranged from 3.32 to 20.19 g kg−1; TN ranged between 0.53 and 2.17 g kg−1. TP varied from 0.23 to 1.64 g kg−1. Soil pH values ranged between 3.95 and 7.83 (Table 1).

The DSA and WSA of larger macroaggregates (2–8 mm) generally increased with increasing pH values (Additional file 1: Figures S1 and S2, Table S2). Moreover, fractions of DSA and WSA (2–8 mm) in acidic soils ranged from 18.7 to 33.4% and from 10.5 to 47.1%, respectively. Conversely, fractions of DSA and WSA in alkaline soils ranged from 39.7 to 56.1% and from 38.1 to 55.6%, respectively. In contrast, size fractions of < 0.053 mm particles gradually decreased with increasing soil pH values, while the average contents of < 0.053 mm particles in acidic soils were 18.8 and 17.8%, compared with only 11.2% and 14.7% in alkaline soils, respectively.

The MWDs of acidic soils (pH < 5.5) were significantly smaller than those of alkaline soils (P < 0.05). The average MWD of acidic soils was 0.78 mm (Additional file 1: Figure S2), while that of neutral and alkaline soils was 1.36 mm. However, little difference in GMDs was observed between acidic (0.85 mm), and alkaline soils (0.91 mm).

Total and colloidal phosphorus content

Generally, the 0.26–2 mm aggregate fraction demonstrated the highest TP content, which accounted for 29.6% of the soil TP (Fig. 2a), and soil aggregates of 2–8 mm demonstrated the second-highest TP content. The TP content of (silt + clay)-sized particles was significantly lower than that of other fractions (P < 0.05, Additional file 1: Table S1), which only accounted for 19.7% of the soil TP (Fig. 2a). Moreover, TDP, TSP, and Pcoll contents were related to soil pH, and the highest TDP content was observed in 0.26–2 mm aggregates in most acidic soils and in (silt + clay)-sized particles in most alkaline soils (P < 0.05, Additional file 1: Table S1). In all soils, no significant difference was observed in the Pcoll fractions between different aggregate sizes (P > 0.05; Fig. 2b). However, the aggregate content associated with Pcoll was the highest in the 0.26–2 mm aggregates, and the lowest in the (silt + clay)-sized particles in acidic soils; in neutral and alkaline soils, (silt + clay)-sized particles demonstrated the highest TDP and Pcoll contents, followed by the 0.26–2 mm aggregates (Table 3).

Fig. 2
figure 2

Soil total P fraction (a), colloidal P (Pcoll) fraction (b) and loss potential (c) of three sized aggregates (2–8 mm, 0.26–2 mm, 0.053–0.26 mm) and (silt + clay) particles (< 0.053 mm) in 15 soils

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Loss potential of colloidal phosphorus

After wet sieving, about 0.16–1.87% of the soil TP was lost in the supernatant as TDP, and Pcoll accounted for 8.5–84.1% of the TDP (Table 2). The proportion of the easy loss P content in the various soils differed due to variations in soil physicochemical properties.

Table 2 The total dissolved P (TDP), and truly soluble P (TSP), colloidal P, colloidal P/TDP, and ratio of TDP to soil total P (TP) in the supernatant of different soils after wet sieving
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In general, the Pcoll loss potential gradually decreased as the size of the soil aggregates increased (Fig. 2c). The Pcoll loss potential was the lowest in 2–8 mm and 0.26–2 mm aggregates, with Pcoll accounting for 52.6% and 60.6% of TDP, respectively. However, the Pcoll loss potential of (silt + clay)-sized particles was the highest, with Pcoll accounting for 75.3% of TDP (Fig. 2a). The CR value of (silt + clay)-sized particles was mostly larger than that of the other aggregate sizes, except for S7, S11 and S15; the CR of larger macroaggregates was lowest in most soils (Table 3).

Table 3 The colloidal P content (mg kg−1) of different-sized soil aggregates and the contribution rate of aggregates to colloidal P (CR) in the total 15 soils
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Considering different land-use types, the Pcoll content in the rice–dry land rotation and vegetable (VE) soils was significantly higher than that in paddy and orchard soils, regardless of different aggregate sizes (Fig. 3a). Higher Pcoll content also was found in macroaggregates (> 0.26 mm), except for the orchard soil (Fig. 3a). The colloidal P content in macro- and microaggregates in the paddy soils (including single cropping rice, and double-cropping rice) accounted for a relatively lower proportion of TDP (P < 0.05) than that in other land-use types (Fig. 3b). Overall, it accounted for only 39.3, 44.1, and 40.2% for the 2–8 mm, 0.26–2, and 0.053–0.26 mm aggregates in rice fields, respectively. Colloidal P in (silt + clay)-sized particles (< 0.053 mm) in paddy soils accounted for a TDP proportion as high as 83.0%, significantly higher than that observed in the orchard and rice–dryland rotation systems (Fig. 3b). This indicated that the loss potential of Pcoll was dominated by fine-grained and (silt + clay)-sized particles in paddy soils. However, the Pcoll carried by all sized aggregates in dryland and rice–dryland rotation systems (orchard, rice–rape rotation, vegetable, and rice–wheat rotation) exceeded 50% of the TDP.

Fig. 3
figure 3

Soil colloidal phosphorus content (a) and loss potential (b) of three sized aggregates (2–8 mm, 0.26–2 mm, 0.053–0.26 mm) and (silt + clay) particles (< 0.053 mm) under different land-use types. OR orchard soils (n = 3), RICE rice fields including single- and double-cropping soils (n = 6), RDR rice and dryland rotation including rice–rape rotation and rice–wheat rotation soils (n = 3), VE vegetable soils (n = 3); capital letters indicated significant difference among different sizes of aggregate at P < 0.05 level. Lowercase indicated significant difference of the same size of aggregate among land-use types at P < 0.05 level

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Factors affecting colloidal P content and loss potential

Correlation analysis revealed no significant correlations between Pcoll and TC or TN (Table 4). The Pcoll content was significantly and positively correlated with TP in all aggregate sizes except for (silt + clay)-sized particles (Fig. 4a). Soil pH positively correlated with the aggregate-associated Pcoll content, but only significantly correlated with the Pcoll content of (silt + clay)-sized particles (P < 0.01) (Fig. 4b). Additionally, Al and Fe significantly and positively correlated with Pcoll in total sizes of soil aggregate (P < 0.05) (Fig. 4c, d). However, only Pcoll in 2–8 mm aggregate significantly and positively correlated with Al and Fe (P < 0.05). Moreover, Pcoll was negatively correlated with C/P (Fig. 4e) and positively correlated with C/N (Fig. 4f). The forward results of the stepwise regression demonstrated that Pcoll can be described by Al, TP, TN and MWD as follows: \({\text{colloidal}}\;{\text{P}} = - \;8.017 + 0.087{\text{Al}} + 10.598{\text{TP}} - 2.257{\text{pH}} - 5.977{\text{MWD}}\), (R2 = 0.605, P < 0.001, Table 4).

Table 4 Results from correlation analyses and stepwise linear regressions of colloidal P and colloidal P/TDP in different-sized aggregates with soil aggregate-associated mean weight diameter (MWD), geometric mean diameter (GMD), pH, total carbon (TC), total nitrogen (TN), C/P, C/N, Al, Fe, and Ca
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Fig. 4
figure 4

Linear relationship between colloidal phosphorus (Pcoll) content and soil total phosphorus (TP) (a), pH (b), Al (c), Fe (d), C/P (e), and C/N (f) of three sized aggregates (2–8 mm, 0.26–2 mm, 0.053–0.26 mm) and (silt+clay) particles (<0.053 mm). Total=total soil aggregate sizes

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The Pcoll loss potential (Pcoll in TDP) in total size of the soil aggregate negatively correlated with the TC, TN, pH, Ca, C/P, C/N ratios of aggregates (Table 4, P < 0.05). Considering different sizes, TC and TN significantly and negatively correlated with Pcoll loss potential in 0.26- to 2-mm-sized aggregates. Except for (silt + clay)-sized particles, Pcoll loss potential was significantly and positively correlated with Al (P < 0.05). Pcoll loss potential in 2- to 8-mm-sized aggregates was significantly and positively correlated with Fe (P < 0.05). However, Pcoll loss potential in 0.053- to 2-mm-sized aggregates negatively correlated with Ca (P < 0.05). The results of the stepwise regression demonstrated that the Pcoll loss potential can be described by TC, Fe, MWD, and GMD as follows: \({\text{colloidal}}\;{\text{P}}/{\text{TDP}} = 0.478 - 0.028{\text{TC}} + 0.015{\text{Fe}} + 0.413{\text{MWD}} - 0.363{\text{GMD}}\), (R2 = 0.539, P < 0.001, Table 4).

Discussion

Total P in aggregates

In our study, we observed that the TP content was the highest in macroaggregates of the 15 soils, while the TP content in the (silt + clay) particles was the lowest. These results indicated that soil P was mainly carried by larger aggregates, which confirmed our hypothesis and were in line with those previously reported [28, 49, 50]. For examples, some scholars have observed that P tends to concentrate in large WSAs in long-term fertilization experiments in a reddish paddy soil [49], and others claim that aggregate-associated total organic C, TN, and TP are preferentially enriched in large WSAs (4.76–2.0 mm) [50], reporting that the TP proportion increased with increasing aggregate size for native lands [35]. Higher P levels may be associated with higher levels of TC and TN in large aggregates [50, 51]. Macroaggregates ([(Cl–P–OM)x]y) are usually formed by organic matter, clay (Cl) and multivalent ions of P, and other substances [52, 53]. Organic matter (and associated P) is protected within stable aggregates against microbial degradation [54]. Moreover, it has been shown that the organic P forms that accumulate in soils are less available to enzymatic hydrolysis when bound to mineral surfaces [55, 56]. On the other hand, the aggregation promoted by organic matter counteracts the dispersion of the small mineral particles (mostly Fe and Al-(hydr) oxides where P is retained [57, 58]. Furthermore, this was validated by the positive correlation between aggregate-associated TP and TC, and the significant correlation between aggregate-associated TP and TN observed in this study (Additional file 1: Tables S2).

Colloidal P content in aggregates

In this study, although no significant difference was observed in the Pcoll fractions between different aggregate sizes in all soils, we observed that TDP, TSP, and Pcoll contents in soil aggregates were significantly related to soil pH. The TDP and Pcoll contents were high in macroaggregates of acidic soils, and low in microaggregates and silt + clay particles; however, contrasting results were observed in alkaline soil aggregates. This was not consistent with our hypothesis which could be attributed to soil clays being mostly negatively charged, but the aggregation of other soil colloids strongly depend on their surface charge, being favored when approaching their point of zero charge [59]. Under acidic conditions, the protonation of Fe-, Al-oxides, and organic matter in colloids results in positive charges, leading to their association with soil particles. However, the dissociation of Fe- and Al-hydroxyl and humic functional groups (R–COOH, R–CH2–OH, R–OH) under alkaline conditions results in a negative charge in the colloid [59], which promotes the release of fine particulate P and colloidal substances, thus increasing the TDP and Pcoll contents in small-sized aggregates and particles. On the other hand, the lower pH enhanced the adsorption of organic matter on the fine particles and masked the inorganic mineralogy, resulting in fewer chances of P carried by Fe- and Al-oxides [60,61,62]. In addition, we observed that the Pcoll content in soil aggregates positively correlated with the aggregate-associated Al and Fe content. This was attributed to the greater contents of Fe and Al in acidic soil than in alkaline soil, and that the presence of Al and Fe oxides may have enhanced the adsorption of P and stabilization of soil aggregates [15, 31, 63]. Al and Fe oxides have been recognized as important carriers of Pcoll [64,65,66,67].

Loss potential of colloidal P in aggregates

We observed that the CR value of (silt + clay)-sized particles was larger than that of aggregates of other sizes, while the CR of large macroaggregates was the lowest in most soils, indicating that the (silt + clay)-sized particles contribute more to the Pcoll loss potential, while macroaggregates immobilized soil Pcoll. Colloidal P is highly bound to Fe and Al on the surface of macroaggregates [15, 68], enabling the formation of a stable composite structure that can resist the shear force of pore flow [64, 65]. Similarly, soil macroaggregates can increase the adsorption of Pcoll on the surface and reduce its mobility [26]. The ratio of Pcoll to TDP reflects the release potential of Pcoll in soil aggregates to soil solution. The high value indicates the high loss potential of Pcoll. We observed a negative correlation between the TC and TN content and Pcoll/TDP in aggregates, indicating that higher the TC and TN content, the less likely release of Pcoll from the soil aggregates, which was further confirmed by the negative correlation between TC and Pcoll/TDP in the regression model (Table 4). Studies had shown that C and N are important carriers of Pcoll (most organics act as organic colloidal complexes) [28, 69, 70], and the organic matter could stabilize Al/Fe colloids [71]. Therefore, increasing the carbon content in soil aggregates could be an important strategy to reduce the migration of Pcoll in the soil. The ratio of Pcoll to TDP for all macroaggregates in paddy soils was lower, which may be related to the long-term flooding of rice fields. Notably, the lower loss potential of Pcoll in macroaggregates of paddy soils does not imply that it is less likely to be lost to water bodies. However, this could indicate that Pcoll has been lost into water and discharged into the water body through the channels during rice seasons, particularly when under long-term flooding [72]. Moreover, flooding resulted in an anaerobic state in soil aggregates, and Fe bound to colloids and aggregates was reduced, resulting in excessive release and loss of Pcoll [15]. We observed that aggregates of all sizes in dryland and rice–dryland rotation systems carried higher Pcoll loss potential. Conversely, in paddy soils, the loss potential of Pcoll in macro- and microaggregates was lower than 50% of TDP. However, Pcoll in (silt + clay)-sized particles (< 0.053 mm) in paddy soils accounted for a TDP proportion as high as 83%, significantly higher than that observed in orchard and rice–dryland rotation systems. Therefore, we believe that Pcoll in paddy soil is mainly carried by small silt and clay particles, which may indicate that the loss of Pcoll is markedly severe in paddy soils.

Conclusions

This study discussed the relationship between Pcoll and soil aggregates, providing a potential solution for soil P loss in agricultural systems. The soil Pcoll content was affected by multiple factors including soil Al, Fe, and TP, and the distribution of Pcoll in aggregates can be regulated by altering aggregate sizes and soil pH. As small macroaggregates contributed the most to the immobilization of Pcoll, it is important to increase this fraction in the soil. To this end, soil organic matter must be improved owing to its crucial role in promoting soil aggregation and reducing the risk of Pcoll loss potential. Paddy soils, due to their high Pcoll/TDP ratio, are particularly at risk of high Pcoll loss through smaller particles and worthy of further attention.