Introduction
The global surface temperature has risen by about 1°C than the preindustrial level and is expected to increase by 1.5°C from 2030 to 2052 (IPCC, 2022). Global warming can profoundly impact carbon (C) cycle of terrestrial ecosystems (Crowther et al., Reference Crowther, Todd-Brown, Rowe, Wieder, Carey, Machmuller, Snoek, Fang, Zhou, Allison, Blair, Bridgham, Burton, Carrillo, Reich, Clark, Classen, Dijkstra, Elberling, Emmett, Estiarte, Frey, Guo, Harte, Jiang, Johnson, Kröel-Dulay, Larsen, Laudon, Lavallee, Luo, Lupascu, Ma, Marhan, Michelsen, Mohan, Niu, Pendall, Penuelas, Pfeifer-Meister, Poll, Reinsch, Reynolds, Schmidt, Sistla, Sokol, Templer, Treseder, Welker and Bradford2016; Koven et al., Reference Koven, Hugelius, Lawrence and Wieder2017; Lavallee et al., Reference Lavallee, Soong and Cotrufo2020). Soils have the largest terrestrial C pool, which is about three times that of the atmosphere C pool and four times that of biotic C pool (Lal, Reference Lal2016). Small changes in soil organic carbon (SOC) stock can have a significant impact on atmospheric CH4 and CO2 concentrations, thus influencing global climate change (Cox et al., Reference Cox, Pearson, Booth, Friedlingstein, Huntingford, Jones and Luke2013). In addition to regulating climate, organic carbon is also important in ecosystem health and function, providing nutrients and energy for plants and microorganisms (Milne et al., Reference Milne, Banwart, Noellemeyer, Abson, Ballabio, Bampa, Bationo, Batjes, Bernoux, Bhattacharyya, Black, Buschiazzo, Cai, Cerri, Cheng, Compagnone, Conant, Coutinho and Zheng2015). Thus, understanding the impact of climate warming on soil organic carbon pools is essential for accurately predicting carbon-climate models and better ecosystem management to alleviate the negative effects of global change.
Soil physical structure refers to the arrangement of the soil solid particles and the pore spaces, and plays a vital role in soil organic carbon dynamics (Bronick and Lal, Reference Bronick and Lal2005; Mustafa et al., Reference Mustafa, Minggang, Ali Shah, Abrar, Nan, Baoren and Núnez-Delgado2020). Soil aggregates are the basic components of soil structure. Good soil aggregate structure is essential for promoting fertility and plant growth, and maintaining appropriate environmental quality, especially for soil carbon sequestration (Ma et al., Reference Ma, Wang, Shen, Li and Li2020; Six et al., Reference Six, Conant, Paul and Paustian2002). Climate change has a significant impact on the formation and development of soil structure (Lal, Reference Lal2020). Increasing greenhouse gas concentrations and global warming can influence soil aggregation by altering temperature and moisture conditions (Comegna et al., Reference Comegna, Picarelli, Bucchignani and Mercogliano2012). Some studies observed that short-term warming (<5 a) increased the non-aggregate silt + clay fractions, and the aggregate stability decreased (Guan et al., Reference Guan, An, Zong, He, Shi, Zhang and He2018). In the medium and long-term warming process (5–10 a), accelerated soil evaporation led to soil drying, which increased soil runoff and erosion, and then hindered the development of soil aggregate structure (Bronick and Lal, Reference Bronick and Lal2005; Xue et al., Reference Xue, Luo, Zhou, Sherry and Jia2011). In addition, some researches indicated that warming reduced SOC content and its availability, thereby reducing aggregate stability (Guo et al., Reference Guo, Zhou, Chen, Wu, Li, Qiao, You, Liu and Xue2022). However, other researches have also shown that long-term warming had no effect on soil nutrients, meaning no effect on soil structure (Zhou et al., Reference Zhou, Chen, Wang, Xu, Duan, Hao and Smaill2013). In general, soil properties do not respond quickly when the surrounding environment changes (Guo et al., Reference Guo, Zhou, Chen, Wu, Li, Qiao, You, Liu and Xue2022). Therefore, long-term warming experiments (>10 a) are more appropriate to study the influence of warming on soil structure, as they can more accurately reflect the variation of soil properties.
Soil organic carbon is a complex compound with varying turnover times. According to the turnover time of organic carbon, the C fractions can be divided into labile or active carbon pool (ACP) and stable or passive carbon pool (PCP) (Liu et al., Reference Liu, Pold, Domeignoz-Horta, Geyer, Caris, Nicolson, Kemner, Frey, Melillo and DeAngelis2021; Majumder et al., Reference Majumder, Mandal, Bandhyopadhyay, Gangopadhyay and Majumder2008). The labile or ACP has a short turnover time, is the main nutrient source of plants and the main energy source of soil microorganisms, and is susceptible to management measures and climatic conditions (Sahoo et al., Reference Sahoo, Singh, Gogoi, Kenye and Sahoo2019). Compared with labile or aACP, stable or PCP has a longer turnover time, which is recalcitrant and is often used as a reliable index of C sequestration potential of a system (Song et al., Reference Song, Liu, Muller, Yang, Wu and Wang2018). With global warming, soil carbon pools are significantly affected. At present, a large number of studies have reported the impact of global warming on soil organic carbon pools and obtained inconsistent conclusions. For example, Xu et al. (Reference Xu, Chen, Berninger, Pumpanen, Bai, Yu and Duan2015) and Samal et al. (Reference Samal, Dwivedi, Rao, Choubey, Prakash, Kumar, Mishra, Bhatt and Moharana2020) found that the ACP was very sensitive to temperature warming. In contrast, Lefevre et al., Reference Lefevre, Barre, Moyano, Christensen, Bardoux, Eglin, Girardin, Houot, Kätterer, Oort and Chenu2014) reported that PCP was more sensitive to elevated temperature. Other studies suggested that ACP and PCP had similar responses to temperature increase (Fang et al., Reference Fang, Smith, Moncrieff and Smith2005; Leifeld and Fuhrer, Reference Leifeld and Fuhrer2005). The highly incompatible results suggest that more attention should be paid to the effects of warming on soil organic carbon pools.
Wheat is one of the world’s important food crops, and about 21% of the world’s food comes from wheat (Ortiz et al., Reference Ortiz, Sayre, Govaerts, Gupta, Subbarao, Tomohiro, Hodson, Dixon, Ortiz-Monasteri and Reynolds2008). China is the country that produces and consumes the most wheat in the world, and wheat is the third major production crop in China. In 2010, China’s wheat production accounted for 17.6% (115 million metric tons) of the world, and wheat harvest area accounted for 11.2% (24 million hectares) of the world (FAO, 2013). Due to the pivotal status of wheat in the grain industry, the importance of maintaining the safety of wheat production cannot be overlooked, and the importance of soil physical structure and soil carbon pools in crop growth and nutrient supply cannot be ignored in the context of global warming. Our study aimed to identify the influence of long-term warming on the soil’s physical structure, including soil pore and aggregate characteristics, and soil carbon pools in wheatland fields.
Materials and Methods
Experimental site
The long-term warming experiment was initiated in August 2012 in the Kaiyuan campus farm of Henan University of Science and Technology, Luoyang, Henan Province, China (34°38′N, 112°22′E). The climate at the study site was a warm temperate semi-arid semi-humid monsoon climate with a mean annual temperature of 13.7°C, and a mean annual precipitation of 650.2 mm. The soil at our site is a typical cinnamon soil with a medium loam texture. The main soil properties are as follows: pH (1:5, soil: H2O) 7.4, bulk density 1.01 g cm-3, soil organic matter 10.7 g kg−1, total N 1.06 g kg−1, available P 3.46 mg kg−1, and available K 135.8 mg kg−1.
Experimental design
Random block design was used in this field experiment, which included two treatments: warmed and unwarmed control (unwarmed) (Fig. 1). Each treatment had three replicates. The area of each replicate plot was 8 m2 (2 m × 4 m). In order to avoid heating contamination, adjacent plots were separated by 10 m.
Figure 1. Differences in soil temperature between the warmed and unwarmed plots over the 2012–2022 growing seasons.
The field warming device used in this study was similar to the device shown by Chen et al. (Reference Chen, Tian, Zhang, Zheng, Song, Deng and Zhang2014) and Zheng et al. (Reference Zheng, Zhang, Chen, Chen, Tian, Deng, Song, Nawaz, Groenigen and Zhang2017). Briefly, it consisted of horizontal steel tubes with adjustable height and reflective curtain fixed on the steel tubes. Except for rainy and snowy days, the warmed plots were covered with curtains from sunset (around 19:00) to sunrise (around 07:00). The unwarmed plots were not covered by curtains. The distance between curtains and wheat canopy was kept at 20–25 cm to reduce the influence of curtains on air exchange. Using a digital temperature monitor (ZDR–41, Beijing Jingcheng Huatai Instrument Co., Ltd., China) to automatically monitor the temperature of 0–10 cm soil layer every 20 minutes during the whole growth period.
Crop management
In this experiment, the local drought-resistant and high-yield wheat variety Luohan 11 (Triticum aestivum L. cv Luohan 11) was selected. Wheat seeds were sown in November by hand at a density of 225 plants m-2 with a row spacing of 20 cm. In June of the second year, the wheat was harvested piece by piece according to different maturity dates of each treatment. The fertilizer application rates of N, P, and K in each plot were 220, 75, and 75 kg ha−1, respectively. Two days before sowing, total P, total K, and 40% N were applied as basal dressing. The remaining 60% of N fertilizer was applied at 30% and 30% ratios at the wheat jointing and heading stages. To maintain the same agronomic management system among different treatments, the same fertilizer was applied to each plot on the same date. If irrigation was required according to soil moisture, the same irrigation system was applied to each plot. Other field management measures, such as weed, pest control, and pesticide application, were implemented according to local wheat planting methods.
Soil sampling and analysis
Soil samples were collected in June 2019 after wheat harvest. Five undisturbed soil samples were collected with a hand auger (5 cm in diameter) at a depth of 0–15 cm surface layer in each plot. Then the five undisturbed samples were thoroughly mixed into one sample. At the same time, three core samples were obtained from the center of the 0–15 cm layers in each plot with ring knives for soil bulk density measurement. Finally, all soil samples were transferred to the laboratory to determine the soil physicochemical properties.
Soil bulk density, total porosity, capillary porosity, and non-capillary porosity were determined by the conventional core method (**Hao et al., 2018; Peng et al., Reference Peng, Dai, Ding, Shi, Li and Research2020). The separation and stability of soil aggregates were determined by conventional dry and wet sieving methods (Kemper and Rosenau, Reference Kemper, Rosenau and Klute1986; Yoder, Reference Yoder1936). The detailed determination process was consistent with that of Wu et al. (Reference Wu, Zhang, Yu, Zhang, Zhu, Zhao, Xiong and Chen2018). The wet oxidation method was used to analyze the content of SOC (Walkley and Black, Reference Walkley and Black1934). The modified Walkley and Black method described by Chan et al. (Reference Chan, Booowman and Oates2001) was adopted to determine the different pools of SOC. Briefly, three acid aqueous solution ratios of 0.5:1, 1:1, and 2:1 were prepared with 5, 10, and 20 ml of concentrated sulfuric acid solution (corresponding to 12 N, 18 N, and 24 N of H2SO4, respectively). Four different SOC pools were extracted according to the order of reduced oxidation capacity:
F1 (very labile carbon pool): organic C oxidized under 12 N H2SO4.
F2 (labile carbon pool): difference of oxidizable under 18 N and 12 N.
F3 (less labile carbon pool): difference of oxidizable under 24 N and 18 N.
F4 (non-labile carbon pool): difference of total SOC and oxidizable under 24 N.
Active carbon pool (ACP) is the cumulative value of F1 and F2, and passive carbon pool (PCP) is the sum of F3 and F4 (Chan et al. Reference Chan, Booowman and Oates2001).
Soil aggregate stability index calculation
The mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (D) were adopted to quantify soil aggregate stability. The larger the MWD and GMD, the stronger the stability of aggregates. The smaller the D, the better soil structure and higher soil stability. R 0.25 is the mass percentage of the >0.25 mm aggregates. These indexes were calculated using the following equations (Cao et al., Reference Cao, Zhou, Zhou, Zhou and Zhou2021; Kemper and Rosenau, Reference Kemper, Rosenau and Klute1986; Tyler and Wheatcraft, Reference Tyler and Wheatcraft1992):
$${\mathop{\rm MWD}\nolimits} {\rm{ = }}\sum\limits_{{i}}^{{n}} {{{xiwi}}} {\rm{/}}\sum\limits_{{i}}^{{n}} {{{wi}}} $$
$${\mathop{\rm GMD}\nolimits} {{ = exp}}\left(\sum\limits_{{i}}^{{n}} {{{wilnxi}}} {/}\sum\limits_{{i}}^{{n}} {{{wi}}} \right)$$
$$D = 3 - \lg \left[ {{{m(i \lt xi)} \over {m{{t}}}}} \right]/\lg \left[ {{{xi} \over {xmax}}} \right]$$
$$R_{0.25} = {{mi \gt 0.25} \over {mt}}$$
Where x i denotes the mean diameter of each aggregate fraction (mm); w i denotes the proportion of ith size fraction (%); m(i < x i ) denotes the mass of aggregates smaller than ith size fraction (g); m t denotes the total mass of aggregates (g); and x max denotes the maximum diameter of the soil aggregate fractions (mm).
Data analysis
All data analyses were performed with Excel 2007 and SPSS 19.0. Two-way analysis of variance with least significant difference test was used to determine the differences among treatment means with probability level <0.05. All data were tested by Shapiro-Wilk and Levene for normality and homogeneity of variance. Origin 9.0 was employed to visualize the data.
Results
Long-term warming affects soil bulk density and porosity
Soil bulk density, porosity, and solid, liquid, and gas ratio in the unwarmed and warmed treatments are presented in Table 1. The soil bulk density in the warmed treatment was significantly higher by 4.5% (p < 0.05) than that in the unwarmed treatment. The total porosity and non-capillary porosity in the warmed treatment significantly decreased by 3.4% and 5.0% (p < 0.05), respectively, when compared with those of the unwarmed; but the capillary porosity showed no significant difference between the two treatments (p > 0.05). Compared with unwarmed treatment, warmed treatment increased the proportion of solids.
Table 1. Soil bulk density, porosity, and solid: liquid: gas ratio in the unwarmed and warmed treatments
Note: Values are means ± standard errors (n = 3). Different lowercase letters (a, b) in the same column denote a significant difference between treatments (p < 0.05).
Long-term warming affects size distribution and structural stability characteristics of soil aggregates
Figure 2 shows the size distribution of dry and wet aggregates in the unwarmed and warmed treatments. For dry aggregates, the 2–0.25 mm size fraction exhibited the highest proportion (60.3–61.1% of the total aggregates), followed by the >2 mm (24.2–29.5%) and 0.25–0.053 mm (8.1–11.6%) size fractions, the <0.053 mm fraction had the lowest proportion (2.1–3.1%) in the two treatments. Besides, the warmed treatment significantly decreased the >2 mm dry aggregates by 17.8% (p < 0.05), and significantly increased the 0.25–0.053 mm and <0.053 mm dry aggregates by 29.7% and 24.2% (p < 0.05), when compared with the unwarmed. For wet aggregates, the proportion of <0.053 mm size fraction (33.5–43.2%) was the dominant size class, followed by the 2–0.25 mm (30.2–31.8%) and 0.25–0.053 mm (16.4–25.8%) size fractions, the >2 mm fraction had the lowest proportion (8.6–10.4%) in the two treatments. Furthermore, the warmed treatment significantly decreased the >2 mm and 0.25–0.053 mm wet aggregates by 16.9% and 36.7% (p < 0.05), and significantly increased the 2–0.25 mm and <0.053 mm wet aggregates by 5.2% and 28.8% (p < 0.05), respectively, when compared with the unwarmed.
Figure 2. Soil aggregate size distribution in the unwarmed and warmed treatments. Different lowercase letters denote a significant difference between treatments (p < 0.05). Bars represent standard errors (n = 3).
Table 2 shows the structural stability characteristics of soil aggregates in the unwarmed and warmed treatments. For dry aggregates, the warmed treatment significantly decreased the MWD, GMD, and R 0.25 by 7.0%, 12.3%, and 4.9% (p < 0.05), and significantly increased the D by 4.0% (p < 0.05), respectively, when compared with the unwarmed. For wet aggregates, the warmed treatment significantly decreased the MWD and GMD by 6.7% and 15.4% (p < 0.05), respectively, when compared with the unwarmed. The D and R 0.25 of wet aggregates showed no significant difference between the two treatments (p > 0.05).
Table 2. Soil aggregate structural stability characteristics in the unwarmed and warmed treatments
Note: MWD, mean weight diameter; GMD, geometric mean diameter; D, fractal dimension; R 0.25 is the mass percentage of the >0.25 mm aggregates. Values are means ± standard errors (n = 3). Different lowercase letters (a, b) in the same column denote a significant difference between treatments (p < 0.05).
Long-term warming affects soil carbon pools
Table 3 shows the content of different soil carbon pools in the unwarmed and warmed treatments. The SOC content in the warmed treatment was significantly lower by 10.6% (p < 0.05) than that in the unwarmed treatment. The F1 and F2 content in the warmed treatment were significantly lower by 30.6% and 43.6% (p < 0.05), respectively, than those in the unwarmed treatment. The F3 and F4 content in the warmed treatment were significantly higher by 94.2% and 21.1% (p < 0.05), respectively, than those in the unwarmed treatment. Compared with the unwarmed, the warmed significantly decreased the ACP by 40.0% (p < 0.05), and significantly increased the PCP by 38.2% (p < 0.05), respectively.
Table 3. The content of different soil carbon pools in the unwarmed and warmed treatments
Note: SOC, soil organic carbon, F1, very labile pool; F2, labile pool; F3, less labile pool; F4, non-labile pool; ACP, active carbon pool; PCP, passive carbon pool. Values are means ± standard errors (n = 3). Different lowercase letters (a, b) in the same column denote a significant difference between treatments (p < 0.05).
The percentage of different soil C pools to total SOC in the unwarmed and warmed treatments is shown in Fig. 3. Compared with the unwarmed, the warmed decreased the percentage of F1 and F2 from 44.3 to 33.4%, and from 22.3 to 14.1%, but increased the percentage of F3 and F4 from 7.8 to 16.9%, and from 25.5 to 34.6%, respectively. The warmed increased the PCP percentage but decreased the ACP percentage compared with the unwarmed.
Figure 3. The percentage of different soil C pools to total SOC in the unwarmed and warmed treatments.
Discussion
In the present study, long-term warming increased soil bulk density of wheatland field (Table 1). A similar result was reported by Bryk et al. (Reference Bryk, KołOdziej, SłOwińska-Jurkiewicz and Jaroszuk-Sierocińska2017), who found that soil bulk density of the upper 0–5 cm layer was significantly negatively correlated with air temperature. This phenomenon is mainly due to the fact that soil bulk density is closely related to SOC content, and higher temperature tends to result in lower standing stock of SOC (Franzluebbers et al., Reference Franzluebbers, Haney, Honeycutt, Arshad, Schomberg and Hons2001), thereby leading to the decrease of soil bulk density. Soil pore system is an important aspect of soil structure, affecting the transport of water, solutes, and air (Kuncoro et al., Reference Kuncoro, Koga, Satta and Muto2014; Menon et al., Reference Menon, Mawodza, Rabbani, Blaud, Lair, Babaei, Kercheva, Rousseva and Banwart2020). Long-term warming decreased soil total porosity and non-capillary porosity (Table 1). Similar trends in the USA Great Plains were reported by Xue et al. (Reference Xue, Luo, Zhou, Sherry and Jia2011). The decrease in soil porosity in the warming system is due to the fact that increasing soil temperature reduces soil moisture (Scharn et al., Reference Scharn, Little, Bacon, Alatalo, Antonelli, Bjrkman, Molau, Nilsson and Björk2021). Dry soil usually has an unstable and poorly developed structure, resulting in high apparent density (compaction) and low porosity (Wen et al., Reference Wen, Chen and Shao2022). As the soil porosity decreased in the warmed treatment, the ratio of soil solids increased (Table 1).
Soil aggregate is an important index reflecting soil structure. The particle size distribution of soil aggregates influences material circulation and energy flow (Polakowski et al., Reference Polakowski, Sochan, Ryak, Beczek, Mazur, Majewska, Turski and Bieganowski2021). Long-term warming altered the particle size distribution of soil aggregates. Specifically, warming decreased the >2 mm fraction proportion and increased <0.053 mm fraction proportion of dry and wet aggregates (Fig. 2). This indicated that warming promoted the breakdown of macroaggregates (>2 mm) into silt + clay-sized aggregates (<0.053 mm). This phenomenon is partly due to warming leading to soil drying, preventing soil aggregation and structural development (Bronick and Lal, Reference Bronick and Lal2005; Guan et al., Reference Guan, An, Zong, He, Shi, Zhang and He2018). In addition, aggregate breakdown is a good measure for soil erodibility, because it increases the proportion of finer, more easily transportable microaggregates, thereby increasing the risk of soil erosion. Therefore, climate warming may increase the risk of soil erosion.
The stability of soil aggregates is a good indicator of soil degradation (Six et al., Reference Six, Bossuyt, Degryze and Denef2004). Long-term warming decreased the MWD and GMD, and increased the D of dry and wet aggregates (Table 2), indicating that warming decreased the aggregate stability and corrosion resistance. This result was consistent with the findings of Guan et al. (Reference Guan, An, Zong, He, Shi, Zhang and He2018) and Guo et al. (Reference Guo, Zhou, Chen, Wu, Li, Qiao, You, Liu and Xue2022). Soil organic matter is very important for the formation of soil aggregates, which combine with small particles to form stable aggregate structures and promote the development of soil structures (Six et al., Reference Six, Bossuyt, Degryze and Denef2004; Tisdall and Oades, Reference Tisdall and Oades1982). Warming will increase the turnover rate of soil organic carbon and the consumption of unstable carbon pools (Guo et al., Reference Guo, Zhou, Chen, Wu, Li, Qiao, You, Liu and Xue2022), leading to a decline in soil organic matter content. Therefore, the stability of soil aggregates will decrease under warming conditions.
Climate change significantly affects soil organic carbon pools (Sahoo et al., Reference Sahoo, Singh, Gogoi, Kenye and Sahoo2019; Samal et al., Reference Samal, Dwivedi, Rao, Choubey, Prakash, Kumar, Mishra, Bhatt and Moharana2020). Our result suggested that long-term warming significantly decreased the SOC content (Table 3). This was consistent with previous researches suggesting that the increase in temperature had a negative impact on soil organic carbon content (Qi et al., Reference Qi, Li, Lin, Li, Li, Yang, Zhang and Zhao2016; Wang et al., Reference Wang, Gao, Li, Zhang and Wang2016). This result can be attributed to the increase in the soil respiration rate and the utilization efficiency of soil microbes for SOC with increasing temperature (Allison et al., Reference Allison, Wallenstein and Bradford2010; Hou et al., Reference Hou, Ouyang, Maxim, Wilsond and Kuzyakov2016; Lefevre et al., Reference Lefevre, Barre, Moyano, Christensen, Bardoux, Eglin, Girardin, Houot, Kätterer, Oort and Chenu2014).
According to the turnover rate of SOC pools, SOC pools can be divided into ACP and PCP. The ACP, represented by the very labile (F1) and the labile pool (F2), refers to the fraction of organic C that is easily decomposed and poorly stable and is strongly influenced by microbial activity (Sahoo et al., Reference Sahoo, Singh, Gogoi, Kenye and Sahoo2019). The PCP, represented by the less labile pool (F3) and the non-labile pool (F4), is considered to be the more stable form of organic C, and is insensitive to soil and crop management (Hazra et al., Reference Hazra, Ghosh, Venkatesh, Nath, Kumar, Singh, Singh and Nadarajan2018). In this study, long-term warming significantly decreased the content of F1 and F2, while increasing the content of F3 and F4, suggesting that long-term warming decreased the ACP, and increased the PCP (Table 3). This finding was in conformity with Samal et al. (Reference Samal, Dwivedi, Rao, Choubey, Prakash, Kumar, Mishra, Bhatt and Moharana2020), who observed that under increased temperature, soil ACP was depleted, while PCP was enriched, and soil total organic carbon declined in subtropical humid climatic regions. The soil’s ACP decreased in response to increased temperature due to the higher decomposition of labile carbon. The PCP increased in response to increased temperature may be due to the reduction of substrates available to microorganisms, resulting in a decrease in the temperature sensitivity of the remaining organic carbon, limiting further decomposition (Moinet et al., Reference Moinet, Hunta, Kirschbaum and Morcom2018; Thiessen et al., Reference Thiessen, Gleixner, Wutzler and Reichstein2013). This leads to the accumulation of more PCP in warm.
Conclusion
An eleven-year warming experiment was conducted in wheat field. Our results indicated that long-term warming negatively impacted on soil’s physical structure. The soil bulk density increased, while the total porosity and non-capillary porosity decreased in warmed treatment. Long-term warming treatment promoted the breakdown of macroaggregates (>2 mm) into silt + clay-sized aggregates (<0.053 mm), and decreased the soil aggregate stability of wheat field. Besides, long-term warming decreased the total SOC content and ACP, while increasing the PCP. Our study demonstrates that long-term warming may alter the soil’s physical structure and affect the distribution and turnover of different soil organic carbon pools of wheatland field.
Funding information
This work was supported by the PhD Startup Foundation of Henan University of Science and Technology (Grant No. 13480107).
Competing interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
