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Microbial trade-off in soil organic carbon storage in a no-till continuous corn agroecosystem
European Journal of Soil Biology 96 (2020) 103146
Contents lists available at ScienceDirect
European Journal of Soil Biology journal homepage: www.elsevier.com/locate/ejsobi
Microbial trade-off in soil organic carbon storage in a no-till continuous corn agroecosystem
T
Xuefeng Zhua,b, Hongtu Xiea, Michael D. Mastersc, Yu Luod, Xudong Zhanga, Chao Lianga,∗ a
Institute of Applied Ecology, Chinese Academy of Sciences. Shenyang, Liaoning, 110016, China University of Chinese Academy of Sciences. Beijing, 100049, China c Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana Champaign. Urbana, IL, 61801, USA d Zhejiang University. Hangzhou, 310058, China b
ARTICLE INFO
ABSTRACT
Handling editor: Yakov Kuzyakov
Recent perspective has highlighted the microbial importance of interplay between catabolic breakdown and anabolic synthesis in influencing soil organic carbon (SOC) dynamics and persistence. However, studies on these contrasting activities remain rare, despite value to global discussions on economic and ecologically sustainable ecosystem management. Here we investigate microbial response in a no-till farm in Northeast China after an 8year manipulation of plant residue returns of varying quantity including control (0%, NT0), low (33%, NT33), medium (67%, NT67) and high (100%, NT100). Topsoil amino sugar biomarker analysis indicated microbial necromass contributed to SOC formation in NT33 and NT67, while the contribution was minimal in NT100. Sequencing data analyses along with subsoil SOC indicated increased microbial degradation of existing SOC upon mulch quantity gradient. We found that a low level (33%) of the previous year's stover return was an optimized trade-off for topsoil (0–5 cm) carbon storage and off-field economic demand for material. This study demonstrates the non-linear relationship between carbon inputs and SOC content, and suggests the importance of the trade-off effects between microbial catabolism and anabolism.
Keywords: 16S rRNA high throughput sequencing No tillage Soil organic carbon Amino sugar Entombing effect Soil organic carbon decomposition
Terrestrial soils contain three times more carbon (C) than the atmosphere, thus small changes in cropland soil organic carbon (SOC) impact local ecosystem productivity and sustainability on a global scale [1]. Improper management of aboveground biomass input, a major C source of soil organic matter (SOM), can cause environmental issues, particularly regarding soil C cycling [2,3]. It is generally assumed that SOM levels are linearly proportional to the exogenous C input [4], theoretically suggesting unlimited exogenous C input for SOM improvement. However, both empirical studies and models demonstrate nonlinear relationships between C input quantity and SOM increment [5–9]. An improvement in the mechanistic understanding of the debated effect of residue quantity on SOM dynamics (decomposition and formation) is necessary to dictate ideal management practice. Soil microbial communities regulate the magnitude and direction in which organic materials are decomposed into products, such as CO2 via catabolic breakdown, microbial necromass via anabolic synthesis, as well as influence SOM turnover and storage [10,11]. One prevailing decomposition hypothesis predicts that increased plant residue inputs might reduce SOC storage through inefficient microbial transformation of exogenous substrates and enhanced existing SOM decomposition
∗
[12–14]. A converse hypothesis proposes that plant residue inputs might enhance SOC storage through accelerated production of microbial residues and their stabilization on soil minerals or within aggregates [10,15,16], which was conceptualized as a soil microbial carbon pump (MCP) framework. The net balance between these two processes acting on exogenous C inputs, i.e. existing SOM decomposition (priming effect, PE) and microbial necromass accumulation (entombing effect, EE), likely determines SOC storage [10], and thus process assessment and consequent SOC change are essential. Conceivably, PE and EE always co-exist to some degree but alternately dominate depending on local conditions such as residue quantity. Consequently, an optimal level of exogenous C such as maize stover returned as mulch for SOC accumulation in agricultural systems may exist. Northeast China, the agricultural grain supply heartland of China [17] and one of the most important Mollisol regions in the world [18], was estimated to contain the highest SOC across Chinese croplands, accounting for more than 35% of the total between 1980 and 2005 [19]. Common agricultural practice in this region often includes postharvest removal of maize stover in continuous maize agroecosystems
Corresponding author. E-mail address: [email protected] (C. Liang).
https://doi.org/10.1016/j.ejsobi.2019.103146 Received 18 July 2019; Received in revised form 21 September 2019; Accepted 18 November 2019 Available online 14 January 2020 1164-5563/ © 2020 Elsevier Masson SAS. All rights reserved.
European Journal of Soil Biology 96 (2020) 103146
X. Zhu, et al.
[20]. The removed stover is an important commodity to the local farmers, used mainly for fuel and forage. However, intensive removal of maize stover has been demonstrated to decrease bulk SOC [20], yet many growers rely on this material as part of their livelihood. Therefore, optimizing levels of residue return to leverage the multifaceted effects of the management and acclimate to the current social-economic need is critical. The objective of this study was to explore microbial-driven SOC dynamics in a no-tillage (NT) agricultural system in Northeast China following the return of various quantities of maize stover as mulch, including 0% (NT0: 0 Mg ha−2), 33% (NT33: 2.5 Mg ha−2), 67% (NT67: 5.0 Mg ha−2), and 100% (NT100: 7.5 Mg ha−2) return of the previous year's stover. We investigated topsoil (0–5 cm) SOC changes, and microbial community and necromass using 16S rRNA high throughput sequencing and amino sugar biomarker analysis. We identified microbial community functions using functional predictions [21,22] and differentially abundant features (potential biomarkers) identification [23,24], and microbial contribution to SOC using amino sugar analysis. We hypothesize there will be differences in bulk topsoil microbial communities and SOC with different rates of stover return. We predict that the changes in SOC along the mulch gradient will be non-linear, likely as a result of trade-offs between microbial degradation of existing SOM (PE) and microbial contribution to SOC (EE). With consideration of the fact that long term changes in C are often correlated to changes in N [25], we predict we will see a similar pattern but smaller magnitude of soil total N change along the mulch gradient. Experimental details can be found in supplementary material (S1). As hypothesized, we observed nonlinear changes in SOC and total nitrogen (TN) content along the quantity gradient of maize stover in the topsoil, and the microbial community function prediction and necromass data partially supported a trade-off between PE and eE. Relative to the NT0 treatment, topsoil SOC and TN increased with 33% and 100% additions of maize stover mulch and did not change in the 67% treatment (Fig. 1), demonstrating a variable microbial response to the quantity of exogenous C inputs. Amino sugar analyses indicated a nonlinear microbial derived (entombed) C contribution to SOC along mulch gradient. Microbial C accumulated in topsoil SOC with 33% additions of maize stover mulch but contributed little to SOC in the 100% treatment, with the greatest entombing ability in the 67% treatment as a turning point (Table 1). This is similar to the non-linear microbial biomass C accumulation results in Li et al. [26], another study with a gradient of exogenous C inputs. Microbial function prediction and potential biomarker analyses based on the sequencing data indicated an increased microbial degradation of existing SOM along the maize mulch gradient (Figs. 2 and 3) with the extra support from the decreasing SOC trend in subsoil along mulch quantity (Fig. S2). We hypothesized we would observe differences in dominance between EE and existing SOM degradation along the gradient in exogenous C present in this study, and the combination of results as a whole support this. It is evident from the results in this study that greater exogenous C input does not always result in stable SOC formation and deeper SOC improvement. Amino sugar analyses and the ratio of amino sugar accumulation to SOC accumulation indicate differences in the microbial contribution to SOC formation. The rate of microbial necromass accumulation exceeded the SOC accumulation rate in NT33 (ratio = 1.05) and NT67 (ratio = 2), while the opposite was observed in NT100 (ratio = 0.31 < 1) (Table 1). This is evidence of increased microbial necromass contribution to SOC formation under low and medium maize stover additions, and decreased necromass contribution to SOC formation under high maize stover addition, relative to NT0. However, we did observe an increase in the microbial necromass contribution to SOC in NT67 without a corresponding increase in bulk SOC, and a decrease in the microbial necromass contribution to SOC in NT100 with a corresponding increase in bulk SOC, suggesting the existence of another counteractive process, likely the PE, and the shift dominance between EE and PE.
Fig. 1. Comparisons of (a) soil organic carbon and (b) total nitrogen concentrations (g/kg soil) under NT treatments in topsoil layer (0–5 cm). Error bars represent ± standard error of the means. Shared letters are not significantly different, p ≥ 0.05. NT, no tillage. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% return of maize stover mulch.
Topsoil sequencing data analyses provided evidence of increased microbial preference for plant residue C in NT33, but indicated a preference for existing SOM in NT67 and NT100 (Fig. 2). In NT33, the most abundant phylum TM7 (Fig. 2), which has been reported to biodegrade aromatic C compounds such as toluene [27], combining with an increase in genes related to secretion systems from function predication analyses, jointly suggested a change in this treatment toward a higher microbial C use efficiency of plant residue, which was probably through extracellular enzyme secretion (Fig. 3) [28]. In contrast, NT67 and NT100 topsoils were enriched with the microbes, which can grow anaerobically utilizing C sources in oxygen depleted soils due to intensive organic matter decomposition, including the genus Candidatus entotheonella (Fig. 2) in NT67, and the phylum OD1, the class OP11-3 and the order CFB-26 in NT100 [29–32] (Fig. 2). Microorganisms in such an unfavorable environment have been suggested to invest more energy in growth and resource acquisition [33] from existing SOM (PE), which is supported by our observed increase in genes related to DNA repair, recombination proteins, and ribosome biogenesis in NT100 (Fig. 3). The evidence here along with the decreasing trend of SOC observed in NT67 and NT100 subsoils (Fig. S2) suggests priming of 2
European Journal of Soil Biology 96 (2020) 103146
X. Zhu, et al.
Table 1 Results of amino sugar (AS) analyses and soil organic carbon (SOC) for the topsoil (0–5 cm) in the no-tillage system with maize stover mulch (NT33/67/100). Treatment
Total amino sugar (AS)
Soil organic carbon (SOC)
Mean g/kg
SE
Mean g/kg
NT0
1.01
0.028
13.92
NT33 NT67 NT100
1.11 1.09 1.05
0.046 0.036 0.064
15.23 14.51 15.83
AS rate
SOC rate
Ratio of AS rate to SOC rate
0.10 0.08 0.04
0.09 0.04 0.14
1.05 2.00 0.31
SE 0.085
0.530 0.588 0.799
The ratio of AS rate to SOC rate indicates the relative speed of the accumulation of microbial necromass and SOC content, which could give an indication of microbial necromass contribution to SOC in the treatment relative to NT0. If the ratio > 1, microbial necromass accumulates faster than SOC content, suggesting increased microbial necromass contribution to SOC formation relative to NT0, and vice versa. If the ratio = 1, microbial necromass accumulates as fast as SOC content, suggesting no changes of microbial necromass contribution to SOC formation relative to NT0. The rate of AS and SOC in the treatments with maize stover mulch (NT33/67/100) relative to the treatments without maize stover addition (NT0) were calculated as below: AS rate=(ASNTX - ASNT0)/ASNT0; SOC rate=(SOCNTX SOCNT0)/SOCNT0; X% represents maize stover addition amount. X can be 33,67 or 100. The ratio of AS rate to SOC rate = AS rate/SOC rate. NT, no-tillage. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch. SE, standard error of the means.
existing SOC at the higher end of the maize stover gradient, similar to those priming phenomena observed in Sayer et al. [34], Shahbaz, et al. [5] and Luo et al. [35]. In theory as Liang et al. [10] proposed, SOC accumulates when EE exceeds PE, is unchanged when PE and EE are equal, and is lost when PE exceeds EE. However, this is overly simplified as local conditions such as litter quantity and quality, soil depth and texture, climate and
moisture are all factors. We found evidence of EE dominance in NT33 and PE dominance in NT100. Although topsoil C accumulated in both of these treatments, the biomarker and sequencing data presented in this study demonstrate the microbial influence on the SOM is markedly different. These same data show partial evidence of both EE (biomarkers, Table 1), and PE (LDA scores, Fig. 2 & Subsoil SOC, Fig. S2) occurring the same intensity in NT67, perhaps the reason why bulk SOC
Fig. 2. (a) Histogram of the linear discriminant analysis (LDA) score for the differentially abundant microbes detected in each treatment for the topsoil (0–5 cm) using LEfSe analysis online tool. (b) Cladogram derived from LEfSe analysis for taxonomic representation of significant differences among groups. Only the taxa with meeting a significant LDA threshold score of > 2 were shown. Differences are represented in the color of the most abundant taxa. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch. 3
European Journal of Soil Biology 96 (2020) 103146
X. Zhu, et al.
Fig. 3. Statistically significant differences in the bacterial predicted functions using PICRUSt analysis and STAMP statistical software in the comparison of no-tillage without and with maize stover mulch for the topsoil (0–5 cm). The graphic shows only the L3 KEGG pathways with statistical differences between the proportions of sequences in each treatment with a confidence interval of 95. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch.
did not increase in this treatment. Taken as a whole, it is evident that the differences in litter quantity applied in this study created very different environments from the common practice control in this region of complete biomass removal, and further research is needed to fully understand these mechanisms. Our findings improve scientific understanding of the interplay between microbial catabolic and anabolic activities by identifying tradeoffs between PE and EE, and also provide important data for crop residue management in view of social-economic need. The combination of nonlinear changes of SOC, microbial degradation of (PE) and necromass contribution to (EE) existing SOC along a maize stover return quantity gradient provides partial field evidence of an alternative domination of two co-existed processes. Our study demonstrates that a low level of stover mulch (33% of the previous year's aboveground biomass, 2.5 Mg ha−1) leads to net topsoil C accumulation in line with high level stover mulch, and also ensures sufficient aboveground biomass removal for human needs. We would expect the magnitude of C accumulation and quantity of litter additions to change with soil types and other abiotic factors present in other locations, but it is feasible the trends observed in this study carry implications beyond this region in China. Hence, our study contributes much to understanding the role of microbes in SOM formation and stabilization, the importance of microbial influence on agricultural management, and global discussions on soil vulnerability and sustainability of soils for productivity, environmental health, and climate policy.
Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ejsobi.2019.103146. Author contributions X-F.Z., and C.L. designed the study. H-T.X., and X-D.Z. oversaw the field site. X-F.Z. conducted bench work and performed data analysis. XF.Z., M.D.M., and C.L. interpreted and wrote the paper with inputs from all co-authors. References [1] J. Sanderman, T. Hengl, G.J. Fiske, Soil carbon debt of 12,000 years of human land use, Proc. Natl. Acad. Sci. 114 (2017) 9575–9580, https://doi.org/10.1073/pnas. 1706103114. [2] P. Buysse, C. Roisin, M. Aubinet, Fifty years of contrasted residue management of an agricultural crop: impacts on the soil carbon budget and on soil heterotrophic respiration, Agric. Ecosyst. Environ. 167 (2013) 52–59, https://doi.org/10.1016/j. agee.2013.01.006. [3] F. Garcia-Orenes, A. Roldan, A. Morugan-Coronado, C. Linares, A. Cerda, F. Caravaca, Organic fertilization in traditional mediterranean grapevine orchards mediates changes in soil microbial community structure and enhances soil fertility, Land Degrad. Dev. 27 (2016), https://doi.org/10.1002/ldr.2496. [4] J. Six, E.A. Conant RTPaul, K. Paustian, Stabilization mechanisms of soil organic matter: implications for C-saturation of soils, [Review], Plant Soil 241 (2002) 155–176, https://doi.org/10.1023/A:1016125726789. [5] M. Shahbaz, Y. Kuzyakov, F. Heitkamp, Decrease of soil organic matter stabilization with increasing inputs: mechanisms and controls, Geoderma 304 (2015), https:// doi.org/10.1016/j.geoderma.2016.05.019 S0016706116302221. [6] C.E. Stewart, A.F. Plante, K. Paustian, R.T. Conant, J. Six, Soil carbon saturation: linking concept and measurable carbon pools, Soil Sci. Soc. Am. J. 72 (2008) 379–392, https://doi.org/10.2136/sssaj2007.0104. [7] C.E. Stewart, K. Paustian, R.T. Conant, A.F. Plante, J. Six, Soil carbon saturation: concept, evidence and evaluation, Biogeochemistry 86 (2007) 19–31, https://doi. org/10.1007/s10533-007-9140-0. [8] D.S. Powlson, M.J. Glendining, K. Coleman, A.P. Whitmore, Implications for soil properties of removing cereal straw: results from long-term studies, Agron. J. 103 (2011) 279, https://doi.org/10.2134/agronj2010.0146s. [9] F. Heitkamp, M. Wendland, K. Offenberger, G. Gerold, Implications of input estimation, residue quality and carbon saturation on the predictive power of the Rothamsted Carbon Model, Geoderma 170 (2012) 168–175, https://doi.org/10. 1016/j.geoderma.2011.11.005. [10] C. Liang, J.P. Schimel, J.D. Jastrow, The importance of anabolism in microbial control over soil carbon storage, Nat. Microbiol. 2 (2017) 17105, https://doi.org/ 10.1038/nmicrobiol.2017.105. [11] N.W. Sokol, J. Sanderman, M.A. Bradford, Pathways of mineral-associated soil
Declaration of competing interest None. Acknowledgements This work was financially supported by the National Key R&D Program of China (No. 2016YFD0200307) and the National Natural Science Foundation of China (No. 41671297 and 31930070). We would like to thank Dr. H. He for her knowledgeable inputs on the biomarker interpretations. We would like to thank F. Wang and C. He for their assistance with sample collection and processing, and P. Shao and T. Zheng for their assistance with sequencing data analysis. 4
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Contents lists available at ScienceDirect
European Journal of Soil Biology journal homepage: www.elsevier.com/locate/ejsobi
Microbial trade-off in soil organic carbon storage in a no-till continuous corn agroecosystem
T
Xuefeng Zhua,b, Hongtu Xiea, Michael D. Mastersc, Yu Luod, Xudong Zhanga, Chao Lianga,∗ a
Institute of Applied Ecology, Chinese Academy of Sciences. Shenyang, Liaoning, 110016, China University of Chinese Academy of Sciences. Beijing, 100049, China c Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana Champaign. Urbana, IL, 61801, USA d Zhejiang University. Hangzhou, 310058, China b
ARTICLE INFO
ABSTRACT
Handling editor: Yakov Kuzyakov
Recent perspective has highlighted the microbial importance of interplay between catabolic breakdown and anabolic synthesis in influencing soil organic carbon (SOC) dynamics and persistence. However, studies on these contrasting activities remain rare, despite value to global discussions on economic and ecologically sustainable ecosystem management. Here we investigate microbial response in a no-till farm in Northeast China after an 8year manipulation of plant residue returns of varying quantity including control (0%, NT0), low (33%, NT33), medium (67%, NT67) and high (100%, NT100). Topsoil amino sugar biomarker analysis indicated microbial necromass contributed to SOC formation in NT33 and NT67, while the contribution was minimal in NT100. Sequencing data analyses along with subsoil SOC indicated increased microbial degradation of existing SOC upon mulch quantity gradient. We found that a low level (33%) of the previous year's stover return was an optimized trade-off for topsoil (0–5 cm) carbon storage and off-field economic demand for material. This study demonstrates the non-linear relationship between carbon inputs and SOC content, and suggests the importance of the trade-off effects between microbial catabolism and anabolism.
Keywords: 16S rRNA high throughput sequencing No tillage Soil organic carbon Amino sugar Entombing effect Soil organic carbon decomposition
Terrestrial soils contain three times more carbon (C) than the atmosphere, thus small changes in cropland soil organic carbon (SOC) impact local ecosystem productivity and sustainability on a global scale [1]. Improper management of aboveground biomass input, a major C source of soil organic matter (SOM), can cause environmental issues, particularly regarding soil C cycling [2,3]. It is generally assumed that SOM levels are linearly proportional to the exogenous C input [4], theoretically suggesting unlimited exogenous C input for SOM improvement. However, both empirical studies and models demonstrate nonlinear relationships between C input quantity and SOM increment [5–9]. An improvement in the mechanistic understanding of the debated effect of residue quantity on SOM dynamics (decomposition and formation) is necessary to dictate ideal management practice. Soil microbial communities regulate the magnitude and direction in which organic materials are decomposed into products, such as CO2 via catabolic breakdown, microbial necromass via anabolic synthesis, as well as influence SOM turnover and storage [10,11]. One prevailing decomposition hypothesis predicts that increased plant residue inputs might reduce SOC storage through inefficient microbial transformation of exogenous substrates and enhanced existing SOM decomposition
∗
[12–14]. A converse hypothesis proposes that plant residue inputs might enhance SOC storage through accelerated production of microbial residues and their stabilization on soil minerals or within aggregates [10,15,16], which was conceptualized as a soil microbial carbon pump (MCP) framework. The net balance between these two processes acting on exogenous C inputs, i.e. existing SOM decomposition (priming effect, PE) and microbial necromass accumulation (entombing effect, EE), likely determines SOC storage [10], and thus process assessment and consequent SOC change are essential. Conceivably, PE and EE always co-exist to some degree but alternately dominate depending on local conditions such as residue quantity. Consequently, an optimal level of exogenous C such as maize stover returned as mulch for SOC accumulation in agricultural systems may exist. Northeast China, the agricultural grain supply heartland of China [17] and one of the most important Mollisol regions in the world [18], was estimated to contain the highest SOC across Chinese croplands, accounting for more than 35% of the total between 1980 and 2005 [19]. Common agricultural practice in this region often includes postharvest removal of maize stover in continuous maize agroecosystems
Corresponding author. E-mail address: [email protected] (C. Liang).
https://doi.org/10.1016/j.ejsobi.2019.103146 Received 18 July 2019; Received in revised form 21 September 2019; Accepted 18 November 2019 Available online 14 January 2020 1164-5563/ © 2020 Elsevier Masson SAS. All rights reserved.
European Journal of Soil Biology 96 (2020) 103146
X. Zhu, et al.
[20]. The removed stover is an important commodity to the local farmers, used mainly for fuel and forage. However, intensive removal of maize stover has been demonstrated to decrease bulk SOC [20], yet many growers rely on this material as part of their livelihood. Therefore, optimizing levels of residue return to leverage the multifaceted effects of the management and acclimate to the current social-economic need is critical. The objective of this study was to explore microbial-driven SOC dynamics in a no-tillage (NT) agricultural system in Northeast China following the return of various quantities of maize stover as mulch, including 0% (NT0: 0 Mg ha−2), 33% (NT33: 2.5 Mg ha−2), 67% (NT67: 5.0 Mg ha−2), and 100% (NT100: 7.5 Mg ha−2) return of the previous year's stover. We investigated topsoil (0–5 cm) SOC changes, and microbial community and necromass using 16S rRNA high throughput sequencing and amino sugar biomarker analysis. We identified microbial community functions using functional predictions [21,22] and differentially abundant features (potential biomarkers) identification [23,24], and microbial contribution to SOC using amino sugar analysis. We hypothesize there will be differences in bulk topsoil microbial communities and SOC with different rates of stover return. We predict that the changes in SOC along the mulch gradient will be non-linear, likely as a result of trade-offs between microbial degradation of existing SOM (PE) and microbial contribution to SOC (EE). With consideration of the fact that long term changes in C are often correlated to changes in N [25], we predict we will see a similar pattern but smaller magnitude of soil total N change along the mulch gradient. Experimental details can be found in supplementary material (S1). As hypothesized, we observed nonlinear changes in SOC and total nitrogen (TN) content along the quantity gradient of maize stover in the topsoil, and the microbial community function prediction and necromass data partially supported a trade-off between PE and eE. Relative to the NT0 treatment, topsoil SOC and TN increased with 33% and 100% additions of maize stover mulch and did not change in the 67% treatment (Fig. 1), demonstrating a variable microbial response to the quantity of exogenous C inputs. Amino sugar analyses indicated a nonlinear microbial derived (entombed) C contribution to SOC along mulch gradient. Microbial C accumulated in topsoil SOC with 33% additions of maize stover mulch but contributed little to SOC in the 100% treatment, with the greatest entombing ability in the 67% treatment as a turning point (Table 1). This is similar to the non-linear microbial biomass C accumulation results in Li et al. [26], another study with a gradient of exogenous C inputs. Microbial function prediction and potential biomarker analyses based on the sequencing data indicated an increased microbial degradation of existing SOM along the maize mulch gradient (Figs. 2 and 3) with the extra support from the decreasing SOC trend in subsoil along mulch quantity (Fig. S2). We hypothesized we would observe differences in dominance between EE and existing SOM degradation along the gradient in exogenous C present in this study, and the combination of results as a whole support this. It is evident from the results in this study that greater exogenous C input does not always result in stable SOC formation and deeper SOC improvement. Amino sugar analyses and the ratio of amino sugar accumulation to SOC accumulation indicate differences in the microbial contribution to SOC formation. The rate of microbial necromass accumulation exceeded the SOC accumulation rate in NT33 (ratio = 1.05) and NT67 (ratio = 2), while the opposite was observed in NT100 (ratio = 0.31 < 1) (Table 1). This is evidence of increased microbial necromass contribution to SOC formation under low and medium maize stover additions, and decreased necromass contribution to SOC formation under high maize stover addition, relative to NT0. However, we did observe an increase in the microbial necromass contribution to SOC in NT67 without a corresponding increase in bulk SOC, and a decrease in the microbial necromass contribution to SOC in NT100 with a corresponding increase in bulk SOC, suggesting the existence of another counteractive process, likely the PE, and the shift dominance between EE and PE.
Fig. 1. Comparisons of (a) soil organic carbon and (b) total nitrogen concentrations (g/kg soil) under NT treatments in topsoil layer (0–5 cm). Error bars represent ± standard error of the means. Shared letters are not significantly different, p ≥ 0.05. NT, no tillage. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% return of maize stover mulch.
Topsoil sequencing data analyses provided evidence of increased microbial preference for plant residue C in NT33, but indicated a preference for existing SOM in NT67 and NT100 (Fig. 2). In NT33, the most abundant phylum TM7 (Fig. 2), which has been reported to biodegrade aromatic C compounds such as toluene [27], combining with an increase in genes related to secretion systems from function predication analyses, jointly suggested a change in this treatment toward a higher microbial C use efficiency of plant residue, which was probably through extracellular enzyme secretion (Fig. 3) [28]. In contrast, NT67 and NT100 topsoils were enriched with the microbes, which can grow anaerobically utilizing C sources in oxygen depleted soils due to intensive organic matter decomposition, including the genus Candidatus entotheonella (Fig. 2) in NT67, and the phylum OD1, the class OP11-3 and the order CFB-26 in NT100 [29–32] (Fig. 2). Microorganisms in such an unfavorable environment have been suggested to invest more energy in growth and resource acquisition [33] from existing SOM (PE), which is supported by our observed increase in genes related to DNA repair, recombination proteins, and ribosome biogenesis in NT100 (Fig. 3). The evidence here along with the decreasing trend of SOC observed in NT67 and NT100 subsoils (Fig. S2) suggests priming of 2
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Table 1 Results of amino sugar (AS) analyses and soil organic carbon (SOC) for the topsoil (0–5 cm) in the no-tillage system with maize stover mulch (NT33/67/100). Treatment
Total amino sugar (AS)
Soil organic carbon (SOC)
Mean g/kg
SE
Mean g/kg
NT0
1.01
0.028
13.92
NT33 NT67 NT100
1.11 1.09 1.05
0.046 0.036 0.064
15.23 14.51 15.83
AS rate
SOC rate
Ratio of AS rate to SOC rate
0.10 0.08 0.04
0.09 0.04 0.14
1.05 2.00 0.31
SE 0.085
0.530 0.588 0.799
The ratio of AS rate to SOC rate indicates the relative speed of the accumulation of microbial necromass and SOC content, which could give an indication of microbial necromass contribution to SOC in the treatment relative to NT0. If the ratio > 1, microbial necromass accumulates faster than SOC content, suggesting increased microbial necromass contribution to SOC formation relative to NT0, and vice versa. If the ratio = 1, microbial necromass accumulates as fast as SOC content, suggesting no changes of microbial necromass contribution to SOC formation relative to NT0. The rate of AS and SOC in the treatments with maize stover mulch (NT33/67/100) relative to the treatments without maize stover addition (NT0) were calculated as below: AS rate=(ASNTX - ASNT0)/ASNT0; SOC rate=(SOCNTX SOCNT0)/SOCNT0; X% represents maize stover addition amount. X can be 33,67 or 100. The ratio of AS rate to SOC rate = AS rate/SOC rate. NT, no-tillage. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch. SE, standard error of the means.
existing SOC at the higher end of the maize stover gradient, similar to those priming phenomena observed in Sayer et al. [34], Shahbaz, et al. [5] and Luo et al. [35]. In theory as Liang et al. [10] proposed, SOC accumulates when EE exceeds PE, is unchanged when PE and EE are equal, and is lost when PE exceeds EE. However, this is overly simplified as local conditions such as litter quantity and quality, soil depth and texture, climate and
moisture are all factors. We found evidence of EE dominance in NT33 and PE dominance in NT100. Although topsoil C accumulated in both of these treatments, the biomarker and sequencing data presented in this study demonstrate the microbial influence on the SOM is markedly different. These same data show partial evidence of both EE (biomarkers, Table 1), and PE (LDA scores, Fig. 2 & Subsoil SOC, Fig. S2) occurring the same intensity in NT67, perhaps the reason why bulk SOC
Fig. 2. (a) Histogram of the linear discriminant analysis (LDA) score for the differentially abundant microbes detected in each treatment for the topsoil (0–5 cm) using LEfSe analysis online tool. (b) Cladogram derived from LEfSe analysis for taxonomic representation of significant differences among groups. Only the taxa with meeting a significant LDA threshold score of > 2 were shown. Differences are represented in the color of the most abundant taxa. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch. 3
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Fig. 3. Statistically significant differences in the bacterial predicted functions using PICRUSt analysis and STAMP statistical software in the comparison of no-tillage without and with maize stover mulch for the topsoil (0–5 cm). The graphic shows only the L3 KEGG pathways with statistical differences between the proportions of sequences in each treatment with a confidence interval of 95. NT0, NT33, NT67, and NT100 represent, respectively, 0, 33, 67, and 100% of maize stover mulch.
did not increase in this treatment. Taken as a whole, it is evident that the differences in litter quantity applied in this study created very different environments from the common practice control in this region of complete biomass removal, and further research is needed to fully understand these mechanisms. Our findings improve scientific understanding of the interplay between microbial catabolic and anabolic activities by identifying tradeoffs between PE and EE, and also provide important data for crop residue management in view of social-economic need. The combination of nonlinear changes of SOC, microbial degradation of (PE) and necromass contribution to (EE) existing SOC along a maize stover return quantity gradient provides partial field evidence of an alternative domination of two co-existed processes. Our study demonstrates that a low level of stover mulch (33% of the previous year's aboveground biomass, 2.5 Mg ha−1) leads to net topsoil C accumulation in line with high level stover mulch, and also ensures sufficient aboveground biomass removal for human needs. We would expect the magnitude of C accumulation and quantity of litter additions to change with soil types and other abiotic factors present in other locations, but it is feasible the trends observed in this study carry implications beyond this region in China. Hence, our study contributes much to understanding the role of microbes in SOM formation and stabilization, the importance of microbial influence on agricultural management, and global discussions on soil vulnerability and sustainability of soils for productivity, environmental health, and climate policy.
Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ejsobi.2019.103146. Author contributions X-F.Z., and C.L. designed the study. H-T.X., and X-D.Z. oversaw the field site. X-F.Z. conducted bench work and performed data analysis. XF.Z., M.D.M., and C.L. interpreted and wrote the paper with inputs from all co-authors. References [1] J. Sanderman, T. Hengl, G.J. Fiske, Soil carbon debt of 12,000 years of human land use, Proc. Natl. Acad. Sci. 114 (2017) 9575–9580, https://doi.org/10.1073/pnas. 1706103114. [2] P. Buysse, C. Roisin, M. Aubinet, Fifty years of contrasted residue management of an agricultural crop: impacts on the soil carbon budget and on soil heterotrophic respiration, Agric. Ecosyst. Environ. 167 (2013) 52–59, https://doi.org/10.1016/j. agee.2013.01.006. [3] F. Garcia-Orenes, A. Roldan, A. Morugan-Coronado, C. Linares, A. Cerda, F. Caravaca, Organic fertilization in traditional mediterranean grapevine orchards mediates changes in soil microbial community structure and enhances soil fertility, Land Degrad. Dev. 27 (2016), https://doi.org/10.1002/ldr.2496. [4] J. Six, E.A. Conant RTPaul, K. Paustian, Stabilization mechanisms of soil organic matter: implications for C-saturation of soils, [Review], Plant Soil 241 (2002) 155–176, https://doi.org/10.1023/A:1016125726789. [5] M. Shahbaz, Y. Kuzyakov, F. Heitkamp, Decrease of soil organic matter stabilization with increasing inputs: mechanisms and controls, Geoderma 304 (2015), https:// doi.org/10.1016/j.geoderma.2016.05.019 S0016706116302221. [6] C.E. Stewart, A.F. Plante, K. Paustian, R.T. Conant, J. Six, Soil carbon saturation: linking concept and measurable carbon pools, Soil Sci. Soc. Am. J. 72 (2008) 379–392, https://doi.org/10.2136/sssaj2007.0104. [7] C.E. Stewart, K. Paustian, R.T. Conant, A.F. Plante, J. Six, Soil carbon saturation: concept, evidence and evaluation, Biogeochemistry 86 (2007) 19–31, https://doi. org/10.1007/s10533-007-9140-0. [8] D.S. Powlson, M.J. Glendining, K. Coleman, A.P. Whitmore, Implications for soil properties of removing cereal straw: results from long-term studies, Agron. J. 103 (2011) 279, https://doi.org/10.2134/agronj2010.0146s. [9] F. Heitkamp, M. Wendland, K. Offenberger, G. Gerold, Implications of input estimation, residue quality and carbon saturation on the predictive power of the Rothamsted Carbon Model, Geoderma 170 (2012) 168–175, https://doi.org/10. 1016/j.geoderma.2011.11.005. [10] C. Liang, J.P. Schimel, J.D. Jastrow, The importance of anabolism in microbial control over soil carbon storage, Nat. Microbiol. 2 (2017) 17105, https://doi.org/ 10.1038/nmicrobiol.2017.105. [11] N.W. Sokol, J. Sanderman, M.A. Bradford, Pathways of mineral-associated soil
Declaration of competing interest None. Acknowledgements This work was financially supported by the National Key R&D Program of China (No. 2016YFD0200307) and the National Natural Science Foundation of China (No. 41671297 and 31930070). We would like to thank Dr. H. He for her knowledgeable inputs on the biomarker interpretations. We would like to thank F. Wang and C. He for their assistance with sample collection and processing, and P. Shao and T. Zheng for their assistance with sequencing data analysis. 4
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