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Article

Effects of the Co-Application of Glucose, Nitrogen, and Elevated Temperature on Buried Black Soil Carbon in a Cool Temperate Deciduous Broad-Leaved Forest

by
Yasuo Iimura
* and
Daichi Tanaka
School of Environmental Science, The University of Shiga Prefecture, 2500 Hassakacho, Hikone 522-8533, Japan
*
Author to whom correspondence should be addressed.
Forests 2024, 15(6), 1057; https://doi.org/10.3390/f15061057
Submission received: 24 May 2024 / Revised: 13 June 2024 / Accepted: 17 June 2024 / Published: 19 June 2024
(This article belongs to the Special Issue Soil Carbon and Nutrient Cycling in Forests)
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Abstract

:
Accurately predicting the feedback mechanisms between forest ecosystem carbon cycling and climate change is crucial for effective climate mitigation. Understanding soil organic carbon (SOC) responses to the combined impacts of plant biomass, litter, and nitrogen deposition, especially regarding temperature sensitivity, is essential but remains poorly understood. We conducted incubation experiments using buried black soil from a cool temperate deciduous broad-leaved forest in Japan, which has high C content and a highly stable molecular structure. The stepwise addition of glucose and a temperature increase from 15 to 35 °C accelerated SOC mineralization by 74.0 mg C kg−1 with a positive priming effect (PE) during the 49-day incubation period, while the simultaneous addition of nitrogen had no significant effect on this phenomenon, with SOC mineralization measured at 75.5 mg C kg−1. Conversely, glucose mineralization was significantly accelerated by 10%, from 241.0 to 261.3 mg C kg−1, by stepwise nitrogen addition and temperature increase. Under the combined impacts, the Q10 value of the soil increased significantly from 1.6 to 2.0 compared to that in the unmodified conditions, primarily due to the stepwise addition of glucose. We also found a strong positive correlation between activation energy (Ea) and Q10. This result strongly supports the carbon quality–temperature (CQT) hypothesis. These results likely stem from interactions between SOC quality and carbon availability, suggesting that, in the future, climate change is likely to have a positive feedback effect, especially on buried black soils.

1. Introduction

Soils represent the largest terrestrial carbon reservoir and are intricately linked to atmospheric CO2, plant biomass, and microbial biomass through the carbon cycle [1]. The dynamics of soil organic carbon (SOC), particularly its decomposition and accumulation, are of significant concern because they are influenced by climate change and provide critical feedback [2]. Therefore, understanding SOC dynamics within the context of climate change is crucial for developing accurate global warming prediction models and formulating effective mitigation and adaptation strategies [3,4].
Many studies on the warming response of SOC in forest ecosystems have been reported based on both field and incubation experiments, often expressing it as Q10 (the proportional increase in CO2 released by soil heterotrophic microbes for a 10 °C increase in temperature). While the Q10 values vary across different soils (ranging from approximately 2 to 5), the factors controlling Q10 are not fully understood due to the complexity of soil environments [5,6]. The carbon quality–temperature (CQT) hypothesis suggests that low-quality SOC, which requires a higher activation energy (Ea) for mineralization, exhibits a greater Q10 than high-quality SOC [2,7]. Recent molecular chemical structure analyses of SOC directly support this quality hypothesis [8]. Thus, it is becoming increasingly clear that the quality of SOC is a crucial factor in determining Q10.
Global warming is expected to affect not only soils but also the above-ground vegetation. Increased atmospheric CO2 levels are anticipated to enhance plant growth through photosynthesis in many ecosystems [9,10], likely increasing the influx of plant-derived biodegradable organic material—such as litter, dead roots, and root exudates—into the soil. These changes in SOM mineralization rates due to plant-derived components are known as the priming effect (PE) [11,12]. The PE varies with the soil conditions—temperature [13], moisture [14], and the quality and quantity of organic matter supplied [15,16]—and has shown positive [17,18,19], neutral [20], and negative [21,22,23] outcomes in different soils. Therefore, considering the PE based on plant–soil interactions is essential for accurately understanding the warming response of SOC.
Additionally, nitrogen deposition is emerging as a significant factor influencing future forest soil dynamics [24]. Projections by Galloway et al. (2004) [25] suggest a doubling of nitrogen deposition by 2050 relative to 1990, primarily in the form of inorganic compounds (NO3-N, NH4-N), raising concerns over its impact on forest SOC dynamics. Based on this prediction, it is highly likely that nitrogen deposition will exceed 10–25 kg-N ha−1 year−1 in many forests, leading to significant nitrogen leaching. This, in turn, is a major concern because of its potentially significant impact on deep soils. Studies, including a meta-analysis by Janssens et al. (2010) [26], have shown that nitrogen deposition generally inhibits SOC degradation, underscoring the potential of nitrogen to suppress the microbial degradation of SOC. Recent studies also demonstrate similar trends [27,28], suggesting that nitrogen deposition in soils generally has a high potential to inhibit SOC mineralization. Several reports have also examined the effect of nitrogen deposition on the temperature sensitivity of soil. For example, it was reported that nitrogen deposition does not change or decreases Q10 in semi-arid soils [29], whereas nitrogen deposition increases Q10 by 1.4 times in subtropical soils [30]. This suggests that the effect of nitrogen deposition on Q10 varies considerably depending on the soil environment.
In recent years, studies on the dynamics of SOC related to the interaction between labile C supply and nitrogen deposition have also gradually increased. In a study on deep soils (60–70 cm) from subtropical forests in China, a leaf litter supply (M. macclurei and P. massoniana) promoted a positive PE, but nitrogen (NO3-N, NH4-N) addition reduced the intensity of this effect [16]. Similarly, in a cropping experiment with subtropical forest soils from China, it was reported that the cumulative PE associated with glucose addition was lower after long-term nitrogen addition compared to that obtained without nitrogen addition [19]. Thus, it was reported that the SOC response to the simultaneous addition of labile C and inorganic nitrogen reflects the interaction effects of the individual additions. Studies on the temperature sensitivity of SOC in response to the simultaneous addition of labile C and nitrogen deposition are extremely limited to date. For example, a study by Li et al. (2017) [31] using subtropical soils reported that the simultaneous addition of nitrogen suppressed the PE compared to the addition of glucose alone, and this phenomenon was more pronounced at 25 °C than at 15 °C. This suggests that the temperature sensitivity of SOC changes in response to labile C addition may be further altered by the concurrent addition of nitrogen. However, there are few studies on this topic, and more research is needed as there are many unknowns.
Volcanic ash soil is a major type of soil in Japan, characterized by very thick, dark-colored A horizons with a large amount of organo–mineral complexes of dark-colored organic matter associated with short-range order minerals (particularly allophane and imogolite) and/or monomeric Al and Fe ions (i.e., active Al and Fe) [32,33]. Although this dark-colored SOC is hypothesized to be very stable, the temperature sensitivity of SOC turnover and the PE in this Japanese black soil remain highly uncertain, especially in buried black layers [34,35].
To gain a deeper understanding of the warming response of forest SOC, it is crucial to consider not only the warming itself but also the combined effects of an increased supply of labile organic matter derived from plants and nitrogen deposition. As mentioned above, while there have been relatively many studies of the warming response of SOC to individual factors such as labile C and nitrogen addition, very few studies have examined the warming response of soil under the combined effects of labile C and nitrogen deposition. In addition, none have focused on deep soils, which are key to the warming response of SOC. The aim of this study was to quantitatively assess the temperature sensitivity of SOC under these combined impacts. To achieve this objective, we conducted incubation experiments with stepwise temperature increases while simultaneously adding 13C-labeled glucose and inorganic nitrogen.

2. Materials and Methods

2.1. Soil Sample

A soil sample was collected from the Takayama Experimental Forest, River Basin Research Center, Gifu University, Japan (36°08′ N, 137°25′ E, 1425 m above sea level). Detailed descriptions of this site are available in previous studies [35,36]. In summary, the mean annual temperature is 7.3 °C, and the mean annual precipitation is approximately 2400 mm (2014–2015). Snow covers the ground from December to April, with depths typically ranging from 1 to 2 m. The dominant tree species include Quercus crispula and Betula platyphylla var. japonica. The forest floor is densely covered by dwarf bamboo (Sasa senanensis). The soil at this site is classified as Andisol (Soil Survey Staff, 2014). We collected the soil sample from the deepest 40–50 cm layer of the buried A horizon within a 1 m soil profile. After collection, the fresh soil sample was sieved through a 2 mm mesh, and all visible plant debris and roots were meticulously removed using tweezers. The fresh soil sample was then stored in a refrigerator at 5 °C for approximately 10 days prior to being used in the incubation experiment. Subsamples for soil characterization were air-dried and processed in the same manner as described above. Table 1 presents several soil characteristics from this study, as reported by Iimura et al. (2020) [35].

2.2. Incubation Experiment

The experimental units comprised fresh sieved soil (equivalent to 50 g of oven-dried samples) placed in 500 mL jars and were incubated at progressively increasing temperatures of 15, 25, and 35 °C over a 49-day period. This incubation continued until CO2 emission from the soil stabilized at each temperature condition (7 days at 15 °C, 21 days at 25 °C, and 21 days at 35 °C). Following a 3-day preincubation at 15 °C, the incubation commenced. Glucose (2.188 atom%) was added to the soil at a rate of 0.25 g of C-glucose per kg of dry soil, associated with temperature increases from 15 °C to 25 °C and from 25 °C to 35 °C, resulting in a total of 0.5 g of C-glucose per kg of dry soil. This was based on the amount of root exudate in temperate forests [20]. Additionally, mineral nitrogen ((NH4)2SO4) was applied at a rate of 50 mg of NH4+-N kg−1, timed to coincide with carbon addition, based on the projected future deposition rates of mineral nitrogen (NH4+ and NO3−) in terrestrial ecosystems [25]. Soil samples without glucose and mineral nitrogen served as controls and were similarly mixed to maintain a consistent physical disturbance. The incubation experiment consisted of four treatments (each with three replicates): soil only (S), soil with mineral nitrogen (SN), soil with glucose (SC), and soil with glucose plus mineral nitrogen (SCN). The soil moisture content was adjusted to 60% of the water-holding capacity using distilled water throughout the incubation period. CO2 emissions were captured in a NaOH solution at 7, 14, 21, 28, 35, 42, and 49 days of incubation. A glass vial containing 20 mL of 0.2 M NaOH solution was placed in each jar to trap the emitted CO2, and the jars were sealed after being flushed with CO2-free air. Each time the NaOH solution was replaced, the jars were again flushed with CO2-free air. The carbon content of the NaOH solution was determined by titration [16]. The δ13C of CO2 was analyzed using an EA/IRMS continuous-flow system following carbonate precipitation with excess BaCl2 and filtration [35] every 7 days during the incubation. δ13C measurements were repeated until the standard deviation was less than 0.2‰. Following incubation, the soil was immediately freeze-dried and stored for subsequent microbial biomass analysis.

2.3. Calculation of PE and Q10 and Ea Values

The substrate (glucose) added to the soil allowed for the separation of the respiration rates (mg CO2-C kg−1 soil) of the native soil C (Rsoil) and of the substrate (Rsub) using mass balance equations [35,37] as follows:
Rsoil + Rsub = Rtotal
Rsoil × δ13Csoil + Rsub × δ13Csub = Rtotal × δ13Ctotal
where δ13Csoil is δ13C of the soil C, δ13Csub is δ13C of glucose C, Rtotal is the total CO2 emitted by the soil with glucose, and δ13Ctotal is its δ13C.
The PE (mg C-CO2 kg−1 soil) induced by the addition of the substrate was calculated as:
PE = (Rsoil soil with substrates) − (Rsoil control soil)
where (Rsoil control soil) is the CO2 emitted by the control soil.
The cumulative CO2 released under each temperature condition was converted to the daily emission rate to calculate the Q10 value for the range of 15–35 °C. This calculation was performed separately for total CO2 and soil-derived CO2. According to Yashiro et al. (2011) [38], the temperature dependence of CO2 efflux and Q10 is calculated as:
R = R0 exp (kT)
Q10 = exp10k
where R is the respiration rate, R0 and k are fitting parameters, and T is temperature.
The activation energy (Ea) was determined using the Arrhenius equation [39]. Following the procedures outlined by He et al. (2024) [7], the following calculation was perfromed:
k = Aexp(−Ea/RT)
Here, k denotes the SOM mineralization rate at temperature T (in Kelvin), A is the pre-exponential factor, Ea represents the activation energy required (in Joules per mole), and R is the universal gas constant (8.314 J mol⁻1 K⁻1) [2]. By applying the natural logarithm to both sides of the equation, Ea was determined as the slope of the linear relationship between −1/RT and the natural logarithm of k.

2.4. Microbial Biomass Carbon

Microbial biomass C in each soil sample after the incubation period (49 days) was determined using the adenosine triphosphate (ATP) method [40]. Soil ATP was sequentially extracted with DMSO and Na3PO4. First, 10 mL of DMSO was added to 1 g of soil (freeze-dried), and the mixture was extracted on a stirrer for 2 min. Subsequently, 40 mL of a 0.01 M Na3PO4 solution was added to the same soil, and the mixture was extracted on a stirrer for 2 min, followed by sonication for 2 min. Then, 1 mL of the supernatant was immediately added to 10 mL of a 0.01 M glycine solution (containing 0.005 M Mg-EDTA), mixed, and then used for ATP measurement. ATP was analyzed using a luminometer and a test kit (Lumitester PD-30 and LuciPac PEN, Kikkoman Biochemifa Company, Tokyo, Japan).
The δ13C values of microbial biomass were measured according to Fontaine et al. (2004) [41]. Each 5 g aliquot of soil after incubation was exposed to ethanol-free chloroform for 2 days and then shaken for 1 h with 20 mL of 30 mM K2SO4. The K2SO4 extracts were filtered through 0.3 μm glass fiber filters. The K2SO4 extracts were then lyophilized, and the recovered crystals were stored in a glass desiccator until the analysis of δ13C.
The contribution ratios of labelled microbial biomass (MBsub) and unlabelled microbial biomass (MBsoil) to total microbial biomass C (MBtotal) were estimated using mass balance equations [41] as follows:
MBsoil + MBsub = MBtotal
MBsoil × δ13Csoil + MBsub × δ13Csub = MBtotal × δ13Cmic
where δ13Csoil is δ13C of the soil C, δ13Csub is δ13C of glucose C, and δ13Cmic is δ13C of each K2SO4 extracts.

2.5. Statistical Analysis

For total CO2 emission, soil-derived CO2 emission, and microbial biomass carbon, one-way analysis of variance (ANOVA) was performed. A t-test was performed to compare glucose-derived CO2 emission from SC and SCN and primed CO2 for each treatment and the control. All statistical analyses were performed using StatPlus:mac Pro (version 7.8.11).

3. Results

3.1. CO2 Emission

3.1.1. Total CO2

Figure 1 shows the temporal changes in total CO2 emissions during the incubation period. The differences in total CO2 emissions between treatments tended to increase over time. Notably, significant increases were observed in the SC and SCN samples, where glucose was added, particularly on day 14 of incubation when the temperature increased from 15 °C to 25 °C and after day 28 when the temperature increased from 25 °C to 35 °C. At the end of the 25 °C incubation, CO2 emissions from SC and SCN were 3.7 times higher than from S. At the end of the 35 °C incubation, CO2 emissions were 3.8 times higher from SC and 4.0 times higher from SCN compared to the S, respectively. However, SN did not show such trends and behaved similarly to S.

3.1.2. Glucose and Soil-Derived CO2

Figure 2a,b show the temporal changes in CO2 emissions from soil and glucose during the incubation period, respectively. The temporal changes in CO2 emissions from the soil showed a trend similar to that of the changes in total CO2 emissions, shown in Figure 1, with significantly higher values for SC and SCN where glucose was added. SC and SCN exhibited significant changes on days 14 and 28, when glucose was added and the temperature increased, with CO2 emissions being 1.7 times higher than from S at the end of the 25 °C incubation and 1.7 times higher at the end of the 35 °C incubation. In contrast, S and SN showed similar trends with no significant differences between them. The CO2 emissions from glucose were generally higher than those from soil, with 1.3 times higher emissions from SC and 1.4 times higher from SCN. Up to day 28 at 25 °C, there were no significant differences between SC and SCN, but significantly higher values were observed for the SC treatment after day 28 when the temperature increased to 35 °C. This trend continued until the end of the incubation period.

3.2. Priming Effect

Table 2 shows the calculated PE from soil-derived CO2 emissions in each treatment. SN showed a trend of lower CO2 emissions compared to S throughout the incubation period, ranging from −9.5 to 1.0 mg C kg−1, but this difference was not significant, and the PE remained neutral. In contrast, SC and SCN had significantly higher soil-derived CO2 emissions compared to S, except at 15 °C, with PE values at 25 °C and 35 °C ranging from 22.4 to 74.0 mg C kg−1 and from 21.1 to 75.5 mg C kg−1, respectively. The PE tended to increase at higher temperatures and with longer incubation periods.

3.3. Temperature Sensitivity

3.3.1. Q10 Values

The results for Q10 calculated from total CO2 emissions and soil-derived CO2 emissions are shown in Figure 3a,b. Both Q10 values exhibited similar trends across different treatment intervals, with significantly higher values for SC and SCN compared to S and SN. The Q10 for total CO2 emissions ranged from 1.6 to 3.3, with the lowest value in S, and the highest value in SCN. Additionally, the Q10 of soil-derived CO2 emissions ranged from 1.6 to 2.0, with the lowest value in S, and higher values in both SC and SCN.

3.3.2. Activation Energy (Ea)

The activation energy (Ea) for each treatment plot showed a similar trend to that of Q10 (Figure 4a,b). For total CO2 emissions, Ea ranged from 34 to 88 kJ mol⁻1, with significantly higher values for SC and SCN compared to S and SN. For soil-derived CO2 emissions, Ea ranged from 34 to 53 kJ mol⁻1, and similar to what observed for total CO2 emissions, the SC and SCN samples showed significantly higher values compared to S and SN. A very strong positive correlation (r = 0.999, p < 0.001) was observed between Q10 and Ea for both total CO2 and soil-derived CO2 (Figure 5a,b).

3.4. Microbial Biomass Carbon

Figure 6 shows the results of microbial biomass for each treatment plot at the end of the incubation period. The microbial biomass in each treatment plot ranged from 45 to 85 mg C kg⁻1. The differences among the treatment plots showed a similar trend to that of Q10 and activation energy, with significantly higher values for the SC and SCN plots compared to the S and SN plots. Additionally, in the SC and SCN plots, 96% of the total biomass was unlabeled.

4. Discussion

In this study, the addition of glucose to buried black SOC resulted in the accelerated decomposition of SOC due to a positive PE. Additionally, this trend intensified with an increasing temperature from 15 °C to 35 °C. The concurrent nitrogen addition enhanced the mineralization and the temperature sensitivity of the added glucose, while having a minimal impact on the mineralization of SOC. This suggests that future increases in nitrogen deposition due to climate change may not be a significant factor in the mineralization of buried black SOC. On the other hand, the addition of nitrogen to soil may promote the mineralization and assimilation of glucose through microbial activity and further stabilize it onto soil particles, effects which could be further accelerated by rising temperatures. Hereafter, we will discuss the effects of the coexistence of glucose addition, nitrogen addition, and warming on the dynamics and temperature sensitivity of glucose and buried black SOC.

4.1. Glucose Dynamics

Throughout the 49-day incubation period, glucose was added to the soil in two stages, i.e., at a temperature from 15 °C to 25 °C and at a temperature from 25 °C to 35 °C, each time adding 0.25 g C kg−1, resulting in a total of 0.5 g C kg−1. The CO2 derived from glucose, calculated using stable isotope ratios, amounted to approximately 0.25 g C kg−1, which is half of the total added amount. In contrast, the carbon derived from glucose detected in the soil microbial biomass at the end of the incubation was only about 3 to 4 mg C kg−1 (Figure 6). Considering that glucose is not adsorbed onto soil particles [42], is a major substrate assimilated by soil microorganisms [43], and is available to most microorganisms [44], it is possible that approximately half of the added glucose was assimilated by microorganisms and that its residues were stabilized in the soil [45]. Such soil carbon sequestration processes mediated by microbial assimilation have recently attracted attention [46,47]. Additionally, the temperature sensitivity of glucose was significantly higher in SCN than in SC (Figure 2b), suggesting that the mineralization, assimilation, and stabilization of glucose in soil are enhanced by nitrogen addition. These phenomena have been described by the stoichiometric theory, which indicates that the mineralization of labile organic matter dominated by r-strategists is particularly accelerated by the addition of nitrogen [48]. Thus, it is possible that glucose, through interactions with black SOC mediated by microorganisms, was converted into a relatively stable part of SOC. This might be one of the reasons why the Q10 of SOC was significantly higher in SC and SCN (see Section 4.3). Directly elucidating these processes remains a challenge for future research.

4.2. SOC Dynamics

The mineralization rate of SOC exhibited a general increasing trend, particularly with the addition of glucose, which showed a positive PE that accelerated by rising temperatures (Figure 2, Table 1). In contrast, no significant effect of nitrogen addition was observed. Research on the PE induced by the addition of labile organic matter (carbon and nitrogen) and its temperature sensitivity has intensified in recent years due to their importance. For instance, a 57-day incubation experiment with temperate forest soil in China demonstrated a negative PE at 5 °C following glucose addition, while positive PEs were observed at 15 °C and 25 °C, with the magnitude increasing with temperature [14]. Additionally, an incubation study using temperate grassland soil collected from a long-term, 7-year field warming experiment showed that the addition of wheat straw accelerated SOM mineralization by 12.7%, indicating that warming enhances SOM mineralization via PE [49]. These findings support our results. Conversely, Li et al. (2023) [50] conducted a meta-analysis of 146 observations from 57 independent soils worldwide, showing that experimental warming significantly suppressed ΔPE (the difference in PE between control and warming treatments) by 0.26. Such contrasting results highlight the complex effects of warming on the PE. The PE and its response to warming in soil are likely dependent on the quantity and quality of the added substrate, particularly the nitrogen content relative to that of labile carbon. SOM is generally more recalcitrant than newly added labile organic matter, and it is well known that the PE is promoted in a positive direction by nitrogen deficiency (high CN ratio) relative to labile carbon content [41,48]. This phenomenon is widely recognized as the N mining theory, a key PE mechanism that also significantly influences the temperature dependence of the PE [37,41,48]. The aforementioned meta-analysis also found that agricultural soils, which are less prone to nitrogen limitation, exhibited a high suppression rate of 0.43, whereas the PE in nitrogen-limited forest soils remained unaffected by warming [50]. Our findings suggest that the positive PE of SOC accelerated with rising temperatures regardless of nitrogen addition, indicating a potential absolute nitrogen limit for SOM mineralization. Conversely, the mineralization of glucose was accelerated by nitrogen addition in this study, suggesting that the optimal CN ratio for substrate utilization may vary. A detailed evaluation of the relationship between the CN ratio of more labile forms and the decomposition characteristics of substrates with different recalcitrance levels could provide clearer insights.

4.3. Temperature Sensitivity

In comparison to the S and SN treatments without glucose addition, the SC and SCN treatments with incremental glucose additions showed significantly higher Q10 values for both total CO2 and SOC-derived CO2 (Figure 3a,b). Although the main factors influencing the Q10 of SOC remain uncertain, the soil carbon energy state [51] and SOC quality [2] are often recognized as key factors. Recently, Zhang et al. (2024) [52] demonstrated that the interaction between SOC quality and carbon availability universally impacts Q10. Specifically, when carbon availability is not limited, SOC quality determines the sensitivity, with more recalcitrant SOC exhibiting a higher Q10. Conversely, when carbon availability is limited, substrate availability determines Q10. The black SOC used in this study is known to be of very low quality with high aromaticity compared to other SOM types [29,32], suggesting that increased carbon availability due to glucose addition in SC and SCN resulted in higher Q10 values compared to those for S and SN. This is further supported by the strong positive correlation between Ea and Q10 (Figure 5b). The CQT hypothesis, widely known [2,7], posits that lower quality SOC requires higher Ea. Additionally, Wagai et al. (2013) [8] analyzed the relationship between the SOC quality of the light fraction (<1.6 g cm−3) and temperature sensitivity using volcanic ash soil, finding that higher proportions of carbon resistant to enzymatic decomposition (aromatic carbon and aliphatic carbon) were associated with higher Q10 values. Considering these findings along with the theory of SOC quality–carbon availability interactions, it can be inferred that low-quality SOC, with high proportions of aromatic and aliphatic carbon, exhibits increased Q10 in response to the supply of highly available glucose.

5. Conclusions

To elucidate the response of SOC to the combined impacts of glucose addition, nitrogen addition, and warming, particularly its temperature sensitivity (Q10, Ea), we conducted an incubation experiment using buried black soil as the test soil. The results revealed the following:
1. The stepwise addition of glucose significantly increased the Q10 of SOC, whereas the simultaneous addition of nitrogen had no effect on Q10.
2. The decomposition of glucose increased with the stepwise addition of nitrogen, especially under high-temperature conditions (35 °C), with approximately half of the glucose being released as CO2, and the remainder retained in the soil.
3. There was a strong positive correlation between Ea and Q10, strongly supporting the CQT hypothesis.
Furthermore, the findings in points 1 and 3 are likely the result of the interaction between SOC quality and carbon availability, and point 2 suggests that a portion of the added glucose was stabilized in the soil through microbial activity. The results of this study provide important insights for more accurately predicting the dynamics of highly stable buried black SOC.

Author Contributions

Conceptualization, Y.I.; validation, Y.I. and D.T.; formal analysis, Y.I. and D.T.; investigation, Y.I. and D.T.; data curation, Y.I.; writing—original draft preparation, Y.I.; writing—review and editing, Y.I. and D.T.; project administration, Y.I.; funding acquisition, Y.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Japan Society for the Promotion of Science KAKENHI (17K00524, 20K12138) to Y.I.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We thank the members of the Laboratory of Soil Science at The University of Shiga Prefecture for their discussion on this research.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Cumulative total CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Asterisks (***) indicate significant differences at p < 0.005 by one-way analysis of variance (ANOVA).
Figure 1. Cumulative total CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Asterisks (***) indicate significant differences at p < 0.005 by one-way analysis of variance (ANOVA).
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Figure 2. (a) Cumulative soil-derived CO2 and (b) glucose-derived CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Asterisks (***) indicate significant differences at p < 0.005 by one-way analysis of variance (ANOVA).
Figure 2. (a) Cumulative soil-derived CO2 and (b) glucose-derived CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Asterisks (***) indicate significant differences at p < 0.005 by one-way analysis of variance (ANOVA).
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Figure 3. Q10 values of (a) total and (b) soil-derived CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
Figure 3. Q10 values of (a) total and (b) soil-derived CO2 emissions from each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
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Figure 4. Activation energy (Ea) calculated from (a) total CO2 and (b) soil-derived CO2 for each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
Figure 4. Activation energy (Ea) calculated from (a) total CO2 and (b) soil-derived CO2 for each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
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Figure 5. Relationship between Q10 and Ea in (a) total CO2 and (b) soil-derived CO2 for each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N.
Figure 5. Relationship between Q10 and Ea in (a) total CO2 and (b) soil-derived CO2 for each treatment. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N.
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Figure 6. 13C-labeled (green) and unlabeled (blue) microbial biomass in each treatment plot. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
Figure 6. 13C-labeled (green) and unlabeled (blue) microbial biomass in each treatment plot. S: soil only (control); SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Bars indicate the standard error of the mean (n = 3). Values with different letters are significantly different (p < 0.05) by Tukey’s HSD post hoc test.
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Table 1. Characteristics of the soil used in this study as demonstrated by Iimura et al. (2020) [35].
Table 1. Characteristics of the soil used in this study as demonstrated by Iimura et al. (2020) [35].
DepthpHT-CC:N RatioMI 1δ13C14C Age 2
(cm)(H2O)(KCl)(NaF)(g kg−1) (‰)(YrBP)
40–505.1 4.3 11.5 89.4 16.0 1.64−19.84764–5082
1 The melanic index of soil humus. 2 The 14C age of soil samples from 40 to 45 cm and from 45 to 50 cm, respectively.
Table 2. Primed CO2 emissions from each treatment. SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Asterisks (*, **, ***) indicate significant differences at p < 0.05, p < 0.01, and p < 0.005, respectively (t-test).
Table 2. Primed CO2 emissions from each treatment. SN: soil with mineral N; SC: soil with glucose; SCN: soil with glucose plus mineral N. Asterisks (*, **, ***) indicate significant differences at p < 0.05, p < 0.01, and p < 0.005, respectively (t-test).
Primed CO2 (mg C kg−1)
DaysTemp. °CSNSCSCN
7150.6 ± 1.90.8 ± 2.91.1 ± 3.3
1425−7.4 ± 2.922.4 ± 2.9 *21.1 ± 3.6 *
2125−8.3 ± 2.427.3 ± 2.6 **26.3 ± 3.8 *
2825−9.5 ± 2.233.7 ± 2.2 ***34.3 ± 2.9 ***
3535−2.6 ± 1.361.5 ± 0.4 ***59.2 ± 2.6 ***
4235−0.8 ± 1.867.0 ± 1.4 ***67.6 ± 2.7 ***
49351.0 ± 2.174.0 ± 1.7 ***75.5 ± 2.9 ***
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Iimura, Y.; Tanaka, D. Effects of the Co-Application of Glucose, Nitrogen, and Elevated Temperature on Buried Black Soil Carbon in a Cool Temperate Deciduous Broad-Leaved Forest. Forests 2024, 15, 1057. https://doi.org/10.3390/f15061057

AMA Style

Iimura Y, Tanaka D. Effects of the Co-Application of Glucose, Nitrogen, and Elevated Temperature on Buried Black Soil Carbon in a Cool Temperate Deciduous Broad-Leaved Forest. Forests. 2024; 15(6):1057. https://doi.org/10.3390/f15061057

Chicago/Turabian Style

Iimura, Yasuo, and Daichi Tanaka. 2024. "Effects of the Co-Application of Glucose, Nitrogen, and Elevated Temperature on Buried Black Soil Carbon in a Cool Temperate Deciduous Broad-Leaved Forest" Forests 15, no. 6: 1057. https://doi.org/10.3390/f15061057

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