the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Drivers of soil C quality and stability: Insights from a topsoil dataset at landscape scale in Ontario, Canada
Abstract. Although soil C is a critical component of soil health, studies robustly exploring the agronomic and pedoclimatic effects on soil C are limited, especially at the landscape scale. Therefore, a dataset of 1511 samples from agricultural fields across Ontario was used to evaluate the impacts of agronomic and pedoclimatic factors on eight soil C indicators including chemistry and thermal stability of soil C using the programmed pyrolysis approach. Soil C quality and stability were largely controlled by the inherent soil characteristics such as soil texture. Significant interactive effects of cropping system and tillage intensity on soil C indicators were observed; however, the number of significant effects varied among the three soil textural classes. All soil C indicators were significantly different among the cropping systems for the coarse textured soils, but the cropping system differences decreased under medium and fine textured soils. From the pyrolysis analysis, the hydrogen index (HI) and oxygen index (OI) also confirmed that the soil C chemistry was influenced by the cropping system. For instance, orchard systems had stable pools of soil C whereas vegetable systems were associated with less advanced degree of soil C decomposition. Remaining soil management variables (cover crop use, tillage intensity, and organic amendments) had less influence on soil C indicators in all soil textural classes. Principal component analysis revealed a close association of soil C indicators with the mean annual precipitation (MAP) and cropping system; suggesting that the quantity and quality of soil C inputs associated with different cropping systems and increase in precipitation had a large influence on soil C. Our results confirm the significant effects of agronomic and pedoclimatic variables on chemistry, thermal stability, and composition of soil C pools, which have long-term implications on soil C storage, mitigating global climate change, and improving soil health.
- Preprint
(901 KB) - Metadata XML
-
Supplement
(374 KB) - BibTeX
- EndNote
Status: open (extended)
-
RC1: 'Comment on egusphere-2025-1055', Anonymous Referee #1, 28 Aug 2025
reply
Dear Editors and Authors,
This manuscript investigates the effects of agronomic practices and pedoclimatic factors on soil carbon (C) quality and stability using a large topsoil dataset (1490 samples post-filtering) from Ontario’s agricultural landscapes. The study’s strength lies in its landscape-scale focus—addressing a critical gap in small-plot-dominated soil C research—and its integration of both traditional (e.g., soil organic carbon [SOC], permanganate oxidizable C [POXC]) and novel (Rock Eval Pyrolysis) C indicators. The findings, particularly regarding the primacy of soil texture and cropping systems as drivers of soil C dynamics, offer relevant implications for sustainable agriculture and climate change mitigation. While the core research question and dataset are valuable, the manuscript requires minor revisions before acceptance.
- Abstract
Line 12: It is better to correct sample size to "a dataset of 1490 topsoil samples" or "a dataset of 1490 post-filtered topsoil samples” here.
Line 23: The statement "Remaining soil management variables (cover crop use, tillage intensity, and organic amendments) had less influence" is vague (e.g., "less influence" relative to what?) and conflicts with two key sources. Table 1 shows tillage intensity explains 18.0% of variance in Cmin-96h and 22.3% in ACE; Table 2 further demonstrates tillage significantly affects POXC in fine-textured soils (P=0.0210). The Introduction cites Sun et al. (2023) and Balota et al. (2004), who show reduced tillage and cover crops increase SOC and C mineralization.
I suggest revising vague "less influence" to "weaker influence than texture/cropping systems"
- Introduction
Line 41: The Introduction cites Weil et al. (2003) for POXC, while Section 2.2 references Moebius-Clune et al. (2016) for POXC methods. The former is the original POXC protocol, the latter is the revised method? Please reconcile the two citations.
- Materials and Methods
Lines 101–102: The original description "Soil samples were collected …… terminated at 30 cm" is ambiguous. Confirm and revise to: "Soil samples were collected from the Ap horizon (agricultural tilled layer). To ensure all samples were restricted to this horizon, sampling was terminated at 30 cm if the Ap horizon exceeded this depth; the median thickness of the sampled Ap horizons across all sites was 25 cm."
Line 112: Overlapping soil texture ranges
The current texture classifications (coarse: 52–94% sand; medium: 2–78% sand; fine: 1–45% sand) have overlapping ranges, leading to ambiguous categorization. Why did the Ref. Moebius-Clune et al., 2016 do like this?
Line 130: Explain ACE (n=151) was measured only on the 151 pyrolysis subsamples (representative of full dataset), tell the reader they are the same 151 samples.
Line 153-162: Programmed pyrolysis (Section 2.2) is central to the study’s novel insights, but key parameters are omitted: helium flow rate (critical for hydrocarbon capture), sample weight precision (±0.1 mg?), and calibration standards used for S1/S2/S3 quantification.
Lines 163–164: the definition of T50 ("temperature at which 50% of the SOC was pyrolyzed") conflicts with the cited reference (Gregorich et al., 2015), which defines T50 for pyrolyzable C (not total SOC).
- Results and Discussion
Soil texture explains 60.5% of SOC variance (Table 1)—the largest driver—but the manuscript only attributes this to "inherent soil characteristics" without linking it to specific processes (e.g., clay mineral adsorption, aggregate protection of C). I suggest expanding discussions to: "Soil texture was the strongest driver of SOC (explaining 60.5% of variance; Table 1), primarily due to texture-mediated C stabilization processes: fine-textured soils (high clay content) enhance C retention via clay mineral adsorption (e.g., smectite and illite bind organic molecules) and aggregate protection (microaggregates physically isolate SOC from microbial decomposition). This aligns with Figure 1B, where fine-textured soils had the highest T50 (greater thermal stability), likely due to increased clay-C binding capacity compared to coarse/medium-textured soils."
Table 1: "Model R²" values (0.16–0.37) are low, indicating unaccounted variance? Other potential variables (e.g., crop residue input rates, microbial community composition, or historical land use,……)? The manuscript does not address this, leaving readers to question if key drivers were omitted.
Line 193: "Tillage intensity was not found to be an important predictor" contradicts Table 2, where tillage affects POXC in fine-textured soils (P=0.0210). Qualify this statement.
Line 201: Perennials and forages had greatest SOC aligns with Table 3, but Table 3 shows coarse-textured perennial SOC (19.4ab) is not statistically distinct from annual grain (16.9ab). Soften the claim to "greater or comparable concentrations."
Line 213: "Diversification of cropping systems... critical for building soil C"—no data on residue inputs to support "quantity/quality of C inputs" as the mechanism. Add a discussion linking cropping systems to measured C inputs (if available) or cite literature on residue differences.
Line 253: "In coarse-textured soils, Cmin-96h, POXC... were significantly impacted by tillage"—Figure 2 (boxplots) for these indicators shows overlapping ranges between tillage intensities, weakening the "significant" claim. Discuss effect size alongside statistical significance.
Line 260: "Medium and fine textured soils had more interactions than coarse"—no explanation for this pattern (e.g., texture-mediated microbial activity). Add a mechanistic hypothesis.
Line 262: Inconsistent terminology: "tillage intensity" vs. "tillage treatments" (Line 262). Standardize to "tillage intensity."
Line 268: "Vegetable systems... less advanced decomposition" is supported by Figure 3 (high HI, low OI), but Table 3 shows vegetable OI in coarse soils (147) is lower than orchard (203) but not statistically distinct from annual grain (168). Clarify this nuance.
Figure 6: "Cover crop" is negatively associated with C indicators, but Table 1 shows cover crops explain <5% variance. Discuss why this association is weak (small sample size: n=55?).
Table 4: "HI vs. ACE (r=0.59***)"—ACE is a labile N/C proxy, but no discussion of why hydrogen-rich labile C correlates with protein. Link this to microbial metabolism of fresh organic matter?
- Conclusion
It is better to explicitly add methodological limitations, e.g. (1) Tillage intensity categories (e.g., 'light disturbance,' 'no disturbance') relied on producer self-reporting of descriptive terms, with no objective metrics (e.g., plowing depth, number of tillage passes) to standardize classification—introducing bias, as 'light disturbance' may vary by grower interpretation; (2) The small sample size for cover crops (n=55) and orchards (n=33) limits the generalizability of results for these management systems. Future studies should adopt objective tillage measurements and balance sample sizes across management categories to strengthen conclusions.
Best regards
Dr. Chao Song
Citation: https://doi.org/10.5194/egusphere-2025-1055-RC1
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
367 | 73 | 17 | 457 | 41 | 17 | 37 |
- HTML: 367
- PDF: 73
- XML: 17
- Total: 457
- Supplement: 41
- BibTeX: 17
- EndNote: 37
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1