The manuscript explores the impact of micro-scale heterogeneity on biogeochemical processes and gas transport in peat soils using a 13C pulse-chase assay and X-ray microtomographic imaging. While the topic is relevant, several critical issues warrant rejecting this manuscript in its current form.

Literature Review:

• The manuscript lacks comprehensive references to existing literature, predominantly citing the authors' previous works. A thorough literature review is essential for contextualizing the study and demonstrating its novelty. The claim that this is the first investigation into spatial heterogeneity in biogeochemical transformation rates appears overstated. Relevant literature includes DOI: 10.1016/j.geoderma.2022.116224, 10.1007/s00374-022-01673-6, 10.1016/j.scitotenv.2023.165192, https://www.ssrn.com/abstract=4092466, 10.1016/j.soilbio.2022.108565, 10.5194/bg-18-1185-2021, 10.1007/s11104-021-04871-7, 10.3389/fenvs.2018.00017, 10.1038/ngeo2963, and 10.1111/gcb.14855.

Experimental Design:

• The study's experimental design lacks clarity or is simply wrong for answering all hypotheses. There were seven replicates for two treatments, but it's unclear how samples were labeled and analyzed at different depths. The division of replicates across three depths at multiple time points compromises the factorial design and diminishes the robustness of replication. A mixed effect model can deal with small sample numbers. However, the nested design, with depths and time points nested within field samples, requires careful statistical handling (need to be included in the error term), which the current sample size may not support adequately.

Introduction and Hypotheses:

• The introduction fails to provide a strong motivation or hypothesis for analyzing different depths. Key parameters are introduced without sufficient context, making many results appear as unstructured data dumps rather than addressing specific research questions.

Discussion and Conclusions:

• The discussion is weak, lacking depth and failing to integrate findings with existing literature. The conclusion that heterogeneity is significant at the core and within-core scales but not at the stand scale is unsupported by the study design, as the core scale and stand scale are conflated. There are no real replicates on the plot scale.

Methodological Details:

• Essential details about the scanning procedure, such as panel size, exposure time, and number of projections, are missing, hindering reproducibility. Additionally, the rationale for cropping images to 90 mm diameter instead of the full 100 mm is unclear, especially considering the impact of fissures and cracks on diffusion, which is evident in the radial porosity analyses.

Pore Network Modeling:

• The term "pore network modeling" is misleading. The study employs image analysis algorithms to extract features like porosity and connectivity, but does not engage in actual modeling of pore networks.

Minor Comments:

• There are several language mistakes / missing words
• Abstract: The sentence "Greater peat air-filled porosity was and pore network metrics could not explain the fraction of label converted to CO2, but greater porosity as well as higher clustering coefficients and betweenness centrality were associated with slower CO2 emissions" needs correction. Clustering coefficients and betweenness centrality should be introduced for reader comprehension.
• Introduction: The first two sentences are misplaced. Begin with the broader relevance of the study.
• Line 18: Contrary to the authors' claim, there is a growing body of literature using X-ray CT and other methods to explore pore heterogeneity in soil functions.
• Line 27: Replace with "anaerobic."
• Line 172: Clarify that certain parameters are critical for transport properties but are not transport properties themselves. Provide references.
• Figures: Ensure all y-axis titles in Figures (e.g., Fig. 2, Figs. 4-6) have correct subscripts. The physics of porous media should be correctly attributed (Line 36). Consider moving Fig. 2 to supplementary information.
• Statistical Analysis: Include a reference for the mixed effect model and details on testing assumptions. The p-value in Fig. 8(e) should be clarified.