the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 May 2025
Fresh tephra deposits from the Tajogaite Volcano boost thermophile proliferation and soil organic matter recovery
Abstract. Tephra fallout deposition during volcanic eruptions overlays existing soils, profoundly altering their physical, chemical, and biological properties. This study investigates the impact of the newly deposited tephra blanket from the 2021 Tajogaite eruption (La Palma Island) on the molecular composition of soil organic matter and microbial diversity across different soil horizons. A combination of 16S and 18S rRNA gene sequencing, pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), and elemental and isotope ratio mass spectrometry (EA/IRMS) was employed. Our results demonstrate that tephra deposits significantly modify the organic matter composition of the underlying soils, promoting microbial activity linked to the degradation and transformation of organic carbon and nitrogen compounds. The soil horizon directly beneath the tephra layer (horizon O) displayed a higher abundance of labile organic compounds and a reduced presence of recalcitrant compounds compared to the deeper horizons (A and Bw). This pattern is strongly associated with the predominance of thermophilic bacteria, which contribute actively to the breakdown of complex organic materials such as lignin and hydrocarbons, and drive key biogeochemical processes including nitrogen and carbon cycling. The continuous geothermal influence of nearby fumaroles further supports the persistence and ecological success of thermophilic communities in these volcanic soils. These findings underscore the critical role of volcanic activity not only in reshaping soil structure but also in enhancing soil fertility and resilience through microbial-mediated processes. Understanding these dynamics is essential for soil management and ecosystem recovery strategies in volcanic regions, providing new insights into the long-term effects of tephra deposition on soil health and the carbon cycle.
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RC1: 'Comment on egusphere-2025-2086', Anonymous Referee #1, 05 Nov 2025
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1 关键假设：引言最后陈述了研究目标，但缺乏明确的科学假设。这使得读者很难事先建立预期的逻辑框架。2 方法描述样本过多且无序。凋落物特性分析以及 DNA 提取、PCR 扩增和 Illumina MiSeq 测序样本过多。引物序列是什么？生物信息学分析和统计处理完全不同。本节不包含生物信息学分析。3 微生物样本的取样方法尚不清楚。是混合样本吗？包括重复多少次？该方法描述了 5 个样本的测定。但微生物学结果中的数据没有反映重复，没有生物统计学意义。4 根据论文规则，建议根据结果和讨论分章写。5 微生物剖面的结果过于简单化。建议增加对土壤元素和土壤微生物的分析。ReplyCitation: https://doi.org/
10.5194/egusphere-2025-2086-RC1 -
CC1: 'Reply on RC1', Nicasio T. Jiménez-Morillo, 28 Jan 2026
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Dear Referee #1. Thank you very much for taking the time to read our article. We appreciate your inputs and comments. We hope the answers provided herein respond satisfactorily to your questions and recommendations. Please note that none of the authors speaks Chinese, which may affect the precision of our replies.
- Key Hypotheses: The introduction states the research objectives but lacks clear scientific hypotheses. This makes it difficult for readers to establish the expected logical framework beforehand.
Answer: Thank you for your comment. The last paragraph of the introduction has been modified to explicitly include the hypothesis as follows: “Under the hypothesis that tephra deposits from volcanic eruptions can modify the microbiota and the organic matter composition of the underlying soils, this work aimed to investigate the impact of the Tajogaite volcanic eruption on the molecular and microbial diversity of an existing soil profile covered by tephra deposits and elucidate its influence on soil resiliency and ecosystem recovery capacity. Using advanced molecular and microbiological techniques, including pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), stable isotope analysis, and 16S rRNA gene-sequencing, the soil profile was analysed to unravel how volcanic ash alters SOM quality and microbial community structure. ”
- Methods Description: Too many samples are described, and the descriptions of litter characterization, DNA extraction, PCR amplification, and Illumina MiSeq sequencing are excessive. What are the primer sequences? Bioinformatics analysis and statistical processing are completely different. This section does not include bioinformatics analysis.
Answer: We thank the reviewer for this helpful suggestion. We have thoroughly revised the Methods section to improve clarity and conciseness and to ensure that laboratory procedures, sequencing, bioinformatics, and downstream analyses are clearly separated:
Sample description and level of detail: We simplified the description of the amplicon dataset and reduced redundant methodological text. The revised section now focuses on the essential information required for reproducibility.
Primers and sequencing information: We added the complete primer information used to amplify the V3–V4 region, including primer names and sequences (341F: 5′-CCTACGGGNGGCWGCAG-3′; 805R: 5′-GACTACHVGGGTATCTAATCC-3′), and clarified that library preparation and sequencing (Illumina MiSeq, 2 × 250 bp) were performed by Novogene. This information is now provided in Section 2.4 (DNA extraction and 16S rRNA gene amplicon sequencing).
Bioinformatics vs statistical analyses: Following the reviewer’s recommendation, we separated bioinformatic processing into two well-differentiated subsections (Section 2.5, Bioinformatic processing and Section 2.6 Diversity and statistical analyses).
- 2.5. Bioinformatic processing:
Raw paired-end reads were processed using QIIME 2 (v2024.5) (Bolyen et al., 2019). Primer sequences were removed prior to denoising to prevent primer-derived artifacts and to improve read merging. Reads were then quality filtered and denoised using the q2-dada2 plugin (Callahan et al., 2016), which infers exact amplicon sequence variants (ASVs) by modeling sequencing errors and resolving unique biological sequences. Forward and reverse reads were merged to reconstruct the full V3–V4 amplicon, generating an ASV feature table for downstream ecological analyses. Chimeric sequences produced during PCR amplification were identified and removed using the consensus approach implemented in DADA2, reducing spurious diversity. Taxonomy was assigned with a Naïve Bayes classifier trained on the V3–V4 region against the SILVA reference database (release 138) (Quast et al., 2013), ensuring that taxonomic classification was optimized for the targeted amplicon region.
- 2.6. Diversity and statistical analyses
Alpha diversity analyse was computed in QIIME 2 (v2024.5). Alpha diversity was calculated to summarize within-sample diversity using richness and diversity indices (e.g., observed ASVs, Chao1, Shannon, and Simpson, as appropriate). To aid interpretation of the ordination, we produced a PCoA biplot by projecting (i) geochemical/pyrolytic descriptors (e.g., compound-class abundances from pyrolysis and elemental contents) and (ii) the relative abundances of dominant microbial phyla onto the same ordination space. Vectors (arrows) represent the direction of increasing values for each variable and their strength of association with the ordination axes (longer vectors indicate stronger relationships). This combined representation was used to highlight which chemical pools and microbial groups co-varied across samples and to identify the main gradients driving separation along PCo1 and PCo2.”
- Sampling Methods for Microbial Samples: Are they pooled samples? How many replicates are included? The method describes the determination of 5 samples. However, the data in the microbiological results do not reflect replication and lack biostatistical significance.
Answer: Thank you for your helpful comments. Each of the samples is composed of a mixture of 5 subsamples. Regarding the number of samples, there are 6 composed samples studied, to clarify this better in the article, the section “2.1 Study site and sampling” has been modified as follows:
- “Sampling included the collection of moss growing on the fresh tephra (MOSS), the tephra layer directly beneath the moss cover (moss substrate, MS), a dark green biofilm on horizon O (Biofilm), and three soil horizons: 0–2 cm (Horizon O) (0–2 cm), A (2–10 cm) (Horizon A) and Bw (10–20 cm) (Horizon Bw) (Fig. 1B). All samples analyzed in this study were composite samples, generated by collecting five subsamples per sample type across distinct sampling points and/or soil horizons, followed by thorough homogenization and pooling into a single representative mixture.”
- Regarding biostatistical significance, we analyzed five composite samples. Each composite was generated by pooling and thoroughly homogenizing five subsamples collected across different sampling points and/or horizons; therefore, each composite is intended to integrate within-site heterogeneity and provide a representative molecular and microbial profile of the corresponding condition. In addition, given the substantial analytical workload required for comprehensive molecular and microbial identification, together with the high cost of these analyses, this study was designed as an in-depth, high-resolution characterization. We consider this approach appropriate to obtain a robust and accurate overview of the dominant compositional patterns in these samples.
- According to the thesis guidelines, it is recommended to separate the results and discussion into chapters.
Answer: Thank you very much for your comment. We fully understand that separating the Results and Discussion sections can be beneficial. However, given the strongly multidisciplinary nature of the study and the use of advanced analytical techniques, we believe that presenting Results and Discussion together provides a clearer, more coherent view of the work and its objectives.
- Microbial profile results are overly simplified: It is recommended to add analyses of soil elements and soil microorganisms.
Answer: We greatly appreciate your comment. In response, we have added a new section presenting a comparative and statistical assessment of the analyzed samples based on principal coordinates analysis (PCoA), integrating elemental C and N data, the relative abundances of the main organic molecular families, and the dominant microbial taxa at the phylum level. This addition has substantially strengthened the manuscript by highlighting the relationships between molecular and microbial variables and clarifying their respective contributions and relevance across the different samples.
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CC1: 'Reply on RC1', Nicasio T. Jiménez-Morillo, 28 Jan 2026
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