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. 2025 May 19;20(1):54.
doi: 10.1186/s40793-025-00718-1.

Distinct microbial communities drive methane cycling in below- and above-ground compartments of tropical cloud forests growing on peat

Affiliations

Distinct microbial communities drive methane cycling in below- and above-ground compartments of tropical cloud forests growing on peat

Fahad Ali Kazmi et al. Environ Microbiome. .

Abstract

Cloud forests are unique yet understudied ecosystems regarding CH4 exchange despite their significance in carbon storage. We investigated CH4 fluxes in peat soil and tree stems of two tropical cloud forests on Réunion Island, one featuring Erica reunionensis and the second a mix of E. reunionensis and Alsophila glaucifolia. The study examined microbiomes across below-ground (soil) and above-ground (canopy soil, leaves, and stems) forest compartments. Metagenomics and qPCR analyses targeted key genes in methanogenesis and methanotrophy in soil and above-ground samples, alongside soil physicochemical measurements. CH4 fluxes from peat soil and tree stems were measured using gas chromatography and portable trace gas analyzers. Peat soil in both forests acted as a CH4 sink (- 23.8 ± 4.84 µg C m- 2 h- 1) and CO2 source (55.5 ± 5.51 µg C m- 2 h- 1), with higher CH4 uptake in sites dominated by endemic tree species E. reunionensis. In forest soils, a high abundance of n-DAMO 16 S rRNA gene (3.42 × 107 ± 7 × 106 copies/g dw) was associated with nitrate levels and higher rates of CH4 uptake and CO2 emissions. NC-10 bacteria (0.1-0.3%) were detected in only the Erica forest soil, verrucomicrobial methanotrophs (0.1-3.1%) only in the mixed forest soil, whereas alphaproteobacterial methanotrophs (0.1-3.3%) were present in all soils. Tree stems in both forests were weak sinks of CH4 (-0.94 ± 0.4 µg C m- 2 h- 1). The canopy soil hosted verrucomicrobial methanotrophs (0.1-0.3%). The leaves in both forests exhibited metabolic potential for CH4 production, e.g., exhibiting high mcrA copy numbers (3.5 × 105 ± 2.3 × 105 copies/g dw). However, no CH4-cycling functional genes were detected in the stem core samples. Tropical cloud forest peat soils showed high anaerobic methanotrophy via the n-DAMO process, while aerobic methanotrophs were abundant in canopy soils. Leaves hosted methanotrophs but predominantly methanogens. These results highlight the significant differences between canopy and soil microbiomes in the CH4 cycle, emphasizing the importance of above-ground microbiomes in forest CH4 gas budgets.

Keywords: Canopy soil microbiome; Leaf microbiome; Peatlands; Phyllosphere microbiome; Soil microbiome; Stem microbiome.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Boxplot illustrating (a) CH4 fluxes and (b) CO2 fluxes from the soil and stems. The colors indicate the dominant plant species in soil and those related to stem fluxes. The box illustrates the interquartile range (IQR), encompassing the 25th and 75th percentiles of the data distribution. The lines extending from the box, referred to as whiskers, show the data range that falls within 1.5 times the IQR. The bars within the box indicate the median. The red dots represent the mean values
Fig. 2
Fig. 2
Abundances of genes (g− 1 dry weight) involved in methanogenesis (mcrA) and methanotrophy (pmoA and n-DAMO 16 S rRNA) in soil (a-c) and plant samples (d-f) quantified in qPCR. Different colors represent the species dominant in the sites in a-c, while the related species in d-f. The box depicts the interquartile range (IQR), which captures the 25th and 75th percentiles of the data. The whiskers that extend from the box represent the data range within 1.5 times the IQR. Inside the box, a line indicates the median value of the data set, while the red dots represent the mean values. Black dots are the outliers. The pairwise relationships are indicated by ns (not significant), * (p ≤ 0.05), ** (p ≤ 0.01), *** (p ≤ 0.001), and **** (p ≤ 0.0001)
Fig. 3
Fig. 3
Functional gene abundance across soil, canopy soil, and leaves samples. The row-scaled heatmap represents the log2-transformed normalized read counts for key functional genes for methanogenesis, aerobic methanotrophy, and methanol oxidation
Fig. 4
Fig. 4
The ratios of the microbial methanogenic (mcrA) to methanotrophic genes (pmoA and n-DAMO 16 S rRNA) (a) in peat soil and (b) in above-ground samples
Fig. 5
Fig. 5
(a) Relative abundance of small subunit rRNA (SSU) sequence of key CH4 cycling microbial genera (including methanogenic archaea, methanotrophs, and methylotrophs) in soil, canopy soil, and leaves across tropical cloud forests: Erica Forest dominated by E. reunionensis (Erica_ER), Mixed Forest dominated by E. reunionensis (Mixed_ER), and dominated by A. glaucifolia (Mixed_AG). (b) Clustering of the forest sites based on principal component analysis biplot of soil variables, including physiochemical properties, gene copy numbers, and microbial functional groups. Big triangles represent the mean values, and colors represent the forest sites. (c) Structural Equation Model (SEM) for the soil CH4 and CO2 fluxes, including key controlling factors, i.e., SWC, soil NO3, n-DAMO, and pmoA gene abundances. Red lines show negative correlations, while green lines show positive correlations. Asterisks represent the significant relationships

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