Biology subjects

Marhan, S.

Publications and source records attributed to Marhan, S..

4 recordsLinked to original sources

bioRxiv2025

Methane sink function of grassland soil microbiomes - negative effects of intensive management persist three years after land-use extensification

Grassland soils are important methane (CH4) sinks through CH4 oxidation by methanotrophs, but intensive management with high nitrogen inputs and grazing densities reduces this potential. While long-term recovery of the CH4 sink after land-use change is generally established, little is known about the short-term effects of reducing land-use intensity index (LUI) through extensive management in grassland. We did not find an effect on potential CH4 oxidation rates (PMORs) and the abundances atmospheric CH4-consuming methanotrophs after three years of LUI reduction (no fertilization, no grazing, and one mowing per year) in 45 intensively managed grassland sites located in three different pedoclimatic regions of Germany. However, we observed a decline in the abundance of CH4 producing methanogens. Moreover, we found greater PMORs and higher abundance of Upland Soil Cluster {gamma} (USC{gamma}) methanotrophs on additional, historically low LUI sites. Soil bulk density decreased already after three years of LUI reduction and was even lower in historically low LUI sites. Strong correlations between the abundance canonical methanotrophs and methanogens highlight a CH4 filter function that was independent from LUI reduction across regions. Our study consistently shows that three years of LUI reduction are not sufficient to restore the CH4 sink function of temperate grasslands. However, the lower soil bulk density and the decreased abundance of methanogens indicate that LUI reduction will affect the habitat and living boundary conditions for CH4-cycling microorganisms in the long term. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/646387v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@876847org.highwire.dtl.DTLVardef@1cf2e69org.highwire.dtl.DTLVardef@f02df9org.highwire.dtl.DTLVardef@5a3f1f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Revisiting soil fungal biomarkers and conversion factors: Interspecific variability in phospholipid fatty acids, ergosterol and rDNA copy numbers

The abundances of fungi and bacteria in soil are used as simple predictors for carbon dynamics, and represent widely available microbial traits. Soil biomarkers serve as quantitative estimates of these microbial groups, though not quantifying microbial biomass per se. The accurate conversion to microbial carbon pools, and an understanding of its comparability among soils is therefore needed. We refined conversion factors for classical fungal biomarkers, and evaluated the application of quantitative PCR (qPCR, rDNA copies) as a biomarker for soil fungi. Based on biomarker contents in pure fungal cultures of 30 isolates, combined with available references, we propose average conversion factors of 95.3 g fungal C g-1 ergosterol, 32.0 mg fungal C {micro}mol-1 PLFA 18:2{omega}6,9 and 0.264 pg fungal C ITS1 DNA copy-1. As expected, interspecific variability was most pronounced in rDNA copies, though qPCR results showed the least phylogenetic bias. A modeling approach based on exemplary agricultural soils further supported the hypothesis that high diversity in soil buffers against biomarker variability, whereas also phylogenetic biases impact the accuracy of comparisons in biomarker estimates. Our analyses suggest that qPCR results cover the fungal community in soil best, though with a variability only partly offset in highly diverse soils. PLFA 18:2{omega}6,9 and ergosterol represent accurate biomarkers to quantify Ascomycota and Basidiomycota. To conclude, the ecological interpretation and coverage of biomarker data prior to their application in global models is important, where the combination of different biomarkers may be most insightful.

ecology↗

bioRxiv2023

A fast-slow trait continuum at the level of entire communities

Across the tree of life, organismal functional strategies form a continuum from slow-to fast-growing organisms, in response to common drivers such as resource availability and disturbance. However, the synchronization of these strategies at the entire community level is untested. We combine trait data for >2800 above-and belowground taxa from 14 trophic guilds spanning a disturbance and resource availability gradient in German grasslands. Most guilds consistently respond to these drivers through both direct and trophically-mediated effects, resulting in a slow-fast axis at the level of the entire community. Fast trait communities were also associated with faster rates of whole ecosystem functioning. These findings demonstrate that slow and fast strategies can be manifested at the level of whole ecosystems, opening new avenues of ecosystem-level functional classification.

ecology↗

bioRxiv2021

Transcriptional dynamics of methane-cycling microbiomes are linked to seasonal CH4 fluxes in two hydromorphic and organic-rich grassland soils

Soil CH4 fluxes are driven by CH4-producing and -consuming microorganisms that determine whether soils are sources or sinks of this potent greenhouse gas. Using quantitative metatranscriptomics, we linked CH4-cycling microbiomes to net surface CH4 fluxes throughout a year in two drained peatland soils differing in grassland land-use intensity and physicochemical properties. CH4 fluxes were highly dynamic; both soils were net CH4 sources in autumn and winter and sinks in spring and summer. Despite similar net CH4 emissions, methanogen and methanotroph loads, as determined by small subunit rRNA transcripts per gram soil, differed strongly between sites. In contrast, mRNA transcript abundances were similar in both soils and correlated well with CH4 fluxes. The methane monooxygenase to methanogenesis mRNA ratio was higher in spring and summer, when the soils were net CH4 sinks. CH4 uptake was linked to an increased proportion of USC and {gamma} and pmoA2 pmoA transcripts. We assume that methanogen transcript abundance may be useful to approximate changes in net surface CH4 emissions from drained peat soils; high methanotroph to methanogen ratios would indicate CH4 sink properties. Our study shows the strength of quantitative metatranscriptomics; mRNA transcript abundance holds promising indicator to link soil microbiome functions to ecosystem-level processes.

microbiology↗