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• Sanchez, Pedro Maria Martin; Wurzbacher, Christian; Fontaine, Laurent; Lara, Maria Jimenez; Juottonen, Heli & Valiente, Nicolas [Show all 9 contributors for this article] (2026). Low determinism in community assembly of transient and resident pelagic fungi across climate zones in Scandinavian lakes. mSystems. 11(9). doi: 10.1128/msystems.00691-26. Full text in Research Archive Show summary

  ABSTRACT In lakes, fungi play pivotal roles in biogeochemical processes, particularly in the decomposition of organic matter. However, these organisms have been underrepresented and taxonomically unresolved in previous research. In this study, we employ high-resolution sequencing to delve into the fungal diversity within two distinct Scandinavian Lake data sets spanning a vast latitudinal gradient across Norway and Sweden, diverse climatic zones ranging from nemoral to arctic, and a wide spectrum of nutrient conditions. Utilizing eukaryotic 18S primers, we reveal that fungi contribute, on average, 2.07% in the Norwegian and 5.4% in the Swedish sequencing data set, with remarkable spikes of up to 55% in forested lakes. Fungus-specific 5.8S-ITS2 sequencing identified the prevalence of several fungal phyla, including Ascomycota , Rozellomycota , Basidiomycota , Chytridiomycota , Aphelidiomycota , and Mortierellomycota . Notably, our research uncovers a striking degree of variability in fungal communities across the studied lakes. Null model analyses on the entire community, as well as subsets of transient and resident members, revealed that deterministic selection plays a secondary role. Instead, community assembly was overwhelmingly governed by stochastic ecological drift across all tested groups. These findings challenge conventional paradigms of eukaryotic communities being strongly guided by deterministic processes and underscore the complexity of community assembly processes across the fungal kingdom. The dominance of ecological drift and stochasticity in the assembly process emphasizes that conservation should target entire communities, processes, and areas instead of single species, as should be the case in deterministically assembled communities. IMPORTANCE Fungi perform a range of key functions in freshwater environments. Here, we show that fungi, including members of the phyla Ascomycota , Rozellomycota , Basidiomycota , and Chytridiomycota , represent a diverse part of the epilimnetic planktonic community in Scandinavian lakes. Fungal community assembly across northern climate zones is shown to have a low signal for determinism, as environmental sorting was weak in overwriting dispersal-related processes and ecological drift. Furthermore, we expand knowledge of the ecological range of key freshwater fungi and link taxa to biogeographic patterns in lakes.

• Wei, Jing; Fontaine, Laurent; Parra, Nicolas Valiente; Dörsch, Peter; Hessen, Dag Olav & Eiler, Alexander (2023). Trajectories of freshwater microbial genomics and greenhouse gas saturation upon glacial retreat. Nature Communications. 14. doi: 10.1038/s41467-023-38806-w. Full text in Research Archive Show summary

  Abstract Due to climate warming, ice sheets around the world are losing mass, contributing to changes across terrestrial landscapes on decadal time spans. However, landscape repercussions on climate are poorly constrained mostly due to limited knowledge on microbial responses to deglaciation. Here, we reveal the genomic succession from chemolithotrophy to photo- and heterotrophy and increases in methane supersaturation in freshwater lakes upon glacial retreat. Arctic lakes at Svalbard also revealed strong microbial signatures form nutrient fertilization by birds. Although methanotrophs were present and increased along lake chronosequences, methane consumption rates were low even in supersaturated systems. Nitrous oxide oversaturation and genomic information suggest active nitrogen cycling across the entire deglaciated landscape, and in the high Arctic, increasing bird populations serve as major modulators at many sites. Our findings show diverse microbial succession patterns, and trajectories in carbon and nitrogen cycle processes representing a positive feedback loop of deglaciation on climate warming.

• Fontaine, Laurent; Pin, Lorenzo; Savio, Domenico; Friberg, Nikolai; Kirschner, Alexander K. T. & Farnleitner, Andreas H. [Show all 7 contributors for this article] (2023). Bacterial bioindicators enable biological status classification along the continental Danube river. Communications Biology. 6. doi: 10.1038/s42003-023-05237-8. Full text in Research Archive Show summary

  Despite the importance of bacteria in aquatic ecosystems and their predictable diversity patterns across space and time, biomonitoring tools for status assessment relying on these organisms are widely lacking. This is partly due to insufficient data and models to identify reliable microbial predictors. Here, we show metabarcoding in combination with multivariate statistics and machine learning allows to identify bacterial bioindicators for existing biological status classification systems. Bacterial beta-diversity dynamics follow environmental gradients and the observed associations highlight potential bioindicators for ecological outcomes. Spatio-temporal links spanning the microbial communities along the river allow accurate prediction of downstream biological status from upstream information. Network analysis on amplicon sequence veariants identify as good indicators genera Fluviicola, Acinetobacter, Flavobacterium, and Rhodoluna, and reveal informational redundancy among taxa, which coincides with taxonomic relatedness. The redundancy among bacterial bioindicators reveals mutually exclusive taxa, which allow accurate biological status modeling using as few as 2–3 amplicon sequence variants. As such our models show that using a few bacterial amplicon sequence variants from globally distributed genera allows for biological status assessment along river systems.

• Parra, Nicolas Valiente; Eiler, Alexander; Allesson, Lina; Andersen, Tom; Clayer, Francois & Crapart, Camille Marie [Show all 13 contributors for this article] (2022). Catchment properties as predictors of greenhouse gas concentrations across a gradient of boreal lakes. Frontiers in Environmental Science. 10. doi: 10.3389/fenvs.2022.880619. Full text in Research Archive Show summary

  Boreal lakes are the most abundant lakes on Earth. Changes in acid rain deposition, climate, and catchment land use have increased lateral fluxes of terrestrial dissolved organic matter (DOM), resulting in a widespread browning of boreal freshwaters. This browning affects the aqueous communities and ecosystem processes, and boost emissions of the greenhouse gases (GHG) CH 4 , CO 2 , and N 2 O. In this study, we predicted biotic saturation of GHGs in boreal lakes by using a set of chemical, hydrological, climate, and land use parameters. For this purpose, concentrations of GHGs and nutrients (organic C, -P, and -N) were determined in surface water samples from 73 lakes in south-eastern Norway covering wide ranges in DOM and nutrient concentrations, as well as catchment properties and land use. The spatial variation in saturation of each GHG is related to explanatory variables. Catchment characteristics (hydrological and climate parameters) such as lake size and summer precipitation, as well as NDVI, were key determinants when fitting GAM models for CH 4 and CO 2 saturation (explaining 71 and 54%, respectively), while summer precipitation and land use data were the best predictors for the N 2 O saturation, explaining almost 50% of deviance. Our results suggest that lake size, precipitation, and terrestrial primary production in the watershed control the saturation of GHG in boreal lakes. These predictions based on the 73-lake dataset was validated against an independent dataset from 46 lakes in the same region. Together, this provides an improved understanding of drivers and spatial variation in GHG saturation in boreal lakes across wide gradients of lake and catchment properties. The assessment highlights the need to incorporate multiple explanatory parameters in prediction models of GHGs for extrapolation across the boreal biome.

• Fontaine, Laurent; Khomich, Maryia; Andersen, Tom; Hessen, Dag Olav; Rasconi, Serena & Davey, Marie Louise [Show all 7 contributors for this article] (2021). Multiple thresholds and trajectories of microbial biodiversity predicted across browning gradients by neural networks and decision tree learning. ISME Communications. 1. doi: 10.1038/s43705-021-00038-8. Full text in Research Archive Show summary

  Ecological association studies often assume monotonicity such as between biodiversity and environmental properties although there is growing evidence that nonmonotonic relations dominate in nature. Here, we apply machine-learning algorithms to reveal the nonmonotonic association between microbial diversity and an anthropogenic-induced large-scale change, the browning of freshwaters, along a longitudinal gradient covering 70 boreal lakes in Scandinavia. Measures of bacterial richness and evenness (alpha-diversity) showed nonmonotonic trends in relation to environmental gradients, peaking at intermediate levels of browning. Depending on the statistical methods, variables indicative for browning could explain 5% of the variance in bacterial community composition (beta-diversity) when applying standard methods assuming monotonic relations and up to 45% with machine- learning methods taking non-monotonicity into account. This non-monotonicity observed at the community level was explained by the complex interchangeable nature of individual taxa responses as shown by a high degree of nonmonotonic responses of individual bacterial sequence variants to browning. Furthermore, the nonmonotonic models provide the position of thresholds and predict alternative bacterial diversity trajectories in boreal freshwater as a result of ongoing climate and land-use changes, which in turn will affect entire ecosystem metabolism and likely greenhouse gas production.

• Juottonen, Heli; Fontaine, Laurent; Wurzbacher, Christian; Drakare, Stina; Peura, Sari & Eiler, Alexander (2020). Archaea in boreal Swedish lakes are diverse, dominated by Woesearchaeota and follow deterministic community assembly. Environmental Microbiology. ISSN 1462-2912. 22(8), p. 3158–3171. doi: 10.1111/1462-2920.15058. Full text in Research Archive Show summary

  Despite their key role in biogeochemical processes, particularly the methane cycle, archaea are widely underrepresented in molecular surveys because of their lower abundance compared with bacteria and eukaryotes. Here, we use parallel high-resolution small subunit rRNA gene sequencing to explore archaeal diversity in 109 Swedish lakes and correlate archaeal community assembly mechanisms to large- scale latitudinal, climatic (nemoral to arctic) and nutrient (oligotrophic to eutrophic) gradients. Sequencing with universal primers showed the con- tribution of archaea was on average 0.8% but increased up to 1.5% of the three domains in forest lakes. Archaea-specific sequencing revealed that freshwater archaeal diversity could be partly explained by lake variables associated with nutrient status. Combined with deterministic co-occurrence patterns this finding suggests that ecological drift is overridden by environmental sorting, as well as other deterministic processes such as biogeographic and evolutionary history, leading to lake-specific archaeal biodiversity. Acetoclastic, hydrogenotrophic and methylotrophic methanogens as well as ammonia- oxidizing archaea were frequently detected across the lakes. Archaea-specific sequencing also revealed representatives of Woesearchaeota and other phyla of the DPANN superphylum. This study adds to our understanding of the ecological range of key archaea in freshwaters and links these taxa to hypotheses about processes governing biogeochemical cycles in lakes.

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• Fontaine, Laurent (2025). Statistical Analysis and Modeling of Microbial Communities in Aquatic Ecosystems. Universitetet i Oslo. Full text in Research Archive Show summary

  This thesis investigates the dynamics of microbial communities within aquatic ecosystems, employing novel statistical approaches and ecological modeling. The research addresses fundamental challenges in microbial ecology, focusing on the detection of non-monotonic relationships in biodiversity patterns, the identification of bacterial bioindicators, and the development of statistical methods for community analysis. We found that microbial diversity in boreal lakes responds to environmental gradients, such as browning, through complex, non-linear relationships, exhibiting distinct ecological thresholds where community composition shifts dramatically. We identified specific bacterial taxa that serve as effective bioindicators for classifying the ecological status of river systems, using metabarcoding data together with machine learning and graph theory. Looking at microbial communities in Australian soils and ocean, we found distinct community assembly patterns across environments and the three domains of life - Archaea, Bacteria and Eukarya. These insights advance our understanding of microbial community ecology, providing crucial frameworks for biomonitoring and conservation efforts in aquatic environments. The developed methodologies offer tools for assessing ecosystem health and predicting responses to environmental change, thereby contributing to evidence-based management strategies in a rapidly changing world.

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