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Microbially mediated iron reduction in such anoxic environments competes with sulfate reduction, which promotes euxinic (sulfide\u2010rich) conditions. Besides the shared demand for organic compounds, the competition is fostered by the produced hydrogen sulfide, which may reduce iron oxides abiotically or co\u2010precipitate with dissolved iron as iron sulfides. Understanding why some environments develop ferruginous rather than euxinic conditions (or vice versa), as well as the attendant effects on methanogenic fermentation, is key to understanding both modern and ancient anoxic ecosystems. Here, we reproduce biogeochemical distributions in multiple anoxic, low\u2010sulfate, meromictic lakes around the world using a biomass\u2010explicit reaction\u2010transport model with a fixed set of metabolism\u2010specific microbial parameters. The results suggest that sulfate reduction and methanogenesis are ubiquitous even in iron\u2010rich systems, and are reflected in microbial surveys. Ferruginous conditions typically develop for surface sulfate concentrations below \u2243100\u2009\u03bcM. Interestingly, there seems to be a dearth of stably stratified water bodies where sulfate concentrations can persist in the medium\u2010sulfate range of several hundred \u03bcM. Rather, when sulfur burial into the sediments becomes iron limited, sulfate tends to accumulate in the water column to much higher (mM) concentrations. A similar mechanism could be suggested to have operated in the variably sulfidic and ferruginous water columns of early oceans. Model simulations also reveal the previously underappreciated role of physical transport in shaping biogeochemical distributions, as minor variations in mixing rates can lead to large variations in microbial abundances. Model applicability across multiple lakes points to an encouraging possibility that geochemical patterns in complex biogeochemical systems may be described from a small number of thermodynamic and kinetic principles using a minimum of fitting parameters.<\/jats:p>","DOI":"10.1111\/gbi.70037","type":"journal-article","created":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T14:54:05Z","timestamp":1760972045000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Understanding Ferruginous Versus Euxinic Conditions by Simulating Microbial Conditions in Meromictic Lakes"],"prefix":"10.1111","volume":"23","author":[{"given":"Vanessa M.","family":"Hawkins","sequence":"first","affiliation":[{"name":"Department of Physics and Astronomy University of Minnesota Duluth  Duluth Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0413-1924","authenticated-orcid":false,"given":"Cody S.","family":"Sheik","sequence":"additional","affiliation":[{"name":"Department of Biology University of Minnesota Duluth  Duluth Minnesota USA"},{"name":"Large Lakes Observatory University of Minnesota Duluth  Duluth Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8577-4299","authenticated-orcid":false,"given":"Sergei","family":"Katsev","sequence":"additional","affiliation":[{"name":"Department of Physics and Astronomy University of Minnesota Duluth  Duluth Minnesota USA"},{"name":"Large Lakes Observatory University of Minnesota Duluth  Duluth Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,10,20]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1130\/G51713.1"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3103"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4163"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsl.2021.117324"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsl.2020.116495"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.2475\/03.2011.01"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemgeo.2004.08.015"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/PL00001353"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz848"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty560"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gca.2024.01.008"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0805313105"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.4319\/lo.2008.53.1.0319"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1258966"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsl.2007.09.026"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/PL00001345"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1130\/G52228.1"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41561-019-0351-5"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gca.2017.07.021"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22453-0"},{"volume-title":"FeGenie: A Comprehensive Tool for the Identification of Iron Genes and Iron Gene Neighborhoods in Genome and Metagenome Assemblies","year":"2020","author":"Garber A. 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