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Distribution of denitrifiers predicted by correlative niche modeling of changing environmental conditions and future climatic scenarios across the Baltic Sea
Södertörn University, School of Natural Sciences, Technology and Environmental Studies, Environmental Science. Södertörn University, Centre for Baltic and East European Studies (CBEES), Baltic & East European Graduate School (BEEGS).ORCID iD: 0000-0002-5636-3957
University of Tabuk, Saudi Arabia.
University of Ha'il, Saudi Arabia.
University of Tabuk, Saudi Arabia.
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2023 (English)In: Ecological Informatics, ISSN 1574-9541, E-ISSN 1878-0512, Vol. 78, article id 102346Article in journal (Refereed) Published
Abstract [en]

Denitrifying microbial communities provide an important ecosystem function in aquatic systems. Yet, knowledge on predictive and modeling of these complex and changing communities is limited. The emergently challenging question of how the geographical distribution of denitrifiers responds to ongoing and future environmental change is not yet fully understood. In our study we use metadata-based correlative niche modeling to analyze the geographical distribution of selected putative denitrifiers in the genus Sphingomonas, Mycoplana, Shewanella, and Alteromonas at different predicted environmental conditions and future climatic scenarios across the Baltic Sea. Using the predictive power of an ensemble modeling approach and eight different machine-learning algorithms, habitat suitability and the distribution of the selected denitrifiers were evaluated using geophysical and bioclimatic variables, benthic conditions, and four Representative Concentration Pathway (RCP) trajectories of future global warming scenarios. All algorithms provided successful prediction capabilities both for variable importance, and for habitat suitability with Area Under the Curve (AUC) values between 0.89 and 1.00. Model findings revealed that salinity and nitrate concentrations significantly explained the variation in distribution of the selected denitrifiers. Rising temperatures of 0.8 to 1.8 °C at future RCP60–2050 trajectories are predicted to diminish or eliminate the bioclimatic suitable habitats for denitrifier distributions across the Baltic Sea. Multi-collated terrestrial and marine environmental variables contributed to the successful prediction of denitrifier distributions within the study area. The correlative niche modeling approach with high AUC values presented in the study allowed for accurate projections of the future distributions of the selected denitrifiers. The modeling approach can be used to improve our understanding of how ongoing and predicted future environmental changes may affect habitat suitability for organisms with denitrification capacity across the Baltic Sea.

Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 78, article id 102346
Keywords [en]
Climate change, Benthic conditions, Ensemble modeling, Habitat suitability, Machine-learning, Multi-collated variables
National Category
Environmental Sciences
Research subject
Environmental Studies; Baltic and East European studies
Identifiers
URN: urn:nbn:se:sh:diva-52629DOI: 10.1016/j.ecoinf.2023.102346ISI: 001109366700001Scopus ID: 2-s2.0-85176443244OAI: oai:DiVA.org:sh-52629DiVA, id: diva2:1810363
Part of project
Response and recovery of benthic biodiversity and ecosystem functions to chemical pollution and eutrophication, The Foundation for Baltic and East European Studies
Funder
The Foundation for Baltic and East European Studies, 77/2017Available from: 2023-11-07 Created: 2023-11-07 Last updated: 2023-12-18Bibliographically approved

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Abdelgadir, MohanadSjöling, SaraDinnétz, Patrik

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
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