View in EDS HTML Full Text PDF Full Text

Meta-analytical insights into organic matter enrichment in the surface microlayer.

Saved in:
Bibliographic Details
Title: Meta-analytical insights into organic matter enrichment in the surface microlayer.
Authors: Silva, Amavi1 (AUTHOR) asilva@geomar.de, Nikzad, Surandokht2,3 (AUTHOR), Barthelmeß, Theresa1 (AUTHOR), Engel, Anja1,4 (AUTHOR), Herrmann, Hartmut5 (AUTHOR), van Pinxteren, Manuela5 (AUTHOR), Wirtz, Kai2,4 (AUTHOR), Wurl, Oliver6 (AUTHOR), Schartau, Markus1 (AUTHOR) mschartau@geomar.de
Source: Biogeosciences. 2026, Vol. 23 Issue 4, p1697-1718. 22p.
Subject Terms: *Sea surface microlayer, *Organic compounds, *Research methodology, *Fatty acids, *Nitrogen compounds, *Amino acids, *Colloidal carbon, *Biogeochemistry
Abstract: The surface microlayer (SML), the uppermost ∼ 1 mm water layer at the air-water interface, plays a critical role in mediating Earth system processes, yet current knowledge of its composition and organic matter enrichment remains scattered across disciplines. Here, we present the first known meta-analysis of SML studies that quantitatively assesses the distributional characteristics of selected organic compounds, including organic carbon and nitrogen, amino acids, fatty acids, transparent exopolymer particles, carbohydrates, lipids and proteins, through probability density estimates, central tendency metrics and correlation analyses. Our results confirm a preferential enrichment of nitrogen-enriched, particulate organic matter in the SML, while also highlighting the significance of surfactant-specific factors that govern selective enrichment in the SML. We find that enrichment patterns can vary systematically with environmental and methodological conditions, underscoring the need to account for such influences when interpreting observations and developing SML-based models. We provide the full range of typical EF values for the studied compounds, offering a clear reference for assessing whether new measurements are typical or extreme. While delving into the ability of EFs to reflect organic matter partitioning in the SML, we also critically examine their limitations in capturing trophic variability and suggest that EF-based assessments be complemented with metrics that remove background variability from underlying water concentrations, enabling more accurate interpretations of true SML enrichment and informing future modelling efforts. Additionally, our meta-analysis demonstrates that logarithmic data transformations and robust central tendency estimates outperform traditional linear-scale approaches, providing more accurate and reliable SML enrichment estimates. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 192129922
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Meta-analytical insights into organic matter enrichment in the surface microlayer.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Silva%2C+Amavi%22">Silva, Amavi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> asilva@geomar.de</i><br /><searchLink fieldCode="AR" term="%22Nikzad%2C+Surandokht%22">Nikzad, Surandokht</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Barthelmeß%2C+Theresa%22">Barthelmeß, Theresa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Engel%2C+Anja%22">Engel, Anja</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Herrmann%2C+Hartmut%22">Herrmann, Hartmut</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22van+Pinxteren%2C+Manuela%22">van Pinxteren, Manuela</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wirtz%2C+Kai%22">Wirtz, Kai</searchLink><relatesTo>2,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wurl%2C+Oliver%22">Wurl, Oliver</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schartau%2C+Markus%22">Schartau, Markus</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mschartau@geomar.de</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Biogeosciences%22">Biogeosciences</searchLink>. 2026, Vol. 23 Issue 4, p1697-1718. 22p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Sea+surface+microlayer%22">Sea surface microlayer</searchLink><br />*<searchLink fieldCode="DE" term="%22Organic+compounds%22">Organic compounds</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br />*<searchLink fieldCode="DE" term="%22Fatty+acids%22">Fatty acids</searchLink><br />*<searchLink fieldCode="DE" term="%22Nitrogen+compounds%22">Nitrogen compounds</searchLink><br />*<searchLink fieldCode="DE" term="%22Amino+acids%22">Amino acids</searchLink><br />*<searchLink fieldCode="DE" term="%22Colloidal+carbon%22">Colloidal carbon</searchLink><br />*<searchLink fieldCode="DE" term="%22Biogeochemistry%22">Biogeochemistry</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The surface microlayer (SML), the uppermost ∼ 1 mm water layer at the air-water interface, plays a critical role in mediating Earth system processes, yet current knowledge of its composition and organic matter enrichment remains scattered across disciplines. Here, we present the first known meta-analysis of SML studies that quantitatively assesses the distributional characteristics of selected organic compounds, including organic carbon and nitrogen, amino acids, fatty acids, transparent exopolymer particles, carbohydrates, lipids and proteins, through probability density estimates, central tendency metrics and correlation analyses. Our results confirm a preferential enrichment of nitrogen-enriched, particulate organic matter in the SML, while also highlighting the significance of surfactant-specific factors that govern selective enrichment in the SML. We find that enrichment patterns can vary systematically with environmental and methodological conditions, underscoring the need to account for such influences when interpreting observations and developing SML-based models. We provide the full range of typical EF values for the studied compounds, offering a clear reference for assessing whether new measurements are typical or extreme. While delving into the ability of EFs to reflect organic matter partitioning in the SML, we also critically examine their limitations in capturing trophic variability and suggest that EF-based assessments be complemented with metrics that remove background variability from underlying water concentrations, enabling more accurate interpretations of true SML enrichment and informing future modelling efforts. Additionally, our meta-analysis demonstrates that logarithmic data transformations and robust central tendency estimates outperform traditional linear-scale approaches, providing more accurate and reliable SML enrichment estimates. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=192129922
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5194/bg-23-1697-2026
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 1697
    Subjects:
      – SubjectFull: Sea surface microlayer
        Type: general
      – SubjectFull: Organic compounds
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Fatty acids
        Type: general
      – SubjectFull: Nitrogen compounds
        Type: general
      – SubjectFull: Amino acids
        Type: general
      – SubjectFull: Colloidal carbon
        Type: general
      – SubjectFull: Biogeochemistry
        Type: general
    Titles:
      – TitleFull: Meta-analytical insights into organic matter enrichment in the surface microlayer.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Silva, Amavi
      – PersonEntity:
          Name:
            NameFull: Nikzad, Surandokht
      – PersonEntity:
          Name:
            NameFull: Barthelmeß, Theresa
      – PersonEntity:
          Name:
            NameFull: Engel, Anja
      – PersonEntity:
          Name:
            NameFull: Herrmann, Hartmut
      – PersonEntity:
          Name:
            NameFull: van Pinxteren, Manuela
      – PersonEntity:
          Name:
            NameFull: Wirtz, Kai
      – PersonEntity:
          Name:
            NameFull: Wurl, Oliver
      – PersonEntity:
          Name:
            NameFull: Schartau, Markus
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 02
              Text: 2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 17264170
          Numbering:
            – Type: volume
              Value: 23
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Biogeosciences
              Type: main
ResultId 1