View in EDS HTML Full Text PDF Full Text

Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale.

Saved in:
Bibliographic Details
Title: Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale.
Authors: Cazorla, Beatriz P.1,2,3 (AUTHOR) b.cazorla@ugr.es, Meijide, Ana4 (AUTHOR), Cabello, Javier2,5 (AUTHOR), Peñas, Julio1,2 (AUTHOR), Martínez-López, Javier2,3,6 (AUTHOR), Vargas, Rodrigo7 (AUTHOR), Montagnani, Leonardo8 (AUTHOR), Knohl, Alexander9 (AUTHOR), Siebicke, Lukas9 (AUTHOR), Gioli, Benimiano10 (AUTHOR), Dušek, Jiří11 (AUTHOR), Šigut, Ladislav11 (AUTHOR), Ibrom, Andreas12 (AUTHOR), Wohlfahrt, Georg13 (AUTHOR), Paul-Limoges, Eugénie14 (AUTHOR), Fuchs, Kathrin15 (AUTHOR), Manco, Antonio16 (AUTHOR), Pavelka, Marian11 (AUTHOR), Merbold, Lutz17 (AUTHOR), Hörtnagl, Lukas18 (AUTHOR)
Source: Biogeosciences. 2026, Vol. 23 Issue 3, p1223-1243. 21p.
Subject Terms: *Satellite-based remote sensing, *Ecosystem dynamics, *Environmental monitoring, *Normalized difference vegetation index
Abstract: Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001–2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity. [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: 191696573
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Cazorla%2C+Beatriz P%2E%22">Cazorla, Beatriz P.</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> b.cazorla@ugr.es</i><br /><searchLink fieldCode="AR" term="%22Meijide%2C+Ana%22">Meijide, Ana</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cabello%2C+Javier%22">Cabello, Javier</searchLink><relatesTo>2,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peñas%2C+Julio%22">Peñas, Julio</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Martínez-López%2C+Javier%22">Martínez-López, Javier</searchLink><relatesTo>2,3,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vargas%2C+Rodrigo%22">Vargas, Rodrigo</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Montagnani%2C+Leonardo%22">Montagnani, Leonardo</searchLink><relatesTo>8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Knohl%2C+Alexander%22">Knohl, Alexander</searchLink><relatesTo>9</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Siebicke%2C+Lukas%22">Siebicke, Lukas</searchLink><relatesTo>9</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gioli%2C+Benimiano%22">Gioli, Benimiano</searchLink><relatesTo>10</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dušek%2C+Jiří%22">Dušek, Jiří</searchLink><relatesTo>11</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Šigut%2C+Ladislav%22">Šigut, Ladislav</searchLink><relatesTo>11</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ibrom%2C+Andreas%22">Ibrom, Andreas</searchLink><relatesTo>12</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wohlfahrt%2C+Georg%22">Wohlfahrt, Georg</searchLink><relatesTo>13</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Paul-Limoges%2C+Eugénie%22">Paul-Limoges, Eugénie</searchLink><relatesTo>14</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fuchs%2C+Kathrin%22">Fuchs, Kathrin</searchLink><relatesTo>15</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Manco%2C+Antonio%22">Manco, Antonio</searchLink><relatesTo>16</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pavelka%2C+Marian%22">Pavelka, Marian</searchLink><relatesTo>11</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Merbold%2C+Lutz%22">Merbold, Lutz</searchLink><relatesTo>17</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hörtnagl%2C+Lukas%22">Hörtnagl, Lukas</searchLink><relatesTo>18</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Biogeosciences%22">Biogeosciences</searchLink>. 2026, Vol. 23 Issue 3, p1223-1243. 21p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Satellite-based+remote+sensing%22">Satellite-based remote sensing</searchLink><br />*<searchLink fieldCode="DE" term="%22Ecosystem+dynamics%22">Ecosystem dynamics</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+monitoring%22">Environmental monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Normalized+difference+vegetation+index%22">Normalized difference vegetation index</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001–2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=191696573
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5194/bg-23-1223-2026
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 1223
    Subjects:
      – SubjectFull: Satellite-based remote sensing
        Type: general
      – SubjectFull: Ecosystem dynamics
        Type: general
      – SubjectFull: Environmental monitoring
        Type: general
      – SubjectFull: Normalized difference vegetation index
        Type: general
    Titles:
      – TitleFull: Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Cazorla, Beatriz P.
      – PersonEntity:
          Name:
            NameFull: Meijide, Ana
      – PersonEntity:
          Name:
            NameFull: Cabello, Javier
      – PersonEntity:
          Name:
            NameFull: Peñas, Julio
      – PersonEntity:
          Name:
            NameFull: Martínez-López, Javier
      – PersonEntity:
          Name:
            NameFull: Vargas, Rodrigo
      – PersonEntity:
          Name:
            NameFull: Montagnani, Leonardo
      – PersonEntity:
          Name:
            NameFull: Knohl, Alexander
      – PersonEntity:
          Name:
            NameFull: Siebicke, Lukas
      – PersonEntity:
          Name:
            NameFull: Gioli, Benimiano
      – PersonEntity:
          Name:
            NameFull: Dušek, Jiří
      – PersonEntity:
          Name:
            NameFull: Šigut, Ladislav
      – PersonEntity:
          Name:
            NameFull: Ibrom, Andreas
      – PersonEntity:
          Name:
            NameFull: Wohlfahrt, Georg
      – PersonEntity:
          Name:
            NameFull: Paul-Limoges, Eugénie
      – PersonEntity:
          Name:
            NameFull: Fuchs, Kathrin
      – PersonEntity:
          Name:
            NameFull: Manco, Antonio
      – PersonEntity:
          Name:
            NameFull: Pavelka, Marian
      – PersonEntity:
          Name:
            NameFull: Merbold, Lutz
      – PersonEntity:
          Name:
            NameFull: Hörtnagl, Lukas
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Text: 2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 17264170
          Numbering:
            – Type: volume
              Value: 23
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Biogeosciences
              Type: main
ResultId 1