Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity
Satellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and...
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| Format: | Article |
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MDPI AG
2023-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/23/5593 |
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| author | Lingling Liu Jeffrey R. Smith Amanda H. Armstrong Domingo Alcaraz-Segura Howard E. Epstein Alejandra Echeverri Kelley E. Langhans Rafael J. P. Schmitt Rebecca Chaplin-Kramer |
| author_facet | Lingling Liu Jeffrey R. Smith Amanda H. Armstrong Domingo Alcaraz-Segura Howard E. Epstein Alejandra Echeverri Kelley E. Langhans Rafael J. P. Schmitt Rebecca Chaplin-Kramer |
| author_sort | Lingling Liu |
| collection | DOAJ |
| description | Satellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and as a predictor for ecosystem functioning, ecosystem services, and resilience. However, the impact of key methodological choices on patterns of EFTs and EFD have not been formally assessed. Using Costa Rica as a study system, we compared EFTs and EFD, derived from MODIS and Landsat data using different methodological assumptions, at both national and local extents. Our results showed that the regional spatial patterns of EFTs and EFD derived from 250 m MODIS and 30 m Landsat are notably different. The selection of sensors for deriving EFTs and EFD is dependent on the study area, data quality, and the research objective. Given its finer spatial resolution, Landsat has greater capacity to differentiate more EFTs than MODIS, though MODIS could be a better choice in frequently cloudy areas due to its shorter revisiting time. We also found that the selection of spatial extent used to derive EFD is critical, as smaller extents (e.g., at a local rather than a national scale) can show much higher diversity. However, diversity levels derived at smaller extents appear to be nested within the diversity levels derived at larger extents. As EFTs and EFD continue to develop as a tool for ecosystem ecology, we highlight the important methodological choices to ensure that these metrics best fit research objectives. |
| first_indexed | 2024-03-09T01:42:57Z |
| format | Article |
| id | doaj.art-55cfaa2096a44ee59b36588af8928555 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T01:42:57Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-55cfaa2096a44ee59b36588af89285552023-12-08T15:25:10ZengMDPI AGRemote Sensing2072-42922023-12-011523559310.3390/rs15235593Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and DiversityLingling Liu0Jeffrey R. Smith1Amanda H. Armstrong2Domingo Alcaraz-Segura3Howard E. Epstein4Alejandra Echeverri5Kelley E. Langhans6Rafael J. P. Schmitt7Rebecca Chaplin-Kramer8Institute on the Environment, University of Minnesota, St. Paul, MI 55108, USADepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USADepartment of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USAi-Ecolab, Inter-University Institute for Earth System Research in Andalusia, University of Granada, 18012 Granada, SpainDepartment of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USADepartment of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, CA 94720, USADepartment of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USANatural Capital Project, Stanford University, Stanford, CA 94305, USAGlobal Science, WWF, 131 Steuart St., San Francisco, CA 94105, USASatellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and as a predictor for ecosystem functioning, ecosystem services, and resilience. However, the impact of key methodological choices on patterns of EFTs and EFD have not been formally assessed. Using Costa Rica as a study system, we compared EFTs and EFD, derived from MODIS and Landsat data using different methodological assumptions, at both national and local extents. Our results showed that the regional spatial patterns of EFTs and EFD derived from 250 m MODIS and 30 m Landsat are notably different. The selection of sensors for deriving EFTs and EFD is dependent on the study area, data quality, and the research objective. Given its finer spatial resolution, Landsat has greater capacity to differentiate more EFTs than MODIS, though MODIS could be a better choice in frequently cloudy areas due to its shorter revisiting time. We also found that the selection of spatial extent used to derive EFD is critical, as smaller extents (e.g., at a local rather than a national scale) can show much higher diversity. However, diversity levels derived at smaller extents appear to be nested within the diversity levels derived at larger extents. As EFTs and EFD continue to develop as a tool for ecosystem ecology, we highlight the important methodological choices to ensure that these metrics best fit research objectives.https://www.mdpi.com/2072-4292/15/23/5593ecosystem functional typeecosystem functional diversityecosystem serviceLandsatMODISspatial resolution |
| spellingShingle | Lingling Liu Jeffrey R. Smith Amanda H. Armstrong Domingo Alcaraz-Segura Howard E. Epstein Alejandra Echeverri Kelley E. Langhans Rafael J. P. Schmitt Rebecca Chaplin-Kramer Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity Remote Sensing ecosystem functional type ecosystem functional diversity ecosystem service Landsat MODIS spatial resolution |
| title | Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity |
| title_full | Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity |
| title_fullStr | Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity |
| title_full_unstemmed | Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity |
| title_short | Influences of Satellite Sensor and Scale on Derivation of Ecosystem Functional Types and Diversity |
| title_sort | influences of satellite sensor and scale on derivation of ecosystem functional types and diversity |
| topic | ecosystem functional type ecosystem functional diversity ecosystem service Landsat MODIS spatial resolution |
| url | https://www.mdpi.com/2072-4292/15/23/5593 |
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