Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models
Since the mid-1980s, the Mediterranean Sea’s surface and deeper layers have warmed at unprecedented rates, with recent projections identifying it as one of the regions most impacted by rising global temperatures. Metrics that characterize phytoplankton abundance, phenology and size structure are wid...
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MDPI AG
2025-07-01
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| Online Access: | https://www.mdpi.com/2072-4292/17/14/2362 |
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| author | John A. Gittings Eleni Livanou Xuerong Sun Robert J. W. Brewin Stella Psarra Manolis Mandalakis Alexandra Peltekis Annalisa Di Cicco Vittorio E. Brando Dionysios E. Raitsos |
| author_facet | John A. Gittings Eleni Livanou Xuerong Sun Robert J. W. Brewin Stella Psarra Manolis Mandalakis Alexandra Peltekis Annalisa Di Cicco Vittorio E. Brando Dionysios E. Raitsos |
| author_sort | John A. Gittings |
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| description | Since the mid-1980s, the Mediterranean Sea’s surface and deeper layers have warmed at unprecedented rates, with recent projections identifying it as one of the regions most impacted by rising global temperatures. Metrics that characterize phytoplankton abundance, phenology and size structure are widely utilized as ecological indicators that enable a quantitative assessment of the status of marine ecosystems in response to environmental change. Here, using an extensive, updated in situ pigment dataset collated from numerous past research campaigns across the Mediterranean Sea, we re-parameterized an abundance-based phytoplankton size class model that infers Chl-a concentration in three phytoplankton size classes: pico- (<2 μm), nano- (2–20 μm) and micro-phytoplankton (>20 μm). Following recent advancements made within this category of size class models, we also incorporated information of sea surface temperature (SST) into the model parameterization. By tying model parameters to SST, the performance of the re-parameterized model was improved based on comparisons with concurrent, independent in situ measurements. Similarly, the application of the model to remotely sensed ocean color observations revealed strong agreement between satellite-derived estimates of phytoplankton size structure and in situ observations, with a performance comparable to the current regional operational datasets on size structure. The proposed conceptual regional model, parameterized with the most extended in situ pigment dataset available to date for the area, serves as a suitable foundation for long-term (1997–present) analyses on phytoplankton size structure and ecological indicators (i.e., phenology), ultimately linking higher trophic level responses to a changing Mediterranean Sea. |
| format | Article |
| id | doaj-art-5b3f9e3b1334474cbe28c879d45845a2 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-5b3f9e3b1334474cbe28c879d45845a22025-08-20T03:08:13ZengMDPI AGRemote Sensing2072-42922025-07-011714236210.3390/rs17142362Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based ModelsJohn A. Gittings0Eleni Livanou1Xuerong Sun2Robert J. W. Brewin3Stella Psarra4Manolis Mandalakis5Alexandra Peltekis6Annalisa Di Cicco7Vittorio E. Brando8Dionysios E. Raitsos9Department of Biology, National and Kapodistrian University of Athens, 15772 Athens, GreeceDepartment of Biology, National and Kapodistrian University of Athens, 15772 Athens, GreeceCentre for Geography and Environmental Science, Department of Earth and Environmental Sciences, Faculty of Environment, Science and Economy, University of Exeter, Cornwall TR10 9FE, UKCentre for Geography and Environmental Science, Department of Earth and Environmental Sciences, Faculty of Environment, Science and Economy, University of Exeter, Cornwall TR10 9FE, UKInstitute of Oceanography, Hellenic Centre for Marine Research, 71003 Heraklion, GreeceInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, 71003 Heraklion, GreeceInstitute of Oceanography, Hellenic Centre for Marine Research, 71003 Heraklion, GreeceConsiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, ItalyConsiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, ItalyDepartment of Biology, National and Kapodistrian University of Athens, 15772 Athens, GreeceSince the mid-1980s, the Mediterranean Sea’s surface and deeper layers have warmed at unprecedented rates, with recent projections identifying it as one of the regions most impacted by rising global temperatures. Metrics that characterize phytoplankton abundance, phenology and size structure are widely utilized as ecological indicators that enable a quantitative assessment of the status of marine ecosystems in response to environmental change. Here, using an extensive, updated in situ pigment dataset collated from numerous past research campaigns across the Mediterranean Sea, we re-parameterized an abundance-based phytoplankton size class model that infers Chl-a concentration in three phytoplankton size classes: pico- (<2 μm), nano- (2–20 μm) and micro-phytoplankton (>20 μm). Following recent advancements made within this category of size class models, we also incorporated information of sea surface temperature (SST) into the model parameterization. By tying model parameters to SST, the performance of the re-parameterized model was improved based on comparisons with concurrent, independent in situ measurements. Similarly, the application of the model to remotely sensed ocean color observations revealed strong agreement between satellite-derived estimates of phytoplankton size structure and in situ observations, with a performance comparable to the current regional operational datasets on size structure. The proposed conceptual regional model, parameterized with the most extended in situ pigment dataset available to date for the area, serves as a suitable foundation for long-term (1997–present) analyses on phytoplankton size structure and ecological indicators (i.e., phenology), ultimately linking higher trophic level responses to a changing Mediterranean Sea.https://www.mdpi.com/2072-4292/17/14/2362phytoplankton size structureocean colorremote sensingecological indicators |
| spellingShingle | John A. Gittings Eleni Livanou Xuerong Sun Robert J. W. Brewin Stella Psarra Manolis Mandalakis Alexandra Peltekis Annalisa Di Cicco Vittorio E. Brando Dionysios E. Raitsos Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models Remote Sensing phytoplankton size structure ocean color remote sensing ecological indicators |
| title | Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models |
| title_full | Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models |
| title_fullStr | Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models |
| title_full_unstemmed | Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models |
| title_short | Remotely Sensing Phytoplankton Size Structure in the Mediterranean Sea: Insights from In Situ Data and Temperature-Corrected Abundance-Based Models |
| title_sort | remotely sensing phytoplankton size structure in the mediterranean sea insights from in situ data and temperature corrected abundance based models |
| topic | phytoplankton size structure ocean color remote sensing ecological indicators |
| url | https://www.mdpi.com/2072-4292/17/14/2362 |
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