BIBLIOS

Document type
Journal articles

Document subtype
Full paper

Title
Coupling ecological concepts with an ocean-colour model: Phytoplankton size structure

Participants in the publication
Xuerong Sun (Author)
Robert J.W. Brewin (Author)
Shubha Sathyendranath (Author)
Giorgio Dall’Olmo (Author)
Ruth Airs (Author)
Ray Barlow (Author)
Astrid Bracher (Author)
Malika Kheireddine (Author)
Vanda Brotas (Author)
Dep. Biologia Vegetal
MARE
Tarron Lamont (Author)
Emilio Marañón (Author)
Xosé Anxelu G. Morán (Author)
Dionysios E. Raitsos (Author)
Fang Shen (Author)
Gavin H. Tilstone (Author)

Summary
Phytoplankton play a central role in the planetary cycling of important elements and compounds. Understand- ing how phytoplankton are responding to climate change is consequently a major question in Earth Sciences. Monitoring phytoplankton is key to answering this question. Satellite remote sensing of ocean colour is our only means of monitoring phytoplankton in the entire surface ocean at high temporal and large spatial scales, and the continuous ocean-colour data record is now approaching a length suitable for addressing questions around climate change, at least in some regions. Yet, developing ocean-colour algorithms for climate change studies requires addressing issues of ambiguity in the ocean-colour signal. For example, for the same chlorophyll-a concentration (Chl-a) of phytoplankton, the colour of the ocean can be different depending on the type of phytoplankton present. One route to tackle the issue of ambiguity is by enriching the ocean-colour data with information on sea surface temperature (SST), a good proxy of changes in three phytoplankton size classes (PSCs) independent of changes in total Chl-a, a measure of phytoplankton biomass. Using a global surface in- situ dataset of HPLC (high performance liquid chromatography) pigments, size-fractionated filtration data, and concurrent satellite SST spanning from 1991 to 2021, we re-tuned, validated and advanced an SST-dependent three-component model that quantifies the relationship between total Chl-a and Chl-a associated with the three PSCs (pico-, nano- and microplankton). Similar to previous studies, striking dependencies between model parameters and SST were captured, which were found to improve model performance significantly. These relationships were applied to 40 years of monthly composites of satellite SST, and significant trends in model parameters were observed globally, in response to climate warming.

Editor(s)
na


Institution
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA

Where published
Remote Sensing of Environment

Publication Identifiers
ISSN - 0034-4257

Address
na

Publisher
Elsevier BV



Document Identifiers
DOI - https://doi.org/10.1016/j.rse.2022.113415
URL - http://dx.doi.org/10.1016/j.rse.2022.113415

Rankings
SCOPUS (2023)
SCOPUS Q1 (2023) - 1 - Remote Sensing