Abstract

The timing of phytoplankton growth (phenology) in tropical oceans is a crucial factor influencing the survival rates of higher trophic levels, food web structure and the functioning of coral reef ecosystems. Phytoplankton phenology is thus categorised as an ‘ecosystem indicator’, which can be utilised to assess ecosystem health in response to environmental and climatic perturbations. Ocean-colour remote sensing is currently the only technique providing global, long-term, synoptic estimates of phenology. However, due to limited available in situ datasets, studies dedicated to the validation of satellite-derived phenology metrics are sparse. The recent development of autonomous oceanographic observation platforms provides an opportunity to bridge this gap. Here, we use satellite-derived surface chlorophyll-a (Chl-a) observations, in conjunction with a Biogeochemical-Argo dataset, to assess the capability of remote sensing to estimate phytoplankton phenology metrics in the northern Red Sea – a typical tropical marine ecosystem. We find that phenology metrics derived from both contemporary platforms match with a high degree of precision (within the same 5-day period). The remotely-sensed surface signatures reflect the overall water column dynamics and successfully capture Chl-a variability related to convective mixing. Our findings offer important insights into the capability of remote sensing for monitoring food availability in tropical marine ecosystems, and support the use of satellite-derived phenology as an ecosystem indicator for marine management strategies in regions with limited data availability.

Details

Title
Evaluating tropical phytoplankton phenology metrics using contemporary tools
Author
Gittings, John A 1 ; Raitsos, Dionysios E 2 ; Kheireddine Malika 3 ; Marie-Fanny, Racault 4   VIAFID ORCID Logo  ; Claustre Hervé 5 ; Hoteit Ibrahim 1 

 King Abdullah University of Science and Technology (KAUST), Department of Earth Science and Engineering, Thuwal, Saudi Arabia (GRID:grid.45672.32) (ISNI:0000 0001 1926 5090) 
 Plymouth Marine Laboratory (PML), Remote Sensing Group, The Hoe, Plymouth, United Kingdom (GRID:grid.22319.3b) (ISNI:0000000121062153); Plymouth Marine Laboratory (PML), National Centre for Earth Observation (NCEO), Plymouth, United Kingdom (GRID:grid.22319.3b) (ISNI:0000000121062153); National and Kapodistrian University of Athens, Department of Biology, Athens, Greece (GRID:grid.5216.0) (ISNI:0000 0001 2155 0800) 
 King Abdullah University of Science and Technology (KAUST), Red Sea Research Centre, Biological and Environmental Science and Engineering Division, Thuwal, Saudi Arabia (GRID:grid.45672.32) (ISNI:0000 0001 1926 5090) 
 Plymouth Marine Laboratory (PML), Remote Sensing Group, The Hoe, Plymouth, United Kingdom (GRID:grid.22319.3b) (ISNI:0000000121062153); Plymouth Marine Laboratory (PML), National Centre for Earth Observation (NCEO), Plymouth, United Kingdom (GRID:grid.22319.3b) (ISNI:0000000121062153) 
 Laboratoire d’Océanographie de Villefranche, Marine Optics and Remote Sensing Laboratory, Villefranche-sur-Mer, France (GRID:grid.499565.2) (ISNI:0000 0004 0366 8890) 
Publication year
2019
Publication date
Jan 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2344210688
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.