Phytoplankton turn seawater green when their concentration increases. This allows us to monitor them using ocean colour. However, as the spectral properties of phytoplankton and their relationship with other coloured substances in seawater vary, subtle differences (anomalies) in ocean colour occur that can cause large errors in estimates of phytoplankton abundance. Identifying and understanding these anomalies is required to interpret ocean-colour data properly, but not all scientists have access to, or can afford, the instrumentation needed to do this. We show that practical, low-cost tools developed in the 19th century (a Secchi disk and Forel-Ule colour scale) can be used to quantify a colour anomaly in the Weddell Sea. Our findings imply that ocean-colour anomalies can be identified using affordable methods. Furthermore, records collected over the last century may contain clues on how ocean ecosystems have changed with climate.
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http://dx.doi.org/10.1093/plankt/fbae027 | DOI Listing |
J Plankton Res
June 2024
Department of Oceanography, Istituto Nazionale di Oceanografia e Geofisica Sperimentale - OGS, Borgo Grotta Gigante 42/c, 34010 Sgonico, Trieste, Italy.
Phytoplankton turn seawater green when their concentration increases. This allows us to monitor them using ocean colour. However, as the spectral properties of phytoplankton and their relationship with other coloured substances in seawater vary, subtle differences (anomalies) in ocean colour occur that can cause large errors in estimates of phytoplankton abundance.
View Article and Find Full Text PDFJ Environ Manage
December 2020
School of Biological & Marine Sciences, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, UK. Electronic address:
Over the past few decades, partitioning of the surface ocean into ecologically-meaningful spatial domains has been approached using a range of data types, with the aim of improving our understanding of open ocean processes, supporting marine management decisions and constraining coupled ocean-biogeochemical models. The simplest partitioning method, which could provide low-latency information for managers at low cost, remains a purely optical classification based on ocean colour remote sensing. The question is whether such a simple approach has value.
View Article and Find Full Text PDFSci Rep
October 2018
CSIRO Oceans and Atmosphere, Hobart, Australia.
Changes over the scale of decades in oceanic environments present a range of challenges for management and utilisation of ocean resources. Here we investigate sources of global temporal variation in Sea Surface Temperature (SST) and Ocean Colour (Chl-a) and their co-variation, over a 14 year period using statistical methodologies that partition sources of variation into inter-annual and annual components and explicitly account for daily auto-correlation. The variation in SST shows bands of increasing variability with increasing latitude, while the analysis of annual variability in Chl-a shows mostly mid-latitude high variability bands.
View Article and Find Full Text PDFProg Oceanogr
February 2017
European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy.
The Gulf of Guinea represents a wide tract of the African coast with complex and rich coastal ecosystems undergoing various pressures. The seasonal variations of chlorophyll-a concentration (Chla) along the Gulf of Guinea (GoG) and their relations with physical oceanographic variables were analyzed using satellite observations covering the period 2002-2012. The effects of sea surface temperature (SST), sea level anomalies (SLA), winds, geostrophic currents, eddy kinetic energy (EKE), mesoscale eddies and fronts were considered on a monthly time scale.
View Article and Find Full Text PDFSurv Geophys
November 2016
1Plymouth Marine Laboratory (PML), Prospect Place, The Hoe, Plymouth, UK.
Phenology relates to the study of timing of periodic events in the life cycle of plants or animals as influenced by environmental conditions and climatic forcing. Phenological metrics provide information essential to quantify variations in the life cycle of these organisms. The metrics also allow us to estimate the speed at which living organisms respond to environmental changes.
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