A Web-based Lesson on Ocean-Color Observations in the Red Sea: Phytoplankton Phenological Indices and Their Importance for Coral Reef Biology

EarthzineOriginal

A Web-based lesson called LearnEO! uses ocean color images to quantify phytoplankton seasonality and help us understand the functioning of coral reef ecosystems.

Figure: Coral Reefs in the Red Sea. Image Credit: D.E. Ralstos

Figure 1: Coral Reefs in the Red Sea. Image Credit: D.E. Raitsos

Coral reefs are among the most biologically diverse ecosystems on Earth. They occupy less than 0.1 percent of the world’s ocean surface, and yet they host 25 percent of all the marine species (1). Coral reefs deliver valuable and vital ecosystem services. They offer a source of food, coastal protection, and employment through fisheries, recreation, and tourism for millions of people around the world. However, coral reefs are fragile ecosystems, facing serious threats from climate change, marine acidification, destructive and unsustainable fishing practices, and water-polluting land-use activities (2).

The Red Sea hosts some of the most pristine coral reefs that have adapted to live in one of the most saline and warm seas in the world (Figure 1). In addition to being a very warm environment, the Red Sea is experiencing a particularly rapid increase in temperature, which began abruptly in the mid-90s and persists (3). These unique conditions make the Red Sea an excellent laboratory for studying the effects of environmental warming on marine organisms.

Microscopic marine algae, so-called phytoplankton, provide an important source of food for coral reef ecosystems. They are grazed on by the larvae of many species, including fish, crustaceans and mollusks. The magnitude and timing of phytoplankton availability are known to play a fundamental role in the survival of larvae (4,5). If fish larvae and sufficient food (i.e., phytoplankton) are present in the water at the same time, larvae will have a food supply adequate for survival. When this is not so, larvae will be vulnerable to death by starvation.

Over the past two decades, remote sensing measurements of ocean-color have provided unique information on surface marine phytoplankton, allowing us to monitor their distribution at high temporal (1 day or shorter) and spatial (1 km or finer) resolutions. The color of the ocean is a good indicator of chlorophyll-a, the primary photosynthetic pigment found in phytoplankton (Figure 2). The concentration of chlorophyll-a varies seasonally following the growth and decline of phytoplankton populations. The seasonal development of phytoplankton populations is defined as the phytoplankton growing season.

Figure 2: Maps of phytoplankton chlorophyll and coral reef location in the Red Sea. Screenshot of the LearnEO! lesson activity showing maps of chlorophyll concentration from the merged product ESA OC-CCI (left panel), and of bathymetry and coral reef data from UNEP-WCMC (right panel). The color scale on the left indicates the chlorophyll concentration in mgChl/m3. The color scale on the right indicates the depth of the Red Sea basin in meters, and each white square represents the position of a coral reef. Image Credit: LearnEO! lesson on Monitoring Phytoplankton Seasonality

Figure 2: Maps of phytoplankton chlorophyll and coral reef location in the Red Sea. Screenshot of the LearnEO! lesson activity showing maps of chlorophyll concentration from the merged product ESA OC-CCI (left panel), and of bathymetry and coral reef data from UNEP-WCMC (right panel). The color scale on the left indicates the chlorophyll concentration in mgChl/m3. The color scale on the right indicates the depth of the Red Sea basin in meters, and each white square represents the position of a coral reef. Image Credit: LearnEO! lesson on Monitoring Phytoplankton Seasonality

A suite of indices has been proposed to quantify phytoplankton seasonality (6) and provide support to investigations on the composition, structure and functioning of the marine ecosystem (7). The study of specific timing of events in the phytoplankton growing season is referred to as phytoplankton phenology. Important phenological indices include8: 1) the timing of initiation; 2) the timing of maximum amplitude; 3) the timing of termination; and 4) the duration of the phytoplankton growing season.

In the Red Sea, general ecological research and long-term large-scale biological datasets are rare, with the latter mainly limited to satellite-based observations of ocean color (9-11). Hence, there is an important opportunity to promote outreach activities that make use of remote-sensing products readily accessible. In this context, we have developed a Web-based lesson for introducing ocean-color observations and phenology indices to non-remote-sensing experts. This lesson was written as part of the European Space Agency (ESA) Bilko Learn Earth Observation (LearnEO!) lesson-writing competition, and it was awarded first prize in 2014.

In this Web-based lesson, using simple visualization tools, users learn to create a map of remotely-sensed chlorophyll concentration and build a video animation to watch how phytoplankton concentrations are changing from one season to the next in the Red Sea. Users also are able to use bathymetry information and a database of coral reef positions to locate and characterize the distribution of the coral reefs in the Red Sea. Finally, the lesson illustrates how to calculate and map the timing of phytoplankton growth (Figure 3) and offers further insight into why this information is key for fisheries management.

Figure 3: Maps of phytoplankton phenology in the Red Sea. Screenshot of the LearnEO! lesson activity showing maps of timing of initiation (left panel), timing of peak (central panel) and duration (right panel) of the phytoplankton growing period. In the left and central maps, the color scale indicates the week when phytoplankton growth starts and peaks. The color scale on the right map provides information on how many days the phytoplankton grows. Image Credit: LearnEO! lesson on Monitoring Phytoplankton Seasonality

Figure 3: Maps of phytoplankton phenology in the Red Sea. Screenshot of the LearnEO! lesson activity showing maps of timing of initiation (left panel), timing of peak (central panel) and duration (right panel) of the phytoplankton growing period. In the left and central maps, the color scale indicates the week when phytoplankton growth starts and peaks. The color scale on the right map provides information on how many days the phytoplankton grows. Image Credit: LearnEO! lesson on Monitoring Phytoplankton Seasonality

The lesson is based on ESA Ocean-Colour Climate Change Initiative (OC-CCI) dataset, which was released in 2014 by the OC-CCI team, led by Professor Shubha Sathyendranath at the Plymouth Marine Laboratory (PML). The dataset represents the most complete, stable, and error-characterized global ocean-color time-series based on merged observations from three independent satellite sensors: SeaWiFS (NASA), MODIS (NASA) and MERIS (ESA) (12). As the Red Sea experiences extreme and particularly challenging environmental conditions, further regional validation of the OC-CCI data product has been performed by PML scientist Bob Brewin using field measurements (13) collected during research cruises led by KAUST and the TARA expedition. The progress made in the OC-CCI project has permitted us to improve coverage of remotely-sensed chlorophyll measurements (Figure 4) and estimate the phenological characteristics (timings and duration) of the phytoplankton growing periods during the winter and summer seasons. With previous ocean-color products, only the winter phytoplankton could be characterized. This information is interesting because the Red Sea had been known as a winter/spring blooming environment (9,14). However, with the OC-CCI dataset, we revealed that most of the reef-bound coastal waters display equal or higher phytoplankton concentration during summer.

Finally, the phenological method proposed in this lesson may be extended to monitor inter-annual variability of phytoplankton seasonality in the Red Sea and in other reef ecosystems in the world’s oceans. It is anticipated that further studies using advanced algorithms will enable serial assessment of the sensitivity of phytoplankton to environmental and climatic conditions (10) and the possible impact on marine trophic interactions.

Figure 4: Data coverage from different ocean-color products in the Red Sea. Spatial and seasonal coverage of chlorophyll data for the period 2003‰ÛÒ2010 for the merged product ESA OC-CCI (which includes data processed using POLYMER atmospheric correction algorithm12 for MERIS, and using SeaDAS algorithm for SeaWiFS and MODIS), and for each individual sensor SeaWiFS, MODIS and MERIS (data processed using SeaDAS atmospheric correction algorithm for all three sensors). Image Credit: Racault et al., 2015

Figure 4: Data coverage from different ocean-color products in the Red Sea. Spatial and seasonal coverage of chlorophyll data for the period 2003‰ÛÒ2010 for the merged product ESA OC-CCI (which includes data processed using POLYMER atmospheric correction algorithm12 for MERIS, and using SeaDAS algorithm for SeaWiFS and MODIS), and for each individual sensor SeaWiFS, MODIS and MERIS (data processed using SeaDAS atmospheric correction algorithm for all three sensors). Image Credit: Racault et al., 2015

Early responses to the lesson have been positive. Maria Thottan, junior marine research fellow, has taken the lesson in her institute at the Fisheries Resource Assessment Division (CMFRI) in Kochi, India, and reported it to be useful in her research on phytoplankton distribution patterns. In her review, Thottan says: ‰ÛÏThe lesson structure can be readily followed and the instructions for the use of the software are very explicit so even non-remote-sensing experts can quickly find themselves mapping and analyzing satellite data.‰Û

Thorran suggested that the lesson could be a useful tool for resource managers as well. ‰ÛÏ(It) helps you to understand how the timing of phytoplankton blooms is important for fish larvae recruitment and how the phenology maps can be useful for fisheries management.‰Û

The lesson also has been tested by students within the field of remote sensing, including John Gittings, a åÊmaster’s student at King Abdullah University of Science and Technology (KAUST). Gittings, who is studying marine science, completed the lesson during an internship in the remote-sensing group at PML. In his review of the resource, Gittings focused on the implications of applying remote-sensing to monitoring of fragile ecosystems such as coral reefs. He recommended the lesson highly as an introduction to the skills necessary for such research.

‰ÛÏThis lesson provides the perfect opportunity to practice several important skills, including the analysis of satellite-derived imagery (i.e., looking for spatial patterns in chlorophyll), creating time-series and the investigation of phytoplankton seasonality ‰Û_ I would recommend this lesson to anyone with an interest in Earth Observation, as the skills acquired are highly transferable to other fields.‰Û

The ability to track phytoplankton blooms in the Red Sea using satellite data has the capacity to further our understanding of the functioning of coral reef ecosystems in ways that will benefit researchers and practitioners alike. It is our hope that the LearnEO! lesson will help broaden the community able to explore and utilize ocean-color data and help us support responsible stewardship of the marine ecosystem

Author Bios

Marie-Fanny Racault and Dionysios Raitsos are earth observation scientists at the Plymouth Marine Laboratory, UK. Their research interests focus on the study of climate-related impact on marine ecosystem resources at regional and global scales using in-situ, remote sensing, and model data.

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