Variations in Remotely-Sensed Phytoplankton Size Structure of a Cyclonic Eddy in the Southwest Indian Ocean

Abstract

Phytoplankton size classes were derived from weekly-averaged MODIS Aqua chlorophyll a data over the southwest Indian Ocean in order to assess changes in surface phytoplankton community structure within a cyclonic eddy as it propagated across the Mozambique Basin in 2013. Satellite altimetry was used to identify and track the southwesterly movement of the eddy from its origin off Madagascar in mid-June until mid-October, when it eventually merged with the Agulhas Current along the east coast of South Africa. Nano-and picophytoplankton comprised most of the community in the early phase of the eddy development in June, but nanophytoplankton then dominated in austral winter (July and August). Microphytoplankton was entrained into the eddy by horizontal advection from the southern Madagascar shelf, increasing the proportion of microphytoplankton to 23% when the chlorophyll a levels reached a peak of 0.36 mg·m −3 in the third week of July. Chlorophyll a levels declined to <0.2 mg·m −3 in austral spring (September and October) as the eddy propagated further to the southwest. Picophytoplankton dominated the community during the spring period, accounting for >50% of the population. As far as is known, this is the first study to investigate temporal changes in chlorophyll a and community structure in a cyclonic eddy propagating across an ocean basin in the southwest Indian Ocean.

Long‐Term Trends in Phytoplankton Chlorophyll a and Size Structure in the Benguela Upwelling System

“…Although previous studies have described a good agreement between in situ and satellite Chla with regard to seasonal and shorter‐term changes and spatial variations (e.g., Lamont, Barlow, et al, ; Lamont, Brewin, et al, ), it is difficult to relate the interannual and long‐term in situ patterns described above to those observed from satellite data. This is primarily due to the spatial and temporal differences in the sampling resolution between the in situ and satellite data.…”

“…Although numerous investigations have shown the utility of ocean color measurements and demonstrated good agreement with in situ observations, with regard to spatial and seasonal changes, as well as shorter‐term variations (Lamont, Barlow, et al, ; Lamont, Brewin, et al, ), several inconsistencies with longer‐term variations and trends have been highlighted, with in situ and satellite time series in some cases showing seemingly contradictory patterns (Jarre et al, ). As discussed by Verheye et al (), in light of the limited availability of in situ data, validation of the long‐term temporal changes identified from ocean color time series is challenging, particularly in regions such as the BUS and surrounding open ocean.…”

“…As discussed by Verheye et al (), in light of the limited availability of in situ data, validation of the long‐term temporal changes identified from ocean color time series is challenging, particularly in regions such as the BUS and surrounding open ocean. The fact that satellite‐derived Chla and size structure are considered to represent the surface layers only (Lamont, Barlow, et al, ; Lamont, Brewin, et al, ) highlights a critical gap in the sampling of phytoplankton communities from space and emphasizes the necessity of sustained accurate long‐term subsurface measurements, for instance, through autonomous platforms such as biogeochemical Argo floats (Claustre et al, ). Nevertheless, these ocean color observations, together with the application of models to assess variations in size structure, as presented in this study, among others (Brewin et al, , ; Hirata et al, ; Lamont, Barlow, et al, ; Lamont, Brewin, et al, ) provide new data sets which afford the opportunity for more detailed investigations of phytoplankton communities, as well as their responses to climate change and variation.…”

“…The fact that satellite‐derived Chla and size structure are considered to represent the surface layers only (Lamont, Barlow, et al, ; Lamont, Brewin, et al, ) highlights a critical gap in the sampling of phytoplankton communities from space and emphasizes the necessity of sustained accurate long‐term subsurface measurements, for instance, through autonomous platforms such as biogeochemical Argo floats (Claustre et al, ). Nevertheless, these ocean color observations, together with the application of models to assess variations in size structure, as presented in this study, among others (Brewin et al, , ; Hirata et al, ; Lamont, Barlow, et al, ; Lamont, Brewin, et al, ) provide new data sets which afford the opportunity for more detailed investigations of phytoplankton communities, as well as their responses to climate change and variation. Since phytoplankton communities form the base of marine ecosystems (Chassot et al, ; Field et al, ; Sathyendranath et al, ), such as the highly productive BUS which supports large fisheries and other ecosystem goods and services of substantial economic value (Kirkman et al, ; Verheye et al, ), understanding and monitoring variations in phytoplankton biomass and community structure is crucial to evaluating the functioning and health status of these ecosystems.…”

“…Microphytoplankton Chla ( C m ) was computed using the remaining fucoxanthin (attributed to the microphytoplankton size class) and peridinin (Brewin, Sathyendranath, et al, ; Devred et al, ). Further details of the refinement, parameterization, and application of the retuned model to the Southern African marine environment are described in Lamont, Brewin, et al () and Lamont, Barlow, et al ().…”