Drivers of the spatial phytoplankton gradient in estuarine–coastal systems: generic implications of a case study in a Dutch tidal bay
As the primary energy and carbon source in aquatic food webs, phytoplankton generally display spatial heterogeneity due to complicated biotic and abiotic controls; however our understanding of the causes of this spatial heterogeneity is challenging, as it involves multiple regulatory mechanisms. We applied a combination of field observation, numerical modeling, and remote sensing to display and interpret the spatial gradient of phytoplankton biomass in a Dutch tidal bay (the Eastern Scheldt) on the east coast of the North Sea. The 19 years (1995–2013) of monitoring data reveal a seaward increa... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2020 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28997339 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://www.vliz.be/imisdocs/publications/27/351027.pdf |
As the primary energy and carbon source in aquatic food webs, phytoplankton generally display spatial heterogeneity due to complicated biotic and abiotic controls; however our understanding of the causes of this spatial heterogeneity is challenging, as it involves multiple regulatory mechanisms. We applied a combination of field observation, numerical modeling, and remote sensing to display and interpret the spatial gradient of phytoplankton biomass in a Dutch tidal bay (the Eastern Scheldt) on the east coast of the North Sea. The 19 years (1995–2013) of monitoring data reveal a seaward increasing trend in chlorophyll-a (chl a ) concentrations during the spring bloom. Using a calibrated and validated three-dimensional hydrodynamic–biogeochemical model, two idealized model scenarios were run: switching off the suspension feeders and halving the open-boundary nutrient and phytoplankton loading. Results reveal that bivalve grazing exerts a dominant control on phytoplankton in the bay and that the tidal import mainly influences algal biomass near the mouth. Satellite data captured a post-bloom snapshot that indicated the temporally variable phytoplankton distribution. Based on a literature review, we found five common spatial phytoplankton patterns in global estuarine–coastal ecosystems for comparison with the Eastern Scheldt case: seaward increasing, seaward decreasing, concave with a chlorophyll maximum, weak spatial gradients, and irregular patterns. We highlight the temporal variability of these spatial patterns and the importance of anthropogenic and environmental influences.