Sea-level rise (SLR) not only increases the threat of coastal flooding, but may also change tidal regimes in estuaries and coastal bays. To investigate such nearshore tidal responses to SLR, a hydrodynamic model of the European Shelf is downscaled to a model of a Dutch coastal bay (the Oosterschelde, i.e., Eastern Scheldt) and forced by SLR scenarios ranging from 0 to 2 m. This way, the effect of SLR on tidal dynamics in the adjacent North Sea is taken into account as well. The model setup does not include meteorological forcing, gravitational circulation, and changes in bottom topography. Our results indicate that SLR up to 2 m induces larger increases in tidal amplitude and stronger nonlinear tidal distortion in the bay compared to the adjacent shelf sea. Under SLR up to 2 m, the bay shifts from a mixed flood- and ebb-dominant state to complete ebb dominance. We also find that tidal asymmetry affects an important component of sediment transport. Considering sand bed-load transport only, the changed tidal asymmetry may lead to enhanced export, with potential implications for shoreline management. In this case study, we find that local impacts of SLR can be highly spatially varying and nonlinear. The model coupling approach applied here is suggested as a useful tool for establishing local SLR projections in estuaries and coastal bays elsewhere. Future studies should include how SLR changes the bed morphology as well as the feedback effect on tides.

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.

Kelp cultivation receives increasing interest for its high-value products and ecological services, especially in Europe and North America. Before industrial kelp farming in marine ecosystems continue to scale up, evaluation of the site-wide production relative to ecological carrying capacity (CC) of the identified system is essential. For this purpose, a mechanistic kelp model was developed and applied for hypothetical numerical experiments of expanding the farming area in a Dutch coastal bay (the Eastern Scheldt), where cultivation of Saccharina latissima (sugar kelp) is emerging. The kelp model was implemented within a three-dimensional hydrodynamic–biogeochemical model to account for the environmental interactions. The model captured the seasonal growth dynamics of S. latissima, as well as its carbon and nitrogen contents measured at the Eastern Scheldt pilot sites. The model results suggest that expanding the kelp farming area to ∼1–30% of the bay (representing ∼3.4–75 kt harvest dry weight in the 350-km2 bay) had the potential to weaken the spring bloom, and thereby affected the coexisting shellfish culture in the bay. Competition between S. latissima and phytoplankton mostly occurred in late spring for nutrients (dissolved inorganic nitrogen). The ecological CC should be weighed according to these negative impacts. However, the production CC was not reached even when farming ∼30% of the Eastern Scheldt, i.e. harvesting totally 75 kt dry mass, given that the simulated overall S. latissima production kept increasing with the farming activity. Our modelling approach can be applied to other systems for S. latissima cultivation and assist in assessing CC and environmental impacts.

The spatiotemporal variability of phytoplankton biomass has been widely studied because of its importance in biogeochemical cycles. Chlorophyll a (Chl-a)—an essential pigment present in photoautotrophic organisms—is widely used as an indicator for oceanic phytoplankton biomass because it could be easily measured with calibrated optical sensors. However, the intracellular Chl-a content varies with light, nutrient levels, and temperature and could misrepresent phytoplankton biomass. In this study, we estimated the concentration of phytoplankton carbon—a more suitable indicator for phytoplankton biomass—using a regionally adjusted bio-optical algorithm with satellite data in the South China Sea (SCS). Phytoplankton carbon and the carbon-to-Chl-a ratio (θ) exhibited considerable variability spatially and seasonally. Generally, phytoplankton carbon in the northern SCS was higher than that in the western and central parts. The regional monthly mean phytoplankton carbon in the northern SCS showed a prominent peak during December and January. A similar pattern was shown in the central part of SCS, but its peak was weaker. Besides the winter peak, the western part of SCS had a secondary maximum of phytoplankton carbon during summer. θ exhibited significant seasonal variability in the northern SCS, but a relatively weak seasonal change in the western and central parts. θ had a peak in September and a trough in January in the northern and central parts of SCS, whereas in the western SCS the minimum and maximum θ was found in August and during October–April of the following year, respectively. Overall, θ ranged from 26.06 to 123.99 in the SCS, which implies that the carbon content could vary up to four times given a specific Chl-a value. The variations in θ were found to be related to changing phytoplankton community composition, as well as dynamic phytoplankton physiological activities in response to environmental influences; which also exhibit much spatial differences in the SCS. Our results imply that the spatiotemporal variability of θ should be considered, rather than simply used a single value when converting Chl-a to phytoplankton carbon biomass in the SCS, especially, when verifying the simulation results of biogeochemical models.

During the altimeter era, the sea level in the South China Sea (SCS) and western tropical Pacific (WTP) experienced significant decadal variability. The sea level rose during 1993–2009 and fell during 2010–2019. The decadal variability of Walker Circulation associated with the Pacific Decadal Oscillation can explain the sea level variability in the WTP to a great extent. The wind forced westward propagating Rossby waves increased (decreased) the sea level in the WTP during 1993–2009 (2010–2019). However, the interior wind forcing has a negligible contribution to the decadal variability of the sea level in the SCS. The remote forcing from WTP through the oceanic bridge was supposed to play a dominant role. The sensitive experiments of a 1½‐layer model and Regional Oceanic Modeling System suggested that the sea level signals via the Sibutu Passage and Mindoro Strait accounted for the decadal variability of sea level in the central basin of SCS.