Search Results (58)

Small pelagic fishes play a crucial role in structuring marine food webs, yet their trophic flexibility and feeding interactions remain poorly understood in highly dynamic, nutrient-rich systems such as upwelling regions. This study combines bulk stable isotope analysis (δ¹³C and δ¹⁵N), compound-specific nitrogen isotope analysis of amino acids (CSIA-AA), and fatty acid (FA) profiles to assess feeding patterns and trophic overlap among four planktivorous species in the North Iberian shelf (Galicia and the Cantabrian Sea). The combined trophic indicators reveal clear niche partitioning between clupeids (sardine and anchovy) and scombrids (mackerel and chub mackerel), with the latter exhibiting higher CSIA-AA-derived trophic positions and distinct FA composition. Our analysis further shows that fatty acid biomarkers are essential for resolving finer-scale differences within each group, driven by variable contributions of phytoplankton and zooplankton to species diets. Although all species shared resources within the same food web, isotopic baselines indicate a decoupling between carbon and nitrogen pathways. For sardine, we compared neutral and polar lipid fractions with the total lipid extract in terms of FA composition and key dietary markers. Our results suggest that separating lipid fractions can improve dietary resolution, especially when lipid content is low. Overall, our findings highlight the value of integrating classical and emerging biochemical tracers to better resolve trophic dynamics in coexisting planktivorous fishes. Full article

The Guajira Upwelling System (GUS) is located between 10–12.5° N and 61–75.5° W in the Southern–Central Caribbean Sea. This study examines its spatial and seasonal variability using upwelling indices derived from surface differences in temperature, salinity, density, and absolute dynamic topography between the GUS and a nearby Caribbean region (78–68° W, 10–16° N) not affected by coastal upwelling. Weekly time series from 1998 to 2022 were analyzed. The difference-based indices were compared with Ekman transport, a conventional proxy for upwelling intensity, and with satellite-derived chlorophyll-a to evaluate the phytoplankton response. Seasonal cycles were further examined at four representative grid points along the system. Among the indices, sea surface temperature most effectively delineated the spatial extent and seasonal variability of the GUS. Comparisons with chlorophyll-a revealed a strong upwelling–biomass relationship in the northern sector (east of 73.5° W), whereas productivity in the southern sector was not primarily driven by coastal upwelling. Correlation maps indicated that the weakening of upwelling influence coincided with the region affected by the Magdalena River plume. Full article

Satellite chlorophyll–a (Chla) products are widely used to study coastal productivity, but their performance often degrades in river-influenced and optically complex waters. We evaluated MODIS-Aqua Chla retrievals in the coastal upwelling area off central-southern Chile, a region strongly affected by seasonal river plumes, using monthly in situ Chla and hydrographic observations from Station 18 (August 2002 to September 2011), daily MODIS products, and matchup analyses based on 3 × 3 pixel windows and 1-, 3-, 5-, and 7-day composites. MODIS Chla and normalized Fluorescence Line Height (nFLH) reproduced the broad seasonal cycle, with maxima during spring–summer, but default MODIS Chla systematically exceeded in situ observations, particularly during periods of enhanced turbidity and river-influenced optical complexity. Among the raw satellite products, 1-day MODIS Chla matchups showed the strongest agreement with in situ Chla (r = 0.77, RMSE = 8.5 mg m⁻³), whereas 5-day composites increased matchup availability to 95% but reduced the correlation (r = 0.46, RMSE = 10.5 mg m⁻³). In contrast, nFLH showed more stable performance across composite lengths, although it underestimated high Chla values and should therefore be interpreted as a complementary fluorescence-based diagnostic rather than as a direct substitute for locally validated Chla retrievals. A gradient boosting model trained with MODIS remote-sensing reflectances improved the correspondence between satellite and in situ Chla relative to the default MODIS product within the available Station 18 matchup dataset. Because this model was evaluated using cross-validation rather than an independent regional validation dataset, the machine-learning results should be interpreted as a local proof of concept rather than a fully validated regional algorithm. These results indicate that standard MODIS algorithms overestimate Chla in this river-influenced upwelling system and highlight the value of local correction approaches, including machine-learning methods, for improving coastal ocean color products, provided that future applications include independent spatially distributed validation and improved bio-optical characterization of river-influenced waters. Full article

Interannual climate variability exerts a strong control on the thermohaline structure of eastern boundary upwelling systems, particularly in transition zones where distinct water masses converge. Seasonal and interannual variability in temperature and salinity were examined in the southern California Current System for the period 2000–2015 using hydrographic observations and satellite altimetry, analyzed by season and ENSO phase. During El Niño, the upper 100 m exhibits positive temperature and salinity anomalies of 1–2 °C and ~0.1–0.2 g kg⁻¹ associated with 50–80 m isopycnal deepening, reduced upwelling-induced ventilation, the expansion of subtropical waters onto the shelf, and enhanced poleward geostrophic transport. In contrast, La Niña conditions shoal isopycnals, enhances upper-layer stratification, and sustains equatorward flow throughout the year. Temperature and salinity anomalies extend below 100 m, suggesting a remote reorganization of the baroclinic structure at the shelf–ocean boundary. Salt fingering is inferred to be the dominant non-conventional mixing process in the region, with peak occurrence in autumn. These results highlight that ENSO confines thermohaline reorganization to the inner continental shelf (~150 km), modulates coastal–ocean density gradients, weakens equatorward geostrophic transport during El Niño, and alters coastal–ocean heat and salt exchanges within the southern CCS transition zone. Full article

Eastern Boundary Upwelling Systems (EBUSs) are among the most productive marine biomes globally, renowned for their substantial pelagic fisheries. While the role of wind-driven upwelling in stimulating primary production is well-documented, the integral contributions of the marine benthos in maintaining ecosystem productivity and fishery yields are often underrepresented. This article analyzes evidence from the Humboldt, California, Benguela, and Canary Current systems to delineate the critical functions of the seabed and its resident communities. Three primary pathways through which the benthos supports fisheries are described: (1) by facilitating the efficient regeneration of nutrients from sedimenting organic matter, thereby replenishing the inorganic nutrient pool for subsequent primary production; (2) by providing essential habitat structure that supports the life history of a myriad of species, including demersal and coastal fish species, serving as nursery and feeding grounds; and (3) by forming the foundational trophic base for benthic-feeding fishes and invertebrates of commercial importance. By comparing system-specific characteristics, such as the influence of oxygen minimum zones on benthic community structure, the integrity of the benthic subsystem as a fundamental determinant of the productivity and sustainability of EBUS fisheries is demonstrated. A holistic management approach that includes benthic habitat conservation is therefore paramount. Full article

The occurrence of marine heatwaves (MHWs) and phytoplankton blooms is accelerating under climate change, yet the frequency and drivers of their compound co-occurrence remain poorly understood. Using coastal-optimized satellite observations from 2003–2020, we mapped global compound MHW–phytoplankton bloom (MHW-PB) events across coastal large marine ecosystems and quantified their spatiotemporal trends and environmental predictors. Compound events are increasing at 4.8% yr⁻¹, driven primarily by a 6.5% yr⁻¹ rise in MHW frequency; a temporal shuffle test confirms this trend falls below random co-occurrence expectation, indicating biological suppression actively constrains compound event growth. The compound independence factor (CIF) reveals latitudinal heterogeneity: low-latitude upwelling systems show MHW–PB mutual exclusivity, while high-latitude and eutrophic coastal regions show positive co-occurrence tendency. Interpretable machine learning further shows that nutrient availability dominates bloom responses at low latitudes whereas light dominates at high latitudes, with MHW intensity exhibiting nutrient-dependent non-linear associations with bloom probability. Paradoxically, compound frequency accelerates nearly twice as fast in low latitudes (6.1% yr⁻¹) as in high latitudes (3.5% yr⁻¹), driven by rapid tropical MHW acceleration. These diverging regimes signal dual ecological risks: trophic mismatches in upwelling systems and escalating hypoxia and harmful algal bloom hazards in eutrophic coastal waters. Full article

The Eastern Tropical Pacific (ETP) comprises several coral ecosystems, which are distributed across a variety of coastal zones and oceanic islands. In these ecosystems, reef fish play key roles in their functioning. In ETP, there is a paucity of studies that have evaluated fish functional diversity (FD) and compared oceanic and coastal systems from a predominantly trophic perspective. A comparative analysis was conducted on fish FD in seven coral ecosystems, encompassing three distinct environmental contexts: (1) Oceanic, (2) Coastal-influenced, and (3) Coastal. The hypothesis that FD varies spatially along this oceanic–coastal gradient is predicated on the premise that such variation is attributable to differences in disturbance regimes and environmental conditions. Our results show that not all functional α-diversity indices exhibited significant variation among zones. However, analysis of functional dominance, divergence, dispersion, and β-diversity analyses revealed clear spatial variation in functional structure, partially supporting expectations related to disturbance regimes across the oceanic–coastal gradient. These patterns may be indicative of increasing disturbance intensity, in conjunction with other interacting processes such as variability in larval supply, recruitment dynamics, and environmental conditions, including fishing pressure, sedimentation, nutrient inputs, and coastal upwelling. The findings of this study demonstrate the efficacy of functional diversity metrics in assessing reef fish responses to both natural and anthropogenic disturbances. In addition, the present study offers actionable insights with regard to the formulation of conservation and management strategies in the Mexican Eastern Tropical Pacific. Full article

Coastal seas around Aotearoa, New Zealand, are among the least observed parts of the global ocean, limiting our ability to monitor and forecast marine conditions. The Moana Project addresses this gap with a new observing system that includes temperature sensors mounted on commercial fishing gear—the Mangōpare fishing vessel network. This study presents the first evaluation of New Zealand’s operational ocean 4D-Var data assimilation system that incorporates these fishing vessel (FV) observations into a regional ROMS model. Using just over one year of operational forecasts, we show that FV temperature profiles significantly improve subsurface temperature representation, especially in coastal regions where satellite products have warm biases or miss key features such as upwelling and mesoscale variability. Assimilation of FV data reduces background temperature biases throughout the upper ocean and enhances forecast skill in areas influenced by major currents and dynamic coastal processes. We also identify sensitivity to periods of missing satellite sea surface temperature, which can lead to overfitting of the available observations. Overall, the results demonstrate that FV observations provide essential subsurface information and can substantially strengthen operational coastal ocean forecasting systems. Full article

Accurate sea surface temperature (SST) forecasting in coastal upwelling systems requires predictive models capable of representing complex oceanic geometries. This work revisits grid-to-mesh coupling strategies in Graph Neural Networks (GNNs) and analyzes how mesh topology and connectivity influence prediction accuracy and artifact formation. This standard coupling process is a significant source of discretization errors and spurious numerical artifacts that compromise the final forecast’s accuracy. Using daily Copernicus SST and 10 m wind reanalysis data from 2000 to 2020 over the Canary Islands and the Northwest African region, we evaluate four mesh configurations under varying grid-to-mesh connection densities. We analyze two structured meshes and propose two new unstructured meshes for which their nodes are distributed according to the bathymetry of the ocean region. The results show that forecast errors exhibit geometric patterns equivalent to order-k Voronoi tessellations generated by the k-nearest neighbor association rule. Bathymetry-aware meshes with $k=3$ and $k=4$ grid-to-mesh connections significantly reduce polygonal artifacts and improve long-term coherence, achieving up to 30% lower $\mathrm{RMSE}$ relative to structured baselines. These findings reveal that the underlying geometry, rather than node count alone, governs error propagation in autoregressive GNNs. The proposed analysis framework provides a clear understanding of the implications of grid-to-mesh connections and establishes a foundation for artifact-aware, geometry-adaptive learning in operational oceanography. Full article

This study investigates the impact of high-resolution Sea Surface Temperature (SST) boundary conditions on atmospheric simulations over the southwestern Atlantic Ocean (12–27° S, 32–48° W). Numerical experiments were conducted using the WRF model with two distinct SST configurations: standard resolution GFS SST data (0.5°) and high-resolution RTG-SST-HR satellite-derived data (0.083°). Simulations covered contrasting seasonal periods (January and July 2016) to capture varying upwelling intensities and atmospheric circulation patterns. Model performance was evaluated against observational data from the Brazilian National Buoy Program (PNBOIA) using statistical metrics including RMSE and Pearson correlation coefficients for wind components. The high-resolution SST experiment demonstrated significant improvements in wind field representation, with RMSE reductions of up to 0.5 m/s for zonal wind components and correlation improvements of approximately 0.1 across multiple validation sites. Most notably, the enhanced SST resolution enabled better representation of mesoscale atmospheric systems, including improved organization and intensification of cyclonic systems in areas near the cyclogenesis regions. The RTG-SST data captured sharp thermal gradients and coastal upwelling signatures that were spatially smoothed in the GFS fields, leading to more realistic surface heat flux patterns and atmospheric boundary layer dynamics. These improvements were particularly pronounced during summer months when thermal gradients were strongest, highlighting the critical importance of accurate SST representation for capturing high-intensity atmospheric phenomena in regions of strong air-sea interaction. Full article

Meiofaunal assemblages are crucial components of benthic ecosystems, significantly contributing to organic matter cycling and energy transfer. However, baseline quantitative data from some upwelling systems remain limited. This study characterizes the abundance, vertical distribution, and secondary production of meiofauna at a coastal upwelling station off southern Peru (14°16′ S) for July 2006 (Neutral conditions) and May 2007 (moderate La Niña, LN), using four-replicated sediment cores sectioned into 0–1, 1–2, 2–5, and 5–10 cm layers. While Nematoda (families Desmodoridae, Chromadoridae, Monhysteridae, Oxystominidae, Comesomatidae) dominated the community (>79% in all layers, both years), the total taxonomic richness did not differ substantially between study periods nor across the sediment column for 2006 or for 2007. Total density (0–10 cm) fluctuated between 3916 ± 2202 Ind 10 cm⁻² in 2006 and 4203 ± 2274 Ind 10 cm⁻² in 2007, with non-significant changes. Biomass (µgC 10 cm⁻²) in 2006 ranged from 80 ± 24 in the 5–10 cm section to 455 ± 134 in the 2–5 cm section. The uppermost 0–1 cm layer showed 238 ± 155, while the 1–2 cm section reached 302 ± 69. In 2007, biomass was consistently higher in the surface layers, with maximum values in the 1–2 cm section (500 ± 534), followed by the 0–1 cm section (376 ± 34). Hierarchical clustering produced depth-ordered groups with high within-depth similarity (>80–90%). SIMPER results identified Desmodora, Comesomatidae, and Chromadoridae among the top contributors to within-depth similarity and to the dissimilarity observed between surface and subsurface assemblages. A depth-related gradient of community composition was detected, suggesting vertical habitat heterogeneity modulated by several environmental factors; however, PERMANOVA analysis residuals (96.73%) indicate a high variation not explained by ENSO phase, sediment section, or their interaction, suggesting other unmeasured factors explaining meiofaunal community structure. Meiofauna’s production ranged from 2.836 ± 0.049 gC m⁻² y⁻¹ in 2006 to 3.106 ± 1.566 gC m⁻² y⁻¹ in 2007. These findings expand the limited knowledge on meiofaunal abundance and metabolic demands in this ocean region, fostering future efforts for comparative analyses across latitudes, depth gradients, and oceanographic regimes. Full article

Coastal upwelling off La Guajira, Colombia, is an atypical system where persistent easterly winds drive upwelling along a zonally oriented coastline. To characterize its seasonal cycle and variability, the ROMS AGRIF hydrodynamic model was implemented under climatological forcing. Three indicators were analyzed: the 25 °C isotherm, the 36.5 isohaline, and sea-level anomalies. The simulations showed that upwelling initiates in December, reaches maximum intensity during February–April, and weakens from September to November. At maturity, vertical velocities up to 8.5 m·day⁻¹ and the shoaling of Subtropical Underwater (T = 22–25 °C; S = 36.5–37.0) dominate the coastal domain, producing widespread surface cooling (23–24 °C) and salinity enhancement. During relaxation, weaker winds and the influence of the Caribbean Coastal Undercurrent displace the upwelled waters to below 80–100 m in depth, with surface temperatures above 27 °C. Model performance against MODIS Aqua SST was high (d > 0.99; RMSE < 1.7 °C), confirming its reliability to reproduce the observed thermal cycle. The multiparametric approach reveals that upwelling persistence depends on both seasonal trade wind forcing and regional circulation. This framework provides a more integrated description of the Guajira upwelling system than previous studies and supports applications in fisheries management, ecosystem monitoring, and maritime operations. Full article

This study examines the upper-ocean response to Typhoon Khanun, which traversed the northern South China Sea in October 2017, by integrating multi-satellite observations with numerical simulations from the Regional Ocean Modeling System (ROMS). For the ROMS simulations, an Arakawa C-grid was adopted with a 4-km horizontal resolution and 40 vertical terrain-following $\sigma$-layers, covering the domain of 105° E to 119° E and 15° N to 23° N. Typhoons significantly influence ocean dynamics, altering sea surface temperature (SST), sea surface salinity (SSS), and ocean currents, thereby modulating air–sea exchange processes and marine ecosystem dynamics. High-resolution satellite datasets, including GHRSSST for SST, SMAP for SSS, GPM IMERG for precipitation, and GLORYS12 for sea surface height, were combined with ROMS simulations configured at a 4-km horizontal resolution with 40 vertical layers to analyze ocean changes from 11 to 18 October 2017. The results show that Typhoon Khanun induced substantial SST cooling, with ROMS simulations indicating a maximum decrease of 1.94 °C and satellite data confirming up to 1.5 °C, primarily on the right side of the storm track due to wind-driven upwelling and vertical mixing. SSS exhibited a complex response: nearshore regions, such as the Beibu Gulf, experienced freshening of up to 0.1 psu driven by intense rainfall, while the right side of the storm track showed a salinity increase of 0.6 psu due to upwelling of saltier deep water. Ocean currents intensified significantly, reaching speeds of 0.5–1 m/s near coastal areas, with pronounced vertical mixing in the upper 70 m driven by Ekman pumping and wave-current interactions. By effectively capturing typhoon-induced oceanic responses, the integration of satellite data and the ROMS model enhances understanding of typhoon–ocean interaction mechanisms, providing a scientific basis for risk assessment and disaster management in typhoon-prone regions. Future research should focus on refining model parameterizations and advancing data assimilation techniques to improve predictions of typhoon–ocean interactions, providing valuable insights for disaster preparedness and environmental management in typhoon-prone regions. Full article

Sea surface temperature (SST) plays a pivotal role in air–sea interactions, with implications for climate, weather, and marine ecosystems, particularly in regions like the Caribbean Sea, where upwelling and dynamic oceanographic processes significantly influence biodiversity and fisheries. This study evaluates the performance of foundational models, Chronos and Lag-Llama, in forecasting SST using 22 years (2002–2023) of high-resolution satellite-derived and in situ data. The Chronos model, leveraging zero-shot learning and tokenization methods, consistently outperformed Lag-Llama across all forecast horizons, demonstrating lower errors and greater stability, especially in regions of moderate SST variability. The Chronos model’s ability to forecast extreme upwelling events is assessed, and a description of such events is presented for two regions in the southern Caribbean upwelling system. The Chronos forecast resembles SST variability in upwelling regions for forecast horizons of up to 7 days, providing reliable short-term predictions. Beyond this, the model exhibits increased bias and error, particularly in regions with strong SST gradients and high variability associated with coastal upwelling processes. The findings highlight the advantages of foundational models, including reduced computational demands and adaptability across diverse tasks, while also underscoring their limitations in regions with complex physical oceanographic phenomena. This study establishes a benchmark for SST forecasting using foundational models and emphasizes the need for hybrid approaches integrating physical principles to improve accuracy in dynamic and ecologically critical regions. Full article

This study evaluates the potential impact of the Copernicus Imaging Microwave Radiometer (CIMR) mission on the sea surface temperature (SST) products of the Mediterranean Sea. Currently, infrared (IR) radiometers provide accurate, high-resolution SST measurements, but they are limited by their inability to see through clouds. Passive microwave (PMW) radiometers, on the other hand, offer monitoring capabilities in almost all weather conditions but typically at lower spatial resolutions. The CIMR mission represents a notable advance in microwave remote sensing of SSTs, as it will ensure a ≤15 km spatial resolution in the recovered SST field. Using an observing system simulation experiment (OSSE), this study evaluates the effect of inserting synthetic CIMR observations into the Copernicus Mediterranean SST analysis system, which is based on an optimal interpolation (OI) algorithm. The OSSE was conducted using data for the year 2017, including daily SST and salinity outputs from a Mediterranean Sea model, hourly precipitation rates from the IMERG, and wind and cloud cover data from ERA5. The results suggest that the improved spatial resolution and accuracy of the CIMR could potentially improve SST retrievals in the Mediterranean Sea, offering better insights for climate and environmental monitoring in semi-closed basins. Including CIMR data in the OI algorithm reduced the mean error and root mean square error (RMSE) of the SST analysis, especially under conditions of low IR coverage. The greatest improvements were found to occur in July, corresponding to coastal upwelling and Atlantic inflow into the Alboran Sea. Improvements ranged from 16% to 29%, with an overall improvement of 26% for the full year of 2017. In conclusion, this preliminary study indicates that Copernicus Mediterranean Sea HR SST products could benefit from the inclusion of the CIMR in the current IR sensor constellation. Full article