Ana Bio

Vegetated intertidal ecosystems, such as seagrass meadows, salt marshes, and macroalgal beds, are vital for biodiversity, coastal protection, and climate regulation; however, they remain highly vulnerable to anthropogenic and climate-induced stressors. This study aims to assess interannual changes in intertidal vegetation cover along the Portuguese mainland coast from 2015 to 2024 using Sentinel-2 satellite imagery calibrated with high-resolution multispectral unoccupied aerial vehicle (UAV) data, to determine the most accurate index for mapping intertidal vegetation. Among the 16 indices tested, the Atmospherically Resilient Vegetation Index (ARVI) showed the highest predictive performance. Based on a model relating intertidal vegetation cover to this index, an ARVI value greater than or equal to 0.214 was established to estimate the area covered with intertidal vegetation. Applying this threshold to time-series data revealed considerable spatial and temporal variability in vegetation cover, with estuarine systems such as the Ria de Aveiro and the Ria Formosa showing the greatest extents and marked fluctuations. At the national level, no consistent overall trend was identified for the study period. Despite limitations related to satellite image resolution and single-site validation, the results demonstrate the feasibility and utility of combining UAV data and satellite indices for long-term, large-scale monitoring of intertidal vegetation.

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the Ave Estuary, a small, shallow system on Portugal’s north-western coast, and their influence on litter transport and distribution. This site was selected for installing an aquatic litter removal technology under the EU-funded MAELSTROM project. A 2DH hydrodynamic model using Delft3D FM, coupled with the Wflow hydrological model, was implemented and validated. Various scenarios were simulated to assess estuarine dynamics and pinpoint zones prone to litter accumulation and flood risk. The results show that tidal action and river discharge mainly drive the estuary’s behaviour. Under low discharge, floating litter should be mostly transported toward the ocean, while high discharge conditions should result in litter movement at all depths due to stronger currents. High water levels and flooding occur mainly upstream and in specific low-lying areas near the mouth. Low-velocity zones, which can favour litter accumulation, were found around the main channel and on the western margin near the estuary’s mouth, even during high flows. These findings highlight persistent accumulation zones, even under extreme event conditions.

Vegetated intertidal ecosystems, such as seagrass meadows, salt marshes, and macroalgal beds, are vital for biodiversity, coastal protection, and climate regulation; however, they remain highly vulnerable to anthropogenic and climate-induced stressors. This study aims to assess interannual changes in intertidal vegetation cover along the Portuguese mainland coast from 2015 to 2024 using Sentinel-2 satellite imagery calibrated with high-resolution multispectral UAV data, to determine the most accurate index for map-ping intertidal vegetation. Among the 16 indices tested, the Atmospherically Resilient Vegetation Index (ARVI) showed the highest predictive performance. An ARVI threshold value of 0.19 was established to delineate vegetated areas. Applying this threshold to time-series data revealed considerable spatial and temporal variability in vegetation cover, with estuarine systems such as the Ria de Aveiro and the Ria Formosa showing the great-est extents and fluctuations. At the national level, vegetation cover reflects both regional environmental dynamics and data acquisition limitations. Despite limitations related to satellite image resolution and single-site validation, the results demonstrate the feasibility and utility of combining UAV data and satellite indices for long-term, large-scale monitoring of intertidal vegetation.

This study assesses the applicability of different-resolution multispectral remote sensing images for mapping and estimating the aboveground biomass (AGB) of Carpobrotus edulis, a prominent invasive species in European coastal areas. This study was carried out on the Cávado estuary sand spit (Portugal). The performance of three sets of multispectral images with different Ground Sample Distances (GSDs) were compared: 2.5 cm, 5 cm, and 10 cm. The images were classified using the supervised classification algorithm random forest and later improved by applying a sieve filter. Samples of C. edulis were also collected, dried, and weighed to estimate the AGB using the relationship between the dry weight (DW) and vegetation indices (VIs). The resulting regression models were evaluated based on their coefficient of determination (R²), Normalised Root Mean Square Error (NRMSE), p-value, Akaike information criterion (AIC), and the Bayesian information criterion (BIC). The results show that the three tested image resolutions allow for constructing reliable coverage maps of C. edulis, with overall accuracy values of 89%, 85%, and 88% for the classification of the 2.5 cm, 5 cm, and 10 cm GSD images, respectively. The best-performing VI-DW regression models achieved R² = 0.87 and NRMSE = 0.09 for the 2.5 cm resolution; R² = 0.77 and NRMSE = 0.12 for the 5 cm resolution; and R² = 0.64 and NRMSE = 0.15 for the 10 cm resolution. The C. edulis area and total AGB were 3441.10 m² and 28,327.1 kg (with an AGB relative error (RE) = 0.08) for the 2.5 cm resolution; 3070.04 m² and 29,170.8 kg (AGB RE = 0.08) for the 5 cm resolution; and 2305.06 m² and 22,135.7 kg (AGB RE = 0.11) for the 10 cm resolution. Spatial and model differences were analysed in detail to determine their causes. Final analyses suggest that multispectral imagery of up to 5 cm GSD is adequate for estimating C. edulis distribution and biomass.

This study assesses the applicability of different-resolution multispectral remote sensing images for mapping and estimating the aboveground biomass (AGB) of Carpobrotus edulis, a prominent invasive species in European coastal areas. The performance of three sets of multispectral images with different resolutions was compared: (i) 2.5 cm Ground Sample Distance (GSD), 5 cm GSD and 10 cm GSD images. The images were classified using the supervised classification algorithm Random Forest and later improved applying a sieve filter. The results show that the three tested image resolutions allow constructing reliable coverage maps of C. edulis, with Overall Accuracy values of 89%, 85% and 88% for the classification of the 2.5 cm, 5 cm and 10 cm GSD images, respectively. Samples were also collected, dried and weighed to estimate AGB using the relationship between the Dry Weight and Vegetation Indices (VI). The regressions were evaluated based on their R² and Normalised RMSE. The best-performing VI-DW regression models achieved: R² = 0.87 and NRMSE = 0.09 for the 2.5 cm resolution; R² = 0.77 and NRMSE = 0.12 for the 5 cm resolution; and, R² = 0.64 and NRMSE = 0.15 for the 10 cm resolution. C. edulis area and total AGB were: 3441.10 m² and 28,327.1 kg (with a Relative Error (RE) = 0.08), for the 2.5 cm resolution; 3070.04 m² and 29,170.8 kg (RE = 0.08), for the 5 cm resolution; and, 2305.06 m² and 22,135.7 kg (RE = 0.11), for the 10 cm resolution. Differences were analysed in detail, spatially, to determine their causes. Final analyses suggest that, for C. edulis, multispectral imagery of up to 5 cm GSD is adequate for the estimation of the species’ distribution and biomass.

Seagrasses are habitat-forming species that support biodiversity and a wide range of associated ecosystem services, from blue carbon capture to providing nursery areas for a variety of organisms. Their decline has been documented worldwide and is attributed to human impacts ranging from habitat loss and eutrophication to the effects of climate change. However, recent recovery trends have also been documented due to reductions in stressors, passive and active restoration, and even changes in environmental conditions owing to local management. In this study, we document for the first time the occurrence of Zostera noltei in the downstream area of the River Minho Estuary. This occurrence was unexpected given the hydrological conditions of the estuary, characterised by dredging and siltation. We reconstructed the occurrence and historical distribution of seagrass beds, and showed that they have existed in the region for more than a decade. The current distribution area was mapped using high-resolution multispectral remote sensing techniques, and in situ photoquadrats to complement the remote sensing information with an evaluation of the seagrass cover. A current seagrass area of 0.81 ha was found with an average cover of 70%. However, the Minho Estuary continues to be strongly affected by sediment deposition, which may affect the seagrass population in the long term. Continued surveys are recommended to confirm the long-term trend of colonisation of this important habitat, which ultimately provides so many benefits to coastal ecosystems and humankind.

Sandspits are important natural defences against the effects of storm events in estuarine regions, and their temporal and spatial dynamics are related to river flow, wave energy, and wind action. Understanding the impact of extreme wave events on the morphodynamics of these structures for current conditions and future projections is of paramount importance to promote coastal and navigation safety. In this work, a numerical analysis of the impact of a storm on the sandspit of the Douro estuary (NW Portugal) was carried out considering several mean sea level conditions induced by climate change. The selected numerical models were SWAN, for hydrodynamics, and XBeach, for hydrodynamic and morphodynamic assessments. The extreme event selected for this study was based on the meteo-oceanic conditions recorded during Hurricane Christina (January 2014), which caused significant damage on the western Portuguese coast. The analysis focused on the short-term (two days) impact of the storm on the morphodynamics of the sandspit in terms of its erosion and accretion patterns. The obtained results demonstrate that the mean sea level rise will induce some increase in the erosion/accretion volumes on the seaward side of the sandspit. Overtopping of the detached breakwater and the possibility of wave overtopping of the sandspit crest were observed for the highest simulated mean sea levels.

O conhecimento pormenorizado da hidrodinâmica estuarina é fulcral para a tomada de medidas que permitam reduzir a vulnerabilidade e aumentar a resiliência dos estuários. Os modelos numéricos podem desempenhar um papel fundamental no apoio à decisão, mas para tal é necessário que produzam resultados fiáveis. Com esse objetivo é proposta a técnica dos ensembles, que permite combinar os resultados de diferentes modelos. Este é o principal objetivo do projeto EsCo-Ensembles, no qual foram desenvolvidos dois modelos numéricos diferentes aplicados nos estuários do Douro e do Minho e para os quais foram desenhados diversos cenários, considerando estados atuais e futuros, fluxos de cheia e valores extremos do nível do mar segundo as projeções dos RCPs do IPCC. É esperado que os resultados deste projeto forneçam uma caracterização hidromorfodinâmica completa das áreas estuarinas consideradas, permitindo avaliar tendências futuras e estimar os riscos de inundação, demostrando que o uso combinado de diferentes modelos reduz a sua incerteza e aumenta a confiança e consistência das previsões.

Seaweed assemblages include a variety of structuring species providing habitats, food and shelter for organisms from different trophic levels. Monitoring intertidal seaweed traditionally involves targeting small areas to collect data on species’ biological traits, which is often labour intensive and covers only a small area of the rocky reef under study. Given the various applications for seaweeds and their compounds, there has been an increase in demand for biomass triggered by the development of new markets. Such biomass demand generates new challenges for biomass quantification and the definition of future in-take harvesting commercial quotas by regulating agencies. The use of Unoccupied Aerial Vehicles (UAVs) as a low-cost yet efficient monitoring solution, combined with new sensors such as multispectral cameras, has been proposed for mapping intertidal reefs and seaweed in particular. In this study, a new methodology was developed and validated to quantify intertidal seaweed biomass based on multispectral UAV imagery, which was made available through an easy-to-use QGIS plugin (named SWUAV_BIO) that automates such biomass estimation. This tool was applied to a case study where the standing stock of Fucus spp. beds located at Viana do Castelo rocky shore (northern Portugal) was assessed using UAV multispectral imagery, providing a reference for future UAV-based ecological studies. Although comparison with the in situ assessments showed that biomass was underestimated by 36%, the SWUAV_BIO plugin is a valuable tool, as it provides an expedited (albeit conservative) seaweed standing stock assessment that can be used to monitor seaweed populations, their changes, and assess the effect of harvesting. These data can be used for an informed and sustainable management of seaweed resources by the competent authorities.