Instituto Português do Mar e da Atmosfera

Submarine landslides can be a major source of tsunamis, with waves highly dependent of the properties of both the landslide and the marine domain. This study investigates the tsunamigenesis of a shallow-water submarine landslide, recently mapped at the mouth of the Tagus delta River, off Lisbon, Portugal. The Tagus delta landslide is estimated to be 8 ky old, with a depositional maximum thickness of ~ 20 m and a volume of approximately 0.27 km³, extending over more than 9 km in length and 3 km in width. We assess the tsunamigenic potential and hazard of this possible early Holocene landslide using numerical simulations over high resolution reconstructed paleo-bathymetry, and project a similar future landslide scenario under the present-day conditions. Results show that both paleo- and future landslide scenarios are tsunamigenic, posing a significant hazard to the nearest coasts of Lisbon and surrounding areas. At the source region, the modelled tsunami reached heights of 0.8 m (paleo-scenario) and 1.45 m (future-scenario), increasing to approximately 2 m (both scenarios) as it propagated towards Lisbon’s coastline. This study is a first attempt to address the tsunamigenic potential of a submarine landslide occurring in a shallow water environment of the Portuguese margin domain. The results reinforce the need to include these small, but frequent, events and their induced tsunamis in marine geo-hazard assessments of the region.

Understanding genetic diversity and population connectivity in marine organisms is essential for fisheries management. In the present study, we examined the population genetics of the European squid, Loligo vulgaris, along the western Iberian Peninsula at two genetic resolutions using the mitochondrial cytochrome oxidase subunit I gene (COI) and genomic markers obtained via double digest restriction-site associated DNA sequencing (ddRADseq). The results obtained revealed 79 haplotypes out of 160 COI sequences, while the SNP data set included 86,431 loci after filtering for 38 individuals with 86,319 neutral data. Mitochondrial COI analyses revealed high haplotype (0.961) and nucleotide (0.010) diversities, and the haplotype network reveals complex sub-structure in Turkish waters within a panmictic population. Both Tajima’s D and Fu’s Fs tests suggest that the population of L. vulgaris analysed is evolving neutrally. Pairwise Fst for neutral SNPs were low (0 < Fst<0.002) and not significant showing high homogeneity among populations, while pairwise comparations for candidate adaptive SNPs (112 loci) showed Fst values ranging from 0.026 to 0.234. While neutral SNPs showed admixture, the candidate adaptive SNPs showed a moderate significant structure with a latitudinal discrimination. Overall, both genetic approaches showed homogeneity and strong genetic flux identifying a unique population along the Western Iberian Peninsula.

Remote sensing satellite data have been a crucial tool in understanding urban climates. The variety of sensors with different spatiotemporal characteristics and retrieval methodologies gave rise to a multitude of approaches when analyzing the surface urban heat island effect (SUHI). Although there are considerable advantages that arise from these different characteristics (spatiotemporal resolution, time of observation, etc.), it also means that there is a need for understanding the ability of sensors in capturing spatial and temporal SUHI patterns. For this, several land surface temperature products are compared for the cities of Madrid and Paris, retrieved from five sensors: the Spinning Enhanced Visible and InfraRed Imager onboard Meteosat Second Generation, the Advanced Very-High-Resolution Radiometer onboard Metop, the Moderate-resolution Imaging Spectroradiometer onboard both Aqua and Terra, and the Thermal Infrared Sensor onboard Landsat 8 and 9. These products span a wide range of LST algorithms, including split-window, single-channel, and temperature–emissivity separation methods. Results show that the diurnal amplitude of SUHI may not be well represented when considering daytime and nighttime polar orbiting platforms. Also, significant differences arise in SUHI intensity and spatial and temporal variability due to the different methods implemented for LST retrieval.

The seasonal and latitudinal distribution of insolation is considered the main factor controlling the magnitude and timing of interglacial periods. However, despite small differences in insolation forcing, vegetation and hydrology in southern Europe during past interglacials are variable and the gradual change in insolation cannot explain the observed short‐lived forest optimum. Here we focus on vegetation and hydroclimatic changes at orbital‐ and suborbital‐scales in southwestern Europe during two past warm interglacial periods with reduced ice‐sheets, namely Marine Isotope Stages (MIS) 9e and 5e. We provide new pollen and sea surface temperatures records for MIS 9e from IODP Site U1385. This pollen record shows a forest expansion in southern Iberia over a 14 ky interval, bracketed by the millennial‐scale cooling events of Termination IV and MIS 9d. Between 334.5 and 332.5 ka, forest expansion reached a maximum, suggesting increased winter moisture during early MIS 9e. Model‐data comparison for MIS 9e and 5e shows that insolation is the main driver of the orbital‐scale vegetation and precipitation changes in Iberia, atmospheric CO2 forcing playing a secondary role. The high‐frequency component of the MIS 9e and 5e forest timeseries highlights the early interglacial forest and precipitation maxima as prominent suborbital events lasting ∼2 ky. We propose that the primarily insolation‐driven forest and precipitation optima were fostered by the non‐equilibrium conditions generated by the millennial‐scale deglacial variability during the early interglacials. Additionally, the early end of these optima may have been favored by a cooling and drying event that is part of the persistent intra‐interglacial variability.

Extreme weather events have become more frequent and severe with ongoing climate change, with a huge implication for the agricultural sector and detrimental effects on crop yield. In this study, we compare several combinations of climate indices and utilized the Least Absolute Shrinkage and Selection Operator (LASSO) to explain the probabilities of substantial drops in silage maize yield (here defined as “yield shock” by using a 15th percentile as threshold) in Germany between 1999 and 2020. We compare the variable importance and the predictability skill of six combinations of climate indices using the Matthews Correlation Coefficient (MCC). Finally, we delve into year-to-year predictions by comparing them against the historical series and examining the variables contributing to high and low predicted yield shock probabilities. We find that cold conditions during April and hot and/or dry conditions during July increase the chance of silage maize yield shock. Moreover, a combination of simple variables (e.g. total precipitation) and complex variables (e.g. cumulative cold under cold nights) enhances predictive accuracy. Lastly, we find that the years with higher predicted yield shock probabilities are characterized mainly by relatively hotter and drier conditions during July compared to years with lower yield shock probabilities. Our findings enhance our understanding of how weather impacts maize crop yield shocks and underscore the importance of considering complex variables and using effective selection methods, particularly when addressing climate-related events.

Fragmentary and contradictory evidence prevents a clear understanding of the possible role of the North Pacific Ocean surface on the ice‐sheet evolution. New palynological data encompassing the Pliocene and Pleistocene at Ocean Drilling Program Site 882 in the northwest Pacific document sea‐surface conditions from dinoflagellate cysts in addition to atmospheric trajectories from pollen grains and spores. The comparison of the Site 882 record with that of Site 887 from the northeast Pacific also permits documenting West to East contrasts across the subarctic North Pacific. The dinocyst assemblages at the two sites indicate strong temperature contrasts until 4.2 Ma, with much warmer conditions in the East. From 4.2 to 3.6 Ma, dinocyst assemblages of both sites are characterized by alternated dominance of the extinct taxa Habibacysta tectata and Impagidinium detroitense suggesting homogenous and cool conditions across the subarctic Pacific gyre. A major transition is recorded in the palynological assemblages at Site 882 around 2.7 Ma. It is marked by the highest occurrence of Habibacysta tectata and high percentages of Filisphaera microornata additionally to thermophilic taxa. Dinocyst record indicates high seasonality and warmer surface conditions due to reinforced stratification, which support the hypothesis of high evaporation at the origin of atmospheric moisture supply to high latitudes. During the last 1.2 Ma, the increase of Operculodinium centrocarpum relative to Nematosphaeropsis labyrinthus is tentatively interpreted as a reinforced influence of the subtropical waters. Hence, we suggest that the warm surface ocean fostered the inception and growth of northwestern North American ice‐sheets during the Pliocene and Pleistocene.

Ocean acidification (OA) is expected to decrease the strength of bivalves’ shells, especially during the early stages of development, with negative consequences to the resilience of natural populations and the economy. The objectives of the present study were to assess the long-term effect of increasing pCO2 after 217 days of exposure under controlled conditions of pH of ∼8.2, 8.0, and 7.7 on the strength and integrity of shells of juveniles of the commercial striped venus clam Chamelea gallina. Shell strength was estimated through compression tests and integrity through scanning electron microscopy (SEM) and dispersive X-ray analyses (EDX). The results showed that under increasing pCO2 the shell strength of juveniles is unaffected, which could be related to the locally elevated total alkalinity of seawater with respect to other parts of the coastal lagoon. However, despite this, it was also observed that the juvenile clams exposed to elevated pCO2 decreased their shell thickness and increased the porosity of their prismatic layer. Under future OA conditions, these changes could eventually compromise the integrity of the shells, becoming more vulnerable to the attack of predators and breakable during fishing operations. Future studies should address the plasticity of the organisms and the effect of the alkalinization of seawater on the resilience of shellfish juveniles under global change conditions.

Fish age and growth data are crucial for understanding vital species’ traits and their populations. Boarfish is a pelagic species widely distributed in the Northeast Atlantic that is one of the most discarded non-commercial species on the Portuguese coast. Due to its potential valorisation as a new fishery in the Northeast Atlantic, boarfish has become object of interest in several published studies. However, since no age standard protocol has been implemented for boarfish, studies have used a variety of different otolith preparation techniques to estimate age, leading to contradicting and discrepant results. This research aims to consolidate biological insights into boarfish age and growth, lay the foundation for a standardized ageing protocol and serve as a benchmark study for the Portuguese west coast before commercial exploitation. Through the comparison of two otolith ageing methodologies, this study recommends using whole otoliths as the best method, revealing a maximum age of 15 years. The growth pattern estimated, indicated a biphasic growth pattern, with a faster initial growth rate that slows down at 2.4 years, the moment of change, when energy is allocated for sexual maturation. This finding was corroborated by a maturity ogive and analysis of fish size and otolith length relationship.

Environmental gradients in the sea may coincide with phenotypic or genetic gradients resulting from an evolutionary balance between selection and dispersal. The population differentiation of the swimming crab, Liocarcinus depurator, an important by-catch species in the Mediterranean Sea and North-East Atlantic, was assessed using both genetic and morphometric approaches. A total of 472 specimens were collected along its distribution area, and 17 morphometric landmarks, one mitochondrial gene (COI) and 11 polymorphic microsatellite markers were scored in 350, 287 and 280 individuals, respectively. Morphometric data lacked significant differences, but genetic analyses showed significant genetic differentiation between Atlantic and Mediterranean populations, with a steeper gradient in COI compared to microsatellite markers. Interestingly, nuclear differentiation was due to an outlier locus with a gradient in the Atlantic-Mediterranean transition area overlapping with the mtDNA gradient. Such overlapping clines are likely to be maintained by natural selection. Our results suggest a scenario of past isolation with local adaptation and secondary contact between the two basins. Local adaptation during the process of vicariance may reinforce genetic differentiation at loci maintained by environmental selection even after secondary contact.

Climate change has become a major concern in the twenty-first century, leading to the amplification of extreme events and, consequently, to severe impacts on society, economy and ecosystems. Heatwave conditions in particular, often coupled with extended periods of dryness, have an important contribution in exacerbating rural fires. Here, we propose to analyse the co-occurring interplay between atmospheric heatwaves and droughts in southern Europe, and marine heatwaves in the East Atlantic and the Mediterranean Sea, between 2001 and 2022, highlighting their linkage to wildfires, on both an individual and compound approach. Positive correlations between air and sea temperatures and negative correlations between air temperature and precipitation values were found. Our analysis reveals that severe wildfires are mostly associated with reduced precipitation and/or elevated air temperatures during the summer season, alongside heightened sea surface temperatures. Marine hot (drier) conditions are prevalent for months in which burned areas remain below (above) the 80th percentile. Months marked by higher fire activity are predominantly associated with extreme climatic conditions, showcasing a substantial occurrence of compound events. This study highlights the potential of considering both land-based atmospheric and marine conditions when exploring compound extremes, crucial for mitigating climatic disasters. Moreover, it highlights the role played by compound extreme events in fire management strategies, particularly considering the present context of climate change and the increasing frequency and severity of extreme events threatening ecosystem stability.

Flash droughts (FDs) are distinguished by a rapid development associated with strong precipitation deficits and/or increases in atmospheric evaporative demand in the short‐term, but little is known about the atmospheric conditions underlying these events. In this study, we analyse for the first time the atmospheric dynamics involved in the development of FDs in Spain over the period 1961–2018. FDs are related to large‐scale atmospheric circulation patterns affecting the region, in particular with the positive phase of the North Atlantic Oscillation (NAO). The NAO is the main atmospheric driver of FDs in winter and autumn, and it is essential in explaining FD development in spring. We also found that FDs are typically linked to strong positive anomalies in 500 hPa geopotential height and sea level pressure over the region during the weeks prior to the onset. At the synoptic scale, the most common weather types (WTs) recorded during the development of FDs are Anticyclonic Western (ANT_W_AD), East (E_AD) and Northeast (NE_AD) advection, and Anticyclonic (ANTICYC). In particular, ANTICYC WT is the main atmospheric driver of FDs in summer. Ridging conditions occur frequently during FDs in all seasons, being the most important factor controlling FD development in spring. Likewise, we noted that some of the FDs recorded in summer are related to and/or exacerbated by Saharan air intrusions associated with pronounced ridges. The results of this research have important implications for the understanding, monitoring and prediction of FDs in Spain, providing a detailed assessment of the main atmospheric dynamics involved in FD triggering at different spatial scales.

Cannibalism and intraguild predation occur in a vast number of small pelagic fish (SPF) species. Egg and larval predation can have important consequences on mortality, and its accurate assessment is important to estimate the impact on recruitment strength and population dynamics of predators and prey. Such assessments are hampered by limitations in visual species identification of many fish eggs and larvae in the predator´s stomachs. European sardine (Sardina pilchardus) and Atlantic chub mackerel (Scomber colias), the dominant species of the pelagic food web off the Canary Current Upwelling ecosystem, are major predators of fish eggs. Egg predation by these SPF species is particularly high on sardine and anchovy eggs, but many preyed fish eggs are not amenable for visual identification. This study provides a proof-of-concept application of molecular identification of diverse fish eggs from SPF stomach contents not amenable to visual identification, as a way to improve our understanding of the impact of intraguild predation on fish population dynamics. Results show a high diversity of fish species in the eggs ingested by sardines and chub mackerel (18 and 15 families, respectively), mostly comprising locally abundant coastal taxa. Sardine ingested predominantly anchovy, sardine and sparid eggs, while chub mackerel ingested predominantly sparid eggs, followed by serranid (Serranus spp.), and sardine eggs. Sardines also showed higher variability in prey composition compared to chub mackerel. Exploratory analyses also suggested variability in prey composition with sampling area, season and maturity stage for sardine and chub mackerel, highlighting the need for dedicated follow-up studies.

Fish by-products can be converted into high-value-added products like fish protein hydrolysates (FPHs), which have high nutritional value and are rich in bioactive peptides with health benefits. This study aims to characterise FPHs derived from salmon heads (HPSs) and Cape hake trimmings (HPHs) using Alcalase for enzymatic hydrolysis and Subcritical Water Hydrolysis (SWH) as an alternative method. All hydrolysates demonstrated high protein content (70.4–88.7%), with the degree of hydrolysis (DH) ranging from 10.7 to 36.4%. The peptide profile of FPHs indicated the breakdown of proteins into small peptides. HPSs showed higher levels of glycine and proline, while HPHs had higher concentrations of glutamic acid, leucine, threonine, and phenylalanine. Similar elemental profiles were observed in both HPHs and HPSs, and the levels of Cd, Pb, and Hg were well below the legislated limits. Hydrolysates do not have a negative effect on cell metabolism and contribute to cell growth. HPSs and HPHs exhibited high 2,2′–azino-bis(3 ethylbenzthiazoline-6)-sulfonic acid (ABTS) radical scavenging activity, Cu2+ and Fe2+ chelating activities, and angiotensin-converting enzyme (ACE) inhibitory activity, with HPHs generally displaying higher activities. The α-amylase inhibition of both FPHs was relatively low. These results indicate that HPHs are a promising natural source of nutritional compounds and bioactive peptides, making them potential candidates for use as an ingredient in new food products or nutraceuticals. SWH at 250 °C is a viable alternative to enzymatic methods for producing FPHs from salmon heads with high antioxidant and chelating properties.

Hydrogen is expected to become a dominant energy vector in a scenario where renewable energies will prevail over other conventional sources. This suggests that beyond its conventional industrial applications, such as in the chemical industry, hydrogen is poised to find numerous additional uses, including serving as a fuel for internal combustion engines. Consequently, global demand is expected to surge significantly, necessitating the implementation of large-scale hydrogen production units from renewable sources. This is particularly pronounced in Europe, where recent energy directives have set ambitious targets in this regard. Consequently, it becomes imperative to evaluate potential locations suitable for hosting these hydrogen production facilities. In this study, particular attention is directed towards photovoltaic-fed water electrolysis as a method for hydrogen production. This choice is informed by the maturity and affordability of these technologies, coupled with the abundant solar energy resource available in Southern Europe. To this end, it is utilized 23 years of hourly meteorological data obtained from the Portuguese Meteorological Service. This dataset enables the development of typical meteorological year files for nearly 90 stations across mainland Portugal. These files were inputted into a model simulating a 120 MWp photovoltaic plant, utilizing the System Advisor Model. The electricity generated by this plant was subsequently used to simulate the hydrogen production using an in-house developed model for the electrolyser. Finally, the simulation results were used to develop the first atlas for Solar Hydrogen production capacity and cost in Portugal. The techno-economic results indicate that annual specific hydrogen production can achieve values above 30 kg/kWp, with the levelized cost of hydrogen below 4.0 €/kg, especially, in the southern regions (Alentejo and Algarve) and the central-east area (Beira Interior). This makes these regions highly attractive for hosting large-scale photovoltaic hydrogen production plants and very competitive in the hydrogen market, especially with neighbouring countries like Morocco and Spain.

Submarine landslides are a major source of tsunamis, with waves highly dependent of the properties of both the landslide and the marine domain. This study investigates the tsunamigenesis of a shallow-water submarine landslide, recently mapped at the mouth of the Tagus delta River, off Lisbon, Portugal. The Tagus delta landslide is estimated to be 8 ky old, with a depositional maximum thickness of ~ 20 m and a volume of approximately 0.27 km ³ , extending over more than 9 km in length and 3 km in width. We assess the tsunamigenic potential and hazard of this possible early Holocene landslide using numerical simulations over high resolution reconstructed paleo-bathymetry, and project a similar future landslide scenario under the present-day conditions. Results show that both paleo- and future landslide scenarios are tsunamigenic, posing a significant tsunami hazard to the nearest coasts of Lisbon and surrounding areas. At the source region, the formed tsunami reached heights of 0.8 m (paleo-scenario) and 1.45 m (future-scenario), increasing to approximately 2 m (both scenarios) as it propagated towards Lisbon’s coastline. This study is a first attempt to address the tsunamigenic potential of a submarine landslide occurring in a shallow water environment of the Portuguese margin domain. The results reinforce the need to include these small, but frequent, events and their induced tsunamis in marine geo-hazard assessments of the region.

In 2023, most parts of the world experienced exceptional heat. In particular, anomalous warm temperatures and heatwave events were evidenced across South America during the second half of the year. The situation was particularly critical in the Amazon region in terms of not only hydrometeorological drought but also ecological and socioeconomic impacts. In this study, remote-sensing data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to observe the changes in temperature and vegetation across Amazonia during the exceptional drought of 2023. This analysis was based on anomalies in the land surface temperature (LST) and vegetation indices: the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI). The amplitude of the LST (AMP-LST), an indicator of the energy partitioning between the latent and sensible heat flux, and fire counts were also considered. The results show widespread and extreme warming across Amazonia during the austral spring in 2023, accompanied by a decline in vegetation greenness, water stress conditions across northern Amazonia, and an enhanced fire occurrence across central and northern Amazonia.

In the last few years, the exploitation of deep-sea regions for minerals extraction raised international attention as an economically viable source for the mining industry. However, most of these minerals are found close to sensitive ecosystems that can be harmed by mining activities. Given the potential impact, there is a need for the establishment of best practices towards the adoption of preventive strategies for the sustainable management and exploitation of deep-sea environments. To accomplish this objective, numerical models have proven to be reliable tools to support decision-making. In the present study, a high-resolution eddy-resolving ocean numerical model was configured and integrated with a semi-Lagrangian model aiming to map the transport of rock-fragments associated with mining activities. The model was applied to an area rich in polymetallic sulphides at the Northern Mid-Atlantic Ridge (NMAR). Model results showed that local topography and circulation dynamics played an important role for the dispersion and settling of the rock-fragments. In the presence of local submesoscale processes, the residence time do not follow the neutral relation H/vs. It was demonstrated that, depending on the local hydrodynamics, rock-fragments released at sub-surface depth can impact wider areas, with a predicted impact on pelagic and benthic organisms.

Evaluation of fish stock status is a key step for fisheries management. Tuna Regional Fisheries Management Organizations (t-RFMOs) are moving towards management strategy evaluation (MSE), a process that combines science and policy and depends on technical aspects, developed by scientists, designed to meet management objectives established by managers and other stakeholders. In the Indian Ocean, the current management advice for swordfish (Xiphias gladius) is based on an ensemble of 24 models considering four areas of uncertainty about the stock dynamics. There is an ongoing MSE process for swordfish, and this paper describes the methodology being applied for the conditioning of the operating model (OM), including model selection and validation. In the MSE, nine sources of uncertainty were considered, each being characterized by 2–3 levels. A partial factorial design was employed to reduce the number of models from a full factorial design to those needed to encompass the overall uncertainty. A selection and validation process was carried out, filtering models that converged, showed good predictive skills, and provided plausible estimates. Overall, the estimated spawning stock biomass (SSB) relative to SSB at maximum sustainable yield (MSY), and fishing mortality (F) relative to FMSY encompasses the estimates of the stock assessment ensemble at the most optimist area of the distribution. The MSE for swordfish is an ongoing process that is expected to provide more robust management advice in the future. Further developments to the OM can still occur, but the methods presented herein can be applied to this, or other species, MSE processes.

Real-world data collections are generally not easily available. Energy measurements from buildings, houses and other devices can be used within different areas of research while being employed to plan or train models, allowing the improvement of power grid energy efficiency or providing more insight on how an energy community can work. This paper provides a dataset concerning a Portuguese community of 172 households that are geographically close to each other, enabling the establishment of relationships among buildings and the analysis of a community's power consumption. In addition to the consumed energy values, the related local weather information is included in the data. The intersection of weather data and energy measurements can be helpful to train AI models, contributing to explain variations in energy consumption and the absolute values of the energy readings. The inclusion of these weather parameters aims to unveil features that can correlate to the energy measurements, enabling them to be used in multiple areas of research. Hence, it will provide added value to the data as it can be reused to explore Machine Learning algorithms or community energy planning by grid operators.