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Antarctica plays a fundamental role in the Earth's climate, oceanic circulation and global ecosystem. It is a priority and a scientific challenge to understand its functioning and responses under different scenarios of global warming. However, extreme environmental conditions, seasonality and isolation hampers the efforts to achieve a comprehensive understanding of the physical, biological, chemical and geological processes taking place in Antarctica. Here we present unmanned aerial vehicles (UAVs) as feasible, rapid and accurate tools for environmental and wildlife research in Antarctica. UAV surveys were carried out on Deception Island (South Shetland Islands) using visible, multispectral and thermal sensors, and a water sampling device to develop precise thematic ecological maps, detect anomalous thermal zones, identify and census wildlife, build 3D images of geometrically complex geological formations, and sample dissolved chemicals (< 0.22 µm) waters from inaccessible or protected areas.

Iron plays a crucial role in the high-nutrient, low-chlorophyll Southern Ocean regions, promoting phytoplankton growth and enhancing atmospheric carbon sequestration. In this area, iron-rich Antarctic krill ( Euphausia superba ) and baleen whale species, which are among their main predators, play a large role in the recycling of iron. However, penguins have received limited attention despite their representing the largest seabird biomass in the southern polar region. Here, we use breeding site guano volumes estimated from drone images, deep learning-powered penguin census, and guano chemical composition to assess the iron export to the Antarctic waters from one of the most abundant penguin species, the Chinstrap penguin ( Pygoscelis antarcticus ). Our results show that these seabirds are a relevant contributor to the iron remobilization pool in the Southern Ocean. With an average guano concentration of 3 mg iron g −1 , we estimate that the Chinstrap penguin population is recycling 521 tonnes iron yr −1 , representing the current iron contribution half of the amount these penguins were able to recycle four decades ago, as they have declined by more than 50% since then. Here the authors show that Chinstrap penguins play a significant role in iron recycling, essential for phytoplankton growth and carbon sequestration, recycling yearly 521 tonnes of iron, half of what they did 40 years ago due to population decline.

A growing awareness of the risks associated with skin exposure to ultraviolet (UV) radiation over the past decades has led to increased use of sunscreen cosmetic products leading the introduction of new chemical compounds in the marine environment. Although coastal tourism and recreation are the largest and most rapidly growing activities in the world, the evaluation of sunscreen as source of chemicals to the coastal marine system has not been addressed. Concentrations of chemical UV filters included in the formulation of sunscreens, such as benzophehone 3 (BZ-3), 4-methylbenzylidene camphor (4-MBC), TiO₂ and ZnO, are detected in nearshore waters with variable concentrations along the day and mainly concentrated in the surface microlayer (i.e. 53.6-577.5 ng L⁻¹ BZ-3; 51.4-113.4 ng L⁻¹ 4-MBC; 6.9-37.6 µg L⁻¹ Ti; 1.0-3.3 µg L⁻¹ Zn). The presence of these compounds in seawater suggests relevant effects on phytoplankton. Indeed, we provide evidences of the negative effect of sunblocks on the growth of the commonly found marine diatom Chaetoceros gracilis (mean EC₅₀ = 125±71 mg L⁻¹). Dissolution of sunscreens in seawater also releases inorganic nutrients (N, P and Si forms) that can fuel algal growth. In particular, PO₄³⁻ is released by these products in notable amounts (up to 17 µmol PO₄³⁻g⁻¹). We conservatively estimate an increase of up to 100% background PO₄³⁻ concentrations (0.12 µmol L⁻¹ over a background level of 0.06 µmol L⁻¹) in nearshore waters during low water renewal conditions in a populated beach in Majorca island. Our results show that sunscreen products are a significant source of organic and inorganic chemicals that reach the sea with potential ecological consequences on the coastal marine ecosystem.

Sunscreen is released into the marine environment and is considered toxic for marine life. The current analytical methods for the quantification of sunscreen are mostly specific to individual chemical ingredients and based on complex analytical and instrumental techniques. A simple, selective, rapid, reproducible and low-cost spectrophotometric procedure for the quantification of commercial sunscreen in seawater is described here. The method is based on the inherent properties of these cosmetics to absorb in the wavelength of 300–400 nm. The absorption at 303 nm wavelength correlates with the concentration of most commercial sunscreens. This method allows the determination of sunscreens in the range of 2.5–1500 mg L -1 , it requires no sample pretreatment and offers a precision of up to 0.2%. The spectrophotometric method was applied to quantify sunscreen concentrations at an Atlantic Beach with values ranging from 10 to 96.7 mg L -1 in the unfiltered fraction and from the undetectable value to 75.7 mg L -1 in the dissolved fraction. This method is suggested as a tool for sunscreen quantifications in environmental investigations and monitoring programs.

Aquatic ecosystems are crucial in preserving biodiversity, regulating biogeochemical cycles, and sustaining human life; however, their resilience against climate change and anthropogenic stressors remains poorly understood. Recently, unmanned aerial vehicles (UAVs) have become a vital monitoring tool, bridging the gap between satellite imagery and ground-based observations in coastal and marine environments with high spatial resolution. The dynamic nature of water surfaces poses a challenge for photogrammetric techniques due to the absence of fixed reference points. Addressing these issues, this study introduces an innovative, efficient, and accurate workflow for georeferencing and mosaicking that overcomes previous limitations. Using open-source Python libraries, this workflow employs direct georeferencing to produce a georeferenced orthomosaic that integrates multiple UAV captures, and this has been tested in multiple locations worldwide with optical RGB, thermal, and multispectral imagery. The best case achieved a Root Mean Square Error of 4.52 m and a standard deviation of 2.51 m for georeferencing accuracy, thus preserving the UAV’s centimeter-scale spatial resolution. This open-source workflow represents a significant advancement in the monitoring of marine and coastal processes, resolving a major limitation facing UAV technology in the remote observation of local-scale phenomena over water surfaces.

Aerosol deposition plays an important role in climate and biogeochemical cycles by supplying nutrients to the open ocean, in turn stimulating ocean productivity and carbon sequestration. Aerosol particles also contain elements such as copper (Cu) that are essential in trace amounts for phytoplankton physiology but that can be toxic at high concentrations. Although the toxicity of Cu associated with aerosols has been demonstrated in bioassay experiments, extrapolation of these laboratory results to natural conditions is not straightforward. This study provides observational evidence of the negative effect of aerosols containing high Cu concentrations on marine phytoplankton over a vast region of the western Mediterranean Sea. Direct aerosol measurements were combined with satellite observations, resulting in the detection of significant declines in phytoplankton biomass after atmospheric aerosol events characterized by high Cu concentrations. The declines were more evident during summer, when nanoflagellates predominate in the phytoplankton population and stratification and oligotrophic conditions prevail in the study region. Together with previous findings concerning atmospheric Cu deposition, these results demonstrate that the toxicity of Cu-rich aerosols can involve large areas of the world’s oceans. Moreover, they highlight the present vulnerability of oceanic ecosystems to Cu-rich aerosols of anthropogenic origins. Because anthropogenic emissions are increasing, large-scale negative effects on marine ecosystems can be anticipated.

Remote-sensing ocean colour studies have already been used to determine coastal water quality, coastal biodiversity, and nutrient availability. In recent years, Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors, originally designed for agriculture applications, have also enabled water-quality studies of coastal waters. However, since the sea surface is constantly changing, commonly used photogrammetric methods fail when applied to UAV images captured over water areas. In this work, we evaluate the applicability of a five-band multispectral sensor mounted on a UAV to derive scientifically valuable water parameters such as chlorophyll-a (Chl-a) concentration and total suspended solids (TSS), including a new Python workflow for the manual generation of an orthomosaic in aquatic areas exclusively based on the sensor’s metadata. We show water-quality details in two different sites along the Maltese coastline on the centimetre-scale, improving the existing approximations that are available for the region through Sentinel-3 OLCI imagery at a much lower spatial resolution of 300 m. The Chl-a and TSS values derived for the studied regions were within the expected ranges and varied between 0 to 3 mg/m3 and 10 to 20 mg/m3, respectively. Spectral comparisons were also carried out along with some statistics calculations such as RMSE, MAE, or bias in order to validate the obtained results.

Marine macrophytes constitute one of the most productive ecosystems on the planet, as well as one of the most threatened by anthropogenic activities and climate change. Their monitoring is therefore essential, which has experienced a fast methodological evolution in recent years, from traditional in situ sampling to the use of satellite remote sensing, and subsequently by sensors mounted on unmanned aerial vehicles (UAV). This study aims to advance the monitoring of these ecosystems through the use of a UAV equipped with a 10-band multispectral camera, using different algorithms [i.e., maximum likelihood classifier (MLC), minimum distance classifier (MDC), and spectral angle classifier (SAC)], and using the Bay of Cádiz Natural Park (southern Spain) as a case of study. The results obtained with MLC confirm the suitability of this technique for detecting and differentiating seagrass meadows in a range of 0–2 m depth and the efficiency of this tool for studying and monitoring marine macrophytes in coastal areas. We inferred the existence of a cover of 25452 m 2 of Cymodocea nodosa , and macroalgae species such as Caulerpa prolifera , covering 22172 m 2 of Santibañez (inner Bay of Cádiz).

The need to gather data in such a harsh, isolated, and hard-to-access environment as Antarctica is a priority for the scientific community aiming to understand this system’s responses to different climate change scenarios. FosterCoast is a dataset collected using a UAV-based LiDAR sensor during the Spanish Antarctic Campaign 2024–2025 (Austral summer 2025), covering the entire inner ring (~35 km) of Port Foster Bay on Deception Island (Antarctica). It comprises the original data along with topographic products – such as orthomosaics, DEMs, and point clouds – derived from the photogrammetric processing of 13 UAV surveys, which include a total of 5,631 high-resolution RGB captures with Post-Processing Kinematic positioning. FosterCoast, available for public download via the Figshare data repository, represents the first complete UAV-based survey covering the entire Port Foster Bay within the volcanic ecosystem of Deception Island. This highly detailed dataset is a valuable asset for the polar scientific community, as well as for other relevant sectors, including the rescue operations, tourism, and navigation.

The study of the functioning and responses of Antarctica to the current climate change scenario is a priority and a challenge for the scientific community aiming to predict and mitigate impacts at a regional and global scale. Due to the difficulty of obtaining aerial data in such extreme, remote, and difficult-to-reach region of the planet, the development of remote sensing techniques with Unmanned Aerial Vehicles (UAVs) has revolutionized polar research. ShetlandsUAVmetry comprises original datasets collected by UAVs during the Spanish Antarctic Campaign 2021–2022 (January to March 2022), along with the photogrammetric products resulting from their processing. It includes data recorded during twenty-eight distinct UAV flights at various study sites on Deception and Livingston islands (South Shetland Islands, Antarctica) and consists of a total of 15,691 high-resolution optical RGB captures. In addition, this dataset is accompanied by additional associated files that facilitate its use and accessibility. It is publicly accessible and can be downloaded from the figshare data repository.