The genome sequence of the butterfly blenny, Blennius ocellaris Linnaeus, 1758

We present a genome assembly from a specimen of Blennius ocellaris (the butterfly blenny; Chordata; Actinopteri; Blenniiformes; Blenniidae). The genome sequence spans 728.70 megabases. Most of the assembly is scaffolded into 24 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 16.5 kilobases in lengt

Marine natural capital training materials

Sea the Value brings together a unique interdisciplinary team and international network of collaborators to address fundamental questions regarding the economics of biodiversity, specifically of blue carbon and marine water quality. The team includes internationally recognised expertise in environmental and ecological economics, marine ecology, human geography, governance, and finance, putting us in an unrivalled position to make a transformative change. Our vision is to determine novel and policy relevant pluralistic values for marine biodiversity and apply these values to co-develop green investment options, leading to a transformative shift in our understanding and utilisation of the economics of biodiversity

Marine heatwaves as hot spots of climate change and impacts on biodiversity and ecosystem services

Intensifying marine heatwaves (MHWs) are pervasive and destructive manifestations of anthropogenic climate change. Over the past two decades, MHWs have driven biological, ecological and socioeconomic change in almost all oceans and seas. In this Review, we assess the impacts of MHWs on marine organisms and the benefits they provide to people, highlight knowledge gaps and consider opportunities to mitigate MHW impacts. Globally, MHWs have become increasingly intense and frequent, and result in mortality or movement of species when acute temperature thresholds are exceeded. Vulnerability and resilience to MHWs vary among species, but these mortality events have been prominent for habitat-forming foundation species such as corals, kelp and seagrass, causing many cascading indirect impacts on ecosystem functioning and biodiversity. Poleward species shifts produce novel and complex species interactions and altered ecosystem functions, which have considerable consequences for people and their livelihoods. Reducing greenhouse gas emissions remains essential and urgent to address impacts long term, but increases in MHW intensities and duration will be unavoidable and prominent for the foreseeable future. As such, closing the current knowledge gaps around MHWs and their impacts on biodiversity, as well as proactive management strategies, are urgently needed to mitigate further damage to ecosystems and people, and to build resilience into the futur

Revealing two decades of chlorophyll-a dynamics in arid oligotrophic lakes of Xinjiang, China using a deep recurrent approach

Oligotrophic lakes in arid and semi-arid regions are vital to local livelihoods and ecosystems, yet research has primarily focused on water levels and volumes in these areas, with limited attention to water quality. As a sensitive indicator of ecological change, chlorophyll-a (Chl-a), which is detectable via remote sensing, can provide valuable insights into subtle variations in water quality. To address this research gap, we investigated Chl-a concentrations in lakes larger than 100 km2 across the expansive Xinjiang region of China using two decades (2002–2023) of MODIS imagery. A robust deep learning model was developed to accurately estimate spatiotemporal Chl-a dynamics, overcoming the limitations of conventional algorithms for oligotrophic lakes. Unlike existing machine learning models that treat remote sensing spectra as static multi-dimensional points, our approach models wavebands as dynamic sequences with a Recurrent Neural Network (RNN) framework. A comparative evaluation with four conventional Chl-a inversion models, four machine learning and five deep learning models demonstrated the superiority of the RNN model with an RMSE of 0.75 mg m−3 and R2 of 0.72. Results over the ice-free period revealed that Chl-a concentrations in major lakes of Xinjiang generally remained below 6 mg m−3, with annual averages below 3 mg m−3, and manifested a slight declining trend in recent years. Further analysis of environmental variables revealed that Chl-a variability in lakes influenced by anthropogenic activities was primarily driven by solar radiation, vegetation cover, and runoff. In contrast, alpine lakes with minimal human disturbance exhibited dynamics largely shaped by lake expansion. This study presents a robust framework for Chl-a estimation, potentially extendable to other water parameters, and advances the understanding of long-term ecological dynamics in arid environments of Xinjiang

Impact of Extreme Weather Events and Land use on Leptospira Distribution in Vembanad Lake and Associated Disease Outbreaks in Near Shore Areas

Leptospirosis is a water-associated zoonotic disease prevalent in tropical and low-income regions. The pathogen enters the environment through rodent excreta, and extreme weather events—such as floods—enhance its transmission to humans. This study analyses the incidence of leptospirosis in Kerala state, examines the distribution of Leptospira in the water column of Vembanad Lake, a Ramsar site and the largest lake in the state, and investigates the influence of land use patterns and the physical and chemical properties of the water column. Water samples for analysis were collected at approximately 20-day intervals over 12 months from 13 stations in Vembanad Lake. Analysis of the decadal dataset of disease incidence indicates that the region is endemic to leptospirosis, with nearly 50% of the cases reported in 2018—particularly in areas surrounding Vembanad Lake—occurring in September, coinciding with a once-in-a-century flood. A significant positive correlation was observed between rainfall and disease incidence (r = 0.73, p < 0.05). Over the past 50 years, built-up areas around the lake have expanded by nearly 150%, providing less space for water and increasing the likelihood of floods that can transmit pathogens. Molecular surveillance using quantitative real-time PCR revealed that Leptospira is prevalent in the lake, with gene copies ranging from 4.62 × 105 (Log₁₀ 5.67) to 3.98 × 10⁷ (Log₁₀ 7.60) per ml during the rainy season (June–December) and 2.8 × 10⁶ (Log₁₀ 6.63) to 1.53 × 10⁸ (Log₁₀ 8.18) per ml during the dry season (January–May). Results indicate that the distribution of Leptospira in Vembanad Lake is influenced by temperature, pH, and nutrient composition (PO₄ and NO₂) of the water column. This study highlights the prevalence of Leptospira in the lake’s water column and the heightened risk of transmission to humans during extreme weather events. It underscores the need for a multifaceted approach, including molecular and remote sensing-based pathogen surveillance, public awareness initiatives, integrated floodwater management, rodent control measures in urban planning, and targeted interventions to mitigate environmental transmission

Effects of zooplankton abundance on the spawning phenology of winter-spawning Downs herring (Clupea harengus)

We have investigated phenological shifts in autumn- and winter-spawning Atlantic herring (Clupea harengus) in the Eastern English Channel and the Southern North Sea (Downs component), in relation to temperature and the availability of potential zooplanktonic prey (Calanus finmarchicus, Calanus helgolandicus, Temora longicornis). A two-tiered approach building on the monthly distribution of commercial herring landings was developed, which consisted of, (1) calculating the timing and duration of spawning season based on estimated deviations from basic harmonic signals and, (2) analysing their inter-annual variations in relation to biotic (zooplankton abundance) and abiotic (temperature) environmental variables through time series analyses. The start, midpoint and ending of herring spawning season were increasingly delayed over the period 1999–2021, a process which was correlated with the abundance of Calanus finmarchicus. The resulting duration of spawning season slightly decreased. Direct effects of sea temperatures on any phenological metrics could not be clearly evidenced. Different ecological processes were likely involved in the start and ending of spawning season. Additional covariates (including size/age composition, the biotic and abiotic factors other than those examined in our study) could contribute to a better explanation of the phenological drift in Downs herring spawnin

Predicting photosynthesis–irradiance relationships from satellite remote‐sensing observations

Photosynthesis–irradiance (PI) relationships are important for phytoplankton ecology and quantifying carbon fixation rates in the environment. However, the parameters of PI relationships are typically unknown across space and time. Here we use machine learning, satellite remote‐sensing, and a database of in situ PI relationships to build models that predict the seasonal cycle of PI parameters as a function of satellite‐observed variables. Using only surface light, temperature, and chlorophyll, we achieve an R 2 of 58% for predicting photosynthesis rates at saturating light () and an R 2 of 78% for predicting the light saturation parameter (). Predictability is maximized when averaging environmental covariates over 30‐d () and 25‐d () timescales, indicating that environmental history and community turnover timescales are important for predicting in situ PI relationships. These results will help improve the parameterization of satellite‐based primary production models and quantify emergent environmental integration timescales in photosynthetic communities

Sensing human health from Space: An assessment of applications and big data platforms

The integration of Earth Observation (EO) into human health research has expanded significantly, particularly since 2009, highlighting its potential for disease modelling, environmental exposure assessment, and public health decision-making. This review explores the evolving role of EO in health applications through a bibliometric analysis of 1751 research documents retrieved from the Web of Science (WoS) database. These documents were selected using targeted keywords and after excluding non-primary literature such as reviews, editorials, and meeting abstracts. Findings revealed a substantial increase in EO-health research outputs, growing from 2 publications in 1991 to 266 in 2024, with a notable surge beginning in 2009. More than 65 % of the selected studies contributed to Sustainable Development Goal (SDG) 13 on Climate Action, followed by SDG 3 on Good Health and Wellbeing (n = 994) and SDG 11 on Sustainable Cities and Communities (n = 980), illustrating EO's cross-cutting relevance. Despite this growth, the field remains fragmented due to inconsistent data formats, limited accessibility, and weak interdisciplinary collaboration. A key challenge is the persistent divide between EO data producers and health practitioners, which hampers the effective translation of EO insights into practice. This review highlights the importance of co-production approaches that bring together researchers, policymakers, and communities to address these barriers. By promoting standardisation, enhancing data interoperability, and fostering interdisciplinary collaboration, EO can be more effectively leveraged to support disease surveillance, environmental health monitoring, and evidence-based policy interventions aligned with global health and sustainability goals

Quantitative metagenomics for marine prokaryotes and photosynthetic eukaryotes

High-throughput sequencing has provided unprecedented insights into microbial biodiversity in marine and other ecosystems. However, most sequencing-based studies report only relative (compositional) rather than absolute abundance, limiting their application in ecological modeling and biogeochemical analyses. Here, we present a metagenomic protocol incorporating genomic internal standards to quantify the absolute abundances of prokaryotes and eukaryotic phytoplankton, which together form the base of the marine food web, in unfractionated seawater. We applied this method to surface waters collected across 50°N to 40°S during the 29th Atlantic Meridional Transect. Using the single-copy recA gene, we estimated an average bacterial abundance of 1.0 × 109 haploid genome equivalents per liter. Leveraging a recent report that the psbO gene is typically single-copy in phytoplankton, we also quantified eukaryotic phytoplankton. Metagenomic estimates closely aligned with flow cytometry data for cyanobacteria (slope = 1.03, Pearson’s r = 0.89) and eukaryotic phytoplankton (slope = 0.72, Pearson’s r = 0.84). Compared to flow cytometry, taxonomic resolution for nano- and picoeukaryotes was greatly improved. Estimates for diatoms, dinoflagellates, and Trichodesmium were considerably higher than microscopy counts, likely reflecting microscopy undercounts and potential ploidy variation. These findings highlight the value of absolute quantification by metagenomics and offer a robust framework for quantitative assessments in microbial oceanography

Can the emerging European seaweed industry contribute to climate change mitigation by enhancing carbon sequestration?

Blue carbon habitats, which exhibit high rates of natural carbon sequestration, typically refer to salt marshes, seagrass meadows, and mangrove forests. Recent studies, however, have argued for the inclusion of seaweed-dominated habitats, like kelp forests, into blue carbon frameworks. Farmed seaweed may also function as a blue carbon habitat, with large-scale seaweed aquaculture suggested as a climate change mitigation strategy, but the evidence base remains limited. Here, existing knowledge on the mechanisms influencing carbon uptake, release, transport, and storage from kelp farms was synthesised, and a literature review was conducted to quantify associated rates of carbon sequestration. We identified strong geographical and methodological biases in the literature, with the majority of studies conducted in Asia and focusing on primary production rates as a proxy for carbon sequestration potential. Estimates of carbon release and storage rates were highly variable across locations, species, and approaches, and a scarcity of research on dissolved organic carbon, sedimentary carbon, and net ecosystem productivity was identified. Although the European kelp farming industry is in its infancy, it is predicted to expand to meet increasing demand for seaweed biomass. This is incentivised by perceived associated ecosystem service benefits such as enhanced carbon sequestration. However, multiple factors including environmental concerns, a lack of quantitative evidence, operational challenges, and regulatory complexities hinder industry expansion. Based on both the synthesised empirical evidence and an examination of key barriers and knowledge gaps, we identify future challenges and research priorities needed to assess the role of seaweed farming for climate change mitigatio