Abstract
<jats:p>Improving environmental management in the offshore Oil & Gas sector requires approaches that capture the ecosystem services (ES) provided by marine sediments, particularly their roles in carbon and nutrient cycling. Microbial communities are central to these processes, and molecular tools offer new opportunities to assess their functional diversity. To explore how different sequencing approaches inform environmental impact assessment, we compared taxonomic and functional prediction based on 16S metabarcoding, shotgun metagenomics and messenger RNA-based metatranscriptomics, targeting prokaryotic communities. Our aims were to evaluate the ability of each approach to detect impact and to determine how well they captured functions relevant to ES. All approaches revealed clear differences in community composition between impacted and non‑impacted sediments at both taxonomic and functional levels, with impact significantly associated with hydrocarbon and barium content. Functional inventories showed substantial overlap across the three approaches, and 48-55 ES-related processes were detectable in all datasets. While metagenomics provided the strongest statistical discrimination between impact groups, metatranscriptomics resolved the actively expressed pathways underpinning ES, yielding the most biologically meaningful functional profiles despite its lower statistical power. All approaches indicated that Oil & Gas activity drives shift towards anaerobic, hydrocarbon-degrading, and sulfur-respiring microbial communities, with hydrocarbon degradation, sulfur cycling, and metal detoxification being the dominant ES processes in impacted sediments. Metabarcoding was confirmed as a cost‑effective option for impact assessment when focused on taxonomic composition. However, functional prediction from metabarcoding data proved less reliable, as several ES showed contrasting associations to impact category between metabarcoding and shotgun sequencing approaches.</jats:p>