The Northwestern Mediterranean Sea is undergoing rapid environmental changes driven by climate variability and intense anthropogenic pressure. To monitor and understand the long-term impacts on marine ecosystems, the Mediterranean Ocean Observing System for the Environment (MOOSE) program combines multidisciplinary observations, including physical, chemical, and biological data across temporal and spatial scales. This study presents a holistic assessment of planktonic communities across the Northwestern Mediterranean using integrated approaches—environmental genomics and high-resolution imaging—spanning all plankton size fractions and depths. Data collected during three MOOSE-GE cruises in 2017, 2018, and 2019 were analyzed to explore plankton diversity patterns in relation to oceanographic features. Plankton assemblages were primarily shaped by organism size and water column depth, with fractions of 0.2–3 and 3–180 µm in the surface and deep chlorophyll maximum layers showing the highest alpha diversity. Fractions > 64 µm were dominated by metazoans, particularly Arthropoda, whereas size classes collected by Niskin bottles were dominated by protists such as Syndiniales and Rhizaria. Differences among cruises and sampling periods were detected in Niskin bottle samples, especially for diatoms and dinoflagellates, while plankton tow samples exhibited less pronounced temporal variability. Physical clustering of stations revealed clear cross-shelf and basin-scale gradients, which aligned more closely with community structure at fine taxonomic resolution (OTU level) for small plankton. Integrating imaging with environmental genomic data enhanced the characterization of key taxa like Copepoda and Rhizaria, demonstrating the complementary strengths of each method. While imaging provided quantitative data, environmental genomics captured cryptic and morphologically indistinct taxa, emphasizing the value of molecular approaches for microbial plankton. This study highlights the critical importance of combining high-resolution molecular and imaging tools with detailed environmental context to unravel plankton biodiversity patterns. It demonstrates that depth, size, and taxonomic resolution are key dimensions for understanding community structure over time. The MOOSE program proves effective for ecosystem-scale monitoring, providing an essential foundation for future assessments of biogeochemical processes and ecosystem responses to climate change and human-induced alterations in the Mediterranean Sea.

Understanding how the structure of ecological communities varies across biotic and abiotic dimensions is a fundamental goal in ecology. This challenge is now approachable due to the increasing availability of data on community structure across the globe. Ecological communities are often defined with respect to the guilds considered and the interactions they engage in, but it is unclear whether interactions of different types respond similarly to large-scale environmental gradients. Therefore, we don't know whether there exist differences in how the emergent structure of ecological networks varies across biogeographical gradients, depending on their constituent interaction types. Here, using a unique dataset of 952 networks across the globe, we provide a first comparison of network structural metrics and their large-scale variability for five overarching interaction types (feeding, frugivory, herbivory, parasitism, pollination). We show that networks of different types tend to be more modular than expected, but other structural metrics do not deviate from what is expected given the degree distributions of the networks. Our analysis also reveals that network sampling intensity is a particularly relevant factor influencing network degree distribution, and that food webs appear in general more sensitive to environmental factors than other interaction types. By analysing common descriptors from the degree distributions of ecological networks, this study underscores for the first time generalities and differences across different interaction types and their response to environmental, sampling, and anthropic factors.