The oceans cover 70% of the Earth’s surface and extend an average of 4000 meters below sea level. The fascination with the ocean has persisted to the test of time, from the history of navigation to the Challenger expedition that marked the start of modern oceanography in the late 19th Century. Since then, modern research efforts have advanced considerably and made attempts at estimating oceanic element budgets and diversity, such as the Tara Oceans expeditions (Sunagawa et al., 2015) or Ocean Sampling Day (Kopf et al., 2015). Regardless, the oceans remain largely undersampled. The increasing efforts of large-scale and sustained ocean observations are revealing the complexity of small-scale oceanographic dynamics and variability in marine ecosystems.

Oceanic processes and marine life naturally vary across spatial and temporal scales, which are best studied using ocean observations ( Figure 1 ). Ocean observations are made with a diverse range of platforms that can be classified into four categories: autonomous remote sensing, autonomous drifting devices, autonomous fixed or stationary devices, and discrete sampling. Remote sensing satellites provide a high spatial and temporal resolution, but only at the ocean surface. Within the ocean, autonomous drifting or tagged devices can resolve the spatial variability at the ocean surface to 2000 meters depth (e.g., Argo floats or Autonomous Underwater Vehicles) and track marine animals (Visser et al., 2021), while autonomous stationary platforms can resolve the temporal variability (i.e., moorings or anchored buoys). Autonomous observations are typically operated using standardized protocols for a range of sensors to monitor physical and some biological and chemical variables, such as temperature, salinity, oxygen, and fluorescence for phytoplankton biomass (Boss et al., 2022). In addition, stationary platforms can also be coupled with autonomous sampling devices to sample for a wider range of variables, such as sediment traps or remote access samplers (RAS). However, many variables, particularly biological and ecological variables, require visual monitoring and discrete hand-sampling of the water column or sediment to survey the spatiotemporal variability. Both, autonomous and discrete ocean observations, rely on trained personnel and major scientific infrastructures. Research vessels provide an essential observation infrastructure across scientific disciplines to deploy a variety of oceanographic instruments (Nieuwejaar and Mazauric, 2019). Modern research vessels host a range of permanently installed sensors and handling capabilities of mobile instruments that include the conductivity-temperature-depth profiler (CTD) coupled to a rosette that provides discrete water samples, towed seismic equipment, box- and multicorer (MUC) systems that provide discrete sediment samples, and nets that passively collect megafauna in the water column or the seafloor (see Paulus, 2021). In 2019, European countries operated 99 research vessels with a greater number and easier access to coastal/local classes (approx. five scientific births) compared to ocean and global classes (>20 scientific births) (Nieuwejaar and Mazauric, 2019).

Repeating observations at a given location over time are known as time series ( Box 1 ). Ocean time series are temporally resolved datasets that are valuable in characterizing ocean climate, biogeochemistry, and ecosystem change (International Group for Marine Ecological Time Series, 2017). The ocean climate and biogeochemistry can be monitored using autonomous platforms, like moorings, while ecosystem changes still crucially rely on monitoring at ship-based time series that, in the case of open ocean time series, can be registered with the OceanSITES global network. Examples of these long-term open-ocean time series sites that combine autonomous and ship-based time series include: Bermuda Atlantic Time-series Study (BATS), DYFAMED Observatory, Hawaii Ocean Time Series (HOT), HAUSGARTEN Observatory, Porcupine Abyssal Plain (PAP), Santander Atlantic Time-Series (SATS), and the Southern Ocean Time-Series (SOTS). These combined sites emphasize the value of cross-validation and allow for the highest degree of observation, while typically also reducing the observation bias of meso- and bathypelagic zones that are also affected by anthropogenic climate change (González-Dávila and Santana-Casiano, 2023).

Open ocean fixed time series are located in all ocean basins ( Figure 2A ), but most ship-based ecological time series are more predominant in shallow coastal areas ( Figure 2B ). However, not all ship-based ecological time series are currently not actively curated in a global database and have to be independently retrieved to perform specific metanalyses (Raes et al., 2024). Previously, efforts of the International Group for Marine Ecological Time Series (IGMETS) demonstrated the collective value of integrating and assessing ship-based time series (O’Brien et al., 2017). Merging the catalogs from IGMETS marine ecological time series metadata (METabase), EuroSea Project (Ratnarajah, 2021), the International Ocean Carbon Coordination Project network (IOCCP, April 2016), and Buttigieg et al. (2018) showed that 54% of time series stations are located in the Atlantic Ocean, which includes the English Channel, Irish Sea, and North Sea ( Supplementary Table 1 ). Next, time series stations exist in the Arctic Ocean ~14%, the Baltic Sea ~12%, the Mediterranean Sea (incl. the Black Sea) ~9%, the Pacific Ocean ~8%, the Indian Ocean, and the Southern Ocean <2% ( Figure 3 ; Supplementary Table 1 ). The accessibility of the station often pre-determines the sampling frequency, which ranges from daily sampling events ~2% to annual sampling campaigns ~24%, although ~5% were listed as variable and unknown ( Figure 3 ). Monitoring Essential Ocean Variables (EOVs) and standardizing sampling protocols would raise the comparability of global datasets since ~82% of ship-based time series observe temporal variability of the pelagic realm with a strong focus on phytoplankton, zooplankton, and microbes (here, bacteria and archaea; Figure 3 ).

Monitoring the natural variability and health of the ocean is becoming more pressing than ever with increasing warming, acidification, pollution, eutrophication, and hypoxic events (Gruber, 2011). Ocean time series are central in quantifying the temporal variability with an additional number of benefits from testing new technologies, conducting in situ experiments within a context of known environmental variability, validating autonomous and remote platforms used in forecasting systems, to informing policy decisions (Karl, 2010; Neuer et al., 2017; O’Brien et al., 2017). Currently, data discoverability and synthesis products limit the full scientific potential of ship-based time series, but efforts are being made to close this gap (Lange et al., 2023, Lange et al., 2024). The scientific needs and future policies for a sustainable ocean are currently being addressed as part of the United Nations Decade of Ocean Science for Sustainable Development (henceforth UN Ocean Decade) between 2021-2030.

Ocean observations typically begin with producing data that feeds into databases, which can then be used for communication and eventually result in end-user interoperability as science-based policy, education, and technology development. User benefits vary based on the key sector, such as safety through monitoring and managing the ocean, food safety, or tourism.

Climate change is increasing the frequency of natural disasters and the risk of crossing several marine-related tipping points (IPCC, 2023). Although the oceans considerably regulate the Earth’s climate, the Sustainable Development Goal (SDG) 14 “Life Below Water”, within the 2030 Agenda for Sustainable Development, receives the least amount of long-term funding of any of the SDGs (United Nations, 2022). Therefore, ocean observations are critical to understanding the changing role of oceans in buffering and moderating the ongoing anthropogenic climate change (e.g., Moran et al., 2022; Przeslawski et al., 2023). Ocean observations are gaining more and more attention with an increasing number of designated journal sections and conferences, such as OceanObs’ conference series (Speich et al., 2019) and UN Ocean Decade conferences as part of the UN Ocean Decade, to inform the relevant industry sectors and end-users. The UN Ocean Decade aims to connect people and transform ocean science solutions for sustainable development using ten challenges between 2021-2030. Specifically, two of the ten challenges focus on ocean observations (Challenge 7) and a digital representation of the ocean (Challenge 8), described thoroughly in a White Papers that outlines the user needs, gaps in science, and strategic measures required to fulfill the objectives by the end of the decade (UNESCO, 2024).

Ocean observations are becoming increasingly important for society, but ocean time series are not sustainably supported despite their far-reaching benefits. There is a large possibility that ocean time series stations are, to a degree or fully, dependent on voluntary contributions from institutional budgets or short-term project-based funding. Only a few ocean observations are supported through program-based funding and RIs for multiple years to decades. In the near future, national governments should recognize that adequate and reliable funding infrastructure of ocean observations is fundamental to meeting user needs and important to build innovation and capacity. Ocean time series elevate the societal and economic benefits of ocean data. In an ideal scenario, national strategic investments combine short-term project funding with long-term funding to maximize the scientific knowledge output of curiosity-driven research and monitoring efforts that feed into the digital twins of the oceans (DITTO).

Ocean observations and ECOPs are the main pillars of sustainable ocean solutions in the future. It is undeniable that human activities are responsible for climate change, which is a complex problem that requires transformative and transdisciplinary approaches. Such transformations require co-design approaches that share knowledge for inclusive engagement and facilitate multi-sectoral collaborations to develop a shared commitment among end-users. Ocean time series are a great tool to observe the ocean, building ocean literacy, and engage a range of end-users. End-users range across sectors, disciplines, regions, generations, and career stages. For example, ECOPs are present in science, policy, and society, where they might ask questions and start new conversations with out-of-the-box ideas to catalyze culture change for inclusivity. In conclusion, promoting inclusion and transparency of the current structures will strengthen the engagement in networks and actions across end-users, in particular among ECOPs that can bridge generational gaps, develop innovative solutions, and play a significant role in ensuring the success of the UN Ocean Decade to shape the ocean we want and need in the future.