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Despite providing many valuable ecosystem services, seagrasses are a threatened habitat and their global distribution is not fully known. For example, Venezuela lacks a national seagrass map. An established regional mapping approach for seagrass exists for the Google Earth Engine (GEE) platform, but requires a long time window to obtain sufficient data to overcome cloud and other challenges. Recently, GEE has released a Cloud Score+ quality band product for the purpose of cloud masking. Cloud masking could potentially reduce the time window needed for a representative multitemporal composite, which would allow for temporal analyses. We compare the performance of Cloud Score+ derived products against previously established multitemporal image composites acquired in different time ranges, and the ACOLITE‐processed single image composite. The Sentinel‐2 (S2) Level‐1C (L1C) imagery for the whole Venezuelan coastline was processed following three different approaches: (a) using a multitemporal composition of the full S2 L1C archive available and processed in GEE using the Dark Object Subtraction; (b) integrating Cloud Score+ data set into the previous approach; and (c) using a single‐image offline approach applying ACOLITE atmospheric correction. Additional raster features were generated and a two‐step classification approach was performed with five classes, namely sand, seagrass, turbid water, deep water, and coral, and bootstrapped 20 times. Quantitatively, the performance within the Cloud Score+ derived products were largely similar. While the full archive approach had the best quantitative results, the ACOLITE approach produced the best maps qualitatively. With this, we produced the first national seagrass map for Venezuela. 

The Marine Biodiversity Observation Network (MBON) is a global community of practice and network that links individuals and groups in an effort to monitor and understand changes in marine biodiversity. MBON functions within the larger framework of the Group on Earth Observations Biodiversity Observation Networks (GEO BON). These networks support mobilization of data to help nations to achieve the Sustainable Development Goals (SDGs) adopted by the United Nations (UN) in 2015 and to address their own internal, local management needs. Marine biodiversity data are important for allowing countries and local communities to monitor changes that result from local human pressures and climate change. Such data enable informed planning and management of coastal areas and resources. 

Coastal wetlands are vulnerable to accelerated sea-level rise, yet knowledge about their extent and distribution is often limited. We developed a land cover classification of wetlands in the coastal plains of the southern United States along the Gulf of Mexico (Texas, Louisiana, Mississippi, Alabama, and Florida) using 6161 very-high (2 m per pixel) resolution WorldView-2 and WorldView-3 satellite images from 2012 to 2015. Area extent estimations were obtained for the following vegetated classes: marsh, scrub, grass, forested upland, and forested wetland, located in elevation brackets between 0 and 10 m above sea level at 0.1 m intervals. Sea-level trends were estimated for each coastal state using tide gauge data collected over the period 1983–2021 and projected for 2100 using the trend estimated over that period. These trends were considered conservative, as sea level rise in the region accelerated between 2010 and 2021. Estimated losses in vegetation area due to sea level rise by 2100 are projected to be at least 12,587 km2, of which 3224 km2 would be coastal wetlands. Louisiana is expected to suffer the largest losses in vegetation (80%) and coastal wetlands (75%) by 2100. Such high-resolution coastal mapping products help to guide adaptation plans in the region, including planning for wetland conservation and coastal development. 

Abstract. The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO2), particulate matter, and dissolved organic carbon. The time series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10–36 years), and bottom depths (80–6000 m), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. The most recently applied methods of the time-series programs usually follow the recommendations outlined by the Bermuda Time Series Workshop report (Lorenzoni and Benway, 2013), which is used as the main reference for “method recommendations by prevalent initiatives in the field”. However, measurements of dissolved oxygen and pH, in particular, still show room for improvement. Additional data quality descriptors include precision and accuracy estimates, indicators for data variability, and offsets compared to a reference and widely recognized data product for the global ocean: the GLobal Ocean Data Analysis Project (GLODAP). Generally, these descriptors indicate a high level of continuity in measurement quality within time-series programs and a good consistency with the GLODAP data product, even though robust comparisons to the latter are limited. The data are available as (i) a merged comma-separated file that is compliant with the World Ocean Circulation Experiment (WOCE) exchange format and (ii) a format dependent on user queries via the Environmental Research Division's Data Access Program (ERDDAP) server of the Global Ocean Observing System (GOOS). The pilot increases the data utility, findability, accessibility, interoperability, and reusability following the FAIR philosophy, enhancing the readiness of biogeochemical time series. It facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, SPOTS, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO2 Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product). Aside from the actual data compilation, the pilot project produced suggestions for reporting metadata, implementing quality control measures, and making estimations about uncertainty. These recommendations aim to encourage the community to adopt more consistent and uniform practices for analysis and reporting and to update these practices regularly. The detailed recommendations, links to the original time-series programs, the original data, their documentation, and related efforts are available on the SPOTS website. This site also provides access to the data product (DOI: https://doi.org/10.26008/1912/bco-dmo.896862.2, Lange et al., 2024) and ancillary data. 

Abstract People depend on biodiversity—the heart of healthy ecosystems—in many ways and every day of our lives. Yet usable knowledge of marine life is a missing link in the way we have designed marine observing and information systems. We lack critical biodiversity information to inform sustainable development from local levels to global scales—information on Essential Ocean Variables such as how many types and how much plankton, seagrasses, macro-algae, mangroves, corals and other invertebrates, fish, turtles, birds, and mammals are in any location at any one time, the value we may derive from that combination of organisms, and how this is changing with time and why. Marine Life 2030 is a program endorsed by the Ocean Decade to develop a coordinated system to deliver such actionable, transdisciplinary knowledge of ocean life to those who need it, promoting human well-being, sustainable development, and ocean conservation. Marine Life 2030 is an open network that invites partners to join us with ideas and energy to connect communities, programs, and sectors into a global, interoperable network, transforming the observation and forecasting of marine life for the future and for the benefit of all people. 

We examine the main drivers that may elevate biomass and biodiversity of non-chemosynthetic benthic megafauna of the lower bathyal (800-3500m depth) of the Mid-Atlantic Ridge in the North Atlantic Ocean (MAR). Specifically: 1. Primary production in surface waters (10°-48°N) from remote sensing data 2002-2020 over the MAR was not significantly different from abyssal regions to the east and west. We reject the hypothesis that presence of a mid ocean ridge may enhance surface primary production. 2. The quantity of particulate organic matter reaching the sea floor was estimated as a proportion of surface export production scaled by bathymetry. Flux was 1.3 to 3.0 times greater on the MAR as a function of shorter vertical transport distance from the surface than on adjacent abyssal regions. 3. Depth variation effect on species richness. Demersal fishes living between 41° and 60°N showed a maximum of species richness at 2000 m depth and linear increase in regional (Gamma) diversity of 32 species per 1,000 m elevation of the MAR above the abyss. Elevated topography provides niches for species that cannot otherwise survive. 4. Substrate heterogeneity. The MAR >95% covered with soft sediment with frequent hard rocky patches spaced at a mean nearest neighbour distance of <500 m. Over 90% were <1 km apart. Animals are readily able to disperse between such patches increasing biodiversity through the additive effect of soft and hard substrate fauna on the MAR. 5. Presence of a biogeographic overlap zone. The MAR harbours bathyal species known from Western Atlantic and Eastern Atlantic continental slopes with meridional asymmetry resulting in bias toward predominance of Eastern species. The mix of species contributes to increased diversity to the east of the MAR. Multiple factors support increase in biomass and biodiversity on the MAR. Biological data are almost entirely absent from 12° to 33°N, the part of the MAR which may be mined for polymetallic sulphide ore deposits. This study enables some predictions of biomass and biodiversity but there is urgent need for intensive biological sampling across the MAR throughout the proposed mining areas south of the Azores. 

Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan.