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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. 

Sea-level rise is impacting the longest undeveloped stretch of coastline in the contiguous United States: The Florida Big Bend. Due to its low elevation and a higher-than-global-average local rate of sea-level rise, the region is losing coastal forest to encroaching marsh at an unprecedented rate. Previous research found a rate of forest-to-marsh conversion of up to 1.2 km² year⁻¹during the nineteenth and twentieth centuries, but these studies evaluated small-scale changes, suffered from data gaps, or are substantially outdated. We replicated and updated these studies with Landsat satellite imagery covering the entire Big Bend region from 2003 to 2016 and corroborated results with in situ landscape photography and high-resolution aerial imagery. Our analysis of satellite and aerial images from 2003 to 2016 indicates a rate of approximately 10 km² year⁻¹representing an increase of over 800%. Areas previously found to be unaffected by the decline are now in rapid retreat.

 

Abstract Marine Life 2030 is a programme endorsed by the United Nations Decade of Ocean Science for Sustainable Development (the Ocean Decade) to establish a globally coordinated system that delivers knowledge of ocean life to those who need it, promoting human well-being, sustainable development, and ocean conservation. It is an open network to unite existing and new programmes into a co-designed, global framework to share information on methods, standards, observations, and applications. Goals include realizing interoperable information and transforming the observation and forecasting of marine life for the benefit of all people. Co-design, sharing local capacity, and coordination between users of ocean resources across regions is fundamental to enable sustainable use and conservation. A novel, bottom-up networking structure is now engaging members of the ocean community to address local issues, with Marine Life 2030 facilitating the linkage between groups across different regions to meet the challenges of the Ocean Decade. A variety of metrics, including those proposed by the Group on Earth Observations, will be used to track the success of the co-design process. 

Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.

 

Predicting microbial metabolic rates and emergent biogeochemical fluxes remains challenging due to the many unknown population dynamical, physiological and reaction‐kinetic parameters and uncertainties in species composition. Here, we show that the need for these parameters can be eliminated when population dynamics and reaction kinetics operate at much shorter time scales than physical mixing processes. Such scenarios are widespread in poorly mixed water columns and sediments. In this ‘fast‐reaction‐transport’ (FRT) limit, all that is required for predictions are chemical boundary conditions, the physical mixing processes and reaction stoichiometries, while no knowledge of species composition, physiology or population/reaction kinetic parameters is needed. Using time‐series data spanning years 2001–2014 and depths 180–900 m across the permanently anoxic Cariaco Basin, we demonstrate that the FRT approach can accurately predict the dynamics of major electron donors and acceptors (Pearsonr ≥ 0.9 in all cases). Hence, many microbial processes in this system are largely transport limited and thus predictable regardless of species composition, population dynamics and kinetics. Our approach enables predictions for many systems in which microbial community dynamics and kinetics are unknown. Our findings also reveal a mechanism for the frequently observed decoupling between function and taxonomy in microbial systems.