Description: Biomolecular ocean observing and research is a rapidly evolving field that uses omics approaches to describe biodiversity at its foundational level, giving insight into the structure and function of marine ecosystems over time and space. It is an especially effective approach for investigating the marine microbiome. To mature marine microbiome research and operations within a global ocean biomolecular observing network (OBON) for the UN Decade of Ocean Science for Sustainable Development and beyond, research groups will need a system to effectively share, discover, and compare “omic” practices and protocols. While numerous informatic tools and standards exist, there is currently no global, publicly-supported platform specifically designed for sharing marine omics [or any omics] protocols across the entire value-chain from initiating a study to the publication and use of its results. Toward that goal, we propose the development of the Minimum Information for an Omic Protocol (MIOP), a community-developed guide of curated, standardized metadata tags and categories that will orient protocols in the value-chain for the facilitated, structured, and user-driven discovery of suitable protocol suites on the Ocean Best Practices System. Users can annotate their protocols with these tags, or use them as search criteria to find appropriate protocols. Implementing such a curated repository is an essential step toward establishing best practices. Sharing protocols and encouraging comparisons through this repository will be the first steps toward designing a decision tree to guide users to community endorsed best practices.

Description: The UN Decade of Ocean Science for Sustainable Development (Ocean Decade) challenges marine science to better inform and stimulate social and economic development while conserving marine ecosystems. To achieve these objectives, we must make our diverse methodologies more comparable and interoperable, expanding global participation and foster capacity development in ocean science through a new and coherent approach to best practice development. We present perspectives on this issue gleaned from the ongoing development of the UNESCO Intergovernmental Oceanographic Commission (IOC) Ocean Best Practices System (OBPS). The OBPS is collaborating with individuals and programs around the world to transform the way ocean methodologies are managed, in strong alignment with the outcomes envisioned for the Ocean Decade. However, significant challenges remain, including: (1) the haphazard management of methodologies across their lifecycle, (2) the ambiguous endorsement of what is "best" and when and where one method may be applicable vs. another, and (3) the inconsistent access to methodological knowledge across disciplines and cultures. To help address these challenges, we recommend that sponsors and leaders in ocean science and education promote consistent documentation and convergence of methodologies to: create and improve context-dependent best practices; incorporate contextualized best practices into Ocean Decade Actions; clarify who endorses which method and why; create a global network of complementary ocean practices systems; and ensure broader consistency and flexibility in international capacity development.

Description: The trace metal iron is considered to be the nutrient that limits marine primary production in one third of the global surface ocean (Martin, 1990; Boyd et al., 2007; Moore et al., 2013). It is also the nutrient that maintains future ocean fertility due to its irreplaceable role in the process of nitrogen fixation, which adds “new” nitrogen (another nutrient for phytoplankton) to the surface ocean (Raven, 1988; Kustka et al., 2003b; Zehr and Capone, 2020). Due to iron’s importance, it is not surprising that the demand for incorporating iron into global biogeochemical models is high. However, including iron in an earth system model has been shown to have no clear benefits with respect to model misfit against observational data (Nickelsen et al., 2015) . How smart is it then to introduce iron models into global biogeochemical models, when the benefits are not clearly identifiable? Especially, when the iron models perform poorly at reproducing observed iron patterns in the ocean (Tagliabue et al., 2016). The poor performance of iron models, coupled with their failure to improve biogeochemical tracer representation of the ocean, inspired this additional effort to identify the advantages of including iron in a global biogeochemical model, both for the preindustrial state and under conditions of a changing climate. The working hypothesis was that the relatively poor performance of iron models might come from inadequate model calibration. A first sensitivity study on biogeochemical model parameter values was conducted in order to identify key parameters for model calibration. It was found that while some of the parameters influence simulated nitrogen, phosphorus, and oxygen concentrations, few parameters influence simulated iron concentrations. This suggests that our modelling skill of the iron cycle is still limited and/or that the observational data base is insufficient for comprehensive model calibration so far. Thus it was decided not to include iron data in further model calibration. A model calibration framework (Kriest et al., 2017) was next applied to a hierarchy of global models with different implementations of iron; one without iron, one with prescribed iron concentrations, and another one with a dynamic iron cycle. Using calibration against global data sets of nitrogen, phosphorus, and oxygen, the misfit of each model was pushed to its minimum. It was found that under an assumed preindustrial steady state, the calibrated model with a full dynamic iron cycle has the lowest model misfit against observations (thus confirming the working hypothesis). It was also found that the calibrated model with a fully dynamic iron cycle has 50% less net primary production (which is closer to empirical estimations) compared to the calibrated model without iron. Finally, transient simulations for all calibrated models were integrated from their pre- industrial state until the end of the 21st century using an atmospheric CO2 concentration pathway consistent with a ’business-as-usual’ CO2 emission scenario. It was found that nitrogen fixation trends diverge among models. This divergence is caused by whether iron limits the productivity of the upwelling regions, e.g. in the eastern tropical Pacific. The export production in the eastern tropical Pacific (and other tropical upwelling regions) reacts differently to warming, depending on whether iron is a limiting nutrient. These different responses trigger a divergent chain of downstream responses that affect nitrogen fixation across the tropical oligotrophic regions in the model. Through the comparison between calibrated models, this thesis quantifies the advantages of including iron in a global biogeochemistry model and reveals how important iron is for future nitrogen fixation trends. It furthermore illustrates the interconnection between tropical upwelling and oligotrophic regions.

Description: Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60 degrees N and 55 degrees S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 approximate to 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 〈 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.

Description: Highlights • Climate engineering presents a novel challenge for global environmental governance • Institutional and discursive structures co-shape global environmental governance • A lack of joint analyses of both structures impedes understanding of governance emergence • A joint neo-institutionalist and post-structuralist analysis addresses this gap • Varying structures shape differing climate engineering governance decisions in several forums Abstract The Anthropocene is giving rise to novel challenges for global environmental governance. The barriers and opportunities shaping the ways in which some of these complex environmental challenges become governable on the global level are of increasing academic and practical relevance. In this article, we bring neo-institutionalist and post-structuralist perspectives together in an innovative framework to analyse how both institutional and discursive structures together bound and shape the global governance opportunities which become thinkable and practicable in the face of new global environmental challenges. We apply this framework to explore how governance of climate engineering – large scale, deliberate invention into the global climate system – is being shaped by discursive and institutional structures in three international forums: The London Convention and its Protocol, the Convention on Biological Diversity, and the United Nations Environment Assembly. We illustrate that the ‘degree of fit’ between discursive and institutional structures made climate engineering (un)governable in each of these forums. Furthermore, we find that the ‘type of fit’ set the discursive and institutional conditions of possibility for what type of governance emerged in each of these cases. Based on our findings, we critically discuss the implications for the future governance of climate engineering at the global level.

Description: Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum–maximum estimates: 12.2–23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9–17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2–11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies—particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O–climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Description: The neritic-oceanic squid Illex argentinus supports one of the largest fisheries in the Southwest Atlantic. It is characterized by extensive migrations across the Patagonian Shelf and complex population structure comprising distinct seasonal spawning groups. To address uncertainty as to the demographic independence of these groups that may compromise sustainable management, a multidisciplinary approach was applied integrating statolith ageing with genome-wide single-nucleotide polymorphism (SNP) analysis. To obtain complete coverage of the spawning groups, sampling was carried out at multiple times during the 2020 fishing season and covered a large proportion of the species' range across the Patagonian Shelf. Statolith and microstructure analysis revealed three distinct seasonal spawning groups of winter-, spring-, and summer-hatched individuals. Subgroups were identified within each seasonal group, with statolith microstructure indicating differences in environmental conditions during ontogeny. Analysis of 〉10 000 SNPs reported no evidence of neutral or non-neutral genetic structure among the various groups. These findings indicate that I. argentinus across the Patagonian Shelf belong to one genetic population and a collaborative management strategy involving international stakeholders is required. The connectivity among spawning groups may represent a "bet-hedging" mechanism important for population resilience.

Description: The ongoing development of the Global Carbon Project (GCP) global methane (CH4) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for 〉40% of the global total emissions (their anthropogenic and natural sources together totaling 〉270 Tg CH4 yr−1 in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (〉75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by 〉20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.

Description: Ocean warming and species exploitation have already caused large‐scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time‐dynamic integrated food web modeling approach (Ecosim) with previous data from community‐level mesocosm experiments to determine the independent and combined effects of ocean warming, ocean acidification and fisheries exploitation on a well‐managed temperate coastal ecosystem. The mesocosm parameters enabled important physiological and behavioral responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. Through model simulations, we show that under sustainable rates of fisheries exploitation, near‐future warming or ocean acidification in isolation could benefit species biomass at higher trophic levels (e.g., mammals, birds, and demersal finfish) in their current climate ranges, with the exception of small pelagic fishes. However, under warming and acidification combined, biomass increases at higher trophic levels will be lower or absent, while in the longer term reduced productivity of prey species is unlikely to support the increased biomass at the top of the food web. We also show that increases in exploitation will suppress any positive effects of human‐driven climate change, causing individual species biomass to decrease at higher trophic levels. Nevertheless, total future potential biomass of some fisheries species in temperate areas might remain high, particularly under acidification, because unharvested opportunistic species will likely benefit from decreased competition and show an increase in biomass. Ecological indicators of species composition such as the Shannon diversity index decline under all climate change scenarios, suggesting a trade‐off between biomass gain and functional diversity. By coupling parameters from multilevel mesocosm food web experiments with dynamic food web models, we were able to simulate the generative mechanisms that drive complex responses of temperate marine ecosystems to global change. This approach, which blends theory with experimental data, provides new prospects for forecasting climate‐driven biodiversity change and its effects on ecosystem processes.