Description: To enable successful management of marine bioinvasions, timely and robust scientific advice is required. This knowledge should inform managers and stakeholders on the magnitude of a pressure (rate of human-mediated introductions), the environmental state of an ecosystem (impacts of non-indigenous species), and the success of management response (prevention, eradication, mitigation). This advice often relies on baseline biodiversity information in the form of measureable parameters (metrics). This can be derived from conventional approaches such as visual surveys, but also by utilizing environmental DNA/RNA-based molecular techniques, which are increasingly being touted as promising tools for assessing biodiversity and detecting rare or invasive species. Depending on the stage of incursion, each approach has merits and limitations. In this review we assess the performance of biosecurity-relevant biodiversity parameters derived from eDNA/eRNA samples and discuss the results in relation to different stages of invasion and management applications. The overall performance of considered methods ranged between 42 and 90% based on defined criteria, with target-specific approaches scoring higher for respective biosecurity applications, followed by eDNA metabarcoding. Caveats are discussed along with avenues which may enhance these techniques and their successful uptake for marine biosecurity surveillance and management. To facilitate and encourage uptake of these techniques, there is a need for an international collaborative framework aimed at unifying molecular sampling and analysis methodologies. Improvement of quantitative capacity and cost-efficiency will also enhance their integration in biosecurity programmes.

Description: 38th IAMSLIC Conference: Anchorage, Alaska, U.S.A., August 26-30, 2012, held jointly with the 24th Cyamus Meeting: August 24-25

Description: Collaborations between artists and ocean scientists are becoming increasingly frequent. As the UN Ocean Decade (2021-2030) stresses the importance of engaging with the public, there is a growing interest in using art as a tool for communication as well as for scientific exploration and experimentation. This mini-review charts the current academic research on art-science collaborations and the ocean, focusing on literature where artists and scientists work together to produce something based on scientific research. The study finds that these relationships are never apolitical, are complex and develop differently depending on each project. In sum the paper will highlight that although the academic literature is limited, its diversity has the potential to reach numerous academic disciplines and that focusing on process and engagement should be a direction for further research to help broaden the academic reach of these important oceanic knowledges.

Description: Joint IAMSLIC/EURASLIC Conference held 14-19 October, 2001 at Brest, France

Description: The Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP) provides a globally coordinated network and oversight of 55 sustained decadal repeat hydrographic reference lines. GO-SHIP is part of the global ocean/climate observing systems (GOOS/GCOS) for study of physical oceanography, the ocean carbon, oxygen and nutrient cycles, and marine biogeochemistry. GO-SHIP enables assessment of the ocean sequestration of heat and carbon, changing ocean circulation and ventilation patterns, and their effects on ocean health and Earth's climate. Rapid quality control and open data release along with incorporation of the GO-SHIP effort in the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) in situ Observing Programs Support Center (JCOMMOPS) have increased the profile of, and participation in, the program and led to increased data use for a range of efforts. In addition to scientific discovery, GO-SHIP provides climate quality observations for ongoing calibration of measurements from existing and new autonomous platforms. This includes biogeochemical observations for the nascent array of biogeochemical (BGC)-Argo floats; temperature and salinity for Deep Argo; and salinity for the core Argo array. GO-SHIP provides the relevant suite of global, full depth, high quality observations and co-located deployment opportunities that, for the foreseeable future, remain crucial to maintenance and evolution of Argo's unique contribution to climate science. The evolution of GO-SHIP from a program primarily focused on physical climate to increased emphasis on ocean health and sustainability has put an emphasis on the addition of essential ocean variables for biology and ecosystems in the program measurement suite. In conjunction with novel automated measurement systems, ocean color, particulate matter, and phytoplankton enumeration are being explored as GO-SHIP variables. The addition of biological and ecosystem measurements will enable GO-SHIP to determine trends and variability in these key indicators of ocean health. The active and adaptive community has sustained the network, quality and relevance of the global repeat hydrography effort through societally important scientific results, increased exposure, and interoperability with new efforts and opportunities within the community. Here we provide key recommendations for the continuation and growth of GO-SHIP in the next decade.

Description: This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates – internally consistently – the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

Description: The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through https://gitlab.pik-potsdam.de/lpjml/LPJmL. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.

Description: 〈jats:p〉In many of the Pacific Islands, local communities have long-held cultural and spiritual attachments to the sea, in particular to species and specific marine areas, processes, habitats, islands, and natural seabed formations. Traditional knowledge, customary marine management approaches and integrated relationships between biodiversity, ecosystems and local communities promote conservation and ensure that marine benefits are reaped in a holistic, sustainable and equitable manner. However, the interaction between local traditional knowledge, contemporary scientific approaches to marine resource management and specific regulatory frameworks has often been challenging. To some extent, the value of community practices and customary law, which have provided an incentive for regional cooperation and coordination around ocean governance, is acknowledged in several legal systems in the Pacific and a number of regional and international instruments, but this important connection can be further enhanced. In this article we present a science-based overview of the marine habitats that would be affected by deep seabed mining (DSM) along with an analysis of some traditional dimensions and cultural/societal aspects of marine resource management. We then assess whether the applicable legal frameworks at different levels attach sufficient importance to these traditional dimensions and to the human and societal aspects of seabed (mineral) resource management in the region. On the basis of this analysis, we identify best practices and formulate recommendations with regard to the current regulatory frameworks and seabed resource management approaches. Indeed, the policies and practices developed in the Pacific could well serve as a suitable model elsewhere to reconcile commercial, ecological, cultural and social values within the context of deep sea mineral exploitation in addition to sustaining the Human Well-being and Sustainable Livelihoods (HWSL) of the Pacific communities and the health of the Global Ocean.〈/jats:p〉

Description: 47th IAMSLIC Annual Conference and 19th EURASLIC Regional Meeting held 12-14 October, 2021 Virtually via Galway, Ireland

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°N and 55°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 ≈ 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.