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- McMahon, C. R., et al.
(författare)
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Animal Borne Ocean Sensors - AniBOS - An Essential Component of the Global Ocean Observing System
- 2021
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Ingår i: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 8
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Forskningsöversikt (refereegranskat)abstract
- Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (similar to 30% of instruments deployed annually, n = 103 +/- 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean's structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.
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| 2. |
- Nielsen, Rasmus J., et al.
(författare)
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Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation
- 2018
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Ingår i: Fish and Fisheries. - : Wiley. - 1467-2960 .- 1467-2979. ; 19:1, s. 1-29
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Forskningsöversikt (refereegranskat)abstract
- Marine ecosystems evolve under many interconnected and area-specific pressures. To fulfil society's intensifying and diversifying needs while ensuring ecologically sustainable development, more effective marine spatial planning and broader-scope management of marine resources is necessary. Integrated ecological–economic fisheries models (IEEFMs) of marine systems are needed to evaluate impacts and sustainability of potential management actions and understand, and anticipate ecological, economic and social dynamics at a range of scales from local to national and regional. To make these models most effective, it is important to determine how model characteristics and methods of communicating results influence the model implementation, the nature of the advice that can be provided and the impact on decisions taken by managers. This article presents a global review and comparative evaluation of 35 IEEFMs applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes although not all the models reviewed achieve that. Modellers must invest more time to make models user friendly and to participate in management fora where models and model results can be explained and discussed. Such involvement is beneficial to all parties, leading to improvement of models and more effective implementation of advice, but demands substantial resources which must be built into the governance process. It takes time to develop effective processes for using IEEFMs requiring a long-term commitment to integrating multidisciplinary modelling advice into management decision-making.
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