Predicting the ocean state in a reliable and interoperable way, while ensuring high-quality products, requires forecasting systems that synergistically combine science-based methodologies with advanced technologies for timely, user-oriented solutions. Achieving this objective necessitates the adoption of best practices when implementing ocean forecasting services, resulting in the proper design of system components and the capacity to evolve through different levels of complexity. The vision of OceanPrediction Decade Collaborative Center, endorsed by the UN Decade of Ocean Science for Sustainable Development 2021-2030, is to support this challenge by developing a “predicted ocean based on a shared and coordinated global effort” and by working within a collaborative framework that encompasses worldwide expertise in ocean science and technology. To measure the capacity of ocean forecasting systems, the OceanPrediction Decade Collaborative Center proposes a novel approach based on the definition of an Operational Readiness Level (ORL). This approach is designed to guide and promote the adoption of best practices by qualifying and quantifying the overall operational status. Considering three identified operational categories - production, validation, and data dissemination - the proposed ORL is computed through a cumulative scoring system. This method is determined by fulfilling specific criteria, starting from a given base level and progressively advancing to higher levels. The goal of ORL and the computed scores per operational category is to support ocean forecasters in using and producing ocean data, information, and knowledge. This is achieved through systems that attain progressively higher levels of readiness, accessibility, and interoperability by adopting best practices that will be linked to the future design of standards and tools. This paper discusses examples of the application of this methodology, concluding on the advantages of its adoption as a reference tool to encourage and endorse services in joining common frameworks.
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RBINS Staff Publications 2023
Escalating human activities threaten ecosystems and the benefits they provide, known as ecosystem services (ES). Despite the recognized importance of ES for both ecological health and human well-being, integrated methods for evaluating ES within decision-making frameworks remain limited. Current environmental assessments, such as ecological risk assessment (ERA), typically focus on risks to specific endpoints such as survival, growth and reproduction of test species without capturing broader ecosystem risks and benefits. This study introduces a novel method designed to quantitatively assess risks and benefits to ES supply by integrating ES as assessment endpoints within ERA. Using cumulative distribution functions, we establish risk and benefit thresholds and calculate the probability and magnitude of exceeding these following human interventions. The method was tested by quantifying risk and benefit metrics for a regulating ES, waste remediation, in three marine offshore case studies: an existing offshore wind farm, a hypothetical mussel longline culture, and a multi-use scenario combining both. The results enabled detailed comparisons of the probability and magnitude of creating risks and providing benefits across scenarios, demonstrating the utility of cumulative distribution functions for both visualizing and quantifying risks and benefits to ES supply. This generic and broadly applicable method can evaluate ES trade-offs regardless of the ecosystem under study, providing a valuable tool to operationalize the integration of ES into decision-making and environmental management frameworks.
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RBINS Staff Publications 2025
