Supplementary report to the final report of the coral reef expert group: S6. Novel technologies in coral reef monitoring

[Extract] This report summarises a review of current technological advances applicable to coral reef monitoring, with a focus on the Great Barrier Reef Marine Park (the Marine Park). The potential of novel technologies to support coral reef monitoring within the Reef 2050 Integrated Monitoring and Reporting Program (RIMReP) framework was evaluated based on their performance, operational maturity and compatibility with traditional methods. Given the complexity of this evaluation, this exercise was systematically structured to address the capabilities of technologies in terms of spatial scales and ecological indicators, using a ranking system to classify expert recommendations.An accessible copy of this report is not yet available from this repository, please contact [email protected] for more information

Artificial intelligence and automated monitoring for assisting conservation of marine ecosystems: A perspective

Conservation of marine ecosystems has been highlighted as a priority to ensure a sustainable future. Effective management requires data collection over large spatio-temporal scales, readily accessible and integrated information from monitoring, and tools to support decision-making. However, there are many roadblocks to achieving adequate and timely information on both the effectiveness, and long-term success of conservation efforts, including limited funding, inadequate sampling, and data processing bottlenecks. These factors can result in ineffective, or even detrimental, management decisions in already impacted ecosystems. An automated approach facilitated by artificial intelligence (AI) provides conservation managers with a toolkit that can help alleviate a number of these issues by reducing the monitoring bottlenecks and long-term costs of monitoring. Automating the collection, transfer, and processing of data provides managers access to greater information, thereby facilitating timely and effective management. Incorporating automation and big data availability into a decision support system with a user-friendly interface also enables effective adaptive management. We summarise the current state of artificial intelligence and automation techniques used in marine science and use examples in other disciplines to identify existing and potentially transferable methods that can enable automated monitoring and improve predictive modelling capabilities to support decision making. We also discuss emerging technologies that are likely to be useful as research in computer science and associated technologies continues to develop and become more accessible. Our perspective highlights the potential of AI and big data analytics for supporting decision-making, but also points to important knowledge gaps in multiple areas of the automation processes. These current challenges should be prioritised in conservation research to move toward implementing AI and automation in conservation management for a more informed understanding of impacted ecosystems to result in successful outcomes for conservation managers. We conclude that the current research and emphasis on automated and AI assisted tools in several scientific disciplines may mean the future of monitoring and management in marine science is facilitated and improved by the implementation of automation

Magnetic and structural-properties of electrodeposited Co1-xPx amorphous ribbons

The specific magnetic moment, coercive force, anisotropy field, and saturation magnetostriction constant have been measured in Co(1-x)P(x) amorphous ribbons with 0.04 less-than-or-equal-to x less-than-or-equal-to 0.27. Differential scanning calorimetry, x-ray diffraction, and transmission electron microscopy analysis have been made in order to study the transition from the amorphous state to the crystalline one. Results suggest that transition takes place when x decreases from 0.19

Implementation of synthetic fast-ion loss detector and imaging heavy ion beam probe diagnostics in the 3D hybrid kinetic-MHD code MEGA

A synthetic fast-ion loss (FIL) detector and an imaging Heavy Ion Beam Probe (i-HIBP) have been implemented in the 3D hybrid kinetic-magnetohydrodynamic code MEGA. First synthetic measurements from these two diagnostics have been obtained for neutral beam injection-driven Alfvén Eigenmode (AE) simulated with MEGA. The synthetic FILs show a strong correlation with the AE amplitude. This correlation is observed in the phase-space, represented in coordinates (P, E), being toroidal canonical momentum and energy, respectively. FILs and the energy exchange diagrams of the confined population are connected with lines of constant E, a linear combination of E and P. First i-HIBP synthetic signals also have been computed for the simulated AE, showing displacements in the strike line of the order of ∼1 mm, above the expected resolution in the i-HIBP scintillator of ∼100 μm.This work received funding from the European Starting Grant (ERC) from project 3D-FIREFLUC and from the Spanish Ministry of Science under Grant No. FPU19/02267. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 and 2019-2020 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission

Substrate stabilisation and small structures in coral restoration: State of knowledge, and considerations for management and implementation.

Coral reef ecosystems are under increasing pressure from local and regional stressors and a changing climate. Current management focuses on reducing stressors to allow for natural recovery, but in many areas where coral reefs are damaged, natural recovery can be restricted, delayed or interrupted because of unstable, unconsolidated coral fragments, or rubble. Rubble fields are a natural component of coral reefs, but repeated or high-magnitude disturbances can prevent natural cementation and consolidation processes, so that coral recruits fail to survive. A suite of interventions have been used to target this issue globally, such as using mesh to stabilise rubble, removing the rubble to reveal hard substrate and deploying rocks or other hard substrates over the rubble to facilitate recruit survival. Small, modular structures can be used at multiple scales, with or without attached coral fragments, to create structural complexity and settlement surfaces. However, these can introduce foreign materials to the reef, and a limited understanding of natural recovery processes exists for the potential of this type of active intervention to successfully restore local coral reef structure. This review synthesises available knowledge about the ecological role of coral rubble, natural coral recolonisation and recovery rates and the potential benefits and risks associated with active interventions in this rapidly evolving field. Fundamental knowledge gaps include baseline levels of rubble, the structural complexity of reef habitats in space and time, natural rubble consolidation processes and the risks associated with each intervention method. Any restoration intervention needs to be underpinned by risk assessment, and the decision to repair rubble fields must arise from an understanding of when and where unconsolidated substrate and lack of structure impair natural reef recovery and ecological function. Monitoring is necessary to ascertain the success or failure of the intervention and impacts of potential risks, but there is a strong need to specify desired outcomes, the spatial and temporal context and indicators to be measured. With a focus on the Great Barrier Reef, we synthesise the techniques, successes and failures associated with rubble stabilisation and the use of small structures, review monitoring methods and indicators, and provide recommendations to ensure that we learn from past projects