Advanced Research Fellow
- Email Address
- neda.trifonova@abdn.ac.uk
- Office Address
School of Biological Sciences
Zoology Building, Rm 416
Tillydrone Avenue
Aberdeen
AB24 2TZ
- School/Department
- School of Biological Sciences
Biography
Neda's research interests include ecosystem modelling; the application of machine learning techniques, such as Bayesian networks, to investigate environmental aspects of offshore renewable energy and climate change. Neda also has interest in natural capital approaches, cumulative and environmental assessments, and evaluation tools for the delivery of environmental net gain and socio-economic benefits.
Qualifications
- PhD Computer Science2016 - Brunel University
Latest Publications
Fishing, Offshore Wind Energy, Climate Change and Marine Spatial Planning: Is it possible to plan for a best use of space?
Watson, S., Szostek, C., Beaumont, N., Scott, B., Declerck, M., Trifonova, N.Ecological Solutions and EvidenceContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1002/2688-8319.70039
A paradigm for understanding whole ecosystem effects of offshore wind farms in shelf seas
Isaksson, N., Scott, B., Hunt, G., Benninghaus, E., Declerck, M. M., Gormley, K., Harris, C., Sjostrand, S., Trifonova, N., Waggitt, J. J., Wihsgott, J., Williams,, C. A., Zampollo, A., Williamson, B.ICES Journal of Marine Science, vol. 82, no. 3, fsad194Contributions to Journals: ArticlesSpatial conflict in offshore wind farms: Challenges and solutions for the commercial fishing industry
Szostek, C., Watson, S., Trifonova, N., Beaumont, N., Scott, B.Energy Policy, vol. 200, 114555Contributions to Journals: ArticlesMachine Learning Applications for Fisheries: At Scales from Genomics to Ecosystems
Kühn, B., Cayetano, A., Fincham, J. I., Moustahfid, H., Sokolova, M., Trifonova, N., Watson, J. T., Fernandes-Salvador, j. A., Uusitalo, L.Reviews in Fisheries Science and AquacultureContributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1080/23308249.2024.2423189
Ecosystem indicators: Predicting population responses to combined climate and anthropogenic changes in shallow seas
Trifonova, N., Scott, B.Ecography, vol. 2024, no. 3, e06925Contributions to Journals: Articles
Prizes and Awards
- Scottish Universities Life Sciences Alliance (SULSA) Early Career Reseacher (ECR) Prize for the Ecosystems Theme
- British Ecological Society/NatureScot Policy Fellowship 2021-2022
Research Areas
Biological and Environmental Sciences
Computing Science
Current Research
ECOFlow/ Establishing a Framework for Quantifiable Evidence and Impact of Ecosystem Change Throughout the Lifecycle of UK Floating Offshore Wind Farms (EQUIFy) (2025-28, NERC/The Crown Estate).EQUIFy will use an array of modelling approaches, autonomous monitoring systems and decision support tools to provide a transferable evidence framework that improves current understanding of the likely future effects of FLOW, with a focus on planned developments in the Celtic Sea. I am a Co-Investigator in Work Package 5 that brings together a range of physical and biological observations and modelling outputs with established decision support tools tailored to enhance the capabilities of planners, spatial managers and industry, to access evidence guiding sustainable development of FLOW.
ECOWind/ Physics-to-Ecosystem Level Assessment of Impacts of Offshore Windfarms (PELAgIO) (2022-25, NERC/The Crown Estate). PELAgIO will support the development of evidence-based policy and marine management through interdisciplinary research that explores the consequences of offshore wind development on marine ecosystems. By observing and modelling over a large range of physical and biological scales, using a combination of autonomous platforms and ocean robots, research vessels and satellite observations, PELAgIO will build an ecosystem-level understanding of projected changes.
The Marine Energy, Biodiversity and Food Nexus (EcoNex) (2022-24, UKERC). This project will work with renewable industry and policy bodies to enable evidence-based, informed actions to improve decision making when balancing environmental, social, and economic impacts and ensuring marine net gain, as part of national policy assessments.
Supergen Offshore Renewable Energy (ORE) Hub (2019-2022 EPSRC). The aim of the project is to bring together and stimulate synergistic adventurous research that supports and accelerates the development of offshore wind, wave and tidal technologies for society’s benefit. Neda will be using machine learning techniques such as Bayesian networks to investigate the effect of offshore renewable energy and climate change on the North Sea marine system. She also will be looking at developing evaluation tools to enable the exploration of trade-offs in a range of currencies for net gain, such that objective judgements can be made as to how to best maximise the environmental and social co-benefits, while delivering net zero.
Past Research
- National Oceanic and Atmospheric Administration’s Integrated Ecosystem Assessment Programme for the Gulf of Mexico (2017-2019). Development of quantitative and qualitative Bayesian network models for the better understanding of population dynamics within different ecosystems.
- PhD in Computer Science from Brunel University, 2016. Development of dynamic Bayesian networks to investigate fish population dynamics throughout space and time within the North Sea and understand their interactions with fisheries and climate. The PhD was conducted in collaboration with the Centre for Environment Fisheries Aquaculture Science (UK) and the Maurice Lamontagne Institute, part of a network of Fisheries and Oceans (DFO), Canada in Mont-Joli, Quebec.
Supervision
- Morgane Declerck, PhD Candidate (2019-2023). Project title: “Sustainable Marine Ecosystems and Offshore Energy: A Bayesian modelling approach”. DEFRA BEIS Hartley Anderson Ltd
- Ella-Sophia Benninghaus, PhD Candidate (2020-2023). Project title: “Climate Change and Predator-prey Populations”. SUPER-DTP
- Alan Anderson, PhD Candidate (2024-2027). Project title: "Using machine learning approaches to predict and understand consequences of extreme events". ORE Supergen Hub Phase 2
Supervisees
- MS ELLA-SOPHIA BENNINGHAUS
- MR ALAN ANDERSON
Funding and Grants
- Scottish Alliance for Geoscience, Environment and Society (SAGES) Postdoctoral and Early Career Researcher Exchange (PECRE) Award (PI)
- Scottish Universities Life Sciences Alliance (SULSA) Early Career Researcher (ECR) Prize Winner 2020 Ecosystems Theme (PI)
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Network approaches for formalizing conceptual models in ecosystem-based management
Reum, J. C. P., Kelble, C. R., Harvey, C. J., Wildermuth, R. P., Trifonova, N., Lucey, S. M., McDonald, P. S., Townsend, H.ICES Journal of Marine Science, vol. 78, no. 10, pp. 3674-3686Contributions to Journals: ArticlesSatellite data for the offshore renewable energy sector: synergies and innovation opportunities
Medina-Lopez, E., McMillan, D., Lazic, J., Hart, E., Zen, S., Angeloudis, A., Bannon, E., Browell, J., Dorling, S., Dorrell, R. M., Forster, R., Old, C., Payne, G. S., Porter, G., Rabaneda, A. S., Sellar, B., Tapoglou, E., Trifonova, N., Woodhouse, I. H., Zampollo, A.Remote Sensing of Environment, vol. 264, 112588Contributions to Journals: ArticlesBayesian Network Modelling provides Spatial and Temporal Understanding of Ecosystem Dynamics within Shallow Shelf Seas
Trifonova, N., Scott, B., Dominicis, M. D., Waggitt, J. J., Wolf, J.Ecological Indicators, vol. 129, 107997Contributions to Journals: ArticlesA new strategic framework to structure cumulative impact assessment (CIA)
Declerck, M., Trifonova, N., Black, J., Hartley, J., Scott, B. E.Contributions to Journals: Conference ArticlesPredicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model
Trifonova, N., Karnauskas, M., Kelble, C.PloS ONE, vol. 14, no. 1, e0209257Contributions to Journals: ArticlesHidden variables in a Dynamic Bayesian Network identify ecosystem level change
Uusitalo, L., Tomczak, M. T., Mueller Karulis, B., Putnis, I., Trifonova, N., Tucker, A.Ecological Informatics, vol. 45, pp. 9-15Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.ecoinf.2018.03.003
Predicting ecosystem responses to changes in fisheries catch, temperature, and primary productivity with a dynamic Bayesian network model
Trifonova, N., Maxwell, D., Pinnegar, J., Kenny, A., Tucker, A.ICES Journal of Marine Science, vol. 74, no. 5, pp. 1334-1343Contributions to Journals: Articles2017 Ecosystem status report update for the Gulf of Mexico
Karnauskas, M., Kelble, C., Regan, S., Quenée, C., Allee, R., Jepson, M., Freitag, A., Craig, K., Carollo, C., Trifonova, N., Barbero, L., Hanisko, D., Zapfe, G.National Oceanic and Atmospheric Administration. 51 pagesBooks and Reports: Commissioned ReportsSpatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology
Trifonova, N., Kenny, A., Maxwell, D., Duplisea, D., Fernandes, J., Tucker, A.Ecological Informatics, vol. 30, pp. 142-158Contributions to Journals: ArticlesA spatio-temporal Bayesian network approach for revealing functional ecological networks in fisheries
Trifonova, N., Duplisea, D., Kenny, A., Tucker, A.Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1007/978-3-319-12571-8_26
