Introduction
Sustainable development is traditionally viewed in relation to three fundamental pillars that represent the social, economic and environmental domains.
This approach has been criticised for failing to acknowledge the intricate and interconnected interactions between the pillars and the dynamic nature of the systems in which they function. Instead, silos are reinforced and governance fragmented(1), leading to failure to address complex challenges(2). To manage natural resources in a more sustainable way a systems-based approach is now needed to identify and capitalise on synergies that may exist between sectors, while minimising or even avoiding trade-offs that result in negative consequences(3).
The long-term overexploitation of marine fish stocks(4) has rendered them poorly able to buffer, adapt and recover from additional stressors and shocks (e.g. policy, economic, climate). Consequently, the fisheries and fishing communities the fish populations support are also imperilled and lack long-term resilience. Acknowledging that fisheries are social-ecological systems(5) in which the fish stocks themselves form the foundations on which economic prosperity and wellbeing of fishing communities depends, future management should adopt a systems dynamics-based approach to enhance sustainability and resilience.
Research Aim and Questions
Focusing on marine fisheries, this interdisciplinary project will use AI to investigate how fishing communities responds to a series of shocks so that lessons may be learnt on how resilience of the resource and the people it supports may be reinforced.
Creating a conceptual systems dynamics model of case-study marine fisheries using causal loop and stocks and flows diagrams and where appropriate build a systems model to test assumptions.
Investigating and quantifying fishing activity over time-scales that cover the period of the shock. AI will be used to enhance the efficiency of interrogating large data-sets available, such as that provided by employing: (a) Automated Identification Systems (AIS) that track fishing vessel activity; (b) geospatial remote sensing satellite data of fishing vessel abundance (e.g. operating in less developed regions of the world where AIS data is unavailable); and social media data for inference when direct evidence is unavailable and difficult to obtain (e.g. for very small vessels or recreational boats).
Exploring shifts in catch from available data on landings for specific species and vessel types.
Obtaining information related to the status of specific fish stocks.
Correlating measures of activity and catch / stock status with metrics that document the consequences of shocks.
The study will help improve understanding of how those dependent on marine fisheries to supply food, respond and adapt in the face of systemic shocks, enabling complex feedback loops to be evaluated and trade-offs, synergies and unintended consequences to be identified. Lessons will be learned on how to enhance the resilience of primary resources and the communities that depend on them in the face of ongoing existential threats, such as climate change.
References:
[1] Bogers, M., Biermann, F., Kalfagianni, A., Kim, R. E., Treep, J. and Vos, M. G.. 2022. The impact of the Sustainable Development Goals on a network of 276 international organizations. Global Environmental Change 76, DOI: 10.1016/j.gloenvcha.2022.102567.
[2] UN 2023. Halfway to 2030, world ‘nowhere near’ reaching Global Goals, UN warns https://news.un.org/en/story/2023/07/1138777
[3] Kemp, P. S., Acuto, M., Larcom, S., Lumbroso, D. and Owen, M. 2022. Exorcising Malthusian ghosts: Vaccinating the nexus to advance integrated water, energy and food resource resilience. Current Research in Environmental Sustainability, 4, [100108]. DOI:10.1016/j.crsust.2021.100108).
[4] Thurstan, R., Brockington, S. & Roberts, C. The effects of 118 years of industrial fishing on UK bottom trawl fisheries. Nat Commun 1, 15 (2010). https://doi.org/10.1038/ncomms1013
[5] Ostrom, E. 2009. A general framework for analyzing sustainability of social-ecological systems. Science 325, 5939, 419-422. DOI: 10.1126/science.1172133