Climate change is accelerating and is already affecting marine ecosystems and their services. Coupled climate models and ocean observations indicate that the world’s oceans are warming and patterns in atmospheric variability are changing, resulting in changes in oceanic stratification, circulation patterns, sea ice and light supply to the surface ocean.

Biological responses to these effects are visible but uncertain. Primary production is currently expected to increase globally but with large geographical differences. Ocean warming and changes in currents are expected to continue causing distributional and phenological changes in plankton communities. However, our understanding of how these climate-driven ecosystem processes translate into production changes in fish populations and other higher trophic levels is poorly understood and largely un-quantified (see IPCC 2007).

We know that climate variability and change affects fish growth and habitats, large scale migration and distribution patterns, and synchronically impacts resources over large regions. Work conducted largely under the umbrella of the GLOBEC programme has demonstrated how climate variability and change drives abundance fluctuations of fish populations at all scales and latitudes, with particularly clear fluctuation patterns linked to warm and cold climate periods over decadal, multi-decadal and multi-centennial scales. Particularly evident are biological responses to reversals in climate indices, such as Pacific tuna in response to El Niño/ La Niña or Sub-Arctic cod stocks in response to the North Atlantic Oscillation, among others.

Despite this volume of work the quantification of direct climate impacts on the production of fish resources at the global scale, and the risks and vulnerabilities of these impacts is hampered by:
a) difficulties of downscaling Global Climate Models to the scales of biological relevance,
b) lack of adequate global ecosystem models capable of capturing biological processes up to fish populations at the right scale and resolution,
c) uncertainties over future global aquatic net primary production (NPP), and the transfer of this production through the food chain and,
d) inadequate methodology to estimate human vulnerabilities to these changes at all scales.

In addition, fish populations are affected by multiple additional stressors related to exploitation practices: fishing has negative effects on biodiversity , habitat and population sustainability, and is considered to affect the sensitivity of fish populations to climate variability and change. Differential geographical and temporal exploitation patterns and policies further difficult the development of predictive models.

The main objective of QUEST-Fish is to elucidate how climate change will affect the potential production for global fisheries resources in the future and to estimate the added vulnerability of these effects on national and regional economies in fishery-dependent areas and on specific elements of the fishery system at different scales”.

The project will be anchored on outputs from the QUEST Earth Systems Model currently under development and from coupled physical/biological ecosystem dynamic models (Global Coastal Ocean Modelling (GCOMS, see Module 1). The second step will involve the use of production algorithms to scale potential fish production according to three hypotheses of increased complexity regarding the relationships between primary production, fish catches, population size structure and predator/prey ratios, largely based on ecosystem metabolic theory (see Module 2). The third step involves using outputs of Module 1 into a spatially defined global fishmeal model which captures 30% of global fish catches, to investigate climate-driven market instabilities, with specific interest in the Scottish aquaculture farming industry as a case study (Module 3). Finally, future vulnerabilities of national economies (and globally) to the consequences of predicted fish and fishmeal production scenarios will be estimated, including other drivers on fisheries, such as fuel dependency and cost and population growth (Module 4).