Shelf and coastal seas provide vital services for society, notably food, from fish, and climate regulation, through their role in drawing down and storing atmospheric CO2. The ecosystems of these seas are vulnerable to global climate change, arising from greenhouse gas emissions. Being able to provide reliable future projections of the impacts of climate change on these regions is therefore vital for our knowledge of how these services may be impacted.
The overall aim of ReCICLE is to identify and quantify the potential future response to climate change of the simple plant life (phytoplankton) forming the base of the food chain of the shelf sea ecosystems and to assess the likely range of this response using a state of the art coupled hydrodynamic-ecosystem model at an exceptionally fine resolution. This is driven by the output of global climate models, which along with aspects of the ecosystem model structure, are selected so as to span the potential response of the system to climate change, and provide a range of views of the future. Statistical methods are then used to characterise this response in terms of timeseries and changes in areas of similar properties (the biogeography), how clearly the climate signal can be detected and how this signal propagates through the food web.
The project will focus on five key indicators of ecosystem response on the Northwest European Continental shelf: primary production, oxygen uptake, nutrient transport, uptake and recycling, biological control, and the habitat of the water column.
We will address these issues with a tightly integrated programme of model experiment design, simulation, evaluation and analysis, organised in four work packages: Experiment design and uncertainty, Model validation using observational analysis, Analysis of ecosystem response, Model products.
ReCICLE will produce an unprecedented view of potential climate impacts on marine ecosystems, including the effects of fine-scale physical processes, non-linear ecosystem interactions and an assessment of the range of likely impacts. This information will be condensed into a set of model products that are readily accessible by scientists of other disciplines and wider stakeholders.
This project has been completed
Project start date: April 2015
Project end date: October 2019
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Dr Susan Kay, Dr Yuri Artioli