The Arctic Ocean is exceptionally susceptible to climate change. Recent studies have shown that surface seawater is warming faster than in other oceans. In addition, atmospheric CO2 dissolution in seawater is causing Ocean Acidification (OA).
The documented retreat of sea-ice will increase light penetration, including UV. These environmental parameters (temperature, OA and UV) are highly likely to act as stressors and alter the Arctic Ocean ecosystem structure and function which in turn will feed back on climate. One such feedback is the cycling of climatically active trace gases and their emission to the atmosphere (here: CH4, N2O, DMS, CO). These trace gases are rapidly produced and consumed by a number of physical and biological processes. For example, the biggest source of CO in surface seawater is via UV-induced photochemical reactions. Yet, the likely response of trace gas cycling to climate change remains largely unexplored. This hinders our ability to predict the future direction of this important climate-feedback. We propose to investigate this feedback by a) developing the basic understanding which will underpin a predictive tool and b) developing the predictive tool itself (computer model). We will achieve this using three complimentary tools:
Firstly, novel, high-tech spatial observations of trace gases (with depth as well as horizontal) which will allow us to identify major controls on their cycles and estimate their present flux to the atmosphere. Secondly, direct experiments where the three stressors will be manipulated while trace gas cycling pathways are monitored. The novelty of our approach here, lies in the use of individual and combined stressor manipulation (e.g. OA alone versus high temperature and OA together). This will allow us to explore potential synergistic or antagonistic effects between stressors. We will use state-of-the-art chemical and biological observations to track changes in trace gas cycling. For example, we will monitor the abundance and activity of key genes involved in trace gas cycling. These experiments will give us explicit and refined understanding of trace gas cycling in relation to the stressors. Thirdly, we will employ computer modelling which will translate this understanding into a predictive tool that will be used to predict the impact of future climate change. Finally, and in order to rapidly translate our relevant findings to policy, we will engage with the public, policymakers, international science programmes and Intergovernmental Panel on Climate Change (IPCC) through our comprehensive impact plan.