Climate change: can plankton save the day?
University of Bristol
Among the plethora of organisms living in the ocean, plankton are arguably the most important ones. For starters, they are the foundation of the aquatic food web, feeding everything from microscopic zooplankton, to small fishes and multi-ton whales. These tiny organisms also account for around 50% of all photosynthesis on earth and generate up to half of the oxygen we breath. In other words, they consume carbon dioxide on a scale comparable to forests and other land plants. Their influence on the natural greenhouse effect is considerable, and no one is yet sure how they will respond to the warming prompted by the extra carbon dioxide produced by human activities. “It could go either ways", says Dr. Jamie Wilson, a researcher at the University of Bristol. "Plankton could help alleviate climate change, or on the contrary, exacerbate it. But either way, their impact is likely to be decisive.” Existing observations and current knowledge of how the plankton “biological carbon pump” works, especially in the deep ocean, are scarce. Hence, future projections of carbon sequestration and productivity are subject to large uncertainties. To address this critical gap, the postgraduate researcher is developing an innovative model coupling state-of-the-art modelling of plankton ecosystems and diversity with the full range of known processes driving organic matter cycling in the deep ocean. The objectives are plural: to establish a clearer link between plankton and climate, to provide an assessment of the impact on global fisheries, and to assess the future risks to plankton-driven carbon sequestration in the deep ocean. The project aims at informing governments and policymakers in time for the 6th Assessment report of the Intergovernmental Panel on Climate Change (IPCC) on impacts adaptation and vulnerabilities.
Photosynthesis in plankton, as in plants, is a process that uses solar energy, water and carbon dioxide to produce oxygen, nutrients and organic compounds (matter that contains a large amount of carbon). “The organic matter produced by plankton ecosystems has two fates significant for society", explains Dr. Wilson. The majority enters pelagic food webs, and a small fraction (usually dead plankton) falls to the deep ocean forming a key mechanism of biologically-driven carbon sequestration (long-term storage of atmospheric carbon dioxide). In short, plankton plays a critical role in supporting global fisheries and in reducing the level of CO2 in the atmosphere. Alarmingly, “anthropogenic emissions of CO2, because they impact the ocean temperature, acidification and deoxygenation, are expected to drive significant changes in the biodiversity of plankton ecosystems”, he reports. However, the processes responsible for nutrient cycling and deep-ocean carbon sequestration are so numerous and diverse, that assessing consequences with any level of certainty is a challenging task. What the present project aims to do is to shed light on these processes, including those happening in “the twilight zone”, as scientists call it, with a focus on assessing which are the most important. “Our current understanding of these processes doesn’t allow us to predict what will happen. In fact, the most recent ocean models developed result in completely different outcomes. For instance, the researcher offers: “a recent modelling study including temperature dependent degradation of sinking particles found that the process reversed the trend of organic matter productivity found by the IPCC models”.
An ecosystem model to go beyond the latest IPCC models
To reduce the level of uncertainty in our understanding, Dr. Wilson aims at developing a more comprehensive modelling approach, one that couples a detailed plankton ecosystem model with the full range of processes affecting organic matter cycling. “Up until about 10 years ago, the data we had looked like nothing exciting was happening in the deep ocean, so concurrently, the models we had were simple, explains the lead researcher. But now, we know it isn’t true, there’s a lot more going on in the deep ocean than we initially thought. So, we’re in a middle ground position, where we know we need other models”. The most frequently used models to quantify the impact of environmental change on plankton ecosystems typically take into account the characteristics of only a few types of plankton. An alternative approach is the “trait-based” model, which represent hundreds of potential “taxa”, each with a unique randomised set of characteristics. “They have a much more dynamic representations of plankton diversity, but usually impose large computational costs, which limits the number of experiments they can run”, Dr. Wilson specifies. The project aims to overcome these constraints by using two complimentary models, a newly developed and computationally-efficient trait-based model coupled with a low-resolution Earth system model (EcoGENIE), and a higher-resolution trait-based model coupled with a higher-resolution ocean model (MITgcm). “Using both models will balance the conflicting needs for computational efficiency and high-resolution future projections, he explains. Indeed, we must be able to run a large number of experiments to ensure a comprehensive uncertainty analysis; while also obtaining precise-enough data to make it relevant for stakeholders and policy-makers”.
Recent studies have brought to light the crucial role played by plankton in our planet’s past glaciation events. Concomitantly, their present role in the carbon cycle is likely going to be decisive in how fast our climate changes in the future. However, the current state of our knowledge on the processes involved in this phenomenon is largely insufficient to predict what lies ahead, let alone to act on it without delay. The findings from projects such as this one will be absolutely decisive in the near future, in the sense that they will provide critical information for researchers focusing on constraining these processes, and stakeholders with crucial information about the risks we currently face.
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