In 2014, I obtained a Fellowship for Young International Scientists of the CAS (Chinese Academy of Sciences) and a Fellowship of the European program Agreenskills, to work at NIGLAS (Nanjing Institute of Geography and Limnology of the Chinese Academy of Science) in Nanjing (China) during 1 year (from the 24th march 2014 to the 24th march 2015) with professor Qin.
Professor Boqiang Qin and other researchers of the Taihu Laboratory for Lake Ecosystem Research (TLLER) of the NIGLAS are interested in the ecosystems of shallow lakes. In particular, they are studying the Lake Taihu, which is the third largest freshwater lake in China, located on the border of Jiangsu and Zhejiang provinces. The Lake Taihu it is the main source of drinking water supply for several millions of people of the Yangtze Delta plain and also provides water for the agriculture. During a long time, the water of the Lake Taihu was known for its high quality and cleanliness. However, due to the fast industrialization and urbanization of the region, the quality of the water is now decreasing tragically. Indeed, the human and industrial nutrient loadings are now so important that the lake doesn’t manage to purify its water any more. The pollution of the Lake causes serious eutrophication problems. In particular, toxic cyanobacterial blooms occur more and more often, which degrades the quality of the water and can be at the origin of water supply problems (as the crisis which occurs in May 2007).
In that context, the study of the evolution of cyanobacterial population is obviously of importance. The objective is first to well understand the dynamics of cyanobacteria, to be then able to predict the blooms and finally control or prevent them. For that, a spatial model of the evolution of cyanobacterial population is needed. This model has to take into account:
- the hydrodynamics of the Lake, that is the fluid dynamics;
- and the biomass evolution, that is the cyanobacteria growth and transport.
The simulation of the hydrodynamics of the Lake Taihu with the open-source code FVCOM has been studied during the first 5 months of my fellowship. The objective is now to develop a sub-model describing the dynamics of microbial biomass in the lake ecosystem and to couple it with the FVCOM model.
The challenges of this research work are multiple and the expected impacts are environmental, economic and societal. Indeed, we expect to get a model sufficiently close to the reality, which can be used for:
- the forecasting of the blooms and the drinking water supply problems (short term): if the model can predict the blooms, even just a few days in advance, it will enable to anticipate the associated problems. The simulation results will be forwarded to administrative departments where the prediction will be evaluated and risk reduction measures will be taken to secure the drinking water supply.
- the identification of blooms origins (short and medium term): the mathematical analysis of the model and the numerical simulations will help us to better understand the dynamics of the blooms and the phenomena which are at the origin of them. If we can identify the causes, the objective will then be to find solutions to act directly on these causes and thus suppress or control the blooms.
- the control and/or prevention of blooms (long term): a better understanding of the dynamics of the blooms will enable us to elaborate strategies to control or prevent the blooms. The model could also be used as a simulator to test different strategies and evaluate their efficiency before applying them on the real Lake.
In the scientific point of view, this work will contribute to the study of the effects of the spatialization and the associated phenomena (transport, diffusion, fluid mechanics, etc.) on the population dynamics in microbial ecosystems. This can have impacts in theoretical ecology but also in agriculture, as for example for the culture of algae for the production of biofuel.
In microbial ecology, according to the competitive exclusion principle, two species competing for a same resource in a homogeneous and stable environment cannot coexist: only the most competitive one stays. The spatial heterogeneity of the environment is one of the possible reasons mentioned by researchers to explain the biodiversity observed in the nature. To verify this hypothesis, we could use the model which will be developed in this project and extend it to the case of two cyanobacteria species.