Predicting the effects of pollutants on river ecosystems •

It is usually not possible to test the impacts of different types of pollutants on biological populations in river systems because these substances can damage the entire ecosystem. Instead, the effects of insecticides, plastic debris, pathogens, chemicals and other toxic substances are tested on individual species under controlled laboratory conditions.

Although this approach helps to identify which species are more or less sensitive to which pollutants, it takes into account population effects or the physical and hydrological characteristics of river systems, in which water moves continuously in one direction and carries materials with it.

In a recent study, however, Peng Zhou (Shanghai Normal University) and Qihua Huang (Southwest University, Chongqing) developed a model that describes interactions between a population and a toxicant in a system characterized by fluid moving in one direction. This model replicates the conditions found in a flowing river and will be useful for scientists wishing to predict how the movement of a pollutant through a river will affect the health and distribution of river dwellers.

When formulating environmental policies aimed at limiting the effects of river pollution, it is important for scientists to understand the impact of a toxic substance on the health of the entire natural community exposed to the substance over a long period of time. term. This cannot be fully assessed using controlled laboratory tests, but mathematical modeling can help simulate river conditions. “Mathematical models play a crucial role in translating individual responses to population-level impacts,” Huang said.

Unfortunately, many existing models that simulate the potential effects of toxic substances on population dynamics often ignore the critical properties of water masses.

“In reality, many hydrological and physical characteristics of water bodies can have a substantial impact on the concentration and distribution of a toxicant,” Huang said. “For example, once a toxicant is released into a river, several dispersal mechanisms – such as diffusion and transport – are present and can contribute to the spread of the toxicant.”

Some models take into account the movement of pollutants in a river using reaction-advection-diffusion equations. These models can show how pollutants distribute under different hydrological influences, such as changes in water flow, and allow researchers to predict concentrations of toxic substances and their impacts on the environment. However, these mathematical models do not take into account the influence of toxins on the dynamics of affected populations.

Zhou and Huang therefore developed this type of model by adding new elements that allowed them to explore the interaction between a toxin and a biological population in a polluted river. Details of their model were published today in the SIAM Journal of Applied Mathematics.

The researchers’ model consists of of them reaction-diffusion-advection equations – one that governs population growth and dispersal under the influence of the toxicant, and another that describes the processes that the toxicant undergoes. “As far as we know, our model represents the first effort to model population-toxicant interactions in an advection environment using reaction-diffusion-advection equations,” Zhou said. “This new model could potentially open up a [novel] search line. »

This arrangement allows researchers to test different scenarios and adjust parameters to see what potential impacts it has on the environment or population of organisms. For example, they tried to change the river flow velocity and advection rate – the rate at which the toxicant or organisms are transported downstream – and observed the effects of these changes on survival and the distribution of the toxicant and the biological population.

One scenario involved a toxicant that had a much slower rate of advection than the population and therefore was not swept away as easily. The model showed that, intuitively, population density decreases with increasing water flow as more individuals are transported downstream and out of the river area in question. However, the concentration of the toxicant increases with increasing flow velocity because it can resist the downstream current and organisms are often swept away before they are affected by it.

Otherwise, the toxicant has a faster rate of advection and is therefore much more sensitive to water flow velocity than population. Then increase the water flow reduced the concentration of toxic substances by sweeping the pollutants. For an average flow velocity, the highest population density occurs downstream because the water flow plays an exchange role; it transports more toxic substances but also transports more individuals downstream.

“In the absence of toxic substances, it is generally known that the higher the flow velocity, the more individuals will be swept away by the river,” Zhou said. “However, our results suggest that, for a given level of toxin, population abundance may to augment as the flow increases.

By using different parameters for certain species and various pollutants, the model can help identify important criteria for the protection and maintenance of aquatic life in the face of pollution. This could ultimately help in the development of policy guidelines regarding target species and toxic substances. “The results here provide the basis for effective decision-making tools for water and environmental managers,” Huang said.

Further modifications of Zhou and Huang’s new model could make it even more applicable to real river ecosystems, for example, by allowing flow velocity and the release of toxic substances to vary over time, or by taking into account of the different ways in which distinct species may react to the same pollutant. This mathematical model can thus help scientists to more accurately assess the risk of a specific pollutant for the populations present in the biological communities inhabiting a river.

By Alison Bosman, Personal editor