Plant ‘rulebook’ can improve forecasts of environmental changes12 May 2020
Predictions of how future landscapes will look can be made more accurate by taking an evolutionary perspective on how plants and trees interact with one another and their environments, new research has shown.
An International team of scientists showed for the first time how three basic principles of plant evolution could be used to produce projections far more reliable than those of far more detailed models.
The study, published today in Nature Plants, provides a simpler method of forecasting future changes to plants and forests as a result of environmental pressures like climate change.
"We will have to make big decisions to combat climate change in the future so it is important the forecasts we base them on are sound" - Professor Sandy Harrison, University of Reading
This is important in helping to understand the impacts on the role of plants in supporting life on Earth, for example through the provision of food and ability to remove carbon dioxide from the atmosphere.
Professor Sandy Harrison, co-author and environmental scientist at the University of Reading, said: “Current models are very complex, and generally assume that different plant types all behave the differently. Future changes are then forecast using natural processes that are often poorly understood.
“In this study, we make the case that there are simple rules governing plant behaviour and that understanding these and incorporating this rulebook' into models could help us construct much more reliable forecasts.
“The IPCC has stated that plant behaviour is a big source of uncertainty in how we plan for global warming. We will have to make big decisions to combat climate change in the future so it is important the forecasts we base them on are sound.”
The new study, led by the International Institute for Applied Systems Analysis (IIASA) in Austria, combines the principles of natural selection, how plants interact with one another in ecosystems, and how they behave collectively in their environments.
These principles have all been used to predict how plants will be affected by the environment, and vice versa, but never altogether.
Previous attempts to improve future projections have involved adding more and more detail on plant processes, such as their water consumption and carbon production, to models. However, each of these processes comes with a degree of uncertainty, resulting in a forecast with a wide range of possibilities.
The team show this problem can be reduced by cutting down on detail, and instead representing the general patterns of natural selection and plant behaviour, in both the short and long term, to predict complex changes in future environments.
Oskar Franklin, lead author and a researcher in the IIASA Ecosystems Services and Management Program, said: “Despite the ever-increasing availability of data, and the fact that vegetation science, like many other scientific fields, is benefitting from increasing access to big data sets and new observation technologies, we also need to understand governing principles like evolution to make sense of the big data.
“Current models are not able to reliably predict long-term vegetation responses.”
Franklin, O., Harrison, S., Dewar, R., Farrior, C., Brännström, A., Dieckmann, U., Pietsch, S., Falster, D., et al. (2020); ‘Organizing principles for vegetation dynamics’; Nature Plants; DOI: 10.1038/s41477-020-0655-x