It models plant reactions to different weather events and identifies sustainable levels of change
Spotted: The World Meteorological Organization (WMO) issued a recent warning regarding temporary global temperature increases. Sometime in the next five years between 2023 and 2027, the organisation estimates that for at least a full year, the world’s temperature will rise more than 1.5 degrees Celsius above pre-industrial levels. And the five years in total are likely to be the warmest ever recorded.
The organisation emphasises that the increases are not necessarily permanent, just that they are occurring more frequently. What that means for the environment is unclear, but many agencies, groups, and projects are trying to predict and mitigate potential damage. Scientists at Brazil’s University of Campinas (UNICAMP) created an algorithm that emphasises the diversity of the country’s rainforest plants in its modelling of potential future scenarios.
Called CAETÊ, which stands for Carbon and Ecosystem functional Trait Evaluation model, the algorithm considers different weather events, including rainfall, carbon dioxide levels, and amount of sunshine, and then predicts a range of scenarios for each type of plant and for the rainforest as an entirety. Some plants may grow more or differently, while others are shown to not survive certain changes.
Bianca Fazio Rius, first author of the research article that presents the artificial intelligence (AI), pointed out the surprising discovery that when precipitation drops by 50 per cent, plant strategy diversity increases while the volume of carbon stored in the plants decreases by more than 57 per cent. That knowledge must shape local and global mitigation plans and strategies.
The research team plans to continue developing the algorithm to include more diversity in its analyses, as well as share the platform with international decision-makers and use it to develop a carbon marketplace.
Much of the world’s conservation and restoration efforts lean heavily on technological advancements, with Springwise’s archive including innovations such as Internet of Things (IoT) sensors in forests and 3D-printed reef blocks.
Written By: Keely Khoury