Considering that it takes hundreds of years for forests to grow, it can be difficult to assess how they'll be affected by climate change in the long term. To address that problem, researchers at Washington State University have created the world's first computer simulation capable of growing realistic forests, using the model to predict how things like frequent wildfires or drought might impact forests across North America.
The new computer simulation allows scientists to grow a virtual forest over the period of a few weeks. Known as LES (after the Russian word for forest), the system simulates the growth of 100 x 100 m (330 x 330 ft) areas of vegetation, that are then scaled up to simulate entire forests. It's more complex than any previous systems, simulating both canopy structures and intricate root systems for each tree. Each leaf competes for sunlight, while beneath the virtual earth, the organisms' roots compete for water resources.
In order to ensure that the model accurately represents real-life forests, the researchers turned to the US Department of Agriculture's Forest Inventory and Analysis program, as well as other forestry databases. They also worked with the US Forest Service to fly drones over and around forests, imaging them to gather further information and develop 3D models, allowing for more accurate vegetation and tree distribution.
The team believes that LES could greatly improve our understanding of exactly how climate change is effecting forests, and how those changes will evolve over time. The researchers hope that the system will allow forest managers to determine the species of trees, as well as ecological factors, that are central to forests re-establishing themselves are being disturbed by events such as wildfires.
"The fear is that drier conditions in the future will prevent forests in places like Washington from re-establishing themselves after a clear-cut or wildfire," said Washington State University's Nikolay Strigul. "This could lead to increasing amounts of once-forested areas converted to desert. Our model can help predict if forests are at risk of desertification or other climate change-related processes and identift what can be done to conserve these systems."
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