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CAS Connect March 2016

New tools for predicting forest, ocean changes

It can take Mother Nature 1,000 years to grow a forest, but Nikolay Strigul, assistant professor of mathematics and statistics at WSU Vancouver, can grow one on a computer in three weeks.

Jean_Lienard-web
Jean Leinard
nik_strigul-web
Nikolay Strigul

He and Jean Lienard, a mathematics postdoctoral researcher, created the first computer simulation that grows realistic forests down to the branches, leaves, and roots of individual trees. They are using the simulation, detailed in a new paper in Royal Society Open Science, to determine how drought, warmer weather, more frequent wildfires, and other climate-related changes will affect forests across North America.

They have already used the computer model to predict increases in fire rates and plant growth in Quebec hardwood forests due to rising CO2 levels and warmer temperatures.

Dan Reed
Daniel Reed
John Harrison
John Harrison

Meanwhile, WSU Vancouver scientists John Harrison and Daniel Reed have developed a first-of-its-kind approach for predicting where coastal “dead” zones are likely to appear around the globe. These low-oxygen zones, which can harm fish, other marine animals, and humans, result from human activities on land as well as oceanic conditions.

More than 400 low-oxygen zones have been documented worldwide, and the number is rising. Some are found in coastal waters off Oregon and Washington. Among other insights, the study suggests that oxygen conditions in Pacific Northwest coastal waters may be particularly sensitive to human activities on land.

Harrison, associate professor in the School of the Environment, and Reed, a research associate, presented their findings this month in Global Biogeochemical Cycles.

Help for maintaining healthy coasts

Dead zones occur when nutrients from agricultural fertilizer use, waste treatment facilities, and other sources end up in coastal waters, stimulating the growth of phytoplankton. As these phytoplankton die and sink toward the sea floor, their decomposition consumes oxygen and creates low-oxygen conditions. These conditions will not occur, however, if enough oxygen mixes down to the sea floor fast enough to counterbalance the processes that consume oxygen.

Dead zone off the coast of La Jolla, San Diego, Calif., USA. Photo: Alejandro Díaz and Ginny Velasquez on Wikipedia
Dead zones are often caused by the decay of algae during algal blooms, like this one off the coast of La Jolla, San Diego, Calif. Wikipedia photo by A. Díaz and G. Velasquez

Reed and Harrison’s new approach accounts for all relevant factors. Importantly, their model also links coastal oxygen concentrations to nutrient inputs from land, making it useful in predicting where low-oxygen regions will form due to changes in population and land-use practices and in estimating how severe the effects of nutrient loading will be.

In addition to its predictions about the Pacific Northwest coast, the model, dubbed COOLBEANS (Coastal Ocean Oxygen Linked to Benthic Exchange and Nutrient Supply), predicts that coastal seas in rapidly developing regions, such as the Bay of Bengal and parts of Southeast Asia, are likely to experience oxygen depletion now or in the near future.

Reed and Harrison have made the COOLBEANS model code and supporting data freely available for download via the Internet for use by scientists and natural resource managers seeking to maintain the health of coastal waters and ecosystems.

Forest model provides intricate detail, adjustable scale

Each colored dot in the picture represents a separate tree in the LES forest simulator. The size and number of dots changes over time to reflect growth and competition for resources in an actual forest.
Each colored dot in the picture represents a separate tree in the LES forest simulator. The size and number of dots changes over time to reflect growth and competition for resources in an actual forest.

The WSU mathematicians call their tree-growing model “LES,” after the Russian word for forest, said Strigul, who grew up in Russia and came to the United States in 2001. “It is a tool that forest managers can use to create 3D representations of their own forests and simulate what will happen to them in the future.”

LES uses recent advances in computing power to grow 100×100-meter stands of drought and shade tolerant trees that can then be scaled up to actual forest size.

The model is unique in several ways. First, it is the only forest-growing simulator that creates intricate root systems and canopy structures for each tree. Previous forest simulators could grow only one or the other.

Below ground, the roots of different trees in LES compete for water resources in each pixel of the model. Above ground, the leaves in each tree’s canopy compete for sunlight in a similar fashion. Over time, the trees’ canopies change shape to expose their leaves to more sunlight.

Real trees are on the right. Trees on the left were made using imaging data collected by aerial drones and the LES forest simulator.
Real trees are on the right. Trees on the left were made using imaging data collected by aerial drones and the LES forest simulator.

The researchers use a combination of data from the U.S. Department of Agriculture’s Forest Inventory and Analysis Program and other forestry databases, as well as aerial reconnaissance from unmanned aerial vehicles, or drones, to customize their model to particular forests. The simulator lets scientists project how changing climate conditions will impact forests over thousands of years.

“In cooperation with the U.S. Forest Service, we developed a method where we fly drones around a forest and take pictures and gather other imaging information,” Lienard said. “We use this data to develop 3D models that have real distributions of space and ecological features.

“Details of our drone work were recently published in PLOS One and Measurement,” he said. “It is a method that can be adapted for practically any forest.”

The effects of a changing climate

For large parts of North America, climate change is leading to more frequent drought, warmer weather and other varying natural conditions. What effect this will have on forests and their ability to recover from dynamic disturbances like wildfires or clear-cutting is difficult to determine.

Scientists know relatively little about the mechanics that drive forest recovery. The process can take several decades to document and involves trees with diverse physiological characteristics competing for resources over large and ecologically varied areas.

Strigul and Lienard plan to use LES to help forest managers determine which species of trees and other ecological factors are necessary for forests to reestablish themselves after being destroyed by wildfires and other disturbances.

“Drive an hour east along the Columbia River from Vancouver and you will notice a complete transition from very dense forests to savanna and then to desert,” Strigul said. “The fear is that drier conditions in the future will prevent forests in places like Washington from reestablishing themselves after a clear-cut or wildfire. 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 identify what can be done to conserve these systems,” he said.

The forest modeling research was partially supported by a grant from the Simons Foundation and a WSU New Faculty SEED grant.

Washington State University