How tree DNA can help predict forest survival

Forests aren’t just big stretches of trees. They’re ecosystems full of life – each species playing its own role, whether it’s helping the soil breathe, feeding animals, or giving shade to new seedlings.

But what happens when one of those species starts to disappear? Or when a once-abundant tree suddenly becomes rare? Untangling those questions has always been a challenge.

Now, scientists have taken a big step forward. Using a mix of tree census records and genetic data, a new model can actually predict how the populations of different tree species in a forest will rise or fall over time.

That kind of foresight could help forest managers, conservationists, and communities make better decisions as climate change, pests, and development continue to put pressure on ecosystems.

Losing one species can hurt a forest

When a tree species becomes rare – or disappears entirely – the ripple effects go beyond just fewer leaves in the canopy. It can throw the whole ecosystem off balance.

“This work is crucial because changes in abundance or loss of a species from a forest can have cascading effects on other species,” said James O’Dwyer, a plant biologist at the University of Illinois Urbana-Champaign who helped lead the research.

Forests with fewer types of trees are also easier targets for diseases and pests. And when you lose variety, you often lose strength.

“Species diversity is lower in forests of the western United States than in other parts of the U.S., but most species have unique roles in the forest,” said James Lutz, a forest ecologist who’s been tracking one forest in southern Washington state since 2010.

“Losing one species, when there are few to begin with, could result in a less productive forest and potentially one that doesn’t support as many small plants or animals.”

Forests are constantly changing

Trying to predict how forest species will shift over time is tricky. Forests aren’t static. Trees grow at different speeds. They live and die at different rates.

“In a forest, there are constantly varying environmental conditions, as well as different tree neighborhoods, with species competing for resources like sunlight and water,” Lutz said.

“Neighboring trees influence each other while living and after death, as snags and wood, all amidst variation in rain and soil conditions.”

To sort through this complexity, researchers usually need decades of detailed data. Some long-term studies have been underway for years, including those coordinated by the Smithsonian Forest Global Earth Observatory. One of the sites is the Wind River Forest Dynamics Plot in Washington.

Life histories predict forest diversity

A few years ago, researchers created a model that used tree “life histories” – basically how fast a species grows, reproduces, and dies – to estimate how likely it was for two or more species to keep coexisting.

From that information, the experts calculated something called the “effective population size,” which helped estimate a species’ long-term survival odds.

“The upshot of that study is that we identified certain combinations of life histories across plant communities that act to maintain diversity over longer timescales, while other combinations would lead to lower diversity,”  O’Dwyer said.

Later, the researchers applied the same method to a tropical forest in Panama. It worked well, but there was one problem: it required decades of observation. That’s not practical for every forest.

The team tried something different. Instead of waiting for decades of data to come in, they collected genomic data from eight common tree species in the Wind River forest. These eight species make up around 90% of the tree stems and most of the forest’s biomass.

The team analyzed DNA from about 100 trees per species, searching for genetic clues about the history and future of each species.

Tree DNA and forest survival

“Effective population size is a fundamental concept in evolutionary biology, first described almost 100 years ago,” said Andy Jones, a professor of botany and plant pathology at Oregon State University.

“Although the true nature of the factors that ultimately determine effective population size is complex, it is perhaps easiest to think of it as the number of individuals that contribute offspring, and therefore their genes, to the next generation.”

In a forest, not all trees reproduce equally. Some leave behind lots of offspring, while others leave none. That uneven success leaves a mark on the genes of future generations. The researchers looked for patterns in the DNA that showed which trees were doing most of the reproducing.

“That balance between random and nonrandom associations in the genome is closely related to effective population size,” O’Dwyer said.

“Those life history traits are in the background, shaping that genomic data. I would say the genome is like a hidden recording device of the history of that species in that forest.”

A model with real predictive power

The team used their genomic findings along with data from the 2011 tree census to train their new model. They tested it to see how well it could predict changes in tree populations in 2016 and 2021.

The results showed that the model outperformed others, accurately tracking how the numbers shifted over time.

“The predictions were highly correlated with the observed fluctuations in abundance,” O’Dwyer said. “That’s very exciting.”

The model shows that DNA holds more information than previously thought – enough to give real insight into how forest communities might change in the near future.

“My sense is that the population genomic variation that we’re looking at is an underused resource,” O’Dwyer said. “It’s carrying a lot of information about the history of that species.”

Using tree DNA in predictive models

The next challenge is to test this model in other forests – especially ones that haven’t been studied for as long as Wind River. If the model holds up, it could be used as a tool for forest managers trying to plan for the future, even in places where long-term data doesn’t yet exist.

“If we can further distill the relationship between genomic variation, census data and ecological dynamics, this could allow us to build predictive models, with consequences for conservation and management across a broad range of ecosystems,” O’Dwyer concluded.

The full study was published in the journal Science.

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