Understanding the link between biodiversity and land-use management

© Cindy Azuero-Pedraza

When she began her PhD studies in Industrial Engineering, Azuero-Pedraza researched bioenergy as a means for climate change mitigation. Bioenergy is a form of renewable energy that comes from biomass, or organic materials such as wood, harvest residues, or waste from our homes. However, she was surprised to learn that burning wood was a form of renewable energy, and started to consider the possible negative impacts of this form of energy.

“It is unclear what the biodiversity impact or food security impact will be if we increase our use of bioenergy,” she says. “I feel that only focusing on costs was a major factor in creating the climate crisis that we are facing. So now, as we try to solve this problem, I worry that if we only focus on emissions, we will generate other problems by only focusing on one thing. We can use bioenergy, but not without understanding the costs to the natural environment.”

This past summer, Azuero-Pedraza endeavored to understand how forest management decisions change when incorporating biodiversity into the decision-making process.

“I want to endogenize biodiversity data instead of doing an ex-post analysis,” she explains. “I want to be able to explore which forest management style we could use, or which land use change might be optimal. Then, if we factor in biodiversity, we will understand how the decision changes with that information.”

According to Azuero-Pedraza, one of the most important components of biodiversity in land use and forest management decisions is compromise.

“The idea is to understand the difference between including and excluding biodiversity in decision making, and where the tradeoffs could be,” she says. “We can check to see what the biodiversity impacts would be in the scenarios that do not include it in a decision-making process. We then add biodiversity in the decision-making and ask where the differences in biodiversity impacts are; what amounts are harvested, such as wood in a certain location; and what forest management regimes are used. These are just some of the factors we compare,” she notes.

 She also explains the importance of factoring species loss data into the model, in order to optimize a forest management or land use decision.

 “If someone has to find the optimal decision, but can’t lose more than a certain amount of species, we can model that to find the best solution,” she explains. “We could also incorporate species loss data as a negative implication. The idea is that these models not only maximize economic surplus, but optimize for biodiversity and encourage decision makers to consider that factor.”

To expand the GLOBIOM forest model, Azuero-Pedraza used biodiversity data from multiple sources, including her own research, existing literature, and existing models such as the Countryside Species Area relationship, which is used in ecology to estimate potential species loss due to habitat loss.

“Species richness is just one indicator of biodiversity,” she says. “There are so many more ways to measure it. But this is just a start, because measuring biodiversity itself is very difficult.”

Azuero-Pedraza says that her current model “will be a starting point to assess future scenarios while considering biodiversity implications.” Ultimately, she hopes to extend her modeling framework with GLOBIOM and into an Integrated Assessment Model, a powerful tool to assess potential future climate change mitigation pathways.

“If we manage to integrate biodiversity impacts in a way that affects these potential pathways, we will have an integrated approach in which we could prioritize solutions that are simultaneously good for biodiversity conservation and climate change,” she says. “I hope that someday, when our society makes decisions about forest management, we will consider not only economic implications, but also biodiversity ones.”