2025 | Forest Composition, Ecosystem Services, and Irreversible Tipping Points

FACULTY SEED GRANT | Global Change Center

Forest composition, ecosystem services, and irreversible tipping points

INVESTIGATORS:

• Dr. Kelly Cobourn, Forest Resources and Environmental Conservation
• Dr. Jeff Borggaard, Mathematics
• Dr. Haldre Rogers, Fish and Wildlife Conservation
• Dr. Stella Schons do Valle, Forest Resources and Environmental Conservation

This study is funded jointly by the Global Change Center at Virginia Tech and the Institute for Society, Culture and Environment (ISCE).

Overharvesting of native forests supports local, short-term economic activity at the cost of environmental harm with global and long-term consequences. A large scientific literature points to the role of deforestation in reducing biodiversity, compromising ecosystems, and compounding climate change. Mounting evidence suggests that these consequences are even more serious than previously thought: deforestation may drive ecosystems past potentially irreversible tipping points, destroying their ability to sustain environmental health and human welfare. This phenomenon is already being observed in the Brazilian Amazon, where tropical rainforest is transitioning into a savannah ecosystem. This shift renders the land unsuitable for timber and agricultural production and degrades the system’s capacity to regulate the global climate.

Whether and when forest ecosystems cross this type of tipping point depends on the harvest of native forests, but also on reforestation and afforestation. In fact, climate policies often encourage secondary forests as a means of sustaining ecosystem services. However, native and secondary forests are not perfect substitutes for one another in terms of ecosystem service provision. Reforested plantations often augment food and fiber production but reduce biodiversity and net carbon storage. Even in naturally regenerating forest areas, a reduction in seed dispersers has been shown to slow regeneration, alter species composition, and reduce carbon storage. If the ecosystem services supported by secondary forests do not fully offset those lost from native forests, ecosystem collapse may occur even as reforestation and afforestation increase net forest cover.

To understand how changes in forest composition affect the risk of an ecosystem tipping point, it is essential to account for differences in ecosystem services between native and secondary forests. However, few studies connect dynamic changes in forests with ecosystem service provision by forest type, and even fewer connect these processes with the risk of non-linear and irreversible ecosystem change. The central hypothesis of this project is that if native and secondary forests differ in the provision of ecosystem services, reforestation and afforestation may be insufficient to guard against ecosystem collapse. Rather, avoiding or delaying ecosystem collapse may require a combination of policies for secondary forest establishment with improved protections for native forests.

This project will develop new modeling capacity to understand how forest composition affects ecosystem service provision and the risk and timing of irreversible tipping points. To do so, the project builds a new team that combines expertise in bio-economic modeling (Cobourn), ecological function in regenerating forests (Rogers), deforestation policy (Schons), and mathematical solution methods for spatial and temporally dynamic problems (Borggaard). The project builds on a theoretical foundation established by PI Cobourn examining changes in forest composition and the timing of ecosystem collapse. This work will extend and enrich this line of inquiry in two ways. First, it will explicitly model spatial aspects of forest loss and degradation that lead to ecosystem collapse, which is critical given that collapse is often observed along the forest periphery and in disturbed or fragmented areas. Second, the project will apply the model to two contrasting empirical study systems—the continental-scale Brazilian Amazon and the island of Guam. The team will leverage expertise and data already collected by PIs Schons (Amazon) and Rogers (Guam) to test the modeling framework and to develop new insight into the biological and economic drivers of forest collapse.

The project will apply the resulting spatial-dynamic model of forest composition, ecosystem service provision, and tipping points to evaluate policy scenarios that affect agricultural production, native forest protections, and reforestation/afforestation. The team will identify and examine a range of policy instruments including reforestation incentives, secondary forest management practices, carbon markets, payments for ecosystem services, and incentives provided under international climate policies such as REDD+. These policies will be instantiated into the model via changes in key parameters and constraints and used to evaluate the efficiency and efficacy of potential approaches to avert or delay tipping points in forested ecosystems. Ultimately, the objective is to support the development of proactive land-use and forest management policies that sustain the capacity of these forests to support human and natural systems long into the future.