A framework for maximizing the benefit from retaining regrowth on private land

Area of Science:

• Ecology
• Conservation Biology
• Environmental Management

Background:

• Conservation interventions often yield suboptimal outcomes due to limitations in retrospective evaluations.
• A prospective counterfactual approach offers a method to estimate potential benefits and optimize conservation designs.
• Natural regeneration of forest and woodland ecosystems (regrowth) is crucial for biodiversity but faces deforestation pressures.

Purpose of the Study:

• To develop and apply a framework for estimating the expected conservation benefits of retaining forest regrowth.
• To identify areas where retaining regrowth provides the greatest additional conservation benefits, considering both averted deforestation and threatened species habitat.
• To inform conservation investment strategies in regions with high deforestation rates and biodiversity.

Main Methods:

• Developed a deforestation risk model to assess the additionality of retaining regrowth.
• Estimated the habitat value of regrowth for 29 threatened species, incorporating regrowth age.
• Combined deforestation risk and habitat value models to identify areas of greatest expected benefit.

Main Results:

• The identification of high-benefit areas for retaining regrowth varied significantly when considering averted clearing and species habitat together versus individually.
• Most high-benefit areas (56%) were consistently identified irrespective of species weighting (equal, threatened status, or habitat proportion).
• The framework was applied to a case study in Queensland, Australia, highlighting regional conservation priorities.

Conclusions:

• The developed framework effectively identifies areas for conservation investment to maximize benefits from retaining forest regrowth.
• Integrating multiple conservation objectives (averted deforestation and species habitat) is essential for effective conservation planning.
• The approach provides a valuable tool for guiding conservation efforts and can be broadly applied to conservation intervention design.