Using expert knowledge to support Endangered Species Act decision-making for data-deficient species.

Area of Science:

• Ecology
• Conservation Biology
• Environmental Science

Background:

• Conservation decision-making often faces extreme uncertainty due to limited empirical data and complex ecological processes.
• Structured protocols for eliciting expert knowledge are increasingly used to address this uncertainty.
• Existing ecological applications frequently use modified Delphi methods, but the Sheffield elicitation framework (SHELF) offers a distinct behavioral approach to synthesizing expert judgments.

Purpose of the Study:

• To remotely assess the extinction risk of three subterranean aquatic species using the SHELF protocol.
• To provide decision-makers with a comprehensive understanding of uncertainty in conservation risk assessments.
• To evaluate the utility of a virtual SHELF implementation for conservation applications.

Main Methods:

• The Sheffield elicitation framework (SHELF) protocol was employed remotely.
• Experts received empirical threat assessments for each species' locality via video conference.
• Judgments on population persistence probability were recorded using online forms and R-shiny apps within the SHELF package.

Main Results:

• Despite significant uncertainty, distinct differences in extirpation risk were identified among the species.
• Spatial variations in threats, land use, management practices, and microhabitat influenced species' risk profiles.
• The resulting probability distributions accurately reflected the probabilistic nature of risk assessments for decision-makers.

Conclusions:

• The virtual SHELF protocol proved flexible and effective for conservation applications with budget and time constraints.
• Discussion during the behavioral aggregation stage clearly identified dominant threats and their interactions with ecological factors.
• The study highlights the value of SHELF in generating detailed uncertainty information for conservation planning.