Quantifying uncertainty in the identification of endangered ecological communities

Abstract

Abstract Ecological community and ecosystem “red lists” have been developed in several jurisdictions to improve ecosystem‐level biodiversity protection. However, a challenge for the conservation and management of listed ecosystems is consistent identification in the field or from plot records. Ecosystem descriptions must have enough detail for positive identification but be broad enough that most instances are included. In many jurisdictions, descriptions are not supported by dichotomous keys or thresholds of ecosystem collapse and identification relies on the interpretation of trained individuals, with potential for opposing opinions. Using a structured process, we assessed the ability of experts to identify a critically endangered ecological community from vegetation plot samples. We compared the allocations made by experts with a numeric classification that underpinned the legal definition of the community. Overall, experts correctly identified the presence or absence of the community in 81% of samples although individual classification rates ranged from 63% to 94%. False positive rates varied among experts (7–50%) and experienced botanists did not necessarily perform better. Disturbance increased uncertainty and experts differed in their opinion about when the community had collapsed and was no longer recoverable. Inconsistent interpretation, in the absence of diagnostic keys and consensus models of collapse, will have implications for recovery and conservation of listed communities and ecosystems, and could impact the effectiveness of laws and policies designed to protect them.

Keywords

• environmental policy
• expert elicitation
• IUCN red list
• threatened ecological communities
• threatened ecosystems
• vegetation communities