The importance of expert selection when identifying threatened ecosystems.

Identifying threatened ecosystem types is fundamental to conservation and management decision-making. When identification relies upon the judgment of suitably trained experts, decisions are vulnerable to inconsistent outcomes and can lack transparency. We elicited judgements of the occurrence of a widespread, critically endangered Australian ecosystem from a diverse pool of 83 experts. We asked: (1) How many experts are required to reliably conclude that the ecosystem is present? (2) How many experts are required to build a reliable model for predicting ecosystem presence? (3) Given expert selection can narrow the range opinions, if enough experts are selected, do selection strategies affect model predictions? (4) Does a diverse selection of experts provide better model predictions? We used power and sample size calculations with a finite population of 200 experts to calculate the number of experts required to reliably assess ecosystem presence in a theoretical scenario. We then used boosted regression trees to model expert elicitation of 122 plots based on real-world data. For a reliable consensus (90% probability of correctly identifying presence and absence), in a relatively certain scenario (85% probability of occurrence) we found at least 17 experts were required. More experts are required when occurrence was less certain; fewer if permissible error rates are relaxed. In comparison, only ∼20 experts were required for a reliable model that could predict for a range of scenarios. Expert selection strategies changed modelled outcomes, often overpredicting presence and underestimate uncertainty. However, smaller but diverse pools of experts produced similar outcomes to a model built from all contributing experts. Combining elicited judgements from a diverse pool of experts in a model-based decision support tool provides an efficient aggregation of a broad range of expertise. Such models can improve the transparency and consistency of conservation and management decision-making especially when ecosystems are defined by complex criteria. This article is protected by copyright. All rights reserved.