Despite the existence of many approaches to reference-condition modeling, Bayesian statistical methods have not been used. We assessed whether a hybrid approach that combined features of existing reference-condition approaches with Bayesian model fitting and assessment of test sites could provide superior results to existing established methods. We used 4 Bayesian models of increasing complexity to develop and test reference-condition models for 5 biotic endpoints across 3 data sets. Our best models were comparable or superior to standard approaches (Benthic Assessment of Sediment, Australian River Assessment System) using the same data. Those of our models with the simplest endpoint (species richness) performed best. On average, those models with the simplest model structures also performed best, but differences in performance among models of different complexity were small. All models performed poorly at detecting the lower levels of simulated impact in the test data. However, these impacts were small relative to the variation among validation sites and consequent predictive uncertainty of the models. The Bayesian approach to reference-condition modeling shows promise as an alternative to existing methods. It also has advantages in terms of the ease of interpretation of model outputs. However, for the approach to be relevant, further development work should be driven by a perceived need to revise standard methods used by management agencies.
You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither BioOne nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the BioOne website.
Vol. 33 • No. 4