alexa A review of methods for the assessment of prediction errors in conservation presence absence models.
Environmental Sciences

Environmental Sciences

Journal of Ecosystem & Ecography

Author(s): ALAN H FIELDING, JOHN F BELL

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Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that predict the presence or absence of a species are normally judged by the number of pre- diction errors. These may be of two types: false posi- tives and false negatives. Many of the prediction errors can be traced to ecological processes such as unsatu- rated habitat and species interactions. Consequently, if prediction errors are not placed in an ecological con- text the results of the model may be misleading. The simplest, and most widely used, measure of prediction accuracy is the number of correctly classified cases. There are other measures of prediction success that may be more appropriate. Strategies for assessing the causes and costs of these errors are discussed. A range of techniques for measuring error in presence/absence models, including some that are seldom used by ecol- ogists (e.g. ROC plots and cost matrices), are de- scribed. A new approach to estimating prediction error, which is based on the spatial characteristics of the errors, is proposed. Thirteen recommendations are made to enable the objective selection of an error assessment technique for ecological presence/absence models.

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This article was published in Environmental Conservation and referenced in Journal of Ecosystem & Ecography

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