New measures for assessing model equilibrium and prediction mismatch in species distribution models

• Published in: Diversity & distributions Vol. 19; no. 10; pp. 1333 - 1338
• Main Authors: Márcia Barbosa, A., Real, Raimundo, Muñoz, A.-Román, Brown, Jennifer A.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.10.2013; John Wiley & Sons Ltd; Blackwell; John Wiley & Sons, Inc
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Applied ecology; Biodiversity; Biodiversity conservation; BIODIVERSITY LETTER; Biogeography; Biological and medical sciences; Climate change; Commission; Conservation biology; Disease models; distribution equilibrium; Ecological modeling; Environmental conservation; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Techniques; Invasive species; Land use; Methods and techniques (sampling, tagging, trapping, modelling...); model evaluation; Modeling; omission; over-prediction; prediction error; Predictive modeling; predictive performance; Species; Synecology; under-prediction; Wildlife conservation; Prediction; predictive performance; Commission; under-prediction; Error; Model study; Biodiversity; Forecast model; Modeling; distribution equilibrium; Spatial distribution; Geographic distribution; model evaluation; prediction error; Performance; omission; over-prediction; Distribution range
• ISSN: 1366-9516; 1472-4642
• DOI: 10.1111/ddi.12100

Models based on species distributions are widely used and serve important purposes in ecology, biogeography and conservation. Their continuous predictions of environmental suitability are commonly converted into a binary classification of predicted (or potential) presences and absences, whose accuracy is then evaluated through a number of measures that have been the subject of recent reviews. We propose four additional measures that analyse observation-prediction mismatch from a different angle – namely, from the perspective of the predicted rather than the observed area – and add to the existing toolset of model evaluation methods. We explain how these measures can complete the view provided by the existing measures, allowing further insights into distribution model predictions. We also describe how they can be particularly useful when using models to forecast the spread of diseases or of invasive species and to predict modifications in species' distributions under climate and land-use change.