Ecological Modelling 186 (2005) 280–289 The evaluation strip: A new and robust method for plotting predicted responses from species distribution models Jane Elith a,∗ , Simon Ferrier b , Falk Huettmann c , John Leathwick d a School of Botany, The University of Melbourne, Parkville, Melbourne, Victoria 3010, Australia b New South Wales Department of Environment and Conservation, PO Box 402, Armidale, NSW 2350, Australia c Institute of Arctic Biology, Dept. of Biology and Wildlife, 419 IRVING 1 – EWHALE lab-University of Alaska-Fairbanks, Fairbanks, AK 99775, USA d National Institute of Water and Atmospheric Research, PO Box 11115, Hamilton, New Zealand Received 1 June 2004; received in revised form 4 December 2004; accepted 13 December 2004 Abstract Increasing use is being made in conservation management of statistical models that couple extensive collections of species and environmental data to make predictions of the geographic distributions of species. While the relationships fitted between a species and its environment are relatively transparent for many of these modeling techniques, others are more ‘black box’ in character, only producing geographic predictions and providing minimal or untraditional summaries of the fitted relationships on which these predictions are based. This in turn prevents robust evaluation of the ecological sensibility of such models, a necessary process if model predictions are to be treated with confidence. Here we propose a new but simple method for visualizing modeled responses that can be implemented with any modeling method, and demonstrate its application using five common methods applied to the prediction of an Australian tree species. This is achieved by insetting an “evaluation strip” into the spatial data layers, which, after predictions have been made, can be clipped out and used for creating plots of the modelled responses. We present findings of the application strip for algorithms GLMs, GAMs, CLIM, DOMAIN and MARS. Evaluation strips can be constructed to investigate either uni-variate responses, or the simultaneous variation in predicted values in relation to two variables. The latter option is particularly useful for evaluating responses in models that allow the fitting of complex interaction terms. © 2004 Elsevier B.V. All rights reserved. Keywords: Evaluation; Predict; Distribution; Habitat model; Plotted response; Visualise ∗ Corresponding author. Phone: +61 8344 4572; fax: +61 3 9347 5460. E-mail address: j.elith@unimelb.edu.au (J. Elith). 1. Introduction Statistical models are frequently used to relate species’ presence, presence–absence or abundance, to the environment at some set of survey sites, and these 0304-3800/$ – see front matter © 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2004.12.007