Evaluating alternative data sets for ecological niche models of birds in the Andes Juan L. Parra, Catherine C. Graham and Juan F. Freile Parra, J. L., Graham, C. C. and Freile, J. F. 2004. Evaluating alternative data sets for ecological niche models of birds in the Andes.  / Ecography 27: 350 /360. Ecological niche modeling (ENM) is an effective tool for providing innovative insights to questions in evolution, ecology and conservation. As environmental datasets accumulate, modelers need to evaluate the relative merit of different types of data for ENM. We used three alternative environmental data sets: climatic data, remote- sensing data (Normalized Difference Vegetation Index), and elevation data, to model the distribution of six bird species of the genus Grallaria in the Ecuadorian Andes. We assessed the performance of models created with each environmental data set and all possible combinations by comparing the geographic predictions of our models with detailed maps developed by expert ornithologists. Results varied depending on the specific measure of performance. Models including climate variables performed relatively well across most measures, whereas models using only NDVI performed poorly. Elevation based models were relatively good at predicting most sites of expected occurrencebut showed a high over-prediction error. Combinations of data sets usually increased the performance of the models, but not significantly. Our results highlight the importance of including climatic variables in ENM and the simultaneous use of various data sets when possible. This strategy attenuates the effects of specific variables that decrease model performance. Remote-sensing data, such as NDVI, should be usedwith caution in topographically complex regions with heavy cloud-cover. Nonetheless, remote-sensing data have the potential to improve ENM. Finally, we suggest a priori designation of modeling purposes to define specific performance measures accordingly. J. L. Parra (juanp@uclink.berkeley.edu) and C. C. Graham, Museum of Vertebrate Zoology, 3101 VLSB, Univ. of California, Berkeley, CA 94720-3160 USA.  / J. F. Freile, Fundacio ´n Numashir para la Conservacio ´n de Ecosistemas Amenazados, Casilla Postal 17-12-122, Quito, Ecuador. Ecological niche models have been used to study issues in evolution (Peterson 2001, Hugall et al. 2002), ecology (Anderson et al. 2002), and conservation (Godown and Peterson 2000, Sa ´nchez-Cordero and Martı ´nez-Meyer 2000, Peterson and Robins 2003). These methods (e.g. BIOCLIM-Nix 1986, Busby 1991; GARP-Stockwell and Noble 1991; DOMAIN-Carpenter et al. 1993) combine geographic locations of a given species with spatial surfaces of environmental data to identify suitable parameters for a given species and then map this information to predict the species geographic distribu- tion. Typically, interpolated climate data (e.g. Berry et al. 2002, Joseph and Stockwell 2002); or environmental data obtained through remote sensing (e.g. Fuentes et al. 2001, Oindo 2002, Zinner et al. 2002) are used to build models. To date, there has been no assessment of the relative performance of models created by these different datasets. In this article, we assess the utility of using climate, remotely-sensed Normalized Difference Vegeta- tion Index (NDVI) data, elevation, and a combination of these variables to predict distributions for six bird species inhabiting the Ecuadorian Andes. Interpolated climate data are derived from direct measurements of climate at weather stations (New et Accepted 29 December 2003 Copyright # ECOGRAPHY 2004 ISSN 0906-7590 ECOGRAPHY 27: 350  /360, 2004 350 ECOGRAPHY 27:3 (2004)