The study by Brotons et al. (2004) compares the performance of two methods for predicting bird habitat suitability: Ecological Niche Factor Analysis (ENFA) using only presence data and Generalized Linear Models (GLM) using both presence and absence data. Using breeding bird atlas data from Catalonia, the researchers found that GLM predictions were more accurate than those obtained with ENFA, especially when species used available habitats proportionally to their suitability, making absence data reliable and useful for enhancing model calibration. Species marginality in niche space was also correlated with predictive accuracy, meaning species with less restricted ecological requirements were less accurately modeled than those with more restricted requirements. The study concludes that modellers should consider species ecological characteristics and prevalence when choosing between methods, and that presence/absence methods may be particularly useful for species with low prevalence and high marginality. The results suggest that if absence data is available, methods using this information should be preferred in most situations.The study by Brotons et al. (2004) compares the performance of two methods for predicting bird habitat suitability: Ecological Niche Factor Analysis (ENFA) using only presence data and Generalized Linear Models (GLM) using both presence and absence data. Using breeding bird atlas data from Catalonia, the researchers found that GLM predictions were more accurate than those obtained with ENFA, especially when species used available habitats proportionally to their suitability, making absence data reliable and useful for enhancing model calibration. Species marginality in niche space was also correlated with predictive accuracy, meaning species with less restricted ecological requirements were less accurately modeled than those with more restricted requirements. The study concludes that modellers should consider species ecological characteristics and prevalence when choosing between methods, and that presence/absence methods may be particularly useful for species with low prevalence and high marginality. The results suggest that if absence data is available, methods using this information should be preferred in most situations.