Using Maxent to model the historic distributions of stonefly species in Illinois streams: The effects of regularization and threshold selections

By Yong Cao, R. DeWalt, Jason L Robinson, T. Tweddale, Leon C. Hinz, M. Pessino. 2013

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Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concern (2014, result): “In contrast, a recent empirical study (Cao et al., 2013) examining the impact of information criterion-based model selection on ENMs found that AICc-based models tended to overestimate species richness compared to survey data, which may be due to underparameterization.”
ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models (2014, background): “Nonetheless, the relative perfor- mance of AICc versus other model evaluation metrics is a topic of ongoing research (e.g. Cao et al. 2013; Radosavljevic & Anderson 2014; Warren et al. 2014), and ENMeval should help advance this line of research.”