Paintings predict the distribution of species, or the challenge of selecting environmental predictors and evaluation statistics

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Outstanding Challenges in the Transferability of Ecological Models. (2018, background): “ecologically, and physiologically meaningful and therefore support transferability [73,94].”
Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models (2019, background): “Instead, good model performance may result from model overfitting as species presences simply coincide with specific conditions, combinations or transformations of environmental variables in overly complex models (Merow et al. 2014; Fourcade et al. 2018).”
Machine learning for digital soil mapping: Applications, challenges and suggested solutions (2020, background): “One drawback of these techniques is their inability to provide information on whether the covariates have a causal link to the modelled soil property or class, which leads several authors to warn against their use for knowledge discovery (e.g. Fourcade et al., 2018).”
Environmental filtering improves ecological niche models across multiple scales (2019, background): “However, an increase in evaluation statistics is not necessarily a sign of a more biologically realistic prediction (Fourcade et al., 2017).”