Species distribution modelling—Effect of design and sample size of pseudo-absence observations

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The global distribution and burden of dengue (2013, unknown): “India19,20 alone contributed 34% (33 [24-44] million infections) of the global total.”
A framework for species distribution modelling with improved pseudo-absence generation (2015, background): “…(TS and TSKM), has been criticized by some au-311 thors for producing artificially high probabilities of occurrence (Wisz and312 Guisan, 2009; Stokland et al., 2011) and wider predicted suitability areas.313 In ecological terms, the variability in the predicted probabilities is related…”
The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models (2013, background): “A number of other studies have shown the importance of the background data selection method through a variety of SDM techniques [19,20,21,22,23,52] and studies have begun to also evaluate MaxEnt [12,14,53,54,55].”