Assessing the effects of pseudo-absences on predictive distribution model performance

@inproceedings{Chefaoui2007AssessingTE,
  title={Assessing the effects of pseudo-absences on predictive distribution model performance},
  author={Rosa M Chefaoui and Jorge M. Lobo},
  year={2007}
}
Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudoabsence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results… CONTINUE READING
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