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Jorge M. Lobo

Researcher at Spanish National Research Council

Publications -  295
Citations -  16755

Jorge M. Lobo is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Species richness & Dung beetle. The author has an hindex of 59, co-authored 288 publications receiving 14537 citations. Previous affiliations of Jorge M. Lobo include University of the Azores.

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AUC: a misleading measure of the performance of predictive distribution models

TL;DR: The area under the receiver operating characteristic (ROC) curve, known as the AUC, is currently considered to be the standard method to assess the accuracy of predictive distribution models as discussed by the authors.
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Threshold criteria for conversion of probability of species presence to either–or presence–absence

TL;DR: Four threshold criteria are compared for a wide range of sample sizes and prevalences, modeling a virtual species in order to avoid the omnipresent error sources that the use of real species data implies.
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Use of niche models in invasive species risk assessments.

TL;DR: This work highlights that, in the case of invasive species, distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using all distributional information available, including information from both the native range and other invaded regions.
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Seven Shortfalls that Beset Large-Scale Knowledge of Biodiversity

TL;DR: The concept of knowledge shortfalls is updated and the tradeoffs between generality and uncertainty are reviewed and a general framework for the combined impacts and consequences of shortfalls of large-scale biodiversity knowledge is concluded.
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Not as good as they seem: the importance of concepts in species distribution modelling

TL;DR: This work discusses three important topics that must be kept in mind when modelling species distributions, namely the distinction between potential and realized distribution, the effect of the relative occurrence area of the species on the results of the evaluation of model performance, and the general inaccuracy of the predictions of the realized distribution provided by species distribution modelling methods.