Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data
By Jorge M. Lobo, M. Tognelli. 2011
177 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/b8d3ceea3f8b7f739d02c5135ee5aa332153aa6d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Jorge M. Lobo
- Canran Liu
- Joaquín Hortal
- G. Newell
- Matt D. White
- Sara Varela
- A. Jiménez‐Valverde
- Maialen Iturbide
Citations in the corpus
- Minimum required number of specimen records to develop accurate species distribution models (2016, background): “Model performance for ecologically and geographically narrow-ranged species is significantly better compared to widespread species found in a wider range of habitats (Hernandez et al. 2006, Mateo et al. 2010, Lobo and Tognelli 2011, Tessarolo et al. 2014).”
- Using species distribution models in paleobiogeography: A matter of data, predictors and concepts (2011, methodology): “However, these pseudo-absences should be used with caution (Lobo and Tognelli, 2011) because the way they are selected has a great influence on the geographic representation of the distribution of the species that is finally obtained (Chefaoui and Lobo, 2008; Anderson and Raza, 2010; Lobo et al.,…”
- Predicting the distribution of vulnerable marine ecosystems in the deep sea using presence-background models (2014, background): “The properties of these spatial biases will subsequently translate from geographical space into environmental space, resulting in a biased perception of the species niche, and thus to inaccurate model outputs (Lobo and Tognelli, 2011).”
- A framework for species distribution modelling with improved pseudo-absence generation (2015, background): “This stresses the importance of well-distributed presence/absence265 data across the environmental and geographical space of the study area in266 16 order to obtain reliable models (Lobo and Tognelli, 2011).267 3.2.”
- The effect of sample size on the accuracy of species distribution models: considering both presences and pseudo‐absences or background sites (2019, background): “2004, Lobo and Tognelli 2011), e.g. selecting random points from the study area (Stockwell and Peters 1999, Ferrier et al.”