articleTop 1% cited
Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?
Ecological Modelling · 2009 · Vol. 220(4) · pp. 589–594
Jeremy VanDerWal✉(James Cook University)Luke P. Shoo(James Cook University)Catherine H. Graham(Stony Brook University)Stephen E. Williams(James Cook University)
Species Distribution and Climate ChangeWildlife Ecology and ConservationEcology and Vegetation Dynamics StudiesSpecies distributionVariable (mathematics)Environmental niche modellingDistribution (mathematics)StatisticsEconometricsEcologyMathematicsComputer scienceBiology
Citations
848
FWCI
44.35
field-weighted impact
References
19
Percentile
100%
vs. same field & year
Citations per year
Cited by
A bitter cup: climate change profile of global production of Arabica and Robusta coffee
Climatic Change · 2014 · 578 citations
Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
Ecological Modelling · 2021 · 435 citations
The global distribution and burden of dengue
Nature · 2013 · 9,995 citations
References
Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns
Ecological Modelling · 2002 · 532 citations
Assessing habitat-suitability models with a virtual species
Ecological Modelling · 2001 · 515 citations
Ensemble forecasting of species distributions
Trends in Ecology & Evolution · 2006 · 3,407 citations
Assessing the effects of pseudo-absences on predictive distribution model performance
Ecological Modelling · 2007 · 406 citations
Maximum entropy modeling of species geographic distributions
Ecological Modelling · 2005 · 17,289 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.