{"id":"W2112315008","doi":"10.1111/j.2006.0906-7590.04596.x","title":"Novel methods improve prediction of species’ distributions from occurrence data","year":2006,"lang":"en","type":"article","venue":"Ecography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":9099,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Herbarium; Computer science; Context (archaeology); Predictive modelling; Species distribution; Environmental niche modelling; Data set; Environmental data; Ecology; Machine learning; Data mining; Data science; Artificial intelligence; Geography; Biology; Habitat","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null}