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Predicting the distribution of poorly-documented species, Northern black widow , using museum specim...

Predicting the distribution of poorly-documented species, Northern black widow , using museum specim...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_gale_infotracacademiconefile_A549443723

Predicting the distribution of poorly-documented species, Northern black widow , using museum specimens and citizen science data

About this item

Full title

Predicting the distribution of poorly-documented species, Northern black widow , using museum specimens and citizen science data

Publisher

Public Library of Science

Journal title

PloS one, 2018-08, Vol.13 (8), p.e0201094

Language

English

Formats

Publication information

Publisher

Public Library of Science

More information

Scope and Contents

Contents

Predicting species distributions requires substantial numbers of georeferenced occurrences and access to remotely sensed climate and land cover data. Reliable estimates of the distribution of most species are unavailable, either because digitized georeferenced distributional data are rare or not digitized. The emergence of online biodiversity infor...

Alternative Titles

Full title

Predicting the distribution of poorly-documented species, Northern black widow , using museum specimens and citizen science data

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_gale_infotracacademiconefile_A549443723

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_gale_infotracacademiconefile_A549443723

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0201094

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