Inventory statistics meet big data: Complications for estimating numbers of species

Abstract We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of samples in which a species is detected saturates, such that crucial numbers of detections of rare species approach zero. Any rare errors can then come to dominate specie...

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Bibliographic Details
Published in:PeerJ preprints 2019-09
Main Authors: Khalighifar, Ali, Jiménez, Laura, Nuñez-Penichet, Claudia, Freeman, Benedictus, Ingenloff, Kate, Jiménez-García, Daniel, A Townsend Peterson
Format: Article
Language:English
Subjects:
Biodiversity
New records
Rare species
Species richness
Online Access:Get full text
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Summary:Abstract We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of samples in which a species is detected saturates, such that crucial numbers of detections of rare species approach zero. Any rare errors can then come to dominate species richness estimates, creating upward biases in estimates of species numbers. We document the problem via simulations of sampling from virtual biotas, illustrate its potential using a large empirical dataset (bird records from Cape May, New Jersey, USA), and outline the circumstances under which these problems may be expected to emerge.
ISSN:2167-9843
DOI:10.7287/peerj.preprints.27965v1