Inventory statistics meet big data: complications for estimating numbers of species
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Issue Date
2020-05-13Author
Khalighifar, Ali
Jiménez, Laura
Nuñez-Penichet, Claudia
Freeman, Benedictus
Ingenloff, Kate
Jiménez-García, Daniel
Peterson, Town
Publisher
PeerJ
Type
Article
Article Version
Scholarly/refereed, publisher version
Rights
Copyright 2020 Khalighifar et al.
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We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of units of inventory effort (e.g., days of inventory effort) 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, NJ, USA), and outline the circumstances under which these problems may be expected to emerge.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
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Citation
Khalighifar, A., Jiménez, L., Nuñez-Penichet, C., Freeman, B., Ingenloff, K., Jiménez-García, D., & Peterson, T. (2020). Inventory statistics meet big data: complications for estimating numbers of species. PeerJ, 8, e8872. https://doi.org/10.7717/peerj.8872
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