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Non-biotic controls of observed diversity in the paleontologic record: an example from the Permo-Triassic Karoo Basin of South Africa

Non-biotic controls of observed diversity in the paleontologic record: an example from the Permo-Triassic Karoo Basin of South Africa
Non-biotic controls of observed diversity in the paleontologic record: an example from the Permo-Triassic Karoo Basin of South Africa
Paleodiversity trends through geologic time can be affected by a number of geologic, taphonomic, and anthropogenic biases that obscure or prejudice paleoecological patterns in the fossil record. Although much work has concentrated on the relationship between geologic exposure, sample size, and taxonomic richness (i.e., number of taxa), few studies have investigated the potential effects of dataset quality and changing taxonomy. We use four different specimen-level datasets of Permo-Triassic tetrapods from the Karoo Basin of South Africa to investigate how sample size, geologic outcrop, dataset quality, and taxonomic revision all affect observed estimates of generic richness, evenness, and relative abundance. Our results indicate that large-scale patterns of richness, evenness, and abundance, such as the effects of the end-Permian mass extinction, are generally robust to these potential biases across the four different datasets. In contrast, absolute values vary significantly as do finer-scale patterns. In agreement with past studies, taxonomic errors, revised taxonomy, and new taxa have little effect on patterns of richness and evenness; instead, the addition of large numbers of new specimens to the dataset has the largest effect on these paleodiversity metrics, despite application of sample-standardization. We conclude that although large specimen datasets (hundreds to thousands of specimens) are robust to various potential biases, and can recover large-scale paleobiologic trends, they are still affected by many non-biotic controls, and workers should strive to improve dataset quality and understand the underlying reasons for observed paleodiversity patterns.
paleoecology, richness, evenness, relative abundance, rarefaction, end-permian mass extinction
0031-0182
62-77
Irmis, Randall B.
1490574b-4ad6-4896-a1d7-b66933a7e12e
Whiteside, Jessica H.
5d9ad7aa-eba3-4ad9-9f6f-81be71b6829b
Kammerer, Christian F.
1b7bfcbc-65d0-43c9-a99d-29fb3831f512
Irmis, Randall B.
1490574b-4ad6-4896-a1d7-b66933a7e12e
Whiteside, Jessica H.
5d9ad7aa-eba3-4ad9-9f6f-81be71b6829b
Kammerer, Christian F.
1b7bfcbc-65d0-43c9-a99d-29fb3831f512

Irmis, Randall B., Whiteside, Jessica H. and Kammerer, Christian F. (2013) Non-biotic controls of observed diversity in the paleontologic record: an example from the Permo-Triassic Karoo Basin of South Africa. [in special issue: Vertebrate palaeobiodiversity patterns and the impact of sampling bias] Palaeogeography, Palaeoclimatology, Palaeoecology, 372, 62-77. (doi:10.1016/j.palaeo.2012.07.014).

Record type: Article

Abstract

Paleodiversity trends through geologic time can be affected by a number of geologic, taphonomic, and anthropogenic biases that obscure or prejudice paleoecological patterns in the fossil record. Although much work has concentrated on the relationship between geologic exposure, sample size, and taxonomic richness (i.e., number of taxa), few studies have investigated the potential effects of dataset quality and changing taxonomy. We use four different specimen-level datasets of Permo-Triassic tetrapods from the Karoo Basin of South Africa to investigate how sample size, geologic outcrop, dataset quality, and taxonomic revision all affect observed estimates of generic richness, evenness, and relative abundance. Our results indicate that large-scale patterns of richness, evenness, and abundance, such as the effects of the end-Permian mass extinction, are generally robust to these potential biases across the four different datasets. In contrast, absolute values vary significantly as do finer-scale patterns. In agreement with past studies, taxonomic errors, revised taxonomy, and new taxa have little effect on patterns of richness and evenness; instead, the addition of large numbers of new specimens to the dataset has the largest effect on these paleodiversity metrics, despite application of sample-standardization. We conclude that although large specimen datasets (hundreds to thousands of specimens) are robust to various potential biases, and can recover large-scale paleobiologic trends, they are still affected by many non-biotic controls, and workers should strive to improve dataset quality and understand the underlying reasons for observed paleodiversity patterns.

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More information

e-pub ahead of print date: 24 July 2012
Published date: 15 February 2013
Keywords: paleoecology, richness, evenness, relative abundance, rarefaction, end-permian mass extinction
Organisations: Paleooceanography & Palaeoclimate

Identifiers

Local EPrints ID: 354692
URI: https://eprints.soton.ac.uk/id/eprint/354692
ISSN: 0031-0182
PURE UUID: 32e61edb-f5f2-485b-a2d0-e1d7b3a6b48a

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Date deposited: 17 Jul 2013 13:01
Last modified: 18 Jul 2017 03:53

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Contributors

Author: Randall B. Irmis
Author: Christian F. Kammerer

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