Estimating times of extinction in the fossil record

Wang, Steve C.; Marshall, Charles R.

doi:10.1098/rsbl.2015.0989

Cited by 43 publications

(34 citation statements)

References 53 publications

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“…according to the age model of Schobben et al (2015). Within this interval, all prerequisites are met for applying classical confidence interval methods (Wang and Marshall, 2016).…”

Section: Resultsmentioning

confidence: 99%

Pre–mass extinction decline of latest Permian ammonoids

Kiessling

Schobben

Ghaderi

et al. 2018

Geology

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The devastating end-Permian mass extinction is widely considered to have been caused by large-scale and rapid greenhouse gas release by Siberian magmatism. Although the proximate extinction mechanisms are disputed, there is widespread agreement that a major extinction pulse occurred immediately below the biostratigraphically defined Permian-Triassic boundary. Our statistical analyses of stratigraphic confidence intervals do not comply with a single end-Permian extinction pulse of ammonoids in Iran. High turnover rates and extinction pulses are observed over the last 700 k.y. of the Permian period in two widely separated sections representative of a larger area. Analyses of body sizes and morphological complexity support a gradual decline over the same interval. Similar pre-mass extinction declines and disturbances of the carbon cycle have sometimes been reported from other regions, suggesting a widespread, but often overlooked, environmental deterioration at a global scale, well before the traditional main extinction pulse.

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“…according to the age model of Schobben et al (2015). Within this interval, all prerequisites are met for applying classical confidence interval methods (Wang and Marshall, 2016).…”

Section: Resultsmentioning

confidence: 99%

Pre–mass extinction decline of latest Permian ammonoids

Kiessling

Schobben

Ghaderi

et al. 2018

Geology

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“…Both tasks deal with the same underestimation problem, use the same data, and have parallels with time‐spans of magmatic phenomena. Wang and Marshall [] provided an extensive reference list for methods to calculate confidence intervals on species endpoints. We examine two of the ways that paleobiologists have presented the underlying logic.…”

Section: Confidence Intervals On Onset and Cessation Timesmentioning

confidence: 99%

Estimating the duration of geologic intervals from a small number of age determinations: A challenge common to petrology and paleobiology

Glazner

Sadler

2016

Geochem Geophys Geosyst

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The duration of a geologic interval, such as the time over which a given volume of magma accumulated to form a pluton, or the lifespan of a large igneous province, is commonly determined from a relatively small number of geochronologic determinations (e.g., 4–10) within that interval. Such sample sets can underestimate the true length of the interval by a significant amount. For example, the average interval determined from a sample of size n = 5, drawn from a uniform random distribution, will underestimate the true interval by 50%. Even for n = 10, the average sample only captures ∼80% of the interval. If the underlying distribution is known then a correction factor can be determined from theory or Monte Carlo analysis; for a uniform random distribution, this factor is n+1n−1. Systematic undersampling of interval lengths can have a large effect on calculated magma fluxes in plutonic systems. The problem is analogous to determining the duration of an extinct species from its fossil occurrences. Confidence interval statistics developed for species origination and extinction times are applicable to the onset and cessation of magmatic events.

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“…This includes: (i) observational records of local and regional extirpations [9,10]; (ii) analyses of declines in abundance and geographical range [11,12]; (iii) models of the controls on population change [6,13]; (iv) inference from genetic changes or other indirect proxies [14,15] and (v) data on historical and deep-time extinctions, including past environmental crises [7,[16][17][18]. When combined with robust approaches to uncertainty, this opens a richer array of questions on extinction dynamics than would be possible through the lens of contemporary species losses.…”

Section: The Science Of Extinctionmentioning

confidence: 99%

Pattern, process, inference and prediction in extinction biology

Brook

Alroy

2017

Biol. Lett.

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Extinction is a key feature of the evolutionary history of life, and assessments of extinction risk are essential for the effective protection of biodiversity. The goal in assembling this special issue of Biology Letters was to highlight problems and questions at the research frontier of extinction biology, with an emphasis on recent developments in the methodology of inferring the patterns and processes of extinction from a background of often noisy and sparse data. In selecting topics, we sought to illustrate how extinction is not simply a selfevident phenomenon, but the subject of a dynamic and quantitatively rigorous field of natural science, with practical applications to conservation.

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Estimating times of extinction in the fossil record

Cited by 43 publications

References 53 publications

Pre–mass extinction decline of latest Permian ammonoids

Pre–mass extinction decline of latest Permian ammonoids

Estimating the duration of geologic intervals from a small number of age determinations: A challenge common to petrology and paleobiology

Pattern, process, inference and prediction in extinction biology

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