Editing Extinction event (section)

=== Tackling biases in the fossil record ===
[[File:Signor Lipps.gif|thumb|252x252px|An illustration of the [[Signor–Lipps effect|Signor-Lipps effect]], a geological bias that posits that increased fossil sampling would help to better constrain the exact time when an organism truly goes extinct.]]
As data continued to accumulate, some authors began to re-evaluate Sepkoski's sample using methods meant to account for [[sampling bias]]es. As early as 1982, a paper by Phillip W. Signor and [[Jere H. Lipps]] noted that the true sharpness of extinctions was diluted by the incompleteness of the fossil record.<ref>Signor III, P. W. and Lipps, J. H. (1982) "[http://specialpapers.gsapubs.org/content/190/291.full.pdf Sampling bias, gradual extinction patterns, and catastrophes in the fossil record]", in ''Geological implications of impacts of large asteroids and comets on the Earth'' (ed. L. T. Silver and P. H. Schultz), Geological Society of America Special Publication, vol. 190, pp. 291–296.</ref> This phenomenon, later called the [[Signor–Lipps effect|Signor-Lipps effect]], notes that a species' true extinction must occur after its last fossil, and that origination must occur before its first fossil. Thus, species that appear to die out just prior to an abrupt extinction event may instead be a victim of the event, despite an apparent gradual decline looking at the fossil record alone. A model by Foote (2007) found that many geological stages had artificially inflated extinction rates due to Signor-Lipps "backsmearing" from later stages with extinction events.<ref name="Foote_2007">{{Cite journal | vauthors = Foote M |date=2007 |title=Extinction and quiescence in marine animal genera |url=https://www.cambridge.org/core/product/identifier/S0094837300023794/type/journal_article |journal=Paleobiology |language=en |volume=33 |issue=2 |pages=261–272 |doi=10.1666/06068.1 |s2cid=53402257 |issn=0094-8373|url-access=subscription }}</ref>
[[File:Foote 2007 Kocsis 2019 extinction graphs.png|left|thumb|502x502px|Estimated extinction rates among genera through time. From Foote (2007), top, and Kocsis et al. (2019), bottom]]
Other biases include the difficulty in assessing taxa with high turnover rates or restricted occurrences, which cannot be directly assessed due to a lack of fine-scale temporal resolution. Many paleontologists opt to assess diversity trends by randomized sampling and [[Rarefaction (ecology)|rarefaction]] of fossil abundances rather than raw temporal range data, in order to account for all of these biases. But that solution is influenced by biases related to sample size. One major bias in particular is the "[[Pull of the recent]]", the fact that the fossil record (and thus known diversity) generally improves closer to the modern day. This means that biodiversity and abundance for older geological periods may be underestimated from raw data alone.<ref name="Foote_2000" /><ref name="Foote_2007" /><ref name="Alroy_2008" />

[[John Alroy|Alroy]] (2010) attempted to circumvent sample size-related biases in diversity estimates using a method he called "[[shareholder]] quorum subsampling" (SQS). In this method, fossils are sampled from a "collection" (such as a time interval) to assess the relative diversity of that collection. Every time a new species (or other [[taxon]]) enters the sample, it brings over all other fossils belonging to that species in the collection (its "[[Share (finance)|share]]" of the collection). For example, a skewed collection with half its fossils from one species will immediately reach a sample share of 50% if that species is the first to be sampled. This continues, adding up the sample shares until a "coverage" or "[[quorum]]" is reached, referring to a pre-set desired sum of share percentages. At that point, the number of species in the sample are counted. A collection with more species is expected to reach a sample quorum with more species, thus accurately comparing the relative diversity change between two collections without relying on the biases inherent to sample size.<ref name="Alroy_2010">{{Cite journal | vauthors = Alroy J |date=2010 |title=Fair Sampling of Taxonomic Richness and Unbiased Estimation of Origination and Extinction Rates |url=http://dx.doi.org/10.1017/s1089332600001819 |journal=The Paleontological Society Papers |volume=16 |pages=55–80 |doi=10.1017/s1089332600001819 |issn=1089-3326|url-access=subscription }}</ref>

Alroy also elaborated on three-timer algorithms, which are meant to counteract biases in estimates of extinction and origination rates. A given taxon is a "three-timer" if it can be found before, after, and within a given time interval, and a "two-timer" if it overlaps with a time interval on one side. Counting "three-timers" and "two-timers" on either end of a time interval, and sampling time intervals in sequence, can together be combined into equations to predict extinction and origination with less bias.<ref name="Alroy_2010" /> In subsequent papers, Alroy continued to refine his equations to improve lingering issues with precision and unusual samples.<ref>{{Cite journal | vauthors = Alroy J |date=2014 |title=Accurate and precise estimates of origination and extinction rates |url=https://www.cambridge.org/core/product/identifier/S0094837300001871/type/journal_article |journal=Paleobiology |language=en |volume=40 |issue=3 |pages=374–397 |doi=10.1666/13036 |s2cid=53125415 |issn=0094-8373|url-access=subscription }}</ref><ref>{{Cite journal | vauthors = Alroy J |date=2015 |title=A more precise speciation and extinction rate estimator |url=https://www.cambridge.org/core/product/identifier/S0094837315000263/type/journal_article |journal=Paleobiology |language=en |volume=41 |issue=4 |pages=633–639 |doi=10.1017/pab.2015.26 |bibcode=2015Pbio...41..633A |s2cid=85842940 |issn=0094-8373|url-access=subscription }}</ref>

McGhee et al. (2013), a paper thatprimarily focused on ecological effects of mass extinctions, also published new estimates of extinction severity based on Alroy's methods. Many extinctions were significantly more impactful under these new estimates, though some were less prominent.<ref name="McGhee_2013">{{Cite journal | vauthors = McGhee Jr GR, Clapham ME, Sheehan PM, Bottjer DJ, Droser ML |date= January 2013 |title=A new ecological-severity ranking of major Phanerozoic biodiversity crises |journal=Palaeogeography, Palaeoclimatology, Palaeoecology |language=en |volume=370 |pages=260–270 |doi=10.1016/j.palaeo.2012.12.019 |bibcode= 2013PPP...370..260M |issn=0031-0182}}</ref>

Stanley (2016) was another paper that attempted to remove two common errors in previous estimates of extinction severity. The first error was the unjustified removal of "singletons", genera unique to only a single time slice. Their removal would mask the influence of groups with high turnover rates or lineages cut short early in their diversification. The second error was the difficulty in distinguishing background extinctions from brief mass extinction events within the same short time interval. To circumvent this issue, background rates of diversity change (extinction/origination) were estimated for stages or substages without mass extinctions, and then assumed to apply to subsequent stages with mass extinctions. For example, the [[Santonian]] and [[Campanian]] stages were each used to estimate diversity changes in the [[Maastrichtian]] prior to the K-Pg mass extinction. Subtracting background extinctions from extinction tallies had the effect of reducing the estimated severity of the six sampled mass extinction events. This effect was stronger for mass extinctions that occurred in periods with high rates of background extinction, like the Devonian.<ref name="Stanley_2016">{{Cite journal | vauthors = Stanley SM |date= October 2016 |title=Estimates of the magnitudes of major marine mass extinctions in earth history |journal= Proceedings of the National Academy of Sciences|language=en |volume=113 |issue=42 |pages= E6325–E6334 |doi=10.1073/pnas.1613094113 |issn=0027-8424 |pmc=5081622 |pmid=27698119|bibcode= 2016PNAS..113E6325S |doi-access= free }}</ref>