Extinction selectivity is systematic variation in the probability or rate of extinction among lineages with different traits, rather than trait-independent loss. Traits may be biological, ecological or geographical: for example, survival may differ between narrow-ranging and widespread taxa within the same extinction interval.
A test needs an explicit denominator of taxa at risk, a defined taxonomic level and time window, and a specified trait measurement. Regional disappearance is not automatically global extinction. Nor is an association necessarily a causal mechanism: traits covary with habitat, abundance and preservation, and their effects can change between background intervals and mass extinctions.
Four documented examples, each tied to its actual context, are:
- Geographic range: widespread marine bivalve genera survived the end-Cretaceous event better than geographically restricted genera. Spatial spread can reduce exposure to some geographically heterogeneous stresses, although this does not guarantee survival of a global perturbation.[ref]Selectivity of end-Cretaceous marine bivalve extinctions by David Jablonski and others. Abstract: lower extinction intensity in geographically widespread genera
- Body size: large-bodied mammals were disproportionately lost during the late Quaternary. The global analysis documents size selectivity across continents and trophic groups; this is not evidence that large body size always raises extinction risk in every geological interval.[ref]Body size downgrading of mammals over the late Quaternary by Felisa Smith and others. Abstract: size-selective losses over the studied late-Quaternary intervals
- Physiological buffering and respiratory capacity: poor capacity to tolerate elevated carbon dioxide and associated oxygen stress has been linked to higher vulnerability among end-Permian marine groups. This is a paleophysiological interpretation informed by living relatives and fossil traits, rather than a direct measurement of a fossil animal’s tolerance.[ref]Paleophysiology and end-Permian mass extinction by Andrew H. Knoll and others. Abstract and section Extinction in the oceans: hypercapnia vulnerability and physiological selectivity
- Sexual dimorphism as a proxy for male reproductive investment: greater male–female carapace differences in fossil cytheroid ostracods were associated with higher estimated extinction rates. The measured fossil trait is dimorphism; interpreting it as investment requires the biological correspondence observed in living relatives.[ref]High male sexual investment as a driver of extinction in fossil ostracods by Maria João Fernandes Martins and others. Abstract: dimorphic fossil carapaces and association with estimated extinction rates
These examples demonstrate event- and group-dependent selectivity. They do not define one universal vulnerability ranking: the bivalve study, for instance, did not find body-size selectivity at the same end-Cretaceous genus-level event.
One fossil-record study is Selectivity of end-Cretaceous marine bivalve extinctions by David Jablonski and others, which compared survival of marine bivalve genera across the end-Cretaceous mass extinction against their pre-event attributes. Geographically widespread genera had lower extinction intensity than narrowly distributed ones. In the same analysis, body size, burrowing versus exposed life position, and shelf bathymetric position were not significant selectors; the apparent feeding-mode contrast was concentrated in particular groups rather than establishing a universal feeding rule.[ref]
Selectivity of end-Cretaceous marine bivalve extinctions by David Jablonski and others. Science 268, pp. 389–391, abstract: tested traits, range result and qualifications to the feeding-mode result
The logic of the test is to define the pre-event genera at risk, classify their geographic ranges using pre-event occurrences, then compare the fractions becoming extinct. Using pre-event rather than surviving ranges avoids measuring the predictor after the outcome. A two-by-two contingency table gives an elementary broad/narrow-range comparison; a logistic regression can instead retain a continuous range measure and include correlated covariates. These are explanations of the inferential design, not a claim that this paper used that exact regression specification.
A persuasive interpretation must address unequal rock exposure, collecting intensity, taxonomic revision, incomplete occurrence records and the difference between local loss and global extinction. The important result is selective survival in a real fossil dataset and the failure of several plausible alternative predictors in that setting. It is observational evidence: geographic range can correlate with unmeasured ecological properties, so the association alone does not prove a unique kill mechanism.
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