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Four documented examples, each tied to its actual context, are:

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]

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.

Extinction selectivity means that the probability of extinction depends systematically on biological or ecological traits, rather than being equal across all species. An empirical association needs a specified event, group and taxonomic level; a trait protective in ordinary background turnover may not protect during every mass extinction.

Geographic range: at the end-Cretaceous crisis, geographically widespread marine bivalve genera had lower extinction intensity than narrowly distributed genera. This makes range breadth a demonstrated selective trait for that dataset. The same analysis found no clear selectivity by body size, so that result should not be generalized to every trait or event.^[ref]

Body size: large-bodied mammals suffered disproportionately during late-Pleistocene and later Quaternary losses, including the loss of many giant herbivores and carnivores. A global analysis over the last $125000$ years found strong size-selective losses across continents and trophic modes. Large size can correlate with slow reproduction, high resource demand and exposure to human hunting, but the observed size pattern and its possible mechanisms should be distinguished.^[ref]

Sexual dimorphism and reproductive investment: a study of fossil cytheroid ostracods found much higher estimated extinction rates in species with stronger male–female carapace dimorphism, interpreted as greater male investment in reproduction. This supplies a third empirical trait association; the observed relationship is not a universal claim that sexual selection is always harmful.^[ref]

The examples concern different time intervals and levels, including genera in the first example and species in the third. They demonstrate extinction selectivity without assuming one set of trait effects is universal across all crises.