The current categories and criteria (version 3.1) were established more than 20 years ago \citep{IUCN2012} and methodological revisions have been suggested \citep{CazalisEtAl2022TrendsinEcologyampEvolution}. At present, the Red List clearly needs to utilize new technologies, data availability, and modern quantitative methods that were not available when its categorization system was first developed.
Criterion B [Geographic Range] is the most commonly used criterion for classifying species into threatened categories \citep{MarshEtAl2023BiodiversConserv}, which requires updating. This criterion employs simple spatial metrics that indirectly calculate species range sizes \citep*{Gaston_2009} and is poorly correlated with species risk of extinction  \citep{MarshEtAl2023BiodiversConserv}. In contrast, contemporary methods, such as species distribution models \citep{PetersonEtAl2018Conserv.Biol.} and GIS approaches \citep{PalacioEtAl2021Divers.Distrib.,Hughes_2021} allow the direct estimation of the species’ Extent of Suitable Habitat (ESH), also called Area of Habitat (AOH). The AOH is a more informative metric for assessing extinction risk \citep{BrooksEtAl2019TrendsEcol.Evol.}, and remote sensing technologies permit the evaluation of its trend over time, quality, or degradation \citep{JacobsonEtAl2019SciRep}.
Similarly, criteria A, C, and D are based on population parameters  \citep{IUCN2012}, which are typically not estimated using standardized methods \citep{Keith2009Significance}. Consequently, the reported abundances and population trends for some species are often “guesstimates” \citep*{MallonJackson2017Oryx} and can be misleading \citep{FoxEtAl2019JInsectConserv,WilsonEtAl2011Conserv.Biol.}. In the oceans, criterion A [Population size reduction] is only of limited value for assessing the level of depletion and exploitation rate of fish stocks and could benefit from integrating new parameters from fisheries sources \citep{MillarDickey-Collas2018,MiqueleizEtAl2022Fishes}. The quantitative criterion E encourages population viability analyses and can indicate species’ probability of extinction. However, to date, it has only been used for four species \citep{IUCN2023} and should be more broadly applied \citep{CazalisEtAl2022TrendsinEcologyampEvolution}. Additionally, we suggest incorporating effective population size whenever possible \citep{SchmidtEtAl2023Conserv.Biol.}, which is also a headline indicator within the Kunming-Montreal Global Biodiversity Framework. 
In addition to the issues with each criterion, the categories and criteria do not account for simultaneously operating threats \citep{GreenvilleEtAl2021Conserv.Lett.}, which may vary across species ranges, populations, and habitat levels \citep{SantiniEtAl2019Conserv.Biol.}. Also, critical factors such as landscape connectivity, genetic diversity, and population adaptation to different niches are not explicitly considered in the Red List \citep{PilotEtAl2006Mol.Ecol.,WilloughbyEtAl2015BiologicalConservation,BreinerEtAl2017Divers.Distrib.,SchmidtEtAl2023Conserv.Biol.}, even though they are critical for species and population persistence \citep{LindborgEriksson2004Ecology,LorenzanaEtAl2020BiologicalConservation}. Hence, the Red List is currently insufficient to inform species-specific decisions on protecting populations and their genetic diversity \citep{SchmidtEtAl2023Conserv.Biol.}.

Shortcomings of the red listing process

Beyond the limitations of the Red List categories and criteria, the assessment process has several shortcomings. It is heavily reliant on a few Red List assessors, where the expert selection process is run through invitations that might favor academic networks with similar biases and exclude conservationists and other local professionals \citep{Tomasini_2018}. Critically, many assessors require more time, expertise, and funding to complete thorough assessments. Assessors are almost entirely volunteers and lack funding; thus, a more standardized process likely requires increased recognition and support, as authoring Red List assessments is secondary to grants and scientific publications. Within this context, it is challenging to reflect regional or local threats to species survival. In fact, integrating local data into Red List assessments is a long overdue process  \citep{RodriguezEtAl2000Nature}. We suggest the red listing process should seek knowledge sources in non-English languages \citep{ChowdhuryEtAl2022Conserv.Biol.}, gray literature \citep*{Haddaway_2015}, and citizen science databases, among other streams of knowledge. Such sources can be essential repositories of context-dependent information, and may increase the effectiveness of conservation interventions \citep{AmanoEtAl2021PLOSBiology} and species recovery \citep{Hu_2018}.