Researchers of a new study recently presented a novel machine learning mechanism for analyzing extinction risk and then employed this tool to show that reptile species enlisted because of lack of data or assessment are more likely to be threatened than analyzed species.
As indicated in a EurekAlert! report, the Iconic Red List of Threatened Species, published by the International Union for Conservation of Nature, or IUCN, has identified species at risk of extinction.
More #reptilespecies may be at risk of #extinction than previously thought @PLOSBiology https://t.co/nQ2Ls9c7IG https://t.co/j4SK9B7pu8
— Phys.org (@physorg_com) May 26, 2022
The Red List of Threatened Species of the IUCN is the most extensive analysis of the extinction risk of species and informs conservation policy and practices worldwide.
However, the process of classifying species is laborious and subject to bias, depending strongly on manual curation by human experts. Many animal species have thus, not been assessed or lack sufficient data creating gaps in protective measures.
'Data Deficient'
Gabriel Henrique de Oliveira Caetano led the study published in PLoS Biology at Ben Gurion University of the Negev, Israel, and his colleagues.
To analyze more than 4,360 reptile species that failed to be prioritized in the past for conservation and develop accurate approaches for analyzing the extinction risk of obscure species, the study investigators created a machine-learning computer model.
This particular model assigned IUCN extinction risk classifications to the 40 percent of the world's reptiles that lacked published analyses or are categorized as "Data Deficient" or DD at the time of the study.
The study authors verified the model's accuracy, comparing it to the risk categorization of the Red List.
The IUCN Red List
As a result, the scientists discovered that the number of threatened species is much higher than the reflected in the IUCN Red List and that both "Not Evaluated" or NE, or unassessed and DD reptiles were more likely to be threatened than evaluated species.
Future studies need to be better when it comes to understanding the particular factors underlying risk in threatened reptile taxa or gaining better data on hidden reptile taxa and developing conservation plans that include identified endangered species.
In their study, the authors reported that their models predict that the condition of reptile conservation is far worse than presently estimated and that immediate action is essential to avoid the disappearance of reptile biodiversity.
Regions and taxa identified as likely to be more endangered need to be given more attention in new assessments and conservation planning.
Finally, the researchers said the approach they present here could be easily implemented to help fill the evaluation gap on other less known taxa.
Species-Rich Reptile Populations
Commenting on the assessment, Shai Meiri, co-author of the study, added, essentially, the additional reptile species identified as threatened by their models are not distributed randomly throughout the world or the reptilian evolutionary tree.
The additional information underscores that more reptile species are in danger, especially in Australia, Madagascar, and the Amazon basin, all places with a high diversity of reptiles and need to be targeted for extra conservation initiatives.
Furthermore, species-rich populations like geckos and elapids such as mambas, cobra snakes, and cobras, among others, are probably more threatened than the Global Reptile Assessment presently highlights these specie populations need to be the focus of more conservation attention.
Related information about reptiles in danger of extinction is shown on Golahura's YouTube video below:
Check out more news and information on Endangered Species in Science Times.
