Modern methods of species distribution are leaving out near-extinct amphibians of Africa, a new study has warned.

According to researchers at the University of York and colleagues, most popular tools for species distribution modelling don't account for a whopping 90 per cent of the African amphibian species listed as threatened on The IUCN Red List of Threatened Species.

Biologists use statistical methods to predict how climate change will affect distribution of species across continents. The present study shows that some creatures - such as amphibians living in Africa - are already so rare that these distribution models have ignored their existence.

The omission could lead to a decrease in their conservation efforts and can potentially skew the predictions of future animal distribution.

"Modern methods to predict species distributions under climate change typically leave out rare and threatened species - the ones that currently underpin global spending on conservation. This is because those species, almost by definition, have too few data for their spatial distributions to be modelled using standard tools. We looked at whether missing them out makes a difference for conservation priority setting, either now or under future climates," said Dr Philip Platts, lead author and Research Fellow with York's Environment Department, according to a news release.

For the study, the researchers used available data on 733 African amphibians in Sub-Saharan Africa. The team found that 400 of these animals have too few records to be used in species distribution modelling at continental scales. What's worse is that 92 percent of these amphibians are listed by IUCN as Vulnerable, Endangered or Critically Endangered.

African amphibians are just one such example of animals that are being omitted under the current statistical models. Researchers say that they chose amphibian species for the study because these creatures face multiple threats such as habitat loss, disease and climate change.

The study is published in the journal Diversity and Distributions.