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Eresus are
considered one of the rarest spiders in Europe, despite
occurring in some of the best studied countries in the world,
and the conspicuous coloration of wandering males; which
considerably reduces under-sampling. The main concern is that
rare is often considered to be a synonym of endangered, but
there are seven recognized types of rarity, and not all of them
are equally correlated with extinction vulnerability. In order
to truly assess extinction risk, most experts regognize the
metrics of the IUCN Red List criteria. However, Red List
assessments are costly, time consuming and logistically complex.
With currents extinction rates, many species may even become
extinct before we are able to assess them. Time is therefore of
the essence, a pragmatic approach that speeds up the assessment
process and provides general trends of extinction across a wider
range of taxonomic groups is an urgent endeavour. The Sampled
Red List Index has been proposed as a solution to many of these
issues. However despite being a sampled approach our knowledge
is still skewed towards better-known groups, often with reduced
species diversity. I will discuss how machine learning can help
us address these issues, and how we can begin to answer specific
conservation questions, such as: Which spider families are more
threaten?. |
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