> That said modeling relationships between taxonomic publications where
> the authors actually read the original species description, reviewed
> the type specimens, and thought about the actual species conscription is
appropriate.
This is the sort of things the Meta-Authorities would take into account when
selecting a "follow-this-treatment" Usage-Instance for the preferred
treatment of a name.
> Also consider that a large proportion of specimens are misidentified,
> and it occurs to me that modeling things like species occurrences as
> if they are Puma concolor (Linnaeus, 1771) sensu stricto is probably
> not appropriate. At best they are something like (Felis concolor /
> Puma concolor) with some significant level of error.
GNA can't helpw ith that directly -- but it can help indirectly. Imagine a_______________________________________________
service that takes ever specimen in a given collection's database, and runs
it against a mapping service as I described in the previous message. I can
easily imagine a GIS-based algorithm that finds "outliers" -- that is
occurrence records that appear to be outside the distribution based on the
occurrence records from other sources. A clver/robust such algorithm could
probably even discern whether the outlier likely represented a range
extension (e.g. poorly-known species, plausible extansion), vs. a
misidentification (e.g., well-known species and/or common
misidentification).
This would lead to a set of flagged records from the collection that might
be misidentified.
Rich
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