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Rate of description of new animal species and *that* Taxatoy graph

As part of the discussion on whether legacy biodiversity literature matters a graph from the following paper came up:

Sarkar, I., Schenk, R., & Norton, C. N. (2008). Exploring historical trends using taxonomic name metadata. BMC Evolutionary Biology, 8(1), 144. doi:10.1186/1471-2148-8-144


So, why is the Sarkar et al. graph bogus? Here is their graph (Fig. 3) for animals:

Taxatoy

This is the number of new animal species described each year, estimated by parsing taxonomic names and extracting the date in the taxonomic authority. There are two prominent "spikes" which are worrying. Sarkar et al. discuss the peak in 1994:

For example, the analyzed data indicate that a significant portion of the 1994 peak is due to an increase in descriptions of the family Cerambycidae, a large group of beetles.


So, 1994 was a bumper year for describing new species of Cerambycidae? Not quite. Taxatoy is based on names in uBio, and I have a local copy of most of these names. The Cerambycidae names contain lots of duplicate names that differ only in taxon authority. For example, searching the name Ancylocera macrotela on uBio finds:


Ancylocera macrotela
Ancylocera macrotela Aurivillius, 1912
Ancylocera macrotela BATES Henry Walter, 1880
Ancylocera macrotela Bates, 1880
Ancylocera macrotela Bates, 1885
Ancylocera macrotela Blackwelder, 1946
Ancylocera macrotela Chemsak & Linsley, 1970
Ancylocera macrotela Chemsak, 1963
Ancylocera macrotela Chemsak, 1964
Ancylocera macrotela Chemsak, Linsley & Mankins, 1980
Ancylocera macrotela Chemsak, Linsley & Noguera, 1992
Ancylocera macrotela Lameere, 1883
Ancylocera macrotela Maes & al., 1994
Ancylocera macrotela Monné & Giesbert, 1994
Ancylocera macrotela Monné, 1994
Ancylocera macrotela Noguera & Chemsak, 1996
Ancylocera macrotela Viana, 1971


These names are chresonyms. The original name is Ancylocera macrotela Bates, 1880 (you can see first publication of this name in BHL), the rest are subsequent citations of that name (gotta love taxonomy...).

Why the spike in 1994? I suspect that this is due to the publication in 1994 of "Checklist of the Cerambycidae and Disteniidae (Coleoptera) of the Western Hemisphere" by Miguel A Monné and Edmund F Giesbert. At least 8552 names from that checklist seem to have ended up in uBio, all with the date "1994". So the spike is an artefact. Similarly, the other peak (1912) corresponds to the publication of a checklist by Per Olof Christopher Aurivillius, which contributes over 3000 names.

One reason I was suspicious of the Taxatoy graph is that it doesn't look anything like the equivalent graph from the Index of Organism Names. After a bit of fussing I've grabbed data from the ION site, and from Taxatoy's Google Code repository and created the following chart:

Taxatoy version2

The data for this chart is on figshare http://dx.doi.org/10.6084/m9.figshare.156862. ION is an index of all new animal names, based on Zoological Record. I place more confidence in its data than data derived from uBio, but it clearly ION has its own issues (such as the gap after 1850, and the uneven sampling of the early years of taxonomy). The key point is that arguments on the temporal distribution of taxonomic descriptions (and the value of legacy literature) need to be aware that the data used is in pretty poor shape.

Update 2013-02-23
Jose Antonio Gonzalez Oreja pointed out in an email that the values for ION that I used were a little higher than those that appear on the ION web site. My script for retrieving those values hadn't quite worked. I've uploaded the corrected data to Figshare http://dx.doi.org/10.6084/m9.figshare.156862, updated the diagram above, and put the web calls I used to fetch the data on GitHub https://gist.github.com/rdmpage/5019153. The story doesn't change, but it helps to have the correct data.

Does the legacy biodiversity literature matter?

I've just come back from a pro-iBiosphere Workshop at Leiden where the role of "legacy literature" became the subject of some discussion. This continued on Twitter as Ross Mounce (@rmounce) and I went back and forth:
Ross was wondering whether we should invest much effort in extracting information from legacy literature, suggesting that this literature was of most interest to taxonomists, whereas other biologists will be more likely to find what they want from ever growing recent literature. I was arguing that because many taxa are poorly studied, the chances that you will find data on your organism in the recent literature is likely to be low, unless you study an economically or medically important taxon, or a model organism (many of which fit first categories). My view is based on papers such as Bob May's 1988 paper:
MAY, R. M. (1988). How Many Species Are There on Earth? Science, 241(4872), 1441-1449. doi:10.1126/science.241.4872.1441
In table 3 May lists the average number of papers per species in the period 1978-1987 across various taxonomic groups. Mammals averaged 1.8 papers per species, beetles averaged 0.01. This means that if you study a beetle species you have a 1/100 chance (on average) of finding a paper on your species in any given year (assuming all beetles are equal, which is clearly false). At this point perhaps we should define "legacy literature". In many ways the issue is not so much the age of the literature, but whether the literature was "born digital", that is, whether from it's authoring to publication the document has been in digital form, so the output is in a format (e.g., HTML, XML, or PDF that contains the document text) from which we can readily extract and mine the text. In contrast, documents that have been digitised from a physical medium (e.g., scans of pages) are less tractable because the text has to be extracted by OCR, and error-prone process. Given these errors is the effort worth it. At this point I should say that BHL is not using the best OCR technology available (my own experience suggests that ABBYY Online is much better), and our community is not making use of research on automating OCR correction). But the question is worth asking. In an effort to answer it, I've done a quick analysis of the PanTHERIA database:
Jones, K. E., Bielby, J., Cardillo, M., Fritz, S. A., O Dell, J., Orme, C. D. L., & Purvis, A. (2009). PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. (W. K. Michener, Ed.)Ecology, 90(9), 2648-2648. doi:10.1890/08-1494.1
PanTHERIA is a database assembled by Kate Jones (@ProfKateJones) and colleagues for comparative biologists (not taxonomists), and collects fundamental biological data about the best studied animal group on the planet (see May's paper above). In the metadata for the database there is a list of the 3143 publications they consulted to populate the database. Below is a table showing the distribution of the year in which these publications appeared:

Decade startingPublications
18401
18601
18901
190010
19104
192014
193048
194061
1950114
1960295
1970527
1980865
19901019
2000183
Pantheria The bulk of the papers came from the second half of the 20th century, and many of these are "legacy" in the sense that they are in archives like JSTOR, and hence the PDFs are based on scanned images and OCR. The oldest papers are from the 19th century, which is legacy by anyone's definition. My interpretation of this data is that even for a well-studied group such as mammals, the basic organismal-level data sought by comparative biologists is in the "legacy" literature. My suspicion is that if we attempt to build PanTHERIA-style databases for other, less well-studied taxa, the data (if it exists at all) will be found not in the modern literature (where the focus has long since moved on from the organism to genomics and system biology) but in the corpus of taxonomic and ecological literature that are being scanned and stored in digital archives.

Update
I've put the articles cited as data sources by the PanTHERIA database in a Mendeley group.

More GBIF specimen identifier strangeness

Continuing the theme of trying to map specimens cited in the literature to the equivalent GBIF records, consider the GBIF record http://data.gbif.org/occurrences/685591320, which according to GBIF is specimen "ZFMK 188762" (a [sic] holotype of Praomys hartwigi).

This is odd, because the original publication of this name (Eisentraut, M. 1968 .Beitrag zur Saugetierfauna von Kamerun. Bonner Zoologische Beitraege, 19:1-14, see PDF below) gives the type (p. 11) as "Museum A. Koenig, Kat. Nr. 68. 7").



The GBIF record includes links to images of ZFMK 188762, such as http://www.biologie.uni-ulm.de/cgi-bin/imgobj.pl?sid=T&lang=e&id=102323.

Bild pl

If we open this link we see that specimen is listed as "ZFMK-68.7", which matches the original description. "ZFMK-68.7" is a link to http://www.biologie.uni-ulm.de/cgi-bin/herbar.pl?herbid=188762&sid=T&lang=e, which is the record for this specimen in the SysTax database.

Note that this URL includes the number 188762, which is treated as the catalogue number by GBIF (i.e., "ZFMK 188762"). So, it seems that in the data provided by SysTax the primary key in that database (188762) has become the catalogue number in GBIF (I tried to verify this by clicking on the original provider message on the GBIF page but it failed to produce anything). This means any naive attempt to locate the specimen "ZFMK-68.7" in GBIF is going to fail because the harvesting and indexing as conflated a local primary key with the catalogue number that appears in publications that refer to this specimen.

Sometimes I think we are doing our level best to make retrieving data as hard as possible...