updates

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You may have run into it already, but we have a new blog for the Frost Entomological Museum. It’ll probably be a bit more active shortly (and certainly more active than our lab blog). Anyway, we just posted an advert for FOUR Frost Museum biodiversity interns, which is pretty exciting. We’re also about to start posting regularly on our progress to digitize the Beatty Odonata collection. Very exciting things happening with respect to those specimens! You can check out the first phase here: spreadsheet of verbatim collecting events, Beatty Mexico expeditions (1957–1959, 1962).

Image of Salto de Eyipantla, from a postcard collected by the Beattys during one of their expeditions to Mexico. Odonata were collected here in 1959 by them.

We also have a couple more papers that have been accepted, which are probably worth discussing in more detail. I’ll wait for the ‘online early’ version, though. One was described as a “tour de force”, which, I have to admit, feels pretty good.

the power of the Web, part 2

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Tacua speciosa (Illiger, 1800)

A quick follow-up to last night’s post. Here is the plate from Illiger’s original description of Tettigonia speciosa (now Tacua speciosa). The plate can be viewed in Wiedemann’s Archiv für die Zoologie, available through the Internet Archive. When you’re done with that surf the Biodiversity Heritage Library’s plates at flickr. That’s enough procrastination material for about a million years …

behold the power of the Web!

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Ah, the World Wide Web. Where would I be without its myriad useful tools?! Sites like BugGuide, flickr, Wikipedia, and twitter … it’s amazing that people could get things done prior to its existence! (Just as it’s amazing that I ever get anything done now because of its existence.)

I saw an opportunity to test the power of the Web today, when a video snippet from the The Daily Show came into my Twitter feed. At 2:00 Jon Stewart references an entomological factoid/stereotype in a joke about the state of gun control in the U.S. I’m a sucker for entomological references outside the world of science, especially ones that are wrong. So how did this one score?

First, the context: The U.S. Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF) is apparently prohibited from investigating gun dealers for inventory discrepancies more than once a year, and the reality is that they only investigate dealers every 17 years. Jon Stewart then joked that he assumed this situation was the result of the ATF not having enough agents/inspectors rather than their agents being cicadas. As Jon Stewart said next: “let that insect joke just wash over you…”

StewartCicada

Of course some periodical cicada species are famous for their synchronized 17-year life cycle—Magicicada septendecim (Linnaeus, 1758), M. septencassini (Fisher, 1851), and M. septendecula (Alexander & Moore, 1962)—but there are about 2,500 species of Cicadidae. A small minority of species take 17 years to develop. What about the species represented in the accompanying image? Doesn’t look like Magicicada to me, not that I’m an Auchenorrhyncha specialist, but at least it’s really a cicada!

Next steps: identify that species and find the science needed to bust this joke apart. It took me about 7 minutes to determine the species, and I literally know next to nothing about cicada taxonomy. A cropped screenshot, run through Google’s image  search came up empty, even after I supplemented the image file with key words, like ‘cicada’ and ‘cicada tropical red yellow’. I thought for sure they must’ve grabbed that image from Wikipedia and therefore would have some useful figure legend. Nope. My quick browse revealed nothing. What about flickr? Surely a lazy image search (or less lazy CC BY 3.0 search) would reveal the image and its associated data … nope. Ok, what about just regular Google searches for ‘cicada black yellow tropical’ etc. This must be a common cicada species if people at the Daily Show found an image! No luck. Back to Wikipedia to browse up and down the classification. (several pages’ worth of browsing) Hmm … Tosena looks close. Search flickr for Tosena and find this image. Not quite there but it seems like right ball park. The image caption mentions Borneo. Back to Google image search: ‘cicada malaysia‘. Ah ha! This cicada looks right:

Tacua speciosa (Illiger 1800). Does it have a 17-year life cycle? Wikipedia doesn’t help. Google Scholar? Seems like almost nothing is known of this species, or at least very little has been published. The Encyclopedia of Life’s Tacua speciosa page doesn’t offer too much information either. This was perhaps the most useful page I could find about the species—http://www.cicadamania.com/cicadas/tacua-speciosa/—which still leaves me hanging with respect to understanding this species’ natural history.

In summary, this exercise drove home two important points: 1) the Web is an increasingly useful tool. I was shocked at how little time it took me to determine this species (not sure I’m right, though!) and how many resources, both amateur and professional, I had at my disposal to get the answer. Again, I literally know next to nothing about cicada taxonomy. So, who needs keys?! (note to self: turn off comments for this post). 2) We know so little about the life histories of even the most conspicuous insects. This species is HUGE, colorful, charismatic, and frequently photographed (but not collected? Only 4 specimens listed in the Cicada Database) , yet we apparently know very little about its biology.

Not sure the Daily Show picked the best image to accompany their joke, but it’s certainly a beautiful insect (and it’s a cicada, so no taxonomic #fail). In the meantime let these beautiful images of Tacua speciosa wash over you.

suggested reading

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I found an old Google doc that my lab mates and I assembled after a long discussion a few years ago about the importance of staying current. (It was obvious at the time that several lab members hadn’t been, shall we say, voracious consumers of scientific literature.) We brainstormed a list of “important publications” and a recommended time table for individuals to visit these journals:

Make yourself read and understand at least one article per issue (published weekly):
Nature
Science
Proceedings of the National Academy of Sciences (PNAS)

Try to read and understand one article per issue:
Systematic Biology (bi-monthly)
PLoS ONE (published daily, read one article per month)
Evolution (monthly)
Scientific Reports

Worth browsing titles monthly for articles of interest (you will undoubtedly end up reading at least one article!):
Biology Letters
BMC Biology
BMC Evolutionary Biology
Current Biology
Journal of Morphology
Journal of Hymenoptera Research
Molecular Biology and Evolution
Molecular Phylogenetics and Evolution
PLoS Biology
PLoS ONE
Systematic Entomology
Trends in Ecology and Evolution
ZooKeys
Zootaxa

Worth browsing every 4-8 months (you will undoubtedly end up reading at least one article!):
Acta Zoologica
Arthropod Structure and Development
Arthropod Systematics and Phylogeny
Bioinformatics
Biological Journal of the Linnaean Society
BMC Bioinformatics
Cladistics
Collection Forum
Evolution and Development
Frontiers in Zoology
Genetics
Insect Molecular Biology
Invertebrate Systematics
Journal of Evolutionary Biology
Journal of Natural History
Journal of Zoological Systematics and Evolutionary Research
Molecular Ecology
Molecular Ecology Resources
Proceedings of the Entomological Society of Washington
Proceedings of the Royal Society Biological Sciences B
Zoologica Scripta
Zoological Journal of the Linnaean Society

Worth browsing annually:
Annual Review of Entomology (published in January)
Annual Review of Ecology and Evolution (published in January)

Seems pretty ambitious when I look at the list now. By my calculations this proposal requires one to read 36 or so articles every month—more than one article a day. I’m also not convinced your average student is going to find useful articles in each of these journals. Collection Forum, for example is a great journal for curators, but does a student need to be dissecting the fine details of collection management workflows? How to recycle alcohol? Maybe.

Now that I think of it … I almost want to grow this list—adding PeerJ, for example, after it gets cranking, or maybe even nontraditional resources, like figshare—but subdivide the reading responsibilities. Assign each lab member a set of journals that s/he is responsible for synthesizing in lab meeting. Divide and conquer.

How do you make sure you stay current? How would you alter this list or the proposed strategy? I’d love some feedback!

undergrad research opportunities at the Frost

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We’ve recently organized a series of projects designed to bring undergrads into the realms of research and outreach. Check ‘em out at the Office of Undergraduate Education’s Research Opportunities for Undergraduates website. I repost them here with a bit more elaboration. Contact me (adeans@psu.edu) if you’re interested! These projects are really just the tip of a gigantic iceberg of ideas we have. Here’s the full ad:

The Frost Entomological Museum research consortium seeks 3–4 undergraduate research assistants to assist with a variety of research projects related to insect biodiversity and evolution. Current projects focus primarily on specimen sorting, preparation, and curation, as well as how to capture and represent phenotype data (high resolution imaging and textual descriptions, for example). There are also opportunities for the development of museum exhibits and field guides. Possible projects include:

  1. Assembling pollinator display(s) for outreach events and for exhibition in the Frost Museum. Helpful skills to have: experience with crafts, excellent written English skills, attention to detail, interest in education and outreach. Skills to be acquired: insect collection and mounting techniques, effective display design, knowledge about local pollinators.
  2. Imaging insects under high resolution for diagnostic features, and aggregating diagnostic information for field guides/handouts. Helpful skills to have: photography skills, experience with Adobe Photoshop (or similar software), attention to detail, knowledge of LaTeX markup, ability to identify insect orders, knowledge of insect anatomy. Skills to be acquired: specimen handling, natural history collection informatics, knowledge of how to identify insects to family, photography of small objects, laser confocal or other microscopy.
  3. Digitizing specimen data, using the latest data standards and imaging tools. Helpful skills to have: accurate data entry (typing skills), attention to detail, knowledge of spreadsheets (MS Excel and Google Docs, for example), excellent communication skills. Skills to be acquired: specimen handling, natural history collection informatics, imaging methods (GigaPan photography and/or light micrographs, for example).
  4. Digitizing descriptions of new species. Images of specimens (holotypes in most cases) will be compiled and associated with original species descriptions. Helpful skills to have: accurate data entry (typing skills), attention to detail, excellent communication skills, information retrieval/library science (how to request an interlibrary loan, for example), knowledge of French and German. Skills to be acquired: image stacking methods, biodiversity informatics (especially phenotype ontologies), formal knowledge representation (OWL, for example).
  5. Adding and curating insect specimens in the teaching collection. The insect teaching collection needs to be expanded significantly and completely overhauled. Helpful skills to have: attention to detail, excellent communication skills, ability to identify insect orders, enthusiasm for field work. Skills to be acquired: insect specimen curation, knowledge of how to identify insects to family.
  6. 3D reconstruction of internal wasp anatomy. We have serially sectioned wasp specimens with a synchrotron and microCT and now need to annotate the slices and assemble them digitally into a 3D image (see example below, from this paper about treehopper morphology). Helpful skills to have: knowledge of anatomy, attention to detail. Skills to be acquired: 3D imaging techniques, exposure to Avizo software.

Students will receive research credit (1 credit for 3 research hours/week; up to 3 credits), training in relevant skills, and will participate in the activities organized by the greater Frost Museum community.

To apply, please send me (adeans@psu.edu) the following information:

  1. Your résumé, including relevant courses.
  2. Cover letter, including details about your research experience, current research interest(s), and career goals.
  3. Number of hours you are available to work weekly.

semantic phenotype annotations and descriptive taxonomy

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Stunning Evaniscus rufithorax specimen – one of the reasons I am enamored of these wasps.

Our lab group has published a small flurry of papers in the last two years, through which we highlight problems in the way that phenotype data are represented (visually and textually) in descriptive taxonomy and comparative morphology. I should probably make time to write these ideas up as blog posts, as I feel pretty strongly that the issues – if not our lab’s solutions – warrant deeper discussion. The two most recent and maybe most approachable syntheses are:

  1. Deans AR, Mikó I, Wipfler B, Friedrich F (2012) Evolutionary phenomics and the emerging enlightenment of arthropod systematics. Invertebrate Systematics 26: 323–330. doi: 10.1071/IS12063
  2. Deans AR, Yoder MJ, Balhoff JP (2012) Time to change how we describe biodiversity. Trends in Ecology and Evolution 27 (2): 78-84. doi: 10.1016/j.tree.2011.11.007

The latest installation, which yields real world examples of semantic phenotype annotations, in the context of descriptive taxonomy (see our TREE opinion) came out today in ZooKeys:

  1. Mullins PL, Kawada R, Balhoff JP, Deans AR (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1–38, doi: 10.3897/zookeys.223.3572

One thing we attempted to do in this paper is layer semantic phenotype annotations (composed in OWL, linked to relevant phenotype ontologies; see Deans et al. 2012) on top of our natural language character descriptions. The end result should be a more explicit textual representation of the phenotype represented in the character. For example, taxonomists, including us, are obsessed with measuring body parts. In this paper we measured the diameter of the lateral ocellus (LOD, for short) and compared it to the shortest distance between the lateral ocellus and the compound eye (OOL, for short):

The ocelli are the somewhat circular light-detecting structures on top of the wasp’s head. This individual has three of them – two lateral ocelli and one median ocellus. I annotated one lateral ocellus to (poorly) illustrate the measurements we made.

The ratio of these measurements in Evaniscus wasps is diagnostic at the species level. But how do we represent these data in a species description? Maybe something like “ocellar ocular line length as long or longer than lateral ocellus diameter” or maybe “OOL ≥ LOD” or maybe even as a character and its state “ocellar ocular line length vs. lateral ocellus diameter: as long or longer”. Or someone could be even more verbose and describe the character as “the shortest distance between the lateral ocellus and the margin of the compound eye equal to or perhaps shorter than the diameter of said ocellus”.

You see where I’m going. There are many different ways to represent this phenotype using prosaic natural language. Human readers probably would interpret most of these variations correctly and understand the character. But what happens when we pool all species descriptions for Hymenoptera (>145,000 described species) or, even better, for Insecta (>1,000,000 described species). Can humans read all these descriptions—composed by thousands of taxonomists with different backgrounds, preferences, eccentricities, or even different languages—and interpret the characters correctly? Almost definitely not. Yet data about ocellus size are potentially relevant to many scientific endeavors. Maybe I found an ocellus mutation in Drosophila melanogaster and want to know how common the phenotype is in nature. Or maybe I have a hypothesis about ocellus size (these structures are relatively larger in temperate insects, where light patterns vary greatly, according to season) that requires massive amounts of standardized phenotype annotations (connected to distribution data) for a proper test.

So, can we represent complex phenotypes using rigorous concepts and a standard syntax, like we do with DNA (i.e., IUPAC nucleotide symbols)? Our working—let’s call it draft—solution is to represent the phenotype in OWL, using multiple phenotype-relevant ontologies. The ocellus character state mentioned above looks like this and is applied to the specimen examined:

has_part some (ocular ocellar line and (is bearer of some (length and ((increased_in_magnitude_relative_to some (length and (inheres in some lateral ocellus))) or (similar_in_magnitude_relative_to some (length and (inheres in some lateral ocellus)))))))

Looks weird perhaps, but the goal is to write these annotations in a way that makes them understandable/retrievable by computers. These annotations would appear in addition to natural language prose in our new model for descriptive taxonomy. I’ll write a bit more about the approach after our next paper is finished, as we have a fair bit of discussion about advantages, limitations, and real utility (e.g., we do some basic queries across a larger species description data set).