Satan’s Skeleton Revealed

content from an oral presentation July 15, 2017 at the annual Joint Meeting of Ichthyologists and Herpetologists in Austin, Texas, USA (http://conferences.k-state.edu/JMIH-Austin-2017/)Satan eurystomus Hubbs & Bailey 1947, the widemouth blindcat, is endemic to the deep Edwards Aquifer below San Antonio, TX. Monotypic Satan is one of four subterranean ictalurids, Trogloglanis pattersoni, Prietella pheatophila and P. lundbergi, that all exhibit common features of stygomorphs: loss of eyes and pigmentation, hypertrophy of some chemo and mechanosensory systems, small size, and variously reduced musculoskeletal system. Each species is distinctive in its own ways, and hypotheses about their phylogenetic positions range from separate ancestries of each scattered among the lineages of epigean ictalurids to exclusive monophyly of a strictly subterranean clade. Specimens of Satan are rare, thus we used highresolution CT scans to develop the first detailed, richly illustrated descriptive and comparative study of its skeleton. Satan exhibits typical and singular reductive features plus complex structures, e.g. 3 novel symphyses closing the posterior cranial fontanel; an unusually deep temporal fossa; and an ornately shaped dorsal fin locking spinelet. Satan shares 15 synapomorphies with other ictalurid troglobites: the stygomorphisms plus bone and joint reductions. Satan shares 11 synapomorphies with Pylodictis, including increased numbers of cephalic sensory pores and paired fin rays, and several features associated with predatory suction feeding: wide gape, depressed head, expanded branchiostegal and opercular membranes and anterior extension of epaxial muscle. Incomplete character information, including lack of molecular data for Satan and Trogloglanis, poor quality of available skeletal preparations for Trogloglanis and Prietella, and uncertain identifications of some specimens of Prietella impede construction of a complete dataset for phylogenetic analysis.Philadelphia Academy of Natural Sciences; University of Texas at Austin Biodiversity Center and College of Natural SciencesIntegrative Biolog

Update on taxonomic & conservation status of North American blindcats (Ictaluridae)

We provide an updated overview of the taxonomic and conservation status of all North American blind Ictalurids, and continuing efforts to better understand them. In Texas’ deep Edwards Aquifer under San Antonio, Satan eurystomus (Widemouth Blindcat) has not been collected since 1984, but fragments of Trogloglanis pattersoni (Toothless Blindcat) continue to appear occasionally from the only well still consistently available for sampling, providing material for its recently published complete mitogenome. A metabarcoding-based eDNA sampling project hoping to detect blindcats (and other taxa) is now in early testing in wells throughout the San Antonio area. Lack of access to wells remains a major roadblock for that effort, but we have promising outreach efforts developing that we hope will open doors for sampling in the near future. In the adjacent transboundary Edwards-Trinity Aquifer, new localities have been found for Prietella phreatophila (Mexican Blindcat) in both Coahuila and Texas, and a captive colony at San Antonio Zoo continues to thrive and grow. Two complete mitochondrial genomes from 2 specimens of this species using different methodologies are now available. We present new CT data that indicate specimens from a cave ~25 km N of the type locality of Prietella lundbergi (Phantom Blindcat) in Tamaulipas, México, initially reported as that species, represent an undescribed taxon. Multiple attempts by divers to obtain additional specimens of P. lundbergi from the type locality have failed, leaving the formalin-preserved holotype as the only specimen of that species.Integrative Biolog

Supplementary animation & Data for: Satan’s skeleton revealed: a tomographic and comparative osteology of Satan eurystomus, the subterranean Widemouth Blindcat (Siluriformes, Ictaluridae). Proceedings of the Academy of Natural Sciences of Philadelphia 165: 117-173

The animations and data archived here, derived from CT scans of two specimens of the Widemouth Blindcat, Satan eurystomus, supplement the content published separately as Lundberg, John G., Dean A. Hendrickson, Kyle Luckenbill, and Mariangeles Arce H. 2017. “Satan’s Skeleton Revealed: A Tomographic and Comparative Osteology of Satan Eurystomus, the Subterranean Widemouth Blindcat (Siluriformes, Ictaluridae).” Proceedings of the Academy of Natural Sciences of Philadelphia 165: 117-173. The files are also stored in an active Morphosource project (Skeletal Morphology of Stygobitic Ictalurids - http://morphosource.org/Detail/ProjectDetail/Show/project_id/398) where they may evolve and additional files may be added. Each file has its own additional description/caption.The Widemouth Blindcat, Satan eurystomus Hubbs and Bailey 1947, was the second of four stygobitic species of Ictaluridae discovered in the subterranean waters of southern Texas and northeastern Mexico. The skeletal anatomy of Satan has been scarcely known from a few, dated radiographs. Using additional radiographs and high resolution CT-datasets for two well-ossified specimens, we applied high-resolution X-ray computed tomography (HRXCT) to visualize, illustrate and describe the bony skeleton of Satan. We also provide an online archive of still and animated tomographic images of the skeletal anatomy of this little-known species. The skeleton and soft anatomy of Satan are distinctive. Twelve skeletal autapomorphies are described that singularly distinguish Satan within Ictaluridae and, probably in combination, from all other catfishes. Some of these are reductive losses or simplifications of skull bones (e.g. loss of one infraorbital bone; reduced ornamentation of the pterotic bone) and joint complexity (e.g. simple overlapping frontal-lateral ethmoid articulation; loosely ligamentous interopercle-posterior ceratohyal joint). Some of the autapomorphies are anatomically and perhaps developmentally complex (e.g. a novel series of three midline joints closing a middle span of the posterior cranial fontanel; a deeply excavated temporal fossa and an unusually enlarged interhyal bone). The tiny dorsal-fin spinelet (first lepidotrich) of Satan has a novel peaked and twisted shape. Ten apparent and exclusive synapomorphies within Ictaluridae gathered from this and previous studies suggest that Satan and Pylodictis are closest relatives. Most of these are functionally related to prey detection and suction feeding: fusion of the symphyseal mandibular sensory pores and increase in the number of preoperculo-mandibular canal pores; depressed, flattened heads and wide transverse mouths; prominent posterior process of the lateral ethmoid alongside and below the frontal bone margin; vertical and blade-like supraoccipital posterior process; unique arrangement of the parasagittal and occipital muscle-attachment crests on the skull roof; large triangular panel of integument within the operculum framed by the opercle, preopercle and interopercle bones; elongated posterior ceratohyal; and, form of the fourth supraneural and loss of its anterior nuchal plate. In contrast, fifteen synapomorphies recovered by Arce-H. et al. 2016, are confirmed suggesting that Satan is one of the four stygobitic ictalurids comprising a “Troglobites” subclade within the family: (Trogloglanis, Satan, Prietella phreatophila, P. lundbergi). These features include three stygomorphic and reduction apomorphies that are exclusive within Ictaluridae: loss of fully developed eyes and pigmentation, and simplification of the fifth vertebra and its joint with the Weberian apparatus. Twelve other synapomorphies shown by the Troglobites are also apparent homoplasies of character states shared with various other ictalurids. These include reductive characters such as shortened lateral line canal, reduced infraorbitals and underdeveloped or incomplete ossifications of the pterotic, supraoccipital, hyoid arch bones and transcapular ligament. Also, the Troglobites and various other ictalurids have: an adnate adipose-caudal fin, foreshortened anterior cranial fontanelle, reduced ventral wings of the frontal bone, replacement of bone by cartilage in hypohyal joints; incompletely ossified transcapular ligament, and consolidation of some hypural bones. Completing a full morphological character dataset across the Troglobites has been impeded by incomplete specimen preparations and study of P. lundbergi and to a lesser extent, P. phreatophila and Trogloglanis.We acknowledge assistance of K. McDermid, J. Krejca, P. Sprouse and B. Larsen of Zara Environmental LLC, Manchaca, TX for dedicated, but unfortunately unsuccessful, efforts to capture fresh specimens and help cleaning the museum specimen data. J. Maisano and M. Colbert of the University of Texas Digimorph Lab took the scans of the USNM specimen and an anonymous donor covered those costs. National Science Foundation Grant DEB 0315963 (Planetary Biodiversity Inventory: All Catfish Species Inventory) supported early groundwork that led to this project. K. Conway, Texas A&M University, Biodiversity Research and Teaching Collections (TCWC) provided specimen data and A. Summers, University of Washington, Friday Harbor Laboratories provided CT data for the TCWC specimen. University of Texas Austin, Department of Integrative Biology, Biodiversity Collections (Texas Natural History Collections - TNHC) supported the work of Hendrickson on this project, and The Academy of Natural Sciences, Department of Ichthyology, Philadelphia, PA supported the other authors' contributions. Smithsonian Institution, National Museum of Natural History, Department of Vertebrate Zoology, Division of Fishes, Washington, DC loaned us the USNM specimen and authorized scanning of it.Integrative Biolog

Appendix 19 Data and R Scripts

Online Appendix 19. R scripts for analysis as a zipped folder

Appendix 18 Ver2 final-results-summary

Online Appendix 18. Final results. Details for Figure 3

Appendix 8 Catfish-user-results

Online Appendix 8. Catfish user scores

Data from: Crowds replicate performance of scientific experts scoring phylogenetic matrices of phenotypes

Scientists building the Tree of Life face an overwhelming challenge to categorize phenotypes (e.g., anatomy, physiology) from millions of living and fossil species. This biodiversity challenge far outstrips the capacities of trained scientific experts. Here we explore whether crowdsourcing can be used to collect matrix data on a large scale with the participation of the non-expert students, or “citizen scientists.” Crowdsourcing, or data collection by non-experts, frequently via the internet, has enabled scientists to tackle some large-scale data collection challenges too massive for individuals or scientific teams alone. The quality of work by non-expert crowds is, however, often questioned and little data has been collected on how such crowds perform on complex tasks such as phylogenetic character coding. We studied a crowd of over 600 non-experts, and found that they could use images to identify anatomical similarity (hypotheses of homology) with an average accuracy of 82% compared to scores provided by experts in the field. This performance pattern held across the Tree of Life, from protists to vertebrates. We introduce a procedure that predicts the difficulty of each character and that can be used to assign harder characters to experts and easier characters to a non-expert crowd for scoring. We test this procedure in a controlled experiment comparing crowd scores to those of experts and show that crowds can produce matrices with over 90% of cells scored correctly while reducing the number of cells to be scored by experts by 50%. Preparation time, including image collection and processing, for a crowdsourcing experiment is significant, and does not currently save time of scientific experts overall. However, if innovations in automation or robotics can reduce such effort, then large-scale implementation of our method could greatly increase the collective scientific knowledge of species phenotypes for phylogenetic tree building. For the field of crowdsourcing, we provide a rare study with ground truth, or an experimental control that many studies lack, and contribute new methods on how to coordinate the work of experts and non-experts. We show that there are important instances in which crowd consensus is not a good proxy for correctness

Data from: Crowds replicate performance of scientific experts scoring phylogenetic matrices of phenotypes

Scientists building the Tree of Life face an overwhelming challenge to categorize phenotypes (e.g., anatomy, physiology) from millions of living and fossil species. This biodiversity challenge far outstrips the capacities of trained scientific experts. Here we explore whether crowdsourcing can be used to collect matrix data on a large scale with the participation of the non-expert students, or “citizen scientists.” Crowdsourcing, or data collection by non-experts, frequently via the internet, has enabled scientists to tackle some large-scale data collection challenges too massive for individuals or scientific teams alone. The quality of work by non-expert crowds is, however, often questioned and little data has been collected on how such crowds perform on complex tasks such as phylogenetic character coding. We studied a crowd of over 600 non-experts, and found that they could use images to identify anatomical similarity (hypotheses of homology) with an average accuracy of 82% compared to scores provided by experts in the field. This performance pattern held across the Tree of Life, from protists to vertebrates. We introduce a procedure that predicts the difficulty of each character and that can be used to assign harder characters to experts and easier characters to a non-expert crowd for scoring. We test this procedure in a controlled experiment comparing crowd scores to those of experts and show that crowds can produce matrices with over 90% of cells scored correctly while reducing the number of cells to be scored by experts by 50%. Preparation time, including image collection and processing, for a crowdsourcing experiment is significant, and does not currently save time of scientific experts overall. However, if innovations in automation or robotics can reduce such effort, then large-scale implementation of our method could greatly increase the collective scientific knowledge of species phenotypes for phylogenetic tree building. For the field of crowdsourcing, we provide a rare study with ground truth, or an experimental control that many studies lack, and contribute new methods on how to coordinate the work of experts and non-experts. We show that there are important instances in which crowd consensus is not a good proxy for correctness

Platydoras brachylecis, a new species of thorny catfish (Siluriformes: Doradidae) from northeastern Brazil

Platydoras brachylecis, new species, is described from coastal drainages of northeastern Brazil (Pindaré to Parnaíba rivers), and diagnosed from congeners by the unique combination of: pale yellow to white stripe beginning above orbits, continuing midlaterally on body and onto middle rays of caudal fin; skin in axil of each midlateral thorn without concentration of pigment forming small dark spot, midlateral scutes shallow (depth of 10th scute 8.8-11.9% of SL), and midlateral scutes on caudal peduncle distinctly separated by strip of skin from middorsal and midventral caudal-peduncle plates. Three additional species of Platydoras are recognized as valid: P. armatulus (lower Orinoco, Amazon and Paraguay-Paraná drainages), P. costatus (coastal drainages of Suriname and French Guiana), and P. hancockii (upper Orinoco, Negro, Essequibo and Demerara drainages). The nominal species P. dentatus and P. helicophilus are tentatively treated as junior synonyms of P. costatus. A key to species of Platydoras is provided

Appendix 3 Anemones-character-taxon-results

Online Appendix 3. Sea anemones character scores. For each character and taxon in the anemones matrix, we show the probability (“Estimate”) that a crowd member’s score would agree with the majority vote of the crowd. We also show the lower confidence interval on this probability (ci.lower), which is the crowd confidence score. Finally, we indicate whether the majority vote was correct, and compute an ROC curve for the crowd’s scores. The Threshold Plot worksheet provides a visualization of this information