References

Anderson, A. M., Friis, C., Gratto-Trevor, C. L., Morrison, R. G., Smith, P. A., & Nol, E. (2019). Consistent declines in wing lengths of Calidridine sandpipers suggest a rapid morphometric response to environmental change. PloS One, 14(4), e0213930. doi:10.1371/journal.pone.0213930.
Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26, 32–46. doi:10.1111/j.1442-9993.2001.01070.pp.x.
Andrew, R. L., Albert, A. Y. K., Renaut, S., Rennison, D. J., Bock, D. G., Vines, T. (2015). Assessing the reproducibility of discriminant function analyses. PeerJ, 3:e1137. doi:10.7717/peerj.1137
Artistotle, 350. Historia Animalium, translated by Thompson, D.W., edited by Smith, J.A., Ross, W.D. London, Oxford University Press.
Baroni Urbani, C. (1998). The number of castes in ants, where major is smaller than minor and queens wear the shield of the soldiers. Insectes Sociaux, 45, 315–333. doi:10.1007/s000400050091.
Bartlett, J. W., Frost, C. (2008). Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound in Obstetrics & Gynecology, 31, 466–475. doi:10.1002/uog.5256.
Baur, H., Leuenberger, C. (2011). Analysis of ratios in multivariate morphometry. Systematic Biology, 60, 813–825. doi:10.1093/sysbio/syr061.
Bland, J. M., Altman, D. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 327, 307–310. doi:10.1016/S0140-6736(03)15270-1.
Bond, J. E., Beamer, D. A. (2006). A morphometric analysis of mygalomorph spider carapace shape and its efficacy as a phylogenetic character (Araneae). Invertebrate Systematics, 20, 1–7. doi::10.1071/IS05041.
Boudinot, B. E. (2019). Toward phylomics in entomology: Current systematic and evolutionary morphology. Insect Systematics and Diversity, 3(6), 1–4. doi:10.1093/isd/ixz019.
Braga, J., Zimmer, V., Dumoncel, J., Samir, C., de Beer, F., Zanolli, C., Pinto, D., Rohlf, F. J., Grine, F. E. (2019). Efficacy of diffeomorphic surface matching and 3D geometric morphometrics for taxonomic discrimination of Early Pleistocene hominin mandibular molars. Journal of Human Evolution, 130, 21–35. doi:10.1016/j.jhevol.2019.01.009.
Brian, M. V., Brian, A. D. (1949). Observations on the taxonomy of the ants Myrmica rubra L. and M. laevinodis Nylander (Hymenoptera: Formicidae). Transactions of the Entomological Society of London, 100(14), 393–409.
Brown, W. L. Jr. (1943). A new metallic ant from the pine barrens of New Jersey. Entomological News, 54, 243–248.
Chuanromanee, T. S., Cohen, J. I., Ryan, G. L. (2019). Morphological Analysis of Size and Shape (MASS): An integrative software program for morphometric analyses of leaves. Applications in Plant Science, 7(9):e11288. doi:10.1002/aps3.11288.
Corrucini, R. S. (1988). Morphometric replicability using chords and cartesian coordinates of the same landmarks. Journal of Zoology, 215, 389–394. doi:10.1111/j.1469-7998.1988.tb02847.x.
Csősz, S., Heinze, J., Mikó, I. (2015). Taxonomic synopsis of the Ponto-Mediterranean ants of Temnothorax nylanderi species-group. PLoS One, 10(11), e0140000. doi:10.1371/journal.pone.0140000.
Csősz, S., Majoros, G. (2009). Ontogenetic origin of mermithogenicMyrmica phenotypes (Hymenoptera, Formicidae). Insectes Sociaux, 56, 70–76. doi:10.1007/s00040-008-1040-3.
DeBiasse, M. B., Ryan, J. F. (2019). Phylotocol: Promoting transparency and overcoming bias in phylogenetics. Systematic Biology, 68, 672–678. doi:10.7287/peerj.preprints.26585v4.
Esquerré, D., Donnellan, S., Brennan, I. G., Lemmon, A. R, Lemmon, E. M., Zaher, H., Grazziotin, G. G., Keogh, J. S. (2020). Phylogenomics, biogeography and morphometrics reveal rapid phenotypic evolution in pythons after crossing Wallace’s line. Systematic Biology, syaa024. doi:10.1093/sysbio/syaa024.
Fodor, E., Hâruţa, O., Milenković, I., Lyubenova, A., Tziros, G., Keča, N., Slavov, S., Diamandis, S., Kostov, K. (2015). Geometric morphometry of Phytophthora plurivora sporangia . Annals of Forest Research, 58, 275–294. doi:10.15287/afr.2015.411.
Fox, J., Weisberg, S. (2019). An R Companion to Applied Regression, Third edition. Sage, Thousand Oaks CA. https://socialsciences.mcmaster.ca/jfox/Books/Companion/.
Fox, N. S., Veneracion, J. J., Blois, J. L. (2020). Are geometric morphometric analyses replicable? Evaluating landmark measurement error and its impact on extant and fossil Microtus classification. Ecology and Evolution, 10, 3260–3275. doi:10.1002/ece3.6063.
Gotzek, D., Brady, S. G., Kallal, R. J., LaPolla, J. S. (2012). The importance of using multiple approaches for identifying emerging invasive species: the case of the rasberry crazy ant in the United States. PLoS One, 7(9), e45314. doi:10.1371/journal.pone.0045314.
Helm, B., Albrecht, H. (2000). Human handedness causes directional asymmetry in avian winglength. Animal Behaviour, 60, 899–902. doi:10.1006/anbe.2000.1534c.
Hennig, W. (1950). Grundzüge einer Theorie der phylogenetischen Systematil. Berlin, Deutscher Zentralverlag.
Hennig, W. (1966). Phylogenetic Systematics, translated by Davis, D., Zangerl, R. Urbana, University of Illinois Press.
Huelsenbeck J. P. (1998). Systematic bias in phylogenetic analysis: is the Strepsiptera problem solved? Systematic Biology, 47, 519–537.
Hita-Garcia, F., Lieberman, Z., Audisio, T. L., Liu, C., Economo, E. P. (2019). Revision of the highly-specialized ant genus Discothyrea(Hymenoptera: Formicidae) in the Afrotropics with x-ray microtomography and 3D cybertaxonomy. Insect Systematics and Diversity, 3, 1–84.
http://www.antarcticglaciers.org/glacial-geology/dating-glacial-sediments-2/precision-and-accuracy-glacial-geology/accessed 2020-03-05.
https://www.nist.gov/pml/nist-technical-note-1297/nist-tn-1297-appendix-d1-terminology/accessed 2020-03-05.
Inäbnit, T., Jochum, A., Kampschulte, M., Martels, G., Ruthensteiner, B., Slapnik, R., Nesselhauf, C., Neubert, E. (2019). An integrative taxonomic study reveals carychiid microsnails of the troglobitic genusZospeum in the Eastern and Dinaric Alps (Gastropoda, Ellobioidea, Carychiinae). Organisms Diversití and Evolution 19:135–177.
Johnson, L., Mantle, B.L., Gardner, J.L., Backwell, P.R.Y. (2013). Morphometric measurements of dragonfly wings: the accuracy of pinned, scanned and detached measurement methods. ZooKeys, 276:77–84.
Jones, C. J., Edwards, K. J., Castiglione, S., Winfield, M. O., Sala, F, Van der Wiel, C, … Karp, A. (1998). Reproducibility testing of AFLPs by a network of European laboratories. pp. 191–192 in Karp A., Isaac, P.G. and Ingram D.S. (Eds) Molecular tools for screening biodiversity. London, New York, Melbourne, Madras, Chapman & Hall.
Keklikoglou, K., Faulwetter, S., Chatzinikolaou, E., Wils, P., Brecko, J., Kvaček, … Arvanitidis, C. (2019). Micro-computed tomography for natural history specimens: a handbook for best practice protocols. European Journal of Taxonomy, 522:1–55.
Klingenberg, C. P. (2011). MorphoJ: an integrated software package for geometric morphometrics. Molecular Ecology Resources, 11:353–357.
Klingenberg, C. P. (2015). Analyzing fluctuating asymmetry with geometric morphometrics: concepts, methods, and applications. Symmetry, 7:843–934.
Legendre, P., Gallagher, E. D. (2001). Ecologically meaningful transformations for ordination of species data. Oecologia, 129:271–280.
Lessells, C. M., Boag, P. T. (1987). Unrepeatable repeatabilities, a common mistake. Auk, 104:116–121.
Lewis, P. O. (2001). A likelihood approach to estimating phylogeny from discrete morphological character data. Systematic Biology, 50:913–925.
Linnaeus, C. (1758). Systema naturae per regna tria naturae, secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Tomus I. Editio decima, reformata. Holmiae [= Stockholm], Laurentii Salvii.
Lösel, P., Heuveline, V. (2016). Enhancing a diffusion algorithm for 4D image segmentation using local information. Proceedings of International Society for Optics and Photonics, 9784:1–11, doi: 10.1117/12.2216202.
Mahendiran, M., Parthiban, M., Azeez, P. A., Nagarajan, R. (2018). In situ measurements of animal morphological features: A non-invasive method. Methods in Ecology and Evolution, 9:613–623.
McMullin, R. T., Maloles, J. R., Selva, S. B., Newmaster, S. G. (2018). A synopsis of Chaenotheca in North America, including a new species from southern Ontario, C. selvae , supported by morphometric analyses. Botany, 96:547–553.
Michener, C. D., Sokal, R. R. (1957). A quantitative approach to a problem in classification. Evolution, 11:130–162.
Miller, M. I., Priebe, C. E., Qiu, A., Fischl, B., Kolasny, A., Brown, T., … Buckner R. L. (2009). Collaborative computational anatomy: an MRI morphometry study of the human brain via diffeomorphic metric mapping. Human Brain Mapping, 30:2132–2141.
Mutanen, M., Pretorius, E. (2007). Subjective visual evaluation vs. traditional and geometric morphometrics in species delimitation: a comparison of moth genitalia. Systematic Entomology, 32:371–386.
Nakagawa, S., Schielzeth, H. (2010). Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biological Reviews, 85:935–956.
Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., … Wagner, H. (2019). vegan: Community Ecology Package. R package version 2.5–6. https://CRAN.R-project.org/package=vegan
Oxnard, C. E. (1983). Multivariate statistics in physical anthropology: testing and interpretation. Zeitschrift für Morphologie und Anthropologie, 73:237–278.
Parins-Fukuchi, C. (2017). Use of continuous traits can improve morphological phylogenetics. Systematic Biology, 67:328–339.
Parins-Fukuchi, C. (2020). Mosaic evolution, preadaptation, and the evolution of evolvability in apes. Evolution, 74:297–310.
Phexell, E., Åkesson, A., Söderberg, M., Bolejko, A. (2019). Intra-and inter-rater reliability in a comparative study of cross-sectional and spiral computed tomography pelvimetry methods. Acta Radiologica Open, 8:2058460119855187.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Randers, J. (2012). 2052 – A Global Forecast for the Next Forty Years. Chelsea Green Publishing, Vermont, 416 pp.
Remane, A. (1952). Die grundlagen des natürlichen Systems, der vergleichenden Anatomie und der Phylogenetik. Akademische Verlagsgesellschaft Geest und Portig, Leipzig.
Rensch, B. (1947). Neuere Probleme der Abstammunglehre die Transspezifische Evolution. Ferdinand Enke, Stuttgart. Pp. 407.
Richter, A., Keller, R. A., Rosumet, F. B., Economo, E. P., Hita Garcia, F., Beutel, R. G. (2019). The cephalic anatomy of the ant speciesWasmannia affinis (Formicidae, Hymenoptera, Insecta) and its evolutionary implications. Arthropod Structure & Development, 49:26–49.
Ridgway, G. R., Henley, S. M. D., Rohrer, J. D., Scahill, R. I., Warren, J. D., Fox, N. C. (2008). Ten simple rules for reporting voxel-based morphometry studies. NeuroImage, 40:149–1435.
Salganik, M. J. Lundberg, I., Kindel, A. T., Ahearn, C. E., Al-Ghoneim, K., Almaatouq, A., … Datta, D. et al. (2020). Measuring the predictability of life outcomes with a scientific mass collaboration. Proceedings of the National Academy of Sciences, 117:8398–8403.
Sarnat, E. M., Hita-Garcia, F., Dudley, K., Liu C., Fischer, G., Economo, E. P. (2019). Ready Species One: exploring the use of augmented reality to enhance systematic biology with a revision of FijianStrumigenys (Hymneoptera: Formicidae). Insect Syst. Diversity 3:1–43.
Savriama, Y. (2018). A step-by-step guide for geometric morphometrics of floral symmetry. Frontiers in Plant Science, 9, 1433. doi:10.3389/fpls.2018.01433
Schlick-Steiner, B. C., Seifert, B., Stauffer, C., Christian, E., Crozier, R. H., Steiner, F. M. (2007). Without morphology, cryptic species stay in taxonomic crypsis following discovery. TREE,22:391–392.
Schlick-Steiner, B. C., Steiner, F. M., Moder, K., Seifert, B., Sanetra, M., Dyreson, E., Stauffer, C., Christian, E. (2006). A multidisciplinary approach reveals cryptic diversity in Western PalearcticTetramorium ants (Hymenoptera: Formicidae). Molecular Phylogenetics and Evolution, 40:259–273.
Schlick-Steiner, B. C., Steiner, F. M., Seifert, B., Stauffer, C., Christian, E., Crozier R. H. (2010). Integrative taxonomy: a multisource approach to exploring biodiversity. Annual Review of Entomology, 55:421–438.
Seifert, B. (1992). A taxonomic revision of the Palaearctic members of the ant subgenus Lasius s.str. (Hymenoptera: Formicidae). -Abh. Ber. Naturkundemus. Görlitz. 66:1–67.
Seifert, B. (2002). How to distinguish most similar insect species - improving the stereomicroscopic and mathematical evaluation of external characters by example of ants. Journal of Applied Entomology, 126:445–454.
Seifert, B. (2003). The ant genus Cardiocondyla (Insecta: Hymenoptera: Formicidae) - a taxonomic revision of the C. elegans , C. bulgarica , C. batesii , C. nuda ,C. shuckardi , C. stambuloffii , C. wroughtonii ,C. emeryi , and C. minutior species groups. Ann. Naturhist. Mus. Wien, B Bot. Zool. 104:203–338.
Seifert, B. (2009). Cryptic species in ants (Hymenoptera: Formicidae) revisited: we need a change in the alpha-taxonomic approach. Myrmecological News, 12:149–166.
Shingleton, A. W., Frankino, W. A., Flatt, T., Nijhout, H. F., Emlen, D. J. (2007). Size and shape: the developmental regulation of static allometry in insects. BioEssays, 29(6):536–548.
Sokal, R. R., Sneath, P. H. N. A. (1963). Principles of Numerical Taxonomy. San Francisco, W. H. Freeman.
Steiner, F.,M., Schlick-Steiner, B.,C., Moder, K. (2006). Morphology-based cyber identification engine to identify ants of theTetramorium caespitum /impurum complex (Hymenoptera: Formicidae). Myrmecologische Nachrichten, 8:175–180.
Takacs, P., Vital, Z., Ferincz, Á., Staszny, Á. (2016). Repeatability, reproducibility, separative power and subjectivity of different fish morphometric analysis methods. PLoS One, 11:e0157890.
Taylor, B. N, Kuyatt, C. E. (2001). Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, [Online]. Available: http://physics.nist.gov/TN1297 [2020, March 5]. National Institute of Standards and Technology, Gaithersburg, MD. Originally published as Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, Barry N. Taylor and Chris E. Kuyatt, NIST Technical Note 1297 (1994 Edition).
Thompson, D. W. (1917). On Growth and Form. Cambridge University Press, London.
Tomiya, S., Meachen, J. A. (2018). Postcranial diversity and recent ecomorphic impoverishment of North American gray wolves. Biological Letter, 14:20170613.
Venables, W. N., Ripley, B. D. (2002). Modern Applied Statistics with S . Springer-Verlag.
Villemant, C., Simbolotti, G., Kenis, M. (2007). Discrimination ofEubazus (Hymenoptera, Braconidae) sibling species using geometric morphometrics analysis of wing venation. Systematic Entomology, 32:625–634.
Yoder, M. J., Mikó, I., Seltmann, K. C., Bertone, M. A., Deans, A. R. (2010). A gross anatomy ontology for Hymenoptera. PLoS ONE, 5:e15991.
Ward, P. S. (1999). Systematics, biogeography and host plant associations of the Pseudomyrmex viduus group (Hymenoptera: Formicidae), Triplaris-and Tachigali-inhabiting ants. Zoological Journal of the Linnean Society, 126:451–540.
Wolak, M. E., Fairbairn, D. J., Paulsen, Y. R. (2012). Guidelines for estimating repeatability. Methods in Ecology and Evolution, 3:129–137.
Wright, A. M. (2019). A systematist’s guide to estimating Bayesian phylogenies from morphological data. Insect Systemaics and Diversity, 3:1–14.
Yezerinac, S. M., Lougheed, S. C., Handford, P. (1992). Measurement error and morphometric studies: statistical power and observer experience. Systematic Biology, 41:471–482.
Table legends
Table 1.
Verbatim trait definitions for morphometric character recording. Abbreviations, definitions and descriptions of morphometric characters are given. This standard protocol was followed by each gauger.
Table 2.
Intraclass correlation coefficients (R), upper and lower bounds, number of cases (n) and average trait sizes are given for each observed characters. Descriptions for abbreviations of morphometric characters are as follows: CL: Head capsule length, CW: Width of head including eyes, CWb: Width of head capsule, FRS: Frontal carinae width ML: Mesosoma length; MW: mesosoma width; NOH: Maximum height of the petiolar node, NOL: Length of the petiolar node, PEH: Maximum petiole height, PEL: Petiolar lenght, PEW: Petiole width, PoOC: Postocular distance, PPH: Postpetiole height; PPL: Postpetiole length, PPW: Postpetiole width, SL: Scape length, SPBA: Spine base width, SPST: Spine length, SPTI: Propodeal spine tip distance, STPL: Propodeal spine tip erection.
Table 3.
Repeatability scores (R) calculated for gaugers. Gauger information in the table follows this format: experience in an insect group, estimated number of individuals measured in a career, maximum magnification of the microscope used, separated by underscores. ICC: intraclass correlation coefficient calculated from the repeated measurements. The gaugers are aligned according to the sequence of their contribution. Gauger alphabet codes in triad format: A: MYRM_9000_100x, B: DIPT_0_100x, C: MYRM_5000_288x, D: MYRM_60000_360x, E: MYRM_500_50x, F: MYRM_500_50x, G: MYRM_450_50x, H: WASP_1000_230x, I: WASP_0_230x, J: MYRM_300_100x, K: MYRM_300_100x.
Figure captions
Fig. 1.
Precision versus accuracy. The bullseye represents the value of the measurand. Accuracy is indicated by closeness to the bullseye—measurements closer to the bullseye are more accurate. Precise measurements are tightly clustered. Accurate and precise measurements are tightly clustered in the bullseye. Graphics produced and used with permission from Dr. Bethan Davies (antarcticglaciers.org).
Fig. 2.
Illustrations for morphometric characters. Head in dorsal view (a) with measurement lines for CL: Head capsule length, CW: Width of head including eyes, CWb: Width of head capsule, PoOC: Postocular distance and SL: Scape length; frontal region of the head dorsum (b) with measurement lines for FRS: Frontal carinae width (red accessory lines and arrows identify the torular lamella); lateral view of mesosoma (c) with measurement line for ML: Mesosoma length; lateral view of propodeum, petiole, and postpetiole (d) with measurement lines for STPL: Propodeal spine tip erection, NOH: Maximum height of the petiolar node, NOL: Length of the petiolar node, PPL: Postpetiole length, and SPST: Spine length; dorsal view of mesosoma (e) with measurement lines for MW: mesosoma width; lateral view of propodeum, petiole, and postpetiole (f) with measurement lines for PEH: Maximum petiole height, PEL: Petiolar lenght, and PPH: Postpetiole height; dorsal view of propodeum, petiole, and postpetiole (g) with measurement lines for SPBA: Spine base width, SPTI: Propodeal spine tip distance, PEW: Petiole width, and PPW: Postpetiole width. Detailed verbatim trait definitions for characters are given in Table 1.
Fig. 3a,b.
Ordination biplot for Principal Component Analysis based on (a) species identity and (b) the accuracy of the measurement. Black and red dots represent repeated observations on the same objects, while black dots represent Nesomyrmex devius , and red dots represent N. hirtellus . Convex hulls for spatial distribution of observations within morphospace represent (a) species and (b) gaugers. Descriptions for abbreviations of morphometric characters (red letters) are as follows: CL: Head capsule length, CW: Width of head including eyes, CWb: Width of head capsule, FRS: Frontal carinae width ML: Mesosoma length; MW: mesosoma width; NOH: Maximum height of the petiolar node, NOL: Length of the petiolar node, PEH: Maximum petiole height, PEL: Petiolar lenght, PEW: Petiole width, PoOC: Postocular distance, PPH: Postpetiole height; PPL: Postpetiole length, PPW: Postpetiole width, SL: Scape length, SPBA: Spine base width, SPST: Spine length, SPTI: Propodeal spine tip distance, STPL: Propodeal spine tip erection. Gauger alphabet codes (B) in triad format: A: MYRM_9000_100x, B: DIPT_0_100x, C: MYRM_5000_288x, D: MYRM_60000_360x, E: MYRM_500_50x, F: MYRM_500_50x, G: MYRM_450_50x, H: WASP_1000_230x, I: WASP_0_230x, J: MYRM_300_100x, K: MYRM_300_100x. Compositional differences between treatments expressed as the results of the PERMANOVA (coefficient of determination, F and p values, details in the text).
Fig. 4.
The correlogram of the studied variables for testing repeatability by the Spearman rank correlation test. The size of each bubble is proportional to the estimated correlation value (r). The heat chart on the right shows the color correspondence for r values.