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Issue: Vol. 5437 No. 2: 12 Apr. 2024
Type: Article
Published: 2024-04-12
DOI: 10.11646/zootaxa.5437.2.3
Page range: 223-244
Abstract views: 5
PDF downloaded: 0

A new species and new records of the spider genus Dubiaranea (Araneae, Linyphiidae) from southern Brazil and Uruguay, with an analysis of the potential distribution of the species

Sección Entomología; Facultad de Ciencias; Universidad de la República; Iguá 4225; PC 11400; Montevideo; Uruguay
Sección Entomología; Facultad de Ciencias; Universidad de la República; Iguá 4225; PC 11400; Montevideo; Uruguay
Universidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP); Departamento de Morfologia e Fisiologia Animal; Via de Acesso Prof. Paulo Donato Castellane km 05; 14884-900 Jaboticabal; São Paulo; Brazil
Laboratorio de Desarrollo Sustentable y Gestión Ambiental del Territorio; Facultad de Ciencias; Universidad de la República; Iguá 4225; PC 11400; Montevideo; Uruguay
Sección Entomología; Facultad de Ciencias; Universidad de la República; Iguá 4225; PC 11400; Montevideo; Uruguay
Sección Entomología; Facultad de Ciencias; Universidad de la República; Iguá 4225; PC 11400; Montevideo; Uruguay
Araneae Taxonomy favourability Neotropical Pampa biome Atlantic Forest

Abstract

Dubiaranea magatama Cajade, Hagopián & Rodrigues n. sp. is described from Uruguay, and southern Brazil based on males and females from several types of native forests, and a potential distribution for this species is modeled. The predicted model for this species indicates a Pampean province and southern Atlantic Forest biome distribution. Three variables contributed significantly to the model with positive influence: the spatial component, the proximity to large rivers, and the tree cover. Also, we provide new records of Dubiaranea difficilis (Mello-Leitão 1944) for Uruguay and a model of its potential distribution was performed. It showed that tree cover, the proximity to large rivers, the spatial component and precipitation/evapotranspiration constraints were recovered for the model with positive influence, expanding the potential distribution area previously proposed.

References

  1. Acevedo, P. & Real, R. (2012) Favourability: concept distinctive characteristics and potential usefulness. Naturwissenschaften, 99, 515–522. https://doi.org/10.1007/s00114-012-0926-0
  2. Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov, B.N. & Csaki, F. (Eds.), 2nd International Symposium on Information Theory, Tsahkadsor,
  3. Armenia, USSR. Akademiai Kiado, Budapest, pp. 267–281.
  4. Allouche, O., Tsoar, A. & Kadmon, R. (2006) Methodological insights. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43, 1223–1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x
  5. Alvarez-Padilla, F. & Hormiga, G. (2007) A protocol for digesting internal soft tissues and mounting spiders for scanning electron microscopy. Journal of Arachnology, 35, 538–542. https://doi.org/10.1636/Sh06-55.1
  6. Barbosa, A.M. (2015) fuzzySim: applying fuzzy logic to binary similarity indices in ecology. Methods in Ecology and Evolution, 6, 853–858. https://doi.org/10.1111/2041-210X.12372
  7. Barbosa, A.M., Brown, J.A., Jiménez-Valverde, A. & Real, R. (2016) modEvA: Model Evaluation and Analysis. R package. Version 2.0. Available from: https://CRAN.Rproject.org/package=modEvA (accessed 20 March 2024)
  8. Barbosa, A.M., Real, R., Muñoz, A.R. & Brown, J.A. (2015) New measures for assessing model equilibrium and prediction mismatch in species distribution models. Diversity and Distributions, 19 (10), 1333–1338. https://doi.org/10.1111/ddi.12100
  9. Benjamini, Y. & Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57, 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
  10. Bernardinis, G.B., Cobos, M.E., Brum, F.T., Marques, M.C.M., Townsend Peterson, A., Carlucci, M.B. & Zwiener, V.P. (2023) Ecological restoration and protection of remnants are key to the survival of the critically endangered Araucaria tree under climate change. Global Ecology and Conservation, 47, e02660. https://doi.org/10.1016/j.gecco.2023.e02668
  11. Bhatt, R. & Hossain, A. (2019) Concept and Consequence of Evapotranspiration for Sustainable Crop Production in the Era of Climate Change. IntechOpen. doi: 10.5772/intechopen.83707
  12. Buchhorn, M., Smets, B., Bertels, L., Lesiv, M., Tsendbazar, N.E., Masiliunas, D., Linlin, L., Herold, M. & Fritz, S. (2020) Copernicus Global Land Service: Land Cover 100m: Collection 3: epoch 2015: Globe. Version Version 3.0.1. [data set]. https://zenodo.org/records/3939038.
  13. Bulluck, L., Fleishman, E., Betrus, C. & Blair, R. (2006) Spatial and temporal variations in species occurrence rate affect the accuracy of occurrence models. Global Ecology and Biogeography, 15, 27–38. https://doi.org/10.1111/j.1466-822X.2006.00170.x
  14. Burnham, K.P. & Anderson, D.R. (2002) Model selection and multimodel inference. A practical information-theoretic approach. 2nd Edition. Springer, New York, XXVI + 488 pp. https://doi.org/10.1007/b97636
  15. Cala-Riquelme, F. (2021) Autodesk Sketchbook: An application that minimizes time and maximizes results of taxonomic drawing. Zootaxa, 4963 (3), 577–586. https://doi.org/10.11646/zootaxa.4963.3.10
  16. Cardoso, P., Stoev, P., Georgiev, T., Senderov, V. & Penev, L. (2016) Species Conservation Profiles compliant with the IUCN Red List of Threatened Species. Biodiversity Data Journal, 4, e10356. https://doi.org/10.3897/BDJ.4.e10356
  17. Costa, M.C., Hagopián, D., Simó, M.R., Guerrero, J.C. & Laborda, A. (2021) First description of the male of Mastophora extraordinaria Holmberg, 1876 (Araneae: Araneidae), with notes on the natural history and potential distribution of the species. Boletín de la Sociedad Zoológica del Uruguay, 30 (1), 14–24. https://doi.org/10.26462/30.1.2
  18. Danielson, J.J. & Gesch, D.B. (2011) Global multi-resolution terrain elevation data 2010 (GMTED2010): U.S. Geological Survey Open-File Report 2011-1073. Available from: https://pubs.usgs.gov/of/2011/1073/ (accessed 20 March 2024)
  19. Da Silva, B.A., Guerrero, J.C., Bidegaray-Batista, L. & Simó, M. (2020) Description of Latica, a new monotypic spider genus from Uruguay and Argentina (Araneae, Herpyllinae, Gnaphosidae): An integrative approach. Zoologischer Anzeiger, 288, 84–96. https://doi.org/10.1016/j.jcz.2020.07.006
  20. Ferretti, N., González, A. & Pérez-Miles, F. (2014) Identification of priority areas for conservation in Argentina: Quantitative biogeography insights from mygalomorph spiders (Araneae: Mygalomorphae). Journal of Insect Conservation, 18 (6), 1087–1096. https://doi.org/10.1007/s10841-014-9718-5
  21. Ghione, S., Coelho, L., Costa, F.G., García, L.F., González, M., Jorge, C., Laborda, A., Montes De Oca, L., Pérez-Miles, F., Postiglioni, R., Simó, M., Toscano-Gadea, C., Viera, C. & Aisenberg, A. (2017) Arácnidos prioritarios para la conservación en Uruguay. Boletín de la Sociedad Zoológica del Uruguay, 26 (1), 1–8. https://doi.org/10.26462/26.1.1
  22. Harrington, P. (2012) n.k. In: Bleiel, J. (Ed.), Machine Learning in Action Manning Publications, New York, New York, pp. 1–384.
  23. Hastie, T.J. & Pregibon, D. (1992) Chapter 6. Generalized linear models. In: Chambers, J.M. & Hastie, T.J. (Eds.), Statistical models in S. Wadsworth and Brooks/Cole, Baldwin, Georgia, pp. 309–376.
  24. Hormiga, G. (2000) Higher level phylogenetics of erigonine spiders (Araneae, Linyphiidae, Erigoninae). Smithsonian Contributions to Zoology 609, 1–160. https://doi.org/10.5479/si.00810282.609
  25. Hormiga, G. & Eberhard, W.G. (2023) Sheet webs of Linyphioid spiders (Araneae: Linyphiidae, Pimoidae): The light of diversity hidden under a linguistic basket. Bulletin of the Museum of Comparative Zoology, 163 (8), 279–415. https://doi.org/10.3099/MCZ75
  26. Hosmer, D.W. & Lemeshow, S. (2000) Applied logistic regression. 2nd Edition. John Wiley and Sons, Inc., New York, New York, 383 pp. https://doi.org/10.1002/0471722146
  27. Jiménez-Valverde, A., Acevedo, P., Barbosa, A.M., Lobo, J.M. & Real, R. (2013) Discrimination capacity in species distribution models depends on the representativeness of the environmental domain. Global Ecology and Biogeography, 22, 508–516. https://doi.org/10.1111/geb.12007
  28. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P. & Kessler, M. (2017) Climatologies at high resolution for the Earth land surface areas. Scientific Data, 4, 170122. https://doi.org/10.1038/sdata.2017.122
  29. Laborda, Á., De Oca, L.M., Pérez-Miles, F., Useta, G. & Simó, M. (2018) The spider fauna from Uruguay River islands: understanding its role in a biological corridor. Biodiversity Data Journal, 6, e27319. https://doi.org/10.3897/BDJ.6.e27319
  30. Laborda, Á., Hagopián, D., Teijón, S., Ginella, J., Guerrero, J.C. & Simó, M. (2020) The spider assemblage in a dendrofloristic hotspot from eastern Uruguay. Boletín de la Sociedad Zoológica del Uruguay, 29 (2), 73–85. https://doi.org/10.26462/29.2.4
  31. Legendre, P. & Legendre, L. (1998) Numerical Ecology. 2nd English Edition. Elsevier Science, Amsterdam, 853 pp.
  32. Lehner, B. & Grill, G. (2013) Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrological Processes, 27 (15), 2171–2186. https://doi.org/10.1002/hyp.9740
  33. Liu, C., White, M. & Newell, G. (2009) Measuring the accuracy of species distribution models: a review. 18th World IMACS/MODSIM Congress, Cairns, Australia. Available from: https://www.mssanz.org.au/modsim09/J1/liu_c_J1b.pdf (accessed 20 March 2024)
  34. Mcpherson, J., Jetz, W. & Rogers, D.J. (2004) The effects of species’ range sizes on the accuracy of distribution models: ecological phenomenon or statistical artifact? Journal of Applied Ecology, 41, 811–823. https://doi.org/10.1111/j.0021-8901.2004.00943.x
  35. Millidge, A.F. (1985) Some linyphiid spiders from South America (Araneae, Linyphiidae). American Museum Novitates, 2836, 1–78.
  36. Millidge, A.F. (1991) Further linyphiid spiders (Araneae) from South America. Bulletin of the American Museum of Natural History, 205, 1–199.
  37. Millidge, A.F. (1993) Further remarks on the taxonomy and relationships of the Linyphiidae, based on the epigynal duct confirmations and other characters (Araneae). Bulletin of the British Arachnological Society, 9, 145–156.
  38. Morrone, J.J., Escalante, T., Rodríguez-Tapia, G., Carmona, A., Arana, M. & Mercado-Gómez, J.D. (2022) Biogeographic regionalization of the Neotropical region: New map and shapefile. Anais da Academia Brasileira de Ciências, 94, e20211167. https://doi.org/10.1590/0001-3765202220211167
  39. Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burguess, N.D., Powell, G.V., Underwood, E.C., D’amico, J.A., Itoua, I., Strand, H.E., Morrison, J.C., Loucks, C.J., Allnutt, T.F., Ricketts, T.H., Kura, Y., Lamoreux, J.F., Wettengel, W.W., Hedao, P. & Kassem, K.R. (2001) Terrestrial Ecoregions of the World: A New Map of Life on Earth. A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience, 51 (11), 933–938. https://doi.org/10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2
  40. Qgis Development Team (2021) QGIS. Version 3.22. Geographic Information System. Open Source Geospatial Foundation Project. Available from: http://qgis.osgeo.org (accessed 20 March 2024)
  41. R Core Team (2021) R: A Language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available from: https://www.R-project.org/ (accessed 20 March 2024)
  42. Real, R., Barbosa, A.M. & Vargas, J.M. (2006) Obtaining environmental favourability functions from logistic regression. Environmental and Ecological Statistics, 13, 237–245. https://doi.org/10.1007/s10651-005-0003-3
  43. Roberts, M.J. (1987) The Spiders of Great Britain and Ireland. Vol. 2. Linyphiidae and checklist. Harley Books Publishers, Colchester, 204 pp.
  44. Rodrigues, E.N., Ott, R. & Brescovit, A.D. (2014) Redescription of Dubiaranea argenteovittata (Araneae: Linyphiidae), type species of the genus, and description of the male. Zoologia, 31, 275–280. https://doi.org/10.1590/S1984-46702014000300010
  45. Rubio, G.D., Rodrigues, E.N. & Acosta, L.E. (2010) Description of the male of the spider Dubiaranea difficilis (Araneae: Linyphiidae), with new records and modeling of its potential geographic distribution. Zootaxa, 2405 (1), 55–62. https://doi.org/10.11646/zootaxa.2405.1.3
  46. Silva-Moreira, T. & Hormiga, G. (2015) Redescription and phylogenetic placement of the Hispaniolan spider genus Lomaita Bryant, 1948 (Araneae, Linyphiidae). Zootaxa, 3920 (2), 249–64. https://doi.org/10.11646/zootaxa.3920.2.2
  47. Silva-Moreira, T. & Hormiga, G. (2022) Revision and phylogenetics of the Neotropical sheet weaving spider genus Diplothyron Millidge, 1991 (Araneae, Linyphiidae) and systematics of the MPME clade. Invertebrate Systematics, 36 (9), 781–848. https://doi.org/10.1071/IS21047
  48. Title, P.O. & Bemmels, J.B. (2018) ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography, 41 (2), 291–307. https://doi.org/10.1111/ecog.02880
  49. World Spider Catalog (2024) World Spider Catalog. Version 25. Natural History Museum Bern, Bern. Available from: http://wsc.nmbe.ch (accessed 20 February 2024) https://doi.org/10.24436/2