Advertisement

Mammalian Biology

, Volume 81, Issue 1, pp 73–81 | Cite as

A test of the Resource’s and Bergmann’s rules in a widely distributed small carnivore from southern South America, Conepatus chinga (Molina, 1782) (Carnivora: Mephitidae)

  • Mauro I. SchiaffiniEmail author
Original Investigation

Abstract

Bergmann’s rule is one of the most known biological rules and relates the body size variation to changes in latitude or temperature. Most recently, a “resource rule” had been presented, which explains several trends in body size, as a consequence of availability of resources. South American Conepatus chinga is one of the most widespread small carnivores in the Neotropics, being geographically distributed from Perú and Brazil to southern Argentina and Chile. This widely distributed species encounters a high environmental variability, which could affect body size and morphological variations. Here, I analyze geographical patterns of variation in body size and morphology estimated using a geometric morphometric approach from museum specimens. The associations between geographical patterns of variation in body size and morphometry and climatic and/or environmental variables were evaluated, using several databases and multiple regressions and redundancy analysis. Throughout the study, the presence of spatial autocorrelation was analyzed, and Spatial Eigenvector Mapping (SEVM) was used. The arid diagonal was identified as containing the smaller specimens of C. chinga, primarily related to net primary productivity (NPP). Bergmann’s rule seems not to be valid for this species. Instead, evidence seems to support the “resource rule” as the primarily explanation for body size variation. A lower amount of morphological variation was explained by NPP, mainly related to relative size variation of premolar and molars.

Keywords

Bergmann’s rule Geometric morphometrics Molina’s hog-nosed skunks Resource rule Spatial autocorrelation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abraham, E., del Valle, H.F., Roig, F., Torres, L, Ares, J.O., Coronato, F., Godagnone, R., 2009. Overview of the geography of the Monte Desert biome (Argentina). J. Arid Environ. 73, 144–153.CrossRefGoogle Scholar
  2. Akaike, H., 1973. Information theory as an extension of the Maximum Likelihood Principle. In: Petrov, B.N., Csaki, F. (Ed.), Second International Symposium on Information Theory. Akademiai Kiado, Budapest, pp. 267–281.Google Scholar
  3. Ashton, K.G., 2002. Do amphibians follow Bergmann’s rule? Can. J. Zool. 80,708-716.CrossRefGoogle Scholar
  4. Ashton, K.G., Tracy, M.C., de Queiroz, A., 2000. Is Bergmann’s rule valid for mammals? Am. Nat. 156, 390–415.Google Scholar
  5. Bergmann, C, 1847. Ueber die Verhältnisse der Wärmeökonomie derThiere zu ihrer Grösse. Gottinger Studien 3, 595–708.Google Scholar
  6. Blackburn, T.M., Gaston, K.J., Loder, N., 1999. Geographic gradients in body size: a clarification of Bergmann’s rule. Divers. Distrib. 5, 165–174.CrossRefGoogle Scholar
  7. Blackburn, T.M., Hawkins, B.A., 2004. Bergmann’s rule and the mammal fauna of northern North America. Ecography 27, 715–724.CrossRefGoogle Scholar
  8. Bortolotto Peters, F., de Oliveira Roth, P.R., Christoff, A.U., 2011. Feeding habits of Molina’s hog-nosed skunk, Conepatus chinga (Carnivora: Mephitidae) in the extreme south of Brazil. Zoologia 28, 193–198.CrossRefGoogle Scholar
  9. Bruniard, E.D., 1982. La diagonal áridaargentina: un límiteclimático real. Rev. Geogr. 95, 5–20.Google Scholar
  10. Burkart, R., Bárbaro, N.O., Sánchez, R.O., Gómez, D.A., 1999. Eco-Regiones de la Argentina. Presidencia de la Nación, Secretaría de Recursos Naturales y Desar-rollo Sustentable. Programa Desarrollo Institucional Ambiental. Componente Política Ambiental, 43.Google Scholar
  11. Burnham, K.P., Anderson, D.R., 2002. Model Selection and Multimodel Inference: A Practical Information—Theoretical Approach, 2nd ed. Springer, New York.Google Scholar
  12. Castillo, D.F., Lucherini, M., Luengos Vidal, E.M., Manfredi, C, Casanave, E.B., 2011. Spatial organization of Molina’s hog-nosed skunk (Conepatus chinga) in two landscapes of the Pampas grassland of Argentina. Can. J. Zool. 89, 229–238.CrossRefGoogle Scholar
  13. Chatterjee, S., Hadi, A.S., 2006. Analysis of Collinear Data, Regression Analysis by Example. John Wiley & Sons, pp. 221–258.Google Scholar
  14. Cusens, J., Wright, S.D., McBride, P.D., Gillman, L.N., 2012. What is the form of the productivity-animal-species-richness relationship? A critical review and metaanalysis. Ecology 93, 2241–2252.PubMedCrossRefPubMedCentralGoogle Scholar
  15. Díaz, M.M., Lucherini, M., 2006. Orden Carnivora. In: Barquez, R.M., Díaz, M.M., Ojeda, R.A. (Ed.), Mamíferos de Argentina, Sistemáticay Distribución. Sociedad Argentina para el Estudio de los Mamíferos, Tucumán, pp. 89–107.Google Scholar
  16. Diniz-Filho,JAF., Bini, L.M., 2005. Modelling geographic patterns in species richness using eigenvector-based spatial filters. Glob. Ecol. Biogeogr. 14, 177–185.CrossRefGoogle Scholar
  17. Diniz-Filho,JAF., Rangel,T.F.LV.B., Bini, L.M., 2008. Model selection and information theory in geographical ecology. Glob. Ecol. Biogeogr. 17, 479–488.CrossRefGoogle Scholar
  18. Donadio, E., Di Martino, S., Aubone, M., Novaro, A.J., 2001. Activity patterns, home range, and habitat selection of the common hog-nosed skunk, Conepatus chinga (Mammalia, Mustelidae), in northwestern Patagonia. Mammalia 65, 49–54.CrossRefGoogle Scholar
  19. Donadio, E., Di Martino, S., Aubone, M., Novaro, A.J., 2004. Feeding ecology of the Andean hog-nosed skunk (Conepatus chinga) in areas under different land use in north-western Patagonia. J. Arid Environ. 56, 709–718.CrossRefGoogle Scholar
  20. Dormann, C.F., Elith, J., Bacher, S., Buchmann, C, Carl, G., Carré, G., García Mar-quéz, J.R., Gruber, B., Lafourcade, B., Leitão, P.J., Münkermüller, T., McClean, C, Osborne, P.E., Reineking, B., Schröder, B., Skidmore, A.K., Zurrell, D., Lautenbach, S., 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46.CrossRefGoogle Scholar
  21. Dragoo, J.W., 2009. Family Mephitidae (skunks). In: Wilson, D.E., Mittermeier, R.A. (Ed.), Handbook of the Mammals of the World, 1 Carnivores. Lynx editions in association with Conservation International and IUCN, Barcelona, pp. 532–563.Google Scholar
  22. Eva, H.D., Belward, A.S., de Miranda, E.E., di Bella, CM., Gonds, V., Huber, O., Jones, S., Sgrenzaroli, M., Fritz, S., 2004. A land cover map of South America. Glob. Change Biol. 10, 731–744.CrossRefGoogle Scholar
  23. ESRI, 2002. Arcview Version3.3. Environmental System Research Institute, Redlands (CA).Google Scholar
  24. Fernández, O.A., Busso, C.A., 1997. Arid and semi-arid rangelands: two thirds of Argentina. RALA Report 200, 41–60.Google Scholar
  25. Foley, J.A., Prentice, C, Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Glob. Biogeochem. Cy. 10, 603–628.CrossRefGoogle Scholar
  26. Fuller, T.K., Johnson, W.E., Franklin, W.L., Johnson, K.A., 1987. Notes on the patago-nian hog-nosed skunk (Conepatus humboldtii) in southern Chile. J. Mammal. 68, 864–867.CrossRefGoogle Scholar
  27. Gardezi, T., daSilva, J., 1999. Diversity in relation to body size in mammals: a comparative study. Am. Nat. 153, 110–123.PubMedCrossRefPubMedCentralGoogle Scholar
  28. Garreaud, R.D., Vuille, M., Compagnucci, R., Marengo, J., 2009. Present-day South American climate. Palaeogeogr. Palaeoclimatol. Palaeoecol. 281, 180–195.CrossRefGoogle Scholar
  29. Gay, S.W., Best, T.L., 1996. Relationships between abiotic variables and geographic variation in skulls of pumas (Puma concolor: Mammalia, Felidae) in North and South America. Zool. J. Linn. Soc. 117, 259–282.CrossRefGoogle Scholar
  30. Geist, V., 1987. Bergmann’s rule is invalid. Can. J. Zool. 65, 1035–1038.CrossRefGoogle Scholar
  31. Graham, M., 2003. Confronting multicollinearity in ecological multiple regression. Ecology 84, 2809–2815.CrossRefGoogle Scholar
  32. Goodall, C, 1991. Procrustes methods in the statistical analysis of shape. J. R. Stat. Soc. 52, 285–339.Google Scholar
  33. Hijmans, R.J., Guarino, L., Mathur, P.Jarvis, A., Rojas, E., Cruz, M., Barrantes, I., 2005a. DIVA-GIS, Version 5., pp. 2.Google Scholar
  34. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005b. Very high resolution interpolated climate surfaces for global land areas. Int. J. Clim. 25, 1965–1978.CrossRefGoogle Scholar
  35. Huete, A., Didan, K., Miura, T., Rodríguez, E.P., Gao, X., Ferreira, L.G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 83, 195–213.CrossRefGoogle Scholar
  36. Johnson, A., 2006. Biogeographical parallels between plants and ants in North American deserts (Hymenoptera: Formicidae; Spermatophyta). Myrmecol. Nachrichten. 8, 209–218.Google Scholar
  37. Johnson, J.B., Omland, K.S., 2004. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108.PubMedCrossRefGoogle Scholar
  38. Kasper, C.B., Fontoura-Rodrigues, M.L., Cavalcanti, G.N., de Freitas, T.R.O., Rodrigues, F.H.G., de Oliveira, T.G., Eizirik, E., 2009. Recent advances in the knowledge of Molina’s Hog-nosed Skunk Conepatus chinga and Striped Hog-nosed Skunk C semistriatus in South America. Small Carnivore Conserv. 41, 25–28.Google Scholar
  39. Kasper, C.B., Soares, J.B.G., Freitas, T.R.O., 2012. Differential patterns of home range, net displacement and resting sites use of Conepatus chinga in southern Brazil. Mamm. Biol. 77, 358–362.CrossRefGoogle Scholar
  40. Klingenberg, C.P., 2011. MorphoJ: An integrated software package for geometric morphometrics. Mol. Ecol. Resour. 11, 353–357.PubMedPubMedCentralCrossRefGoogle Scholar
  41. Kucharik, C.J., Foley, J.A.,Delire,C, Fisher, V.A., Coe, M.T., Lenters, J.D., Young-Molling, C, Ramankutty, N., 2000. Testing the performance of a Dynamic Global Ecosystem Model: water balance, carbon balance, and vegetation structure. Glob. Biogeochem. Cy. 14, 795–825.CrossRefGoogle Scholar
  42. Kühn, I., Dormann, C.F., 2012. Less than eight (and a half) misconceptions of spatial analysis. J. Biogeogr. 39, 995–998.CrossRefGoogle Scholar
  43. Kullback, S., Leibler, R.A., 1951. On information and sufficiency. Ann. Math. Stat. 22, 79–86.CrossRefGoogle Scholar
  44. Lindstedt, S.L., Boyce, M.S., 1985. Seasonality, fasting endurance, and body size in mammals. Am. Nat. 125, 873–878.CrossRefGoogle Scholar
  45. Mancini, M.V., Paez, M.M., Prieto, A.R., Stutz, S., Tonello, M., Vilanova, I., 2005. Mid-Holocene climatic variability reconstruction from pollen records. Quat. Int. 132, 47–59.CrossRefGoogle Scholar
  46. McNab, B.K., 1971. On the ecological significance of Bergmann’s rule. Ecology 52, 845–854.CrossRefGoogle Scholar
  47. McNab, B.K., 1974. The energetic of endotherms. Ohio J. Sci. 74, 370–380.Google Scholar
  48. McNab, B.K., 2010. Geographic and temporal correlations of mammalian size reconsidered: a resource rule. Oecología 164, 13–23.PubMedCrossRefGoogle Scholar
  49. Martínez, PA, Marti, DA, Molina, W.F., Bidau, C.J., 2013. Bergmann’s rule across the equator: a case study in Cerdocyon thous (Canidae). J. Anim. Ecol. 82, 997–1008.PubMedCrossRefGoogle Scholar
  50. Medina, A.I., Marti, DA, Bidau, J.C., 2007. Subterranean rodents of the genus Ctenomys (Caviomorpha, Ctenomyidae) follow the converse to Bergmann’s rule. J. Biogeogr. 34, 1439–1454.CrossRefGoogle Scholar
  51. Medina, C.E., Díaz, C.V., Delgado, FA., Ynga, G.A., Zela, H.F., 2009. Dieta de Conepatus chinga (Carnivora: Mephitidae) en un bosque de Polylepis del departamento de Arequipa. Perú. Rev. Peru. Biol. 16, 183–186.Google Scholar
  52. Meiri, S., 2011. Bergmann’s rule - what’s in a name? Glob. Ecol. Biogeogr. 20, 203–207.CrossRefGoogle Scholar
  53. Meiri, S., Dayan,T., 2003. On the validity of Bergmann’s rule. J. Biogeogr. 30, 331–351.CrossRefGoogle Scholar
  54. Meiri, S., Dayan, T., Simberloff, D., 2004. Carnivores, biases and Bergmann’s rule. Biol. J. Linn. Soc. 81, 579–588.CrossRefGoogle Scholar
  55. Meiri, S., Yom-Tov, Y., Geffen, E., 2007. What determines conformity to Bergmann’s rule? Glob. Ecol. Biogeogr. 16, 788–794.CrossRefGoogle Scholar
  56. Morales, M.M., Giannini, N.P., 2010. Morphofunctional patterns in Neotropical felids: species co-existence and historical assembly. Biol. J. Linn. Soc. 100, 711–724.CrossRefGoogle Scholar
  57. Morello, JA, 1985. Grandes ecosistemas de Sudamérica, Textos para Discusión. Fun-dación Bariloche/3, Bariloche, pp. 116.Google Scholar
  58. Naumann, M., Madariaga, M., 2003. Atlas Argentino/Argentinienatlas. Programa de Acción Nacional de Lucha contra la Desertificación, Secretaría de Ambiente y Desarrollo Sustentable. InstitutoNacionaldeTecnologíaAgropecuaria, Deutsche Gesekkschaft für Technische Zusammenarbeit, Buenos Aires, pp. 94.Google Scholar
  59. Noy-Meir, I., 1974. Desert ecosystems: highertropic levels. Annu. Rev. Ecol. Syst. 5, 195–214.CrossRefGoogle Scholar
  60. Ochocinska, D., Taylor, J.R.E., 2003. Bergmann’s rule in shrews: geographical variation of body size in Paleartic Sorex species. Biol. J. Linn. Soc. 78, 365–381.CrossRefGoogle Scholar
  61. Olalla-Tárraga, M.A., Rodríguez, M.A., Hawkins, B.A., 2006. Broad-scale patterns of body size in squamate reptiles of Europe and North America. J. Biogeogr. 33, 781–793.CrossRefGoogle Scholar
  62. Olson, D.M., Dinerstein, E., Wikramanayake, E.D., Burgess, N.D., Powell, G.V.N., Underwood, E.C., D’Amico, JA, Itoua, I., Strand, H.E., Morrison, J.C., Loucks, C.J., Allnutt, T.F., Rikkets, 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. BioScience 51, 933–938.CrossRefGoogle Scholar
  63. R Development Core Team, 2013. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.Google Scholar
  64. Rangel, T.F.L.V.B., Diniz-Filho,JAF., Bini, L.M., 2010. SAM: a comprehensive application for spatial analysis in macroecology. Ecography 33, 1–5.CrossRefGoogle Scholar
  65. Redford, K.H., Eisenberg, J.F., 1992. Mammals ofthe Neotropics. Volume 2, The Southern Cone, Chile, Argentina, Uruguay, Paraguay. The University of Chicago Press, Chicago, pp. 430.Google Scholar
  66. Reynolds, J.F., Kemp, P.R., Ogle, K., Fernández, R.J., 2004. Modifying the “pulse-reserve” paradigm for deserts of North America: precipitation pulses, soil water, and plant responses. Oecologia 141, 194–210.PubMedCrossRefPubMedCentralGoogle Scholar
  67. Rodríguez, MA, López-Sanudo, I.L., Hawkins, BA, 2006. The geographic distribution of mammal body size in Europe. Glob. Ecol. Biogeogr. 15, 173–181.CrossRefGoogle Scholar
  68. Roig-Junent, S., Flores, G., Claver, S., Debandi, G., Marvaldi, A., 2001. Monte desert (Argentina): insect biodiversity and natural areas. J. Arid Environ. 47, 77–94.CrossRefGoogle Scholar
  69. Rohlf, J.F., 1999. Shape statistics: Procrustes superimpositions and tangent spaces. J. Classif. 16, 197–223.CrossRefGoogle Scholar
  70. Rohlf, J.F., 2008a. TPSUtil, Version 1.40. Ecology and Evolution. SUNY, Stony Brook.Google Scholar
  71. Rohlf, J.F., 2008b. TPSDig2, Version 2.12. Ecology and Evolution. SUNY, Stony Brook.Google Scholar
  72. Ruggiero, A., Kitzberger, T., 2004. Environmental correlates of mammal species richness in South America: effects of spatial structure, taxonomy and geographic range. Ecography 27, 401–416.CrossRefGoogle Scholar
  73. Schiaffini, M.I., Gabrielli, M., Prevosti, F.J., Cardoso, Y.P., Castillo, D., Bo, R., Casanave, E., Lizarralde, M., 2013. Taxonomic status of southern South American Conepatus (Carnivora: Mephitidae). Zool. J. Linn. Soc. 167, 327–344.CrossRefGoogle Scholar
  74. Sheets, H.D., 2002. IMP-Integrated Morphometrics Package. Department of Physics, Canisius College, Buffalo, NY.Google Scholar
  75. Swihart, R.K., Slade, NA, Bergstrom, N.J., 1988. Relating body size to the rate of home range use in mammals. Ecology 69, 393–399.CrossRefGoogle Scholar
  76. ter Braak, C.J., Šmilauer, P., 2002. Canoco 4.5: Reference Manual and Canodraw for Windows, User’s Guide: Software from Canonical Community Ordination (version 4.5). Microcomputer Power, Ithaca, New York.Google Scholar
  77. Travaini, A., Delibes, M., Ceballos, O., 1998. Summer foods of the Andean hog-nosed skunk (Conepatus chinga) in Patagonia. J. Zool. (Lond.) 246, 457–460.CrossRefGoogle Scholar
  78. Van Gelder, R.G., 1968. The genus Conepatus (Mammalia, Mustelidae): variation within a population. Am. Mus. Novit. 2322, 1–37.Google Scholar
  79. VanValkenburgh, B., 1989. Carnivore dental adaptations and diet: a study of trophic diversity withinguilds. In: Gittleman,J.D. (Ed.), Carnivore Behavior, Ecology, and Evolution. Springer, USA, pp. 410–435.CrossRefGoogle Scholar
  80. Van Valkenburgh, B., 2007. Déjà vu: the evolution of feeding morphologies in the Carnivora. Integr. Comp. Biol. 47, 147–163.PubMedCrossRefPubMedCentralGoogle Scholar
  81. Willmott, C.J., Matsuura, K., 2001. Terrestrial Water Budget Data Archive: Monthly Time Series (1959-1999). Center for Climate Research, University of Delaware, DE.Google Scholar
  82. Wozencraft, W.C., 2005. Order Carnivora. In: Wilson, D.E., Reeder, D.M. (Ed.), Mammal Species of the World. A Taxonomic and Geographic Reference, Volume 1. , third ed. The John Hopkins University Press, Baltimore, Maryland, pp. 601–624.Google Scholar
  83. Yom-Tov, Y., Geffen, E., 2006. Geographic variation in body size: the effect of ambient temperature and precipitation. Oecologia 148, 213–218.PubMedPubMedCentralCrossRefGoogle Scholar
  84. Zapata, S.C., Travaini, A., Martínez-Peck, R., 2001. Seasonal feeding habits of the Patagonian hog-nosed skunk Conepatus humboldtii in southern Patagonia. Acta Theriol. 46, 97–102.Google Scholar
  85. Zelditch, M.L., Swiderski, D.L., Sheets, H.D., Fink, W.L., 2004. Geometric Morphometrics for Biologist. A Primer. Elsevier Academic Press, San Diego, pp. 443.Google Scholar

Copyright information

© Deutsche Gesellschaft für Säugetierkunde 2014

Authors and Affiliations

  1. 1.CONICET - Consejo Nacional de Investigaciones Científicas y Técnicas, CIEMEP-LIEB - Centro de Investigación Esquel de Montaña y Estepa Patagónicas, Laboratorio de Investigaciones en Evolución y Biodiversidad, Facultad de Ciencias NaturalesUniversidad Nacional de la Patagonia SJB, sede EsquelChubutArgentina

Personalised recommendations