Russian Journal of Ecology

, Volume 49, Issue 3, pp 241–247 | Cite as

Morphogenetic Effects of Drought and Nonselective Elimination in Population of Bank Vole (Clethrionomys glareolus) in Southern Taiga Subzone

  • A. G. Vasil’ev
  • V. N. Bol’shakov
  • I. A. Vasil’eva
  • N. G. Evdokimov
  • N. V. Sineva


Methods of geometric morphometrics have been used to estimate the influence ratio of nonselective elimination and drought factors on variation in the shape and size of the mandible in the population of bank vole (Clethrionomys glareolus Schreb.) in the southern taiga subzone. Nonselective elimination of rodent populations for medical and sanitary purposes was carried out in a felling site located in a focus of hemorrhagic fever, in the spring of a climatically normal year and of a dry year. The summer samples of mature young of the year from control bank vole colonies and impact colonies (i.e., recovered after deratization) in adjacent years have been compared. The results show that drought, nonselective elimination, and the interaction of these factors have significant effects on the size and shape of the mandible. Changes in its shape under drought conditions are largely due to allometry. Morphogenetic effects of nonselective elimination are highly repeatable between climatically different years. A significantly higher level of within-group morphological disparity (MNND) of the undisturbed control cenopopulation in a dry year has been revealed, which indirectly indicates a stronger destabilization of morphogenesis upon exposure to the autecological factor. Every ecological factor contributes to the development of specific configurations of the mandible; i.e., it induces certain changes in morphogenesis in response to aut- and synecological effects and their combination.


population nonselective elimination drought variation mandible bank vole allometry geometric morphometrics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mayr, E., Animal Species and Evolution, Cambridge: Harvard Univ. Press, 1963. Translated under the title Zoologicheskii vid i evolyutsiya, Moscow: Mir, 1968.CrossRefGoogle Scholar
  2. 2.
    Shvarts, S.S., Evolyutsionnaya ekologiya zhivotnykh: Ekologicheskie mekhanizmy evolyutsionnogo protsessa (Evolutionary Ecology of Animals: Ecological Mechanisms of the Evolutionary Process), Sverdlovsk: Ural. Fil. Akad. Nauk SSSR, 1969.Google Scholar
  3. 3.
    Nei, M., Maruyama, T., and Chakraborty, R., The bottleneck effect and variability in populations, Evolution, 1975, vol. 29, pp. 1–10.CrossRefPubMedGoogle Scholar
  4. 4.
    Shvarts, S.S., Ekologicheskie zakonomernosti evolyutsii (Ecological Patterns of Evolution), Moscow: Nauka, 1980.Google Scholar
  5. 5.
    Vasil’ev, A.G., Epigeneticheskie osnovy fenetiki: na puti k populyatsionnoi meronomii (Epigenetic Bases of Phenetics: On the Way to Population Meronomy), Yekaterinburg: Akademkniga, 2005.Google Scholar
  6. 6.
    Vasil’ev, A.G., Bol’shakov, V.N., Vasil’eva, I.A., et al., Assessment of nonselective elimination effects in rodent communities by methods of geometric morphometrics, Russ. J. Ecol., 2016, vol. 47, no. 4, pp. 383–391.CrossRefGoogle Scholar
  7. 7.
    Semerikov, V.L., Semerikova, S.A., Polezhaeva, M.A., et al., Southern montane populations did not contribute to the recolonization of West Siberian Plain by Siberian larch (Larix sibirica): A range-wide analysis of cytoplasmic markers, Mol. Ecol., 2013, vol. 22, pp. 4958–4971.CrossRefPubMedGoogle Scholar
  8. 8.
    Lee, Y.S., Markov, N., Voloshina, I., et al., Genetic diversity and genetic structure of the Siberian roe deer (Capreolus pygargus) populations from Asia, BMC Genet., 2015, vol. 16, no. 100, pp. 1–15.Google Scholar
  9. 9.
    Yablokov, A.V., Izmenchivost’ mlekopitayushchikh (Variation in Mammals), Moscow: Nauka, 1966.Google Scholar
  10. 10.
    Olenev, G.V., Population mechanisms of adaptation to extreme environmental factors: The example of bank vole, Zh. Obshch. Biol., 1981, no. 4, pp. 506–511.Google Scholar
  11. 11.
    Rohlf, F.J. and Slice, D., Extension of the Procrustes method for the optimal superimposition of landmarks, Syst. Zool., 1990, vol. 39, no. 1, pp. 40–59.CrossRefGoogle Scholar
  12. 12.
    Zelditch, M.L., Swiderski, D.L., Sheets, H.D., and Fink, W.L., Geometric Morphometrics for Biologists: A Primer, New York: Elsevier, 2004.Google Scholar
  13. 13.
    Klingenberg, C.P., MorphoJ: An integrated software package for geometric morphometrics, Mol. Ecol. Resour., 2011, vol. 11, pp. 353–357.CrossRefPubMedGoogle Scholar
  14. 14.
    Rohlf, F.J., TpsUtil, File Utility Program, Version 1.60, Stony Brook, NY: Department of Ecology and Evolution, State University of New York, 2013.Google Scholar
  15. 15.
    Rohlf, F.J., TpsDig, Digitize Landmarks and Outlines, Version 2.17, Stony Brook, NY: Department of Ecology and Evolution, State University of New York, 2013.Google Scholar
  16. 16.
    Rohlf, F.J., Shape statistics: Procrustes superimpositions and tangent spaces, J. Classification, 1999, vol. 16, pp. 197–223.CrossRefGoogle Scholar
  17. 17.
    Vasil’ev, A.G., Vasil’eva, I.A., Gorodilova, Yu.V., and Dobrinskii., N.L, Chernov’s compensation principle and the effect of rodent community completeness on the variability of bank vole (Clethrionomys glareolus) population in the Middle Urals, Russ. J. Ecol., 2017, vol. 48, no. 2, pp. 161–169.CrossRefGoogle Scholar
  18. 18.
    Mitteroecker, P., Gunz, P., Windhage, S., and Schaefer, K., A brief review of shape, form, and allometry in geometric morphometrics, with applications to human facial morphology, Hystrix, 2013, vol. 24, pp. 59–66.Google Scholar
  19. 19.
    Davis, J.C., Statistics and Data Analysis in Geology, New York: Wiley, 1986. Translated under the title Statisticheskii analiz dannykh v geologii, Moscow: Nedra, 1990, vol.2.Google Scholar
  20. 20.
    Hammer, O., New methods for the statistical analysis of point alignments, Comput. Geosci., 2009, vol. 35, pp. 659–666.CrossRefGoogle Scholar
  21. 21.
    Donnelly, K.P., Simulations to determine the variance and edge effect of total nearest-neighbour distances, in Simulation Methods in Archaeology, Hodder, I., Ed., Cambridge: Cambridge Univ. Press, 1978, pp. 91–95.Google Scholar
  22. 22.
    Hammer, Ø., Harper, D.A.T., and Ryan, P.D., PAST: Paleontological statistics software package for education and data analysis, Palaeontol. Electron., 2001, vol. 4, no.1.Google Scholar
  23. 23.
    Vasil’ev, A.G., Bol’shakov, V.N., Vasil’eva, I.A., and Sineva, N.V., Aftereffects of muskrat introduction in Western Siberia: Morphological and functional aspects, Russ. J. Biol. Invasions, 2017, vol. 8, no. 1, pp. 1–9.CrossRefGoogle Scholar
  24. 24.
    Evdokimov, N.G., Analysis of mechanisms of abundance recovery in an artificially depleted population of rodents in a forest biocenosis, in Populyatsionnaya ekologiya i izmenchivost’ zhivotnykh (Animal Population Ecology and Variation), Sverdlovsk: Ural. Nauch. Tsentr Akad. Nauk SSSR, 1979, pp. 84–95.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • A. G. Vasil’ev
    • 1
  • V. N. Bol’shakov
    • 1
  • I. A. Vasil’eva
    • 1
  • N. G. Evdokimov
    • 1
  • N. V. Sineva
    • 1
  1. 1.Institute of Plant and Animal Ecology, Ural BranchRussian Academy of SciencesYekaterinburgRussia

Personalised recommendations