Shitikov V., Terekhova V., Uzbekov B., Kydralieva K., Khudaibergenova B. Dose-response modeling for the environmental risk assessment in cases of technogenic soil contamination // Principy èkologii. 2015. № 3. P. 73‒88. DOI: 10.15393/j1.art.2015.4221


Issue № 3

Original research

pdf-version

Dose-response modeling for the environmental risk assessment in cases of technogenic soil contamination

Shitikov
   Vladimir Kirilloviсh
Institute of Ecology of the Volga River Basin of the Russian Academy of Science, 445003, Togliatty, Komzina st., 10, stok1946@gmail.com
Terekhova
   Vera Alexandrovna
Severtsov Institute of Ecology and Evolution RAS, Moscow State University, Leninskij pr., 33, Moscow, 117071 Russia, vterekhova@gmail.com
Uzbekov
   Beksultan Almazovich
International University of Kyrgyzstan, Chuiskij ave., 255, Bishkek 720001, Kyrgyzstan, phytorem@mail.ru
Kydralieva
   Kamila Asylbekovna
Institute of Chemistry and Chemical Technology NAS KR, Chuiskij ave., 267, Bishkek 720071, Kyrgyzstan, kamila.kydralieva@gmail.com
Khudaibergenova
   Bermet Merlisovna
Institute of Biotechnology NAS KR, Chuiskij ave., 265, Bishkek 720071, Kyrgyzstan, bermet66@gmail.com
Keywords:
biodiagnostics
estimation of ecological risk
radioactive contamination
soil of Kirgizia
a dose-response model
logistical regression
Summary: The review of regression models for the approximation of dependences "dose- response" was performed based on ecotoxicological results. The advantages and deficiencies of different models as well as the problems arising both in modeling and subsequent interpreting results are discussed for the purpose of ecological rationing and estimation of negative influence risk. Search procedures of best dependences based on statistical criteria and the methods of uncertainty estimation of calculated parameters are shown. Construction of models is illustrated in detail using the analysis of toxicity results of soil samples received from uranium mines tailings in Kadzhi-Say province (Kyrgyzstan). Threshold values of activity for U-238 and Ra-226 radionuclides providing the minimum probability of ecological risk were determined.

© Petrozavodsk State University

Reviewer: N. M. Kalinkina
Received on: 17 May 2015
Published on: 16 October 2015

References

Vopobeychik E.L. Sadykov O.F. Farafontov M.G. Ecological regulation of technogenic pollution of terrestrial ecosystems (local level). Ekaterinburg: Nauka, 1994. 280 p.

Methods of soil microbiology and biochemistry. Pod.red. Zvyaginceva D.G. M.: Izd-vo Mosk. Un-ta, 1991. 303 p.

Motuzova G.V. Contamination of soils and related media. M.: Izd-vo MGU, 2000. 71 p.

Terehova V.A. Yakimenko O.S. Voronina L.P. Kydralieva K.A. Method of measurement of the biological activity of humic substances using phytoassay «Phytoscan». M.: Dobroe slovo,  2014. 24 p.

Shitikov V.K. Rozenberg G.S. Randomization and bootstrap:  statistical analysis in biology and ecology using R. Tol'yatti: Kassandra, 2014. 314 p. URL: http://www.ievbras.ru/ecostat/Kiril (data obrascheniya 16.05.2015).

Brain P., Cousens R. An equation to describe dose responses where there is stimulation of growth at low doses, Weed Research. 1989. V. 29. P. 93–96.

Cedergreen N., Ritz C., Streibig J.C. Improved empirical models describing hormesis, Environ. Toxicol. Chem. 2005. V. 24. P. 3166–3172.

Chapman P.A. Decision making framework for sediment assessment developed for theGreat Lakes// Human and Ecological Risk Assessment. 2002. V. 8. No. 7. P. 1641–1655.

Dagnino A., Sforzini S., Dondero F. et al. "Weight-of-Evidence" approach for the integration of environmental ‘‘Triad’’ data to assess ecological risk and biological vulnerability, Integr. Environ. Assess. Manage. 2008. No. 4. R. 314–326

Finney D.J. Bioassay and the Practise of Statistical Inference, Int. Statist. Rev. 1979. V. 47. P. 1–12.

Moore D.R., Caux P.Y. Estimating low toxic effects, Environ. Toxicol. Chem. 1997. V. 16. P. 794-801.

Process for Conducting Probabilistic Risk Assessment, Risk Assessment Guidance for Superfund (RAGS). 2001. Vol. III. Part A. 385 p.

Ritz C. Towards a unified approach to dose-response modeling in ecotoxicology, Environ. Toxicol. Chem. 2010. V. 29. P. 220–229.

Ritz C., Martinussen T. Lack-of-fit tests for assessing mean structures for continuous dose-response data, Environmental and Ecological Statistics, 2011. V. 18. P. 349–366.

Ritz C., Streibig J.C. Bioassay analysis using R, J. Stat. Soft. 2005. V. 12. P. 1-22.

Seber G.A., Wild C.J. Nonlinear Regression.New York: John Wiley, 1989. 768 r.

Shcheglov F.I., Tsvetnova O.B., Klyashtorin A.L. Biogeochemical migration of technogenic radionuclides in forest ecosystems. M.: Nauka, 2001. 235 p.

Slob W. Dose-response modeling of continuous endpoints, Toxicol Sci. 2002. V. 66. P. 298–312.

Species sensitivity distributions in ecotoxicology, Ed. by Posthuma L., Suter G., Traas T. Boca Raton: Lewis Publishers, 2002. 587 p.

Terekhova V.A. Soil Bioassay: Problems and Approaches, Eurasian Soil Science. 2011. V.44, no 2. P. 173–179.

Terekhova V., Pukalchik M., Yakovlev A. The triad approach to ecological assessment of urban soils,  Eurasian Soil Science. 2014. V. 47, no. 9. P. 952–958.

 Wood S.N. Generalized Additive Models: An Introduction with R.  Chapman, Hall/CRC, 2006. 410 p.

Displays: 7782; Downloads: 2189;