Studia Geophysica et Geodaetica

, Volume 57, Issue 4, pp 647–668 | Cite as

Numerical relationships between magnetic parameters measured in Quaternary sediments and global paleoclimatic proxies

  • Alfredo Peralta
  • Vincenzo Costanzo-Alvarez
  • Eduardo Carrillo
  • Leonardo Evert Durán
  • Milagrosa Aldana
  • Daniel Rey
Article

Abstract

The complexity of most geological and geophysical problems prompts sometimes the use of non linear mathematical methods to handle them. An adaptive neuro fuzzy inference system (ANFIS) that combines fuzzy logic with neural networks, is applied here to study a paleoclimate section from the Quaternary sedimentary fill of the Lake Mucubají (western Venezuela). The purpose of this work is to find a set of numerical relationships that could predict the possible connections between oxygen isotope (δ18O) values from two different locations in the northern hemisphere (Ammersee in southern Germany and an ice core from the Greenland Ice Core Project — GRIP) and rock-magnetic parameters measured in Mucubají samples (i.e. mass-specific magnetic susceptibility — χ, magnetic remanence S-ratio, mass-specific saturation isothermal remanent magnetization — SIRM and anhysteretic remanent magnetization — ARM). The best inferences in terms of coefficient of determionation R2 and the Root Mean-Square Error (RMSE) are obtained using those magnetic data as input that include information about magnetite grain size distributions, e.g., SIRM and ARM in FIS structures [1χ, 4ARM] and [4ARM, 1SIRM]. A comparison between Ammersee and GRIP actual data, as well as their corresponding inferences for the FIS structure [4ARM, 1SIRM], reveals a reasonable good inference of global trends for both records, overlooking the regional and/or local paleoclimate forcings that might have affected Ammersee. A better correlation between global isotope paleoclimate records and magnetic proxies, is perhaps prevented by the role played by local and regional paleoclimate and tectonism in Mucubají. We also argue that the ratio of ARM over SIRM appears to be related in a complex way to the onset and to the end of the Younger Dryas. Our novel approach to the assessment of a specific paleoclimate case study shows the potential of the ANFIS technique in solving problems where traditional univariate and multivariate linear regression methods could prove inadequate.

Keywords

Holocene Neuro Fuzzy System paleoclimate rock magnetic properties 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alexander I., Kroon D. and Thompson R., 1993. Late Quaternary paleoenvironmental change on the northeastern Australian margin as evidenced in oxygen isotope stratigraphy, mineral magnetism and sedimentology. In: McKenzie J.A., Davies P.J., Palmer-Juslon A. et al. (Eds.), Proceedings of the Ocean Drilling Program, Scientific Results, 133, College Station, TX (Ocean Drilling Program), 129–161, DOI: 10.2973/odp.proc.sr.133.224.1993.Google Scholar
  2. Audemard F.A., Pantosti D., Machette M., Costa C., Okumura K., Cowan H., Diederix H. and Sawop Participants, 1999. Trench investigation along the Merida section of the Boconó fault (central Venezuelan Andes). Tectonophysics, 308, 1–21.CrossRefGoogle Scholar
  3. Balsam W., Ji J. and Chen J., 2004. Climatic interpretation of the Luochuan and Lingtai loess sections, China, based on changing iron oxide mineralogy and magnetic susceptibility. Earth Planet. Sci. Lett., 223, 335–348.CrossRefGoogle Scholar
  4. Brachfeld S.A. and Banerjee S.K., 2000. Rock-magnetic carriers of century-scale susceptibility cycles in glacial-marine sediments from the Palmer Deep, Antarctic Peninsula. Earth Planet. Sci. Lett., 176, 443–455.CrossRefGoogle Scholar
  5. Bowen G.J. 2008 Spatial analysis of the intra-annual variation of precipitation isotope ratios and its climatological corollaries. J. Geophys. Res., 113, D05113, DOI: 10.1029/2007JD009295.CrossRefGoogle Scholar
  6. Bloemendal J., King J.W., Hall F.R. and Doh S.J., 1992. Rock magnetism of Late Neogene and Pleistocene deep-sea sediments: relationship to sediment source, diagenetic processes and sediment lithology. J. Geophys. Res., 97, 4361–4375.CrossRefGoogle Scholar
  7. Carrillo E, Beck A., Audemard F.A., Moreno E. and Ollarves R., 2008. Disentangling Late Quaternary climatic and seismo-tectonic controls on Lake Mucubají sedimentation (Mérida Andes, Venezuela). Palaeogeogr. Palaeoclimatol. Palaeoecol., 259, 284–300.CrossRefGoogle Scholar
  8. Da Silva A., Costanzo-Álvarez V., Hurtado N., Aldana M., Bayona G., Guzmán O. and López-Rodríguez D., 2010 Study of a possible correlation between Miocene global climatic changes and magnetic proxies d18O, using neuro fuzzy logic analysis: stratigraphic well Saltarín 1A (Llanos foreland basin, Colombia. Stud. Geophys. Geod., 54, 607–631CrossRefGoogle Scholar
  9. Finol J. and Jing X.D., 2002. Predicting petrophysical parameters in a fuzzy environment in soft computing for reservoir characterisation and modeling. In: Wong P., Aminzadeh F. and Nikravesh M. (Eds.), Soft Computing for Reservoir Characterization and Modeling. Studies in Fuzziness and Soft Computing, 80, Physica-Verlag, Heidelberg, 183–217.CrossRefGoogle Scholar
  10. Frank U. and Nowaczyk N.R., 2008. Mineral magnetic properties of artificial samples systematically mixed from haematite and magnetite. Geophys. J. Int., 175, 449–461.CrossRefGoogle Scholar
  11. Gautam D.K and Holz K.P., 2001. Rainfall-runoff modeling using adaptive neuro-fuzzy systems. J. Hydroinform., 3, 3–10.Google Scholar
  12. Geiss C.E. and Banerjee S.K., 1997. A multi-parameter rock magnetic record of the last glacialinterglacial paleoclimate from south-central Illinois, USA. Earth Planet. Sci. Lett., 152, 203–216.CrossRefGoogle Scholar
  13. Giegengack R., Grauch R.I. and Sahagam R., 1976. Geometry of Late Cenozoic displacement along the Boconó Fault, Venezuelan Andes. Boletín de Geología Publicación Especial, 7/2, 1201–1223Google Scholar
  14. Giegengack R., 1984. Late Cenozoic tectonic environments of the central Venezuelan Andes. Geol. Soc. Amer. Mem., 162, 343–364.CrossRefGoogle Scholar
  15. Harris S.E. and Mix A., 2002. Climatic and tectonic influences on continental erosion of tropical South America, 0–13 Ma. Geology, 30, 447–450.CrossRefGoogle Scholar
  16. Harris S.E. and Mix A.C., 1999, Pleistocene precipitation balance in the Amazon Basin recorded in deep-sea sediments. Quat. Res., 51, 14–26.CrossRefGoogle Scholar
  17. Hodell D.A., Brenner M., Curtis J.H. and Guilderson T., 2001 Solar forcing of drought frequency in the Maya Lowlands. Science, 292, 1367–1370CrossRefGoogle Scholar
  18. Hu S.Y., Wang S.M. and Appel E., 2000. The environmental mechanism of fluctuations of magnetic susceptibility recorded in lacustrine sediments from Jalai Nur, Inner Mongolia. Sci. China Ser. D — Earth Sci., 43, 534–540.CrossRefGoogle Scholar
  19. Huang C. and Leung Y., 1999 Estimating the relationship between isoseismal area and earthquake magnitude by a hybrid fuzzy-neural-network method. Fuzzy Set Syst., 107, 131–146.CrossRefGoogle Scholar
  20. Huang Y., Gedeon T.D. and Wong PM., 2001 An integrated neural-fuzzy-genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs. Eng. App. Artif. Intel., 14, 15–21.CrossRefGoogle Scholar
  21. Hurtado N., Aldana M. and Torres J., 2008. Comparison between neuro-fuzzy and fractal models for permeability prediction. Comput. Geosci., 13, 181–186.CrossRefGoogle Scholar
  22. Janakiraman K.K. and Konno M., 2002 Cross-borehole geological interpretation model based on a fuzzy neural network and geotomography. Geophysics, 67, 1177–1183.CrossRefGoogle Scholar
  23. Johnson K.R. and Ingram B.L., 2004. Spatial and temporal variability in the stable isotope systematics of modern precipitation in China: implications for paleoclimate reconstructions. Earth Planet. Sci. Lett., 220, 365–377CrossRefGoogle Scholar
  24. Jones P.D., Osborn T.J. and Briffa K.R., 2001. The evolution of climate over the last millennium. Science, 292, 662–667CrossRefGoogle Scholar
  25. Kent D.V., 1982. Apparent correlation of palaeomagnetic intensity and climatic records in deep-sea sediments. Nature, 299, 538–539.CrossRefGoogle Scholar
  26. Kowalski E.A., 2002. Mean annual temperature estimation based on leaf morphology: a test from tropical South America. Palaeogeogr. Palaeoclimatol. Palaeoecol., 188, 141–165CrossRefGoogle Scholar
  27. Lea D.W., Pak D.K., Peterson L.C. and Hughen K.A., 2003. Synchroneity of tropical and highlatitude Atlantic temperatures over the last glacial termination. Science, 301, 1361–1364.CrossRefGoogle Scholar
  28. Lin H.-L., Peterson L.C., Overpeck J.T., Trumbore S.E. and Murray D.W., 1997. Late Quaternary climate change from δ18O records of multiple species of planktonic foraminifera: highresolution records from the anoxic Cariaco Basin, Venezuela. Paleoceanography, 12, 415–427.CrossRefGoogle Scholar
  29. Mahaney W., Milner M.W., Voros J., Kalm V., Hütt G., Bezada M., Hancock M.G.V. and Aufreiter S., 2000. Stratotype for the Mérida Glaciation at Pueblo Llano in the northern Venezuelan Andes. J. South Am. Earth. Sci., 13, 761–774.CrossRefGoogle Scholar
  30. Moreno E., Thouveny N., Delanghe D., McCave N.I. and Shackleton N.J., 2002. Climatic and oceanographic changes in the Northeast Atlantic reflected by magnetic properties of sediments deposited on the Portuguese Margin during the last 340 ka. Earth Planet. Sci. Lett., 202, 465–480.CrossRefGoogle Scholar
  31. Mourguiart Ph., Correge T., Wirrmann D., Argollo J., Montenegro M.E., Pourchet M. and Carbonel P., 1998. Holocene palaeohydrology of Lake Titicaca estimated from an ostracodbased transfer function. Palaeogeogr. Palaeoclimatol. Palaeoecol., 143, 51–72CrossRefGoogle Scholar
  32. Muller S., Legrand J.-F., Muller J.-D., Cansi Y. and Crusem R., 1998. seismic events discrimination by neuro.fuzzy-based data merging. Geophys. Res. Lett., 25, 3449–3452.CrossRefGoogle Scholar
  33. Muller S., Garda P., Muller J.-D. and Cansi Y., 1999. Seismic events discrimination by neuro-fuzzy merging of signal and catalogue features. Phys. Chem. Earth A, 24, 201–206.CrossRefGoogle Scholar
  34. Nikravesh M. and Aminzadeh F., 2001. Mining and fusion of petroleum data with fuzzy logic and neural network agents. J. Petrol. Sci. Eng., 29, 221–238.CrossRefGoogle Scholar
  35. Pérez O., Bilham R., Bendick R., Hernández N., Hoyer M., Velando J., Moncayo C. and Kozuch M., 2001. Velocidad relative entre las places del Caribe y Sudamérica a partir de observaciones dentro del sistema de posicionamiento global (GPS) an el norte de Venezuela. Interciencia, 26, 69–74 (in Spanish).Google Scholar
  36. Poage M.A. and Chamberlain C.P., 2001. Empirical relationships between elevation and the stable isotope composition of precipitation and surface waters: considerations for studies of paleoelevation change. Am. J. Sci., 301, 1–15CrossRefGoogle Scholar
  37. Rajaee T., Mirbagheri S.A., Nourani V. and Alikhani A., 2010. Prediction of daily suspended sediment load using wavelet and neuro fuzzy combined model. Int. J. Environ. Sci. Tech., 7, 93–110.CrossRefGoogle Scholar
  38. Retallack G.J., Sheldon N.D., Cogoini M. and Elmore R.D., 2003. Magnetic susceptibility of early Paleozoic and Precambrian paleosols. Palaeogeogr. Palaeoclimatol. Palaeoecol., 198, 373–380.CrossRefGoogle Scholar
  39. Rull V., 1996. Late Pleistocene and Holocene climates of Venezuela. Quat. Int., 31, 85–94.CrossRefGoogle Scholar
  40. Salgado-Labouriau M.L. and Schubert C., 1976. Palynology of Holocene peat bogs from the central Venezuelan Andes. Palaeogeogr. Palaeoclimatol. Palaeoecol., 19, 147–156.CrossRefGoogle Scholar
  41. Shackleton N.J. and Opdyke N.D., 1973. Oxygen isotope and paleomagnetic stratigraphy ofequatorial Pacific core V28–238: Oxygen isotope temperatures and ice volumes on a 105-year and 106-year scale. Quat. Res., 3, 39–55.CrossRefGoogle Scholar
  42. Schubert C., 1982. Neotectonics of Boconó Fault, western Venezuela. Tectonophysics, 85, 205–220.CrossRefGoogle Scholar
  43. Singh U.K., Singh D.K. and Singh H., 2010. Application of neuro fuzzy pattern recognition method in borehole geophysics. Acta Geod. Geoph. Hung., 45, 417–425.CrossRefGoogle Scholar
  44. Sturm C.; Hoffmann G. and Langmann B., 2007. Simulation of the stable water isotopes in precipitation over South America: comparing regional to global circulation models. J. Climate, 20, 3730–3750CrossRefGoogle Scholar
  45. Tahmasebi P. and Hezarkhani A., 2010. Application of adaptive neuro-fuzzy inference system for grade estimation; case study, Sarcheshmeh Porphyry Copper deposit, Kerman, Iran. Aust. J. Basic Appl. Sci., 4, 408–420.Google Scholar
  46. Tutmez B., Hatipoglu Z. and Kaymak U., 2006. Modelling electrical conductivity of groundwater using an adaptive neuro-fuzzy inference system. Comput. Geosci., 32, 421–433CrossRefGoogle Scholar
  47. Volkman J.K., Barrerr S.M., Blackburn S.I. and Sikes E.L., 1995. Alkenones in Gephyrocapsa oceanica: Implications for studies of paleoclimate. Geochim. Cosmochim. Acta, 59, 513–520.CrossRefGoogle Scholar
  48. von Grafenstein U., Erlenkeuser H., Brauer A., Jouzel J. and Johnsen S.J., 1999. A Mid-European decadal isotope-climate record from 15,500 to 5000 years B.P. Science, 284, 1654–1657.CrossRefGoogle Scholar
  49. Ziaii M., Pouyan A.A. and Ziaei M., 2009. Neuro-fuzzy modelling in mining geochemistry: Identification of geochemical anomalies. J. Geochem. Explor., 100, 25–36CrossRefGoogle Scholar
  50. Zoveidavianpoor M., Samsuri A. and Shadizadeh S.R., 2013. Adaptive neuro fuzzy inference system for compressional wave velocity prediction in a carbonate reservoir. J. Appl. Geophys., 89, 96–107.CrossRefGoogle Scholar
  51. Zhu R.X., Shi C.D., Suchy V., Zeman A., Guo B. and Pan Y., 2001. Magnetic properties and paleoclimatic implications of loess-paleosol sequences of Czech Republic. Sci. China Ser. D — Earth Sci., 44, 385–394.CrossRefGoogle Scholar

Copyright information

© Institute of Geophysics of the ASCR, v.v.i 2013

Authors and Affiliations

  • Alfredo Peralta
    • 1
  • Vincenzo Costanzo-Alvarez
    • 1
  • Eduardo Carrillo
    • 2
  • Leonardo Evert Durán
    • 1
  • Milagrosa Aldana
    • 1
  • Daniel Rey
    • 3
  1. 1.Dpto. Ciencias de la TierraUniversidad Simón BolívarCaracasVenezuela
  2. 2.Instituto de Ciencias de la TierraUniversidad Central de VenezuelaCaracasVenezuela
  3. 3.Departamento de Geociencias Mariñas e Ordenación do TerritorioUniversidad de VigoVigoSpain

Personalised recommendations