Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-27T12:42:33.420Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment and calibration of representational bias in soil phytolith assemblages in Northeast China and its implications for paleovegetation reconstruction

Published online by Cambridge University Press:  10 April 2018

Guizai Gao ,
Dongmei Jie ,
Lidan Liu ,
Hongyan Liu ,
Dehui Li ,
Nannan Li ,
Jichen Shi ,
Chengcheng Leng  and
Zhihe Qiao
Guizai Gao
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Dongmei Jie*
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China Key Laboratory of Vegetation Ecology, Ministry of Education, Changchun 130024, China
Lidan Liu
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Hongyan Liu
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Dehui Li
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Nannan Li
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Jichen Shi
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Chengcheng Leng
Affiliation:
School of Geographical Science, Northeast Normal University, Changchun 130024, China
Zhihe Qiao
Affiliation:
Daqing Normal University, Daqing 163000, PR China
*
*Corresponding author at: School of Geographical Science, Northeast Normal University, Changchun 130024, China. E-mail address: jiedongmei@nenu.edu.cn (D.M. Jie).
Get access Rights & Permissions [Opens in a new window]

Abstract

The assessment and calibration of representational bias in modern soil phytolith assemblages provide the basis for improving interpretation of fossil phytolith assemblages. We studied soil phytolith representation by comparing phytoliths from living plant communities with those from paired surface soils, representing 39 plant communities in Northeast China. Together with the use of representation indices, the 34 and 30 soil morphotypes observed in forest and grassland samples, respectively, were both classified into the following four groups: “Associated types” were similarly represented in soils and in the corresponding species inventory data; “Over-represented types” and “Under-represented types” were respectively over- and under-represented in soils compared to the inventory data; and, in the case of “Special types,” the relationship with the parent plants was unclear. In addition, the diagnostic types exhibited different degrees of representation, while the most common morphotypes were equally represented between grassland samples and forest samples. On this basis, a comparison between the original and corrected soil phytolith indices of the additional 29 soil samples was conducted. The soil phytoliths frequencies corrected by R-values differed between plots with differing plant compositions, and were moderately consistent with actual plant richness in the plot inventory data. We therefore confirmed that R-values are a promising means of correcting soil phytoliths for representational bias in temperate regions. The corrected soil phytoliths can be used to reliably reflect vegetation variability. Overall, our study provides an improved understanding of soil phytolith representation and offers a potential method for improving the accuracy of paleovegetation reconstruction.

Keywords

PhytolithRepresentationCalibrationPaleovegetation reconstructionNortheast China
Type
Research Article
Information
Quaternary Research , Volume 90 , Issue 1 , July 2018 , pp. 38 - 49
Copyright
Copyright © University of Washington. Published by Cambridge University Press, 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Albert, R.M., Bamford, M.K., Cabanes, D., 2006. Taphonomy of phytoliths and macroplants in different soils from Olduvai Gorge (Tanzania) and the application to Plio-Pleistocene palaeoanthropological samples. Quaternary International 148, 78–94.CrossRefGoogle Scholar
Alexandre, A., Meunier, J.D., Colin, F., Koud, J.M., 1997. Plant impact on the biogeochemical cycle of silicon and related weathering processes. Geochimica et Cosmochimica Acta 61, 677–682.Google Scholar
Biswas, O., Ghosh, R., Paruya, D.K., Mukherjee, B., Thapa, K.K., Bera, S., 2016. Can grass phytoliths and indices be relied on during vegetation and climate interpretations in the eastern Himalayas? Studies from Darjeeling and Arunachal Pradesh, India. Quaternary Science Reviews 134, 114–132.CrossRefGoogle Scholar
Blinnikov, M., Busacca, A., Whitlock, C., 2002. Reconstruction of the late Pleistocene grassland of the Columbia basin, Washington, USA, based on phytolith records in loess. Palaeogeography, Palaeoclimatology, Palaeoecology 177, 77–101.CrossRefGoogle Scholar
Blinnikov, M.S., Bagent, C.M., Reyerson, P.E., 2013. Phytolith assemblages and opal concentrations from modern soils differentiate temperate grasslands of controlled composition on experimental plots at Cedar Creek, Minnesota. Quaternary International 287, 101–113.Google Scholar
Bremond, L., Alexandre, A., Hely, C., Guiot, J., 2005a. A phytolith index as a proxy of tree cover density in tropical areas: calibration with Leaf Area Index on forest savanna transects in southeastern Cameroon. Global and Planetary Change 45, 277–293.Google Scholar
Bremond, L., Alexandre, A., Peyron, O., Guiot, J., 2005b. Grass water stress estimated from phytoliths in West Africa. Journal of Biogeography 32, 311–327.CrossRefGoogle Scholar
Bremond, L., Alexandre, A., Wooller, M.J., Hély, C., Williamson, D., Schäfer, P.A., Majule, A., Guiot, J., 2008. Phytolith indices as proxies of grass subfamilies on East African tropical mountains. Global and Planetary Change 61, 209–224.Google Scholar
Cabanes, D., Weiner, S., Shahack-Gross, R., 2011. Stability of phytoliths in the archaeological record: a dissolution study of modern and fossil phytoliths. Journal of Archaeological Science 38, 2480–2490.Google Scholar
Cabanes, D., Shahack-Gross, R., 2015. Understanding Fossil Phytolith Preservation: The Role of Partial Dissolution in Paleoecology and Archaeology. PLoS ONE 10, e0125532. http://dx.doi.org/10.1371/journal.pone.0125532.Google Scholar
Calegari, M.R., Paisani, S.D.L., Cecchet, F.A., Ewald, P.L.L., Osterrieth, M.L., Paisani, J.C., Pontelli, M.E., 2015. Phytolith signature on the Araucarias Plateau–Vegetation change evidence in Late Quaternary (South Brasil). Quaternary International, 1–12.Google Scholar
Carnelli, A.L., Theurillat, J.P., Madella, M., 2004. Phytolith types and type-frequencies in subalpine – alpine plant species of the European Alps. Review of Palaeobotany and Palynology 129, 39–65.Google Scholar
Coe, H.H.G., Alexandre, A., Carvalho, C.N., Santos, G.M., Silva, A.S.D., Sousa, L.O.F., Lepsch, I.F., 2013. Changes in Holocene tree cover density in Cabo Frio (Rio de Janeiro, Brazil): evidence from soil phytolith assemblages. Quaternary International 287, 63–72.Google Scholar
Davis, M.B., 1963. On the theory of pollen analysis. American Journal of Science 261, 897–912.Google Scholar
Delhon, C., Alexandre, A., Berger, J.F., Thiébault, S., Brochier, J.L., Meunier, J.D., 2003. Phytolith assemblages as a promising tool for reconstructing Mediterranean Holocene vegetation. Quaternary Research 59, 48–60.Google Scholar
Dunn, R.E., Strömberg, C.A.E., Madden, R.H., Kohn, M.J., Carlini, A.A., 2015. Linked canopy, climate, and faunal change in the Cenozoic of Patagonia. Science 347, 258–261.CrossRefGoogle ScholarPubMed
Fraysse, F., Pokrovsky, O.S., Schott, J., Meunier, J.D., 2006. Surface properties, solubility and dissolution kinetics of bamboo phytoliths. Geochimica et Cosmochimica Acta 70, 1939–1951.Google Scholar
Fraysse, F., Pokrovsky, O.S., Schott, J., Meunier, J.D., 2009. Surface chemistry and reactivity of plant phytoliths in aqueous solutions. Chemical Geology 258, 197–206.CrossRefGoogle Scholar
Gao, G. Z., Jie, D.M., Wang, Y., Liu, L.D., Liu, H.Y., Li, D.H., Li, N.N., Shi, J.C., Leng, C.C., 2017. Phytolith reference study for identifying vegetation changes in the forest-grassland region of northeast China. Boreas, Doi.org/10.1111/bor.12280.Google Scholar
Ghosh, R., Naskar, M., Bera, S., 2011. Phytolith assemblages of grasses from the Sunderbans, India and their implications for the reconstruction of deltaic environments. Palaeogeography, Palaeoclimatology, Palaeoecology 311, 93–102.CrossRefGoogle Scholar
Hodson, M.J., White, P.J., Mead, A., Broadley, M.R., 2005. Phylogenetic variation in the silicon composition of plants. Annals of Botany 96, 1027–1046.CrossRefGoogle ScholarPubMed
Hyland, E., Smith, S.Y., Sheldon, N.D., 2013. Representational bias in phytoliths from modern soils of central North America: Implications for paleovegetation reconstructions. Palaeogeography, Palaeoclimatology, Palaeoecology 374, 338–348.Google Scholar
Kerns, B.K., 2001. Diagnostic phytoliths for a Ponderosa Pine-bunchgrass community near Flagstaff, AZ. The Southwestern Naturalist 46, 282–294.CrossRefGoogle Scholar
Kirchholtes, R.P.J., Mourik, J.M., Johnson., B.R., 2014. Phytoliths as indicators of plant community change: a case study of the reconstruction of the historical extent of the oak savanna in the Willamette Valley Oregon, USA. Catena 132, 89–96.Google Scholar
Ma, Z.Y., Lin, E.D., Wu, Z.F., 2007. Eco–climate characteristics of the wetlands in Northeast China. Resources Science 29, 16–24.Google Scholar
Madella, M., Alexandre, A., Ball, T., 2005. International Code for Phytolith Nomenclature 1.0. ICPN Working Group. Annals of Botany 96, 253–260.CrossRefGoogle Scholar
Madella, M., Jones, M.K., Echlin, P., Powers-Jones, A.H., Moore, M., 2009. Plant water availability and analytical microscopy of phytoliths: implications for ancient irrigation in arid zones. Quaternary International 193, 32–40.CrossRefGoogle Scholar
Madella, M., Lancelottib, C., 2012. Taphonomy and phytoliths: a user manual. Quaternary International 275, 76–83.Google Scholar
Mercader, J., Bennett, T., Esselmont, C., Simpson, S., Walde, D., 2009. Phytoliths in woody plants from the Miombo woodlands of Mozambique. Annals of Botany 104, 91–113.Google Scholar
Morris, L.R., Baker, F.A., Morris, C., Ryel, R.J., 2009. Phytolith types and type-frequencies in native and introduced species of the sagebrush steppe and pinyon–juniper woodlands of the Great Basin, USA. Review of Palaeobotany and Palynology 157, 339–357.Google Scholar
Osterrieth, M., Madella, M., Zurro, D., Alvarez, M.F., 2009. Taphonomical aspects of silica phytoliths in the loess sediments of the Argentinean Pampas. Quaternary International 193, 70–79.Google Scholar
Owen, K.D., 1984. Pollen frequencies reflect vegetation patterns in a great basin (USA) mountain range. Review of Palaeobotany and Palynology 40, 295–315.Google Scholar
Pataki, D.E., Oren, R., 2003. Species differences in stomatal control of water loss at the canopy scale in mature bottomland deciduous forest. Advances in Water Resources 26, 1267–1278.Google Scholar
Piperno, D.R., 2006. Phytoliths: A Comprehensive Guide for Archaeologists and Paleoecologists. AltaMira, Lanham, Maryland.Google Scholar
Prebble, M.J., Schallenberg, M., Carter, J.A., Shulmeister, J., 2002. An analysis of phytolith assemblages for the quantitative reconstruction of Late Quaternary environments of the Lower Taieri Plain, Otago, New Zealand I. Modern transfer functions. Journal of Paleolimnology 27, 393–413.CrossRefGoogle Scholar
Strömberg, C.A.E., Werdelin, L., Friis, E.M., Saraç, G., 2007. The spread of grass-dominated habitats in Turkey and surrounding areas during the Cenozoic: Phytolith evidence. Palaeogeography, Palaeoclimatology, Palaeoecology 250, 18–49.Google Scholar
Sun, X.L., Ren, B.Z., Zhao, Z., Gao, C.Q., Zhou, G.P., 2006. Faunal composition of grasshopper in different habitats of Northeast China. Chinese Journal of Ecology 25, 286–289.Google Scholar
Wang, Y.G., Lu, H.Y., 1992. Phytolith Study and its Application. China Ocean Press, Beijing.Google Scholar
Zhao, G.S., Wang, J.B., Fan, W.Y., Ying, T.Y., 2011. Vegetation net primary productivity in Northeast China in 2000–2008: simulation and seasonal change. Chinese Journal of Applied Ecology 22, 621–630.Google Scholar
Supplementary material: File

Gao et al. supplementary material 1

Gao et al. supplementary material

Download Gao et al. supplementary material 1(File)
File 29.9 KB