Tracking Environmental Change Using Lake Sediments: Data by H. John B. Birks, André F. Lotter, Steve Juggins, John P.

By H. John B. Birks, André F. Lotter, Steve Juggins, John P. Smol

Numerical and statistical tools have speedily develop into a part of a palaeolimnologist’s tool-kit. they're used to discover and summarise advanced info, reconstruct prior environmental variables from fossil assemblages, and attempt competing hypotheses concerning the explanations of saw alterations in lake biota via background. This booklet brings jointly a wide range of numerical and statistical strategies at the moment on hand to be used in palaeolimnology and different branches of palaeoecology. ​

Visit http://extras.springer.com the Springer's Extras web site to view data-sets, figures, software program, and R scripts used or pointed out during this book.

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Extra info for Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques

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Cambridge University Press, Cambridge, pp 23–54 Birks HJB, Gordon AD (1985) Numerical methods in Quaternary pollen analysis. Academic Press, London Birks HJB, Line JM, Juggins S, Stevenson AC, ter Braak CJF (1990) Diatoms and pH reconstruction. Philos Trans R Soc Lond B 327:263–278 Birks HJB, Heiri O, Sepp¨a H, Bjune AE (2010) Strengths and weaknesses of quantitative climate reconstructions based on late-Quaternary biological proxies. Open Ecol J 3:68–110 Brown AG (1985) Traditional and multivariate techniques applied to the interpretations of floodplain sediment grain size variations.

Pollen and spores, and mollusca, although other groups are more rarely studied such as beetles, oribatid mites, testate amoebae, and biochemical markers such as photosynthetic pigments, lipids, and DNA (see Smol et al. 2001a, b for detailed accounts of the different types of biological remains studied in lake sediment). The sediments are themselves valuable sources of abiotic palaeolimnological data, such as inorganic and organic geochemistry, magnetic properties, sediment composition and grainsize information, stable isotopes of H, C, N, and O, etc.

2012: Chap. 6). The errors depend on the size of the count and on the proportion in the count sum of the taxon of interest. Methods for estimating errors and confidence intervals associated with concentrations are also available. Deriving the total error requires careful propagation of errors associated with the various steps involved in estimating concentration values.

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