@article{Trauth2013,
  author    = {Trauth, Martin H.},
  title     = {TURBO2 - a MATLAB simulation to study the effects of bioturbation on paleoceanographic time series},
  series = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology},
  volume    = {61},
  journal   = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology},
  number    = {12},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0098-3004},
  doi       = {10.1016/j.cageo.2013.05.003},
  pages     = {1 -- 10},
  year      = {2013},
  abstract  = {Bioturbation (or benthic mixing) causes significant distortions in marine stable isotope signals and other palaeoceanographic records. Although the influence of bioturbation on these records is well known it has rarely been dealt systematically. The MATLAB program called TURBO2 can be used to simulate the effect of bioturbation on individual sediment particles. It can therefore be used to model the distortion of all physical, chemical, and biological signals in deep-sea sediments, such as Mg/Ca ratios and UK37-based sea-surface temperature (SST) variations. In particular, it can be used to study the distortions in paleoceanographic records that are based on individual sediment particles, such as SST records based on foraminifera assemblages. Furthermore. TURBO2 provides a tool to study the effect of benthic mixing of isotope signals such as C-14, delta O-18, and delta C-13, measured in a stratigraphic carrier such as foraminifera shells.},
  language  = {en}
}
@article{Trauth2021,
  author    = {Trauth, Martin H.},
  title     = {Spectral analysis in quaternary sciences},
  series = {Quaternary science reviews : the international multidisciplinary research and review journal},
  volume    = {270},
  journal   = {Quaternary science reviews : the international multidisciplinary research and review journal},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0277-3791},
  doi       = {10.1016/j.quascirev.2021.107157},
  pages     = {13},
  year      = {2021},
  abstract  = {Spectral analysis is a technique of time-series analysis that decomposes signals into linear combinations of harmonic components. Rooted in the 19th century, spectral analysis gained popularity in palaeoclimatology since the early 1980s. This was partly due to the availability of long time series of past climates, but also the development of new, partly adapted methods and the increasing spread of affordable personal computers. This paper reviews the most important methods of spectral analysis for palaeoclimate time series and discusses the prerequisites for their application as well as advantages and disadvantages. The paper also offers an overview of suitable software, as well as computer code for using the methods on synthetic examples.},
  language  = {en}
}
@article{EbertTrauth2015,
  author    = {Ebert, Thomas and Trauth, Martin H.},
  title     = {Semi-automated detection of annual laminae (varves) in lake sediments using a fuzzy logic algorithm},
  series = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences},
  volume    = {435},
  journal   = {Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0031-0182},
  doi       = {10.1016/j.palaeo.2015.05.024},
  pages     = {272 -- 282},
  year      = {2015},
  abstract  = {Annual laminae (varves) in lake sediments are typically visually identified, measured and counted, although numerous attempts have been made to automate this process. The reason for the failure of most of these automated algorithms for varve counting is the complexity of the seasonal laminations, typically rich in lateral fades variations and internal heterogeneities. In the manual counting of varves, the investigator acquired and interpreted flexible numbers of complex decision criteria to understand whether a particular simple lamination is a varve or not. Fuzzy systems simulate the flexible decision making process in a computer by introducing a smooth transition between true varve and false varve. In our investigation, we use an adaptive neuro fuzzy inference system (ANFIS) to detect varves on the basis of a digital image of the sediment. The results of the application of the ANFIS to laminated sediments from the Meerfelder Maar (Eifel, Germany) and from a landslide-dammed lake in the Quebrada de Cafayate of Argentina are compared with manual varve counts and possible reasons for the differences are discussed. (C) 2015 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{Trauth2014,
  author    = {Trauth, Martin H.},
  title     = {A new probabilistic technique to build an age model for complex stratigraphic sequences},
  series = {Quaternary geochronology : the international research and review journal on advances in quaternary dating techniques},
  volume    = {22},
  journal   = {Quaternary geochronology : the international research and review journal on advances in quaternary dating techniques},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {1871-1014},
  doi       = {10.1016/j.quageo.2014.03.001},
  pages     = {65 -- 71},
  year      = {2014},
  abstract  = {The age models of fluvio-lacustrine sedimentary sequences are often subject of discussions in paleoclimate research. The techniques employed to build an age model are very diverse, ranging from visual or intuitive estimation of the age-depth relationship over linear or spline interpolations between age control points to sophisticated Bayesian techniques also taking into account the most likely deposition times of the type of sediment within the sequence. All these methods, however, fail in detecting abrupt variations in sedimentation rates, including the possibility of episodes of no deposition (hiatus), which is the strength of the method presented in this work. The new technique simply compares the deposition time of equally thick sediment slices from the differences of subsequent radiometric age dates and the unit deposition times of the various sediment types. The percentage overlap of the distributions of these two sources of information, together with the evidence from the sedimentary record, helps to build an age model of complex sequences including abrupt variations in the rate of deposition including one or many hiatuses. (C) 2014 Elsevier B.V. All rights reserved.},
  language  = {en}
}