Abstract
Transfer functions that implement organism–environment relationships are now commonly used for inferring past environmental conditions in paleoecology. Specific software for developing and evaluating commonly used modelling techniques such as Weighted averaging (WA), Weighted averaging partial least square (WA-PLS), Maximum likelihood (ML), and Modern analog technique (MAT) are available. A new software programme, PaleoNet, is now available for modelling organism–environment relationships which is specifically designed for the development and the evaluation of artificial neural network (ANN) based transfer functions in paleoecology. Here we present the main characteristics of this new software PaleoNet (User guide version 1.01) and discuss in more detail one of its specific features: the pruning.
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Acknowledgements
We would like to thanks John Birks, Christian Bigler, Marie-Andrée Fallu, Irene Gregory-Eaves, Dörte Köster, Isabelle Larocque, Aline Philibert and Ian Walker for their permission to use their calibration data set. PaleoNet was developed at the University of Nouvelle Calédonie. The development of this software has benefitted from support obtained through the NSERC-CRO project “Late Pleistocene Paleoclimate of Eastern Beringia” awarded to Les Cwynar, from NSERC operating grants awarded to R. Pienitz and Y.T. Prairie and from the Conseil National de la Recherche grants awarded to R. Racca.
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Racca, J.M.J., Racca, R., Pienitz, R. et al. PaleoNet: new software for building, evaluating and applying neural network based transfer functions in paleoecology. J Paleolimnol 38, 467–472 (2007). https://doi.org/10.1007/s10933-006-9082-x
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DOI: https://doi.org/10.1007/s10933-006-9082-x