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Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Testing peatland testate amoeba transfer functions: Appropriate methods for clustered training-sets
Author(s): Payne, Richard
Telford, Richard J
Blackford, Jeffrey J
Blundell, Antony
Booth, Robert K
Charman, Dan J
Lamentowicz, Lukasz
Lamentowicz, Mariusz
Mitchell, Edward A D
Potts, Genevieve
Swindles, Graeme T
Warner, Barry G
Woodland, Wendy
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Keywords: cluster bootstrap
clustered data
leave-one-site-out cross-validation
transfer functions
Issue Date: Jul-2012
Date Deposited: 1-Nov-2013
Citation: Payne R, Telford RJ, Blackford JJ, Blundell A, Booth RK, Charman DJ, Lamentowicz L, Lamentowicz M, Mitchell EAD, Potts G, Swindles GT, Warner BG & Woodland W (2012) Testing peatland testate amoeba transfer functions: Appropriate methods for clustered training-sets. Holocene, 22 (7), pp. 819-825.
Abstract: Transfer functions are widely used in palaeoecology to infer past environmental conditions from fossil remains of many groups of organisms. In contrast to traditional training-set design with one observation per site, some training-sets, including those for peatland testate amoeba-hydrology transfer functions, have a clustered structure with many observations from each site. Here we show that this clustered design causes standard performance statistics to be overly optimistic. Model performance when applied to independent data sets is considerably weaker than suggested by statistical cross-validation. We discuss the reasons for these problems and describe leave-one-site-out cross-validation and the cluster bootstrap as appropriate methods for clustered training-sets. Using these methods we show that the performance of most testate amoeba-hydrology transfer functions is worse than previously assumed and reconstructions are more uncertain.
DOI Link: 10.1177/0959683611430412
Rights: Publisher policy allows this work to be made available in this repository. Published in The Holocene July 2012 vol. 22 no. 7 819-825 by SAGE. The original publication is available at:

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