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  To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments

Kreyling, J., Schweiger, A. H., Bahn, M., Ineson, P., Migliavacca, M., Morel-Journel, T., et al. (2018). To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments. Ecology Letters, 21(11), 1629-1638. doi:10.1111/ele.13134.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0002-0E09-6 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-405B-8
Genre: Journal Article

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 Creators:
Kreyling, Juergen, Author
Schweiger, Andreas H., Author
Bahn, Michael, Author
Ineson, Phil, Author
Migliavacca, Mirco1, Author           
Morel-Journel, Thibaut, Author
Christiansen, Jesper Riis, Author
Schtickzelle, Nicolas, Author
Larsen, Klaus Steenberg, Author
Affiliations:
1Biosphere-Atmosphere Interactions and Experimentation, Dr. M. Migliavacca, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938307              

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 Abstract: A fundamental challenge in experimental ecology is to capture nonlinearities of ecological
responses to interacting environmental drivers. Here, we demonstrate that gradient designs outperform
replicated designs for detecting and quantifying nonlinear responses. We report the results
of (1) multiple computer simulations and (2) two purpose-designed empirical experiments. The
findings consistently revealed that unreplicated sampling at a maximum number of sampling locations
maximised prediction success (i.e. the R² to the known truth) irrespective of the amount of
stochasticity and the underlying response surfaces, including combinations of two linear, unimodal
or saturating drivers. For the two empirical experiments, the same pattern was found, with gradient
designs outperforming replicated designs in revealing the response surfaces of underlying
drivers. Our findings suggest that a move to gradient designs in ecological experiments could be a
major step towards unravelling underlying response patterns to continuous and interacting environmental
drivers in a feasible and statistically powerful way.

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 Dates: 2018-07-192018-08-232018-10
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC2910
DOI: 10.1111/ele.13134
 Degree: -

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Title: Ecology Letters
Source Genre: Journal
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Publ. Info: Oxford, UK : Blackwell Science
Pages: - Volume / Issue: 21 (11) Sequence Number: - Start / End Page: 1629 - 1638 Identifier: ISSN: 1461-023X
CoNE: https://pure.mpg.de/cone/journals/resource/954925625294