Data from 14 labortories testing the impact of introduced variability on the reproducibility of a microcosm ecological experiment

DOI

Although microcosm experiments are a frequent tool used to address fundamental ecological questions, there has been no quantitative assessment of the reproducibility of any microcosm experiment. This dataset contains the response variables measured in a multi-laboratory microcosm study in which the same microcosm experiment was repeated in 14 laboratories across Europe. All laboratories simultaneously run a simple microcosm experiment using grass (Brachypodium distachyon L.) monocultures and grass and legume (Medicago truncatula Gaertn.) mixtures. All twelve variables were then used to calculate the effect of the presence of nitrogen-fixing legume on the grass-legume mixtures (i.e. the net legume effect).The project tested a controversial hypotheses postulating that stringent levels of environmental and biotic standardization in experimental studies reduces reproducibility by amplifying impacts of lab-specific environmental factors not accounted for in the experimental design. This implies that the deliberate introduction of controlled systematic variability (CSV) in experimental designs can increase reproducibility. To test this hypothesis, each laboratory followed the same experimental protocol and introduced environmental and genotypic controlled systematic variability (CSV) within and among replicated microcosms established in either growth chambers (with stringent control of environmental conditions) or glasshouses (with more variable environmental conditions). Data were used to test the extent to which the effect size of the net legume effect varied with the CSV treatment and to estimate the number of laboratories that produced results that can be considered reproducible.

Supplement to: Milcu, Alexandru; Puga-Freitas, Ruben; Ellison, Aaron M; Blouin, Manuel; Scheu, Stefan; Girin, Thomas; Freschet, Grégoire T; Rose, Laura; Scherer-Lorenzen, Michael; Barot, Sebastien; Lata, Jean-Christophe; Cesarz, Simone; Eisenhauer, Nico; Gigon, Agnès; Weigelt, Alexandra; Hansart, Amandine; Greiner, Anna; Pando, Anne; Gessler, Arthur; Grignani, Carlo; Assandri, Davide; Gleixner, Gerd; LeGalliard, Jean-Francois; Urban-Mead, Katherine; Zavattaro, Laura; Müller, Marina E H; Lange, Markus; Lukac, Martin; Bonkowski, Michael; Mannerheim, Neringa; Buchmann, Nina; Butenschoen, Olaf; Rotter, Paula; Seyhun, Rahme; Devidal, Sébastien; Kayler, Zachary; Roy, Jacques (2018): Genotypic variability enhances the reproducibility of an ecological study. Nature Ecology & Evolution, 2, 279-287

Identifier
DOI https://doi.org/10.1594/PANGAEA.880980
Related Identifier https://doi.org/10.1038/s41559-017-0434-x
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.880980
Provenance
Creator Milcu, Alexandru ORCID logo; Puga-Freitas, Ruben ORCID logo; Ellison, Aaron M ORCID logo; Blouin, Manuel ORCID logo; Scheu, Stefan ORCID logo; Girin, Thomas ORCID logo; Freschet, Grégoire T; Rose, Laura ORCID logo; Scherer-Lorenzen, Michael (ORCID: 0000-0001-9566-590X); Barot, Sebastien; Lata, Jean-Christophe; Cesarz, Simone ORCID logo; Eisenhauer, Nico ORCID logo; Gigon, Agnès; Weigelt, Alexandra (ORCID: 0000-0001-6242-603X); Hansart, Amandine; Greiner, Anna; Pando, Anne; Gessler, Arthur ORCID logo; Grignani, Carlo; Assandri, Davide ORCID logo; Gleixner, Gerd ORCID logo; LeGalliard, Jean-Francois; Urban-Mead, Katherine; Zavattaro, Laura ORCID logo; Müller, Marina E H; Lange, Markus ORCID logo; Lukac, Martin ORCID logo; Bonkowski, Michael; Mannerheim, Neringa; Buchmann, Nina ORCID logo; Butenschoen, Olaf ORCID logo; Rotter, Paula; Seyhun, Rahme; Devidal, Sébastien; Kayler, Zachary ORCID logo; Roy, Jacques ORCID logo
Publisher PANGAEA
Publication Year 2017
Rights Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported; https://creativecommons.org/licenses/by-nc-nd/3.0/
OpenAccess true
Representation
Language English
Resource Type Supplementary Dataset; Dataset
Format text/tab-separated-values
Size 18824 data points
Discipline Earth System Research