ORCID Profile
0000-0001-9958-8913
Current Organisation
University of Salford
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Publisher: Springer Science and Business Media LLC
Date: 02-03-2020
DOI: 10.1038/S41597-020-0420-Z
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Wiley
Date: 30-05-2017
DOI: 10.1111/BRV.12343
Abstract: We synthesize findings from one of the world's largest and longest-running experimental investigations, the Biological Dynamics of Forest Fragments Project (BDFFP). Spanning an area of ∼1000 km
Publisher: Wiley
Date: 07-2018
DOI: 10.1111/GEB.12729
Publisher: Springer Science and Business Media LLC
Date: 08-01-2020
DOI: 10.1038/S41597-019-0344-7
Abstract: The use of functional information in the form of species traits plays an important role in explaining bio ersity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the s ling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the ersity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.
Publisher: Springer Science and Business Media LLC
Date: 11-12-2020
DOI: 10.1038/S41467-020-20142-Y
Abstract: Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention s ling were used by just 23% of intervention studies in bio ersity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Christoph F. J. Meyer.