Anna Sher

Dr. Anna Sher


Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 April 2004 in Oecologia
Verified
Journal Article
Closed access
PDF file
PCPeter Chesson
Peter Chesson
RGRenate L. E. Gebauer
Renate L. E. Gebauer
SSSusan Schwinning
Susan Schwinning
NHNancy Huntly
Nancy Huntly
KWKerstin Wiegand
Kerstin Wiegand
JWJake F. Weltzin
Jake F. Weltzin

1 August 2015 in Journal of Environmental Management
Verified
Journal Article
Closed access
EGEduardo González
Eduardo González
ASAnna Sher
Anna Sher
ETEric Tabacchi
Eric Tabacchi
AMAdrià Masip
Adrià Masip
MPMonique Poulin
Monique Poulin

1 July 2017 in Biological Conservation
Verified
Journal Article
Closed access
EGEduardo González
Eduardo González
MFMaría R. Felipe-Lucia
María R. Felipe-Lucia
BBBérenger Bourgeois
Bérenger Bourgeois
BBBruno Boz
Bruno Boz
CNChrister Nilsson
Christer Nilsson
ASAnna Sher
Anna Sher

11 December 2020 in Nature Communications
Verified
Journal Article
Open access
PDF file
ACAlec P. Christie
Alec P. Christie
DADavid Abecasis
David Abecasis
MAMehdi Adjeroud
Mehdi Adjeroud
JAJuan C. Alonso
Juan C. Alonso
TATatsuya Amano
Tatsuya Amano
WSWilliam J. Sutherland
William J. Sutherland
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 sampling were used by just 23% of intervention studies in biodiversity 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.

1 June 1999 in Biological Invasions
Verified
Journal Article
Closed access
PDF file
ASAnna Sher
Anna Sher
LHLaura A. Hyatt
Laura A. Hyatt

11 December 2003 in Oecologia
Verified
Journal Article
Closed access
PDF file
ASAnna Sher
Anna Sher
DGDeborah E. Goldberg
Deborah E. Goldberg
ANAriel Novoplansky
Ariel Novoplansky