Author

M. Lagisz

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 2 Evolutionary Biology· 2 Scientific Communication & Education· 2 Animal Behavior & Cognition· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Research Focus:benchmarking· 3 Approach:benchmark study· 2 Research Focus:ecology & biodiversity· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:chromatin & epigenetic regulation· 1

Frequent Co-Authors

S. Nakagawa· 7 shared Y. Yang· 3 shared A. R. Martinig· 2 shared A. Senior· 2 shared C. Williams· 2 shared J. Mason· 2 shared K. Morrison· 2 shared L. Ricolfi· 2 shared

Activity by Year

2019-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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7 shared papersEcology

S. Nakagawa

Mutual co-authors in cluster

Author profile →

7 papers

Recent·Most cited

Bivariate multilevel meta-analysis of log response ratio and standardized mean difference for robust and reproducible environmental and biological sciences

Y. Yang, C. Williams, A. Senior, K. Morrison, L. Ricolfi, J. Pan, M. Lagisz, S. Nakagawa

This paper introduces a bivariate multilevel meta-analysis method for log response ratio and standardized mean difference to improve reproducibility and reduce false positives in environmental and biological meta-analyses.

bioRxiv · May 13, 2024 · PreprintEcology

Best Paper awards lack transparency, inclusivity, and support for Open Science

M. Lagisz, J. Rutkowska, U. Aich, R. M. Ross, M. S. Santana, J. Wang, N. Trubanova, M. J. Page, A. A. Y. Pua, Y. Yang, B. Amin, A. R. Martinig, A. Barnett, A. Surendran, J. Zhang, , S. Nakagawa

This paper surveys 222 Best Paper awards across disciplines and finds they lack transparency, inclusivity, and support for Open Science, with geographic and gender biases.

bioRxiv · Dec 11, 2023Scientific Communication & Education

Keywords to success: a practical guide to maximise the visibility and impact of academic papers

P. Pottier, M. Lagisz, S. Burke, S. M. Drobniak, P. A. Downing, E. L. Macartney, A. R. Martinig, A. Mizuno, K. Morrison, P. Pollo, L. Ricolfi, J. Tam, C. Williams, Y. Yang, S. Nakagawa

The paper provides evidence-based recommendations to improve the discoverability and impact of academic papers through optimized use of keywords and abstract structure.

bioRxiv · Oct 2, 2023 · PreprintScientific Communication & Education

Sex differences in allometry for mouse phenotypic traits indicate that females are not scaled males

L. A. B. Wilson, S. R. K. Zajitschek, M. Lagisz, J. Mason, H. Haselimashhadi, S. Nakagawa

The paper quantifies sex differences in allometric relationships for 375 phenotypic traits in mice, finding that body weight differences do not fully explain sex differences in trait values.

bioRxiv · Mar 29, 2022 · PreprintEvolutionary Biology

Sex and Power: sexual dimorphism in trait variability and its eco-evolutionary and statistical implications

S. R. K. Zajitschek, F. Zajitschek, R. Bonduriansky, R. C. Brooks, W. K. Cornwell, D. S. Falster, M. Lagisz, J. Mason, A. Senior, D. Noble, S. Nakagawa

The paper tests sex differences in trait variability using mouse data, finding trait-dependent patterns that challenge existing hypotheses and highlight eco-evolutionary and statistical implications.

bioRxiv · May 23, 2020Evolutionary Biology

Consistent trade-offs in ecosystem services between land covers with different production intensities

C. Gómez-Creutzberg, M. Lagisz, S. Nakagawa, E. G. Brockerhoff, J. M. Tylianakis

The paper quantifies ecosystem service supply across different land covers in New Zealand, finding consistent trade-offs between high-intensity production and extensive/no production land covers, but no distinct patterns for forest cover.

bioRxiv · Apr 23, 2020Ecology

Pharmacological manipulations of judgement bias: a systematic review and meta-analysis

V. Neville, S. Nakagawa, J. Zidar, E. S. Paul, M. Lagisz, M. Bateson, H. Lovlie, M. Mendl

This study reviews and analyzes 19 pharmacological studies on judgement bias in animals, finding that drug-induced affective states alter bias as predicted, but with moderating factors like drug target and dosage.

bioRxiv · Apr 18, 2019Animal Behavior & Cognition