Author

M. C. Orr

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· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:ecology & biodiversity· 2 Organism:multiple species· 2 Research Focus:benchmarking· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:database / resource· 1 Research Focus:development & morphogenesis· 1 Approach:experimental assay· 1

Frequent Co-Authors

A. C. Hughes· 2 shared J. M. Meiners· 2 shared K. Riemer· 2 shared A. Falcon-Brindis· 1 shared A. L. Russell· 1 shared A. Nava-Bolanos· 1 shared A. Smith-Pardo· 1 shared B. Ribeiro· 1 shared

Activity by Year

2018-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersEcology

A. C. Hughes

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Author profile →

4 papers

Recent·Most cited

Buzz-world: Global patterns and drivers of buzzing bees and poricidal plants

A. L. Russell, S. L. Buchmann, J. S. Ascher, Z. Wang, R. Kriebel, D. D. Jolles, M. C. Orr, A. C. Hughes

This study examines global patterns and drivers of buzzing bee distribution, finding that poricidal plant richness significantly influences buzzing bee biodiversity.

bioRxiv · Mar 6, 2024 · PreprintEcology

A globally synthesised and flagged bee occurrence dataset and cleaning workflow

J. B. Dorey, E. E. Fischer, P. R. Chesshire, A. Nava-Bolanos, R. L. OReilly, S. Bossert, S. M. Collins, E. M. Lichtenberg, E. M. Tucker, A. Smith-Pardo, A. Falcon-Brindis, D. A. Guevara, B. Ribeiro, D. de Pedro, J. Pickering, , N. S. Cobb

The paper presents a cleaned and flagged global bee occurrence dataset and an R package to improve data accessibility and reliability for conservation and research.

bioRxiv · Jun 30, 2023Ecology

The influence of data type and functional traits on native bee phenology metrics: Opportunistic versus inventory records

J. M. Meiners, M. C. Orr, K. Riemer, T. L. Griswold, J. L. Simonis

This study compares phenology metrics of native bees using opportunistic museum records and systematic inventory data, finding significant differences in flight duration, peak dates, and peak numbers across species and data types.

bioRxiv · Apr 16, 2020 · PreprintEcology

Comparison of large-scale citizen science data and long-term study data for phenology modeling

S. D. Taylor, J. M. Meiners, K. Riemer, M. C. Orr, E. P. White

This paper compares phenology models built from citizen science data and long-term ecological study data, finding that model performance depends on dataset scale and complexity.

bioRxiv · May 31, 2018Ecology