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Peer-reviewedCC BY 4.0The New Phytologist

Ten rules for robust taxonomy in ecological datasets

  • Renato A. Ferreira de Lima1
  • Guilherme S. Grittz2
  • Moabe F. Fernandes3
  • Hans ter Steege4,5
  • Kyle G. Dexter6,7,8
  • Oliver Phillips9
  • Marli P. Morim10
  • Jérôme Chave11
  • Géraldine Derroire12,13
  • Filipe M. França14,15
  • Tamara Heartsill‐Scalley16
  • Ricardo A. Segovia17,18
7 more authors
  • Caroline E. R. Lehmann7,8
  • Luis Cayuela19
  • Karina Banda20
  • Cecilia Blundo21
  • Jesús Aguirre‐Gutiérrez22,23
  • André L. de Gasper24
  • R. Toby Pennington8,25,26,27
27 affiliations
  1. 1Departamento de Ciências Biológicas, Escola Superior de Agricultura “Luiz de Queiroz” Universidade de São Paulo Avenida Pádua Dias, 11 13418‐900 Piracicaba Brazil
  2. 2Programa de Pós‐Graduação em Recursos Florestais, Escola Superior de Agricultura “Luiz de Queiroz” Universidade de São Paulo Avenida Pádua Dias, 11 13418‐900 Piracicaba Brazil
  3. 3Royal Botanic Gardens Kew Richmond TW9 3AB Surrey UK
  4. 4Naturalis Biodiversity Center 2333 CR Leiden the Netherlands
  5. 5Quantitative Biodiversity Dynamics, Department of Biology Utrecht University 3584 CH Utrecht the Netherlands
  6. 6Dipartimento di Scienze della Vita e Biologia dei Sistemi Università di Torino 10123 Turin Italy
  7. 7School of GeoSciences University of Edinburgh EH8 9XP Edinburgh UK
  8. 8Taxonomy and Macroecology, Royal Botanic Garden Edinburgh EH3 5LR Edinburgh UK
  9. 9School of Geography University of Leeds LS2 9JT Leeds UK
  10. 10Jardim Botânico do Rio de Janeiro Rua Pacheco Leão, 915 22460‐030 Rio de Janeiro Brazil
  11. 11Centre de Recherche Biodiversité Environnement UMR 5300 (CNRS/IRD/UPS/INPT) 31062 Toulouse Cedex 9 France
  12. 12Cirad, UPR Forêts et Sociétés University of Montpellier 34398 Montpellier France
  13. 13Department of Forestry University of Brasilia Campus Darcy Ribeiro 70910‐900 Brasília Brazil
  14. 14School of Biological Sciences University of Bristol BS8 1TQ Bristol UK
  15. 15Programa de Pós‐Graduação em Ecologia Universidade Federal do Pará 66075‐110 Belém Brazil
  16. 16International Institute of Tropical Forestry, USDA Forest Service 00926‐1119 Río Piedras Puerto Rico
  17. 17Departamento de Botánica Universidad de Concepción 4070386 Concepción Chile
  18. 18Instituto de Ecología y Biodiversidad (IEB) 7800024 Santiago Chile
  19. 19Department of Biology, ESCET Universidad Rey Juan Carlos 28933 Madrid Spain
  20. 20Fundación Ecosistemas Secos de Colombia 081001 Puerto Colombia Colombia
  21. 21Instituto de Ecología Regional Universidad Nacional de Tucumán – Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Casilla de Correo 34 4107 Tucumán Argentina
  22. 22Environmental Change Institute University of Oxford OX1 3QY Oxford UK
  23. 23Facultad de Ciencias Forestales y Ambientales Universidad Juárez del Estado de Durango 34120 Durango Mexico
  24. 24Departamento de Ciências Naturais Universidade Regional de Blumenau 89030‐903 Blumenau Brazil
  25. 25Department of Biology Washington University St Louis MO 63130 USA
  26. 26Missouri Botanical Garden St Louis MO 63130 USA
  27. 27Geography Department, College of Life and Environmental Sciences University of Exeter EX4 4QE Exeter UK
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Abstract

Accurate taxonomy, including species identification and naming, underpins ecological inference, yet taxonomic information in ecological datasets is often inconsistently recorded or weakly standardized. With the increasing integration of ecological datasets across taxa and regions, datasets with poor taxonomic practices can hinder data exchange and propagate errors. We propose 10 rules to improve the storage and management of taxonomic information in ecological datasets. These rules draw on our experiences in plant ecology and taxonomy, but the conclusions may be generalized to other organisms and disciplines. They emphasize aspects from species identification to the permanent storage of verifiable records (e.g. voucher specimens) and include taxonomic standardization, nomenclature, validation, and updating. We also address the treatment of morphotypes and incomplete identifications, the use of automated name‐matching tools, and (meta)data standards. Closer collaboration between ecologists and taxonomists is key to ensuring more robust datasets. The application of these rules consumes more time and resources, but they enhance data quality and interoperability, saving time during data integration and improving the reliability and scalability of ecological research.

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Cite

BibTeXRIS
BibTeX
@article{lima2026rules,
  title = {{Ten rules for robust taxonomy in ecological datasets}},
  author = {Renato A. Ferreira de Lima and Guilherme S. Grittz and Moabe F. Fernandes and Hans ter Steege and Kyle G. Dexter and Oliver Phillips and Marli P. Morim and Jérôme Chave and Géraldine Derroire and Filipe M. França and Tamara Heartsill‐Scalley and Ricardo A. Segovia and Caroline E. R. Lehmann and Luis Cayuela and Karina Banda and Cecilia Blundo and Jesús Aguirre‐Gutiérrez and André L. de Gasper and R. Toby Pennington},
  journal = {The New Phytologist},
  year = {2026},
  month = oct,
  doi = {10.1111/nph.71658},
  url = {https://doi.org/10.1111/nph.71658},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Ten rules for robust taxonomy in ecological datasets
AU  - Renato A. Ferreira de Lima
AU  - Guilherme S. Grittz
AU  - Moabe F. Fernandes
AU  - Hans ter Steege
AU  - Kyle G. Dexter
AU  - Oliver Phillips
AU  - Marli P. Morim
AU  - Jérôme Chave
AU  - Géraldine Derroire
AU  - Filipe M. França
AU  - Tamara Heartsill‐Scalley
AU  - Ricardo A. Segovia
AU  - Caroline E. R. Lehmann
AU  - Luis Cayuela
AU  - Karina Banda
AU  - Cecilia Blundo
AU  - Jesús Aguirre‐Gutiérrez
AU  - André L. de Gasper
AU  - R. Toby Pennington
PY  - 2026
DA  - 2026/10/12
JO  - The New Phytologist
DO  - 10.1111/nph.71658
UR  - https://doi.org/10.1111/nph.71658
AB  - Accurate taxonomy, including species identification and naming, underpins ecological inference, yet taxonomic information in ecological datasets is often inconsistently recorded or weakly standardized. With the increasing integration of ecological datasets across taxa and regions, datasets with poor taxonomic practices can hinder data exchange and propagate errors. We propose 10 rules to improve the storage and management of taxonomic information in ecological datasets. These rules draw on our experiences in plant ecology and taxonomy, but the conclusions may be generalized to other organisms and disciplines. They emphasize aspects from species identification to the permanent storage of verifiable records (e.g. voucher specimens) and include taxonomic standardization, nomenclature, validation, and updating. We also address the treatment of morphotypes and incomplete identifications, the use of automated name‐matching tools, and (meta)data standards. Closer collaboration between ecologists and taxonomists is key to ensuring more robust datasets. The application of these rules consumes more time and resources, but they enhance data quality and interoperability, saving time during data integration and improving the reliability and scalability of ecological research.
SN  - 0028-646X
SN  - 1469-8137
ER  -