Quantifying leaf herbivory: A guide to methodological trade‐offs and best practices
Year: 2026
Type: article
Abstract: Leaf herbivory is a ubiquitous ecological interaction that varies significantly in intensity across species, habitats, and biogeographic regions. Although quantification of leaf damage is crucial for understanding many ecological processes, the accuracy and precision of various damage estimation methods used by researchers, including visual estimation, digital image analysis, and artificial intelligence, have not been evaluated and compared. We use a phylogenetically diverse group of tropical plants to compare the accuracy and precision of damage estimation methods and use the results to provide a guide to herbivory estimation that balances the advantages and disadvantages of each method. We found that visual estimation tended to overestimate herbivory levels compared to digital methods but was 15 times faster and improved in accuracy and speed with training. Conversely, deep-learning algorithms underestimated herbivory relative to image analysis with ImageJ when it was on the margin, but showed similar accuracy for damage inside of leaf margins. Our results indicate that while visual methods allow for rapid assessment of large sample sizes and are suitable for detecting broad patterns of damage, image analysis is crucial for accurate and precise quantification. The disadvantages of each method, however, can be minimized through proper training and efficient use of each tool, and we therefore provide a guide of practical approaches to herbivory estimation.
Source: Ecology
DOI: 10.1002/ecy.70308
Authors: Tatiana Cornelissen, Gisele M. Mendes, Fernando A. O. Silveira, Wesley Dáttilo, Roger Guevara, Ramiro Aguilar, Maria Gabriela Boaventura, Ricardo Campos, Ek del Val, Guilherme Ramos Demetrio, Marcilio Fagundes, Rafael de Paiva Farias, Geraldo W. Fernandes, Tiago Fernandes, Inácio Gomes, Thiago Kloss, Juliana Kuchenbecker, Leandro Maracahipes, Frederico Neves, Lucas Paolucci, Cássio Cardoso Pereira, Elenir Queiroz, Letícia Ramos, Sérvio P. Ribeiro, Gustavo Q. Romero, Carolina Oliveira, Jhonathan O. Silva, Tathiana Sobrinho, Ricardo Solar, Heraldo Vasconcelos, Gabriela Zorzal, William C. Wetzel
Institutions: Universidade Federal de Minas Gerais, Instituto de Ecología, Universidad Nacional de Córdoba, Instituto Multidisciplinario de Biología Vegetal, Universidade Federal de Viçosa, Universidad Nacional Autónoma de México, Universidade Federal de Alagoas, Universidade Estadual de Montes Claros, Universidade Federal da Bahia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Yale University, Universidade Federal de Ouro Preto, Universidade Estadual de Campinas (UNICAMP), Universidade Federal do Vale do São Francisco, Universidade Federal do Espírito Santo, Universidade Federal de Uberlândia, Montana State University
Language: English
Subfield: Insect Science
Domain: Life Sciences
SDGs: Life on land, Zero hunger
Open Access status: hybrid
Estimated APC paid: $3,970
Funders: National Science Foundation, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Fundação de Amparo à Pesquisa do Estado de Alagoas, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Fundação de Amparo à Pesquisa e Inovação do Espírito Santo
OpenAlex ID: W7127427590