Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.tree.2023.12.005
Title (Primary) Predicting plant–pollinator interactions: concepts, methods, and challenges
Author Peralta, G.; CaraDonna, P.J.; Rakosy, D.; Fründ, J.; Pascual Tudanca, M.P.; Dormann, C.F.; Burkle, L.A.; Kaiser-Bunbury, C.N.; Knight, T.M.; Resasco, J.; Winfree, R.; Blüthgen, N.; Castillo, W.J.; Vázquez, D.P.
Source Titel Trends in Ecology & Evolution
Year 2024
Department CLE; iDiv; SIE
Volume 39
Issue 5
Page From 494
Page To 505
Language englisch
Topic T5 Future Landscapes
Keywords abundance; mechanistic model; phenomenological model; sampling effects; spatial and temporal distribution; trait matching
Abstract Plant–pollinator interactions are ecologically and economically important, and, as a result, their prediction is a crucial theoretical and applied goal for ecologists. Although various analytical methods are available, we still have a limited ability to predict plant–pollinator interactions. The predictive ability of different plant–pollinator interaction models depends on the specific definitions used to conceptualize and quantify species attributes (e.g., morphological traits), sampling effects (e.g., detection probabilities), and data resolution and availability. Progress in the study of plant–pollinator interactions requires conceptual and methodological advances concerning the mechanisms and species attributes governing interactions as well as improved modeling approaches to predict interactions. Current methods to predict plant–pollinator interactions present ample opportunities for improvement and spark new horizons for basic and applied research.
Persistent UFZ Identifier
Peralta, G., CaraDonna, P.J., Rakosy, D., Fründ, J., Pascual Tudanca, M.P., Dormann, C.F., Burkle, L.A., Kaiser-Bunbury, C.N., Knight, T.M., Resasco, J., Winfree, R., Blüthgen, N., Castillo, W.J., Vázquez, D.P. (2024):
Predicting plant–pollinator interactions: concepts, methods, and challenges
Trends Ecol. Evol. 39 (5), 494 - 505 10.1016/j.tree.2023.12.005