Predicting plant–pollinator interactions: concepts, methods, and challenges
传粉者
生态学
地理
生物
授粉
花粉
作者
Guadalupe Peralta,Paul J. CaraDonna,Demetra Rákosy,Jochen Fründ,María Paula Pascual Tudanca,Carsten F. Dormann,Laura A. Burkle,Christopher N. Kaiser‐Bunbury,Tiffany M. Knight,Julian Resasco,Rachael Winfree,Nico Blüthgen,William J. Castillo,Diego P. Vázquez
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.