Article
Predicting plant - pollinator interactions: concepts, methods, and challenges
Authors
Guadalupe Peralta, Paul J. CaraDonna, Demetra Rakosy, Jochen Fruend, Maria P. Pascual Tudanca, Carsten F. Dormann, Laura A. Burkle, Christopher N. Kaiser-Bunbury, Tiffany M. Knight, Julian Resasco, Rachael Winfree, Nico Bluethgen, William J. Castillo, Diego P. Vazquez
Publication
Trends in Ecology & Evolution
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.
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This collection of Montana State authored publications is collected by the Library to highlight the achievements of Montana State researchers and more fully understand the research output of the University. They use a number of resources to pull together as complete a list as possible and understand that there may be publications that are missed. If you note the omission of a current publication or want to know more about the collection and display of this information email Leila Sterman.