Guadalupe Peralta, Paul J CaraDonna, Demetra Rakosy, Jochen Fründ, María P 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
{"title":"Predicting plant-pollinator interactions: concepts, methods, and challenges.","authors":"Guadalupe Peralta, Paul J CaraDonna, Demetra Rakosy, Jochen Fründ, María P 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","doi":"10.1016/j.tree.2023.12.005","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23274,"journal":{"name":"Trends in ecology & evolution","volume":null,"pages":null},"PeriodicalIF":16.7000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in ecology & evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tree.2023.12.005","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Trends in Ecology & Evolution (TREE) is a comprehensive journal featuring polished, concise, and readable reviews, opinions, and letters in all areas of ecology and evolutionary science. Catering to researchers, lecturers, teachers, field workers, and students, it serves as a valuable source of information. The journal keeps scientists informed about new developments and ideas across the spectrum of ecology and evolutionary biology, spanning from pure to applied and molecular to global perspectives. In the face of global environmental change, Trends in Ecology & Evolution plays a crucial role in covering all significant issues concerning organisms and their environments, making it a major forum for life scientists.