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Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

Please always quote using this URN: urn:nbn:de:bvb:20-opus-167642
  • Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data couldLand-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises.show moreshow less

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Author: Adriana De Palma, Stefan Abrahamczyk, Marcelo A. Aizen, Matthias Albrecht, Yves Basset, Adam Bates, Robin J. Blake, Céline Boutin, Rob Bugter, Stuart Connop, Leopoldo Cruz-López, Saul A. Cunningham, Ben Darvill, Tim Diekötter, Silvia Dorn, Nicola Downing, Martin H. Entling, Nina Farwig, Antonio Felicioli, Steven J. Fonte, Robert Fowler, Markus Franzén Franzen, Dave Goulson, Ingo Grass, Mick E. Hanley, Stephen D. Hendrix, Farina Herrmann, Felix Herzog, Andrea Holzschuh, Birgit Jauker, Michael Kessler, M. E. Knight, Andreas Kruess, Patrick Lavelle, Violette Le Féon, Pia Lentini, Louise A. Malone, Jon Marshall, Eliana Martínez Pachón, Quinn S. McFrederick, Carolina L. Morales, Sonja Mudri-Stojnic, Guiomar Nates-Parra, Sven G. Nilsson, Erik Öckinger, Lynne Osgathorpe, Alejandro Parra-H, Carlos A. Peres, Anna S. Persson, Theodora Petanidou, Katja Poveda, Eileen F. Power, Marino Quaranta, Carolina Quintero, Romina Rader, Miriam H. Richards, T’ai Roulston, Laurent Rousseau, Jonathan P. Sadler, Ulrika Samnegård, Nancy A. Schellhorn, Christof Schüepp, Oliver Schweiger, Allan H. Smith-Pardo, Ingolf Steffan-Dewenter, Jane C. Stout, Rebecca K. Tonietto, Teja Tscharntke, Jason M. Tylianakis, Hans A. F. Verboven, Carlos H. Vergara, Jort Verhulst, Catrin Westphal, Hyung Joo Yoon, Andy Purvis
URN:urn:nbn:de:bvb:20-opus-167642
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):Scientific Reports
Year of Completion:2016
Volume:6
Pagenumber:31153
Source:Scientific Reports 6:31153 (2016). DOI: 10.1038/srep31153
DOI:https://doi.org/10.1038/srep31153
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:bee community; geographic biases; global dataset; intensification; land-use change; taxonomic biases
Release Date:2019/09/03
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International