Predictive systems models can help elucidate bee declines driven by multiple combined stressors

Authored by Volker Grimm, Mickael Henry, Matthias A Becher, Juliet L Osborne, Peter J Kennedy, Pierrick Aupinel, Vincent Bretagnolle, Francois Brun, Juliane Horn, Fabrice Requier

Date Published: 2017

DOI: 10.1007/s13592-016-0476-0

Sponsors: European Union Biotechnology and Biological Sciences Research Council (BBSRC)

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Bee declines are driven by multiple combined stresses, making it exceedingly difficult to identify experimentally the most critical threats to bees and their pollination services. We highlight here the too often ignored potential of mechanistic models in identifying critical stress combinations. Advanced bee models are now available as open access tools and offer an unprecedented opportunity for bee biologists to explore bee resilience tipping points in a variety of environmental contexts. We provide general guidelines on how to run bee models to help detect a priori critical stress combinations to be targeted in the field. This so-called funnel analysis should be performed in tight conjunction with the recent development of large-scale field monitoring programs for bee health surveillance.
Tags
Agent-based models Dynamics ecology Apis mellifera exposure Honeybees Protocol Failure Field monitoring program Mechanistic modeling Combined pesticide Colony survival Honeybee Beehave