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