  Coextinction models are useful to understand community robustness to species
loss and resilience to disturbances. We simulated pollinator extinctions in
pollination networks by using a hybrid model that combined a recently developed
stochastic coextinction model (SCM) for plant extinctions and a topological
model (TCM) for animal extinctions. Our model accounted for variation in
interaction strengths and included empirical estimates of plant dependence on
pollinators to set seeds. The stochastic nature of such model allowed us
determining plant survival to single (and multiple) extinction events, and
identifying which pollinators (keystone species) were more likely to trigger
secondary extinctions. Consistently across three different pollinator removal
sequences, plant robustness was lower than in a pure TCM, and plant survival
was more determined by dependence on the mutualism than by interaction
strength. As expected, highly connected and dependent plants were the most
sensitive to pollinator loss and collapsed faster in extinction cascades. We
predict that the relationship between dependence and plant connectivity is
crucial to determine network robustness to interaction loss. Finally, we showed
that honeybees and several beetles were keystone species in our communities.
This information is of great value to foresee consequences of pollinator losses
facing current global change and to identify target species for effective
conservation.
