Plant survival and keystone pollinator species in stochastic coextinction models: role of intrinsic dependence on animal-pollination

Cristina Tur,Anna Traveset,Víctor M Eguíluz

doi:10.1038/s41598-017-07037-7

Abstract

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.

Highlights

Anthropogenic disturbances, such as habitat transformation, climate change or biological invasions, are at present main drivers of species loss and disruption of ecological interactions[1,2,3]
A simple stochastic coextinction model (SCM) has been developed[17] that simulates species extinction cascades in mutualistic networks accounting for variation in interaction strengths and species dependence on the mutualism, relaxing the assumption that coextinctions require the loss of all partners
When comparing the different model variants of SCM under the random extinction scenario, we found that models not incorporating plant dependence on pollinators led to greater extinction cascades and smaller fractions of surviving species than models considering plant dependencies (Fig. 2)

Summary

Introduction

Anthropogenic disturbances, such as habitat transformation, climate change or biological invasions, are at present main drivers of species loss and disruption of ecological interactions[1,2,3]. These models are mainly based on static network structure and have several important constraints They assume that a species can only become extinct when all its interacting partners are lost; the primary loss of a pollinator species in real plant-pollinator networks may cause the coextinction of a plant, leading in turn to the coextinction of other pollinators that strongly depended on that plant, and even to the indirect coextinction of other plants which rely on those pollinators. A simple stochastic coextinction model (SCM) has been developed[17] that simulates species extinction cascades in mutualistic networks accounting for variation in interaction strengths and species dependence on the mutualism, relaxing the assumption that coextinctions require the loss of all partners. We aimed at identifying the plant species that are more sensitive to pollinator extinctions and which pollinator losses cause the highest number of plant coextinctions

Methods

Results

Conclusion