Temporal development and collapse of an Arctic plant-pollinator network.
BACKGROUND
The temporal dynamics and formation of plant-pollinator networks are difficult to study as it requires detailed observations of how the networks change over time. Understanding the temporal dynamics might provide insight into sustainability and robustness of the networks and how they react to environmental changes, such as global warming. Here we study an Arctic plant-pollinator network in two consecutive years using a simple mathematical model and describe the temporal dynamics (daily assembly and disassembly of links) by random mechanisms.


RESULTS
We develop a mathematical model with parameters governed by the probabilities for entering, leaving and making connections in the network and demonstrate that A. The dynamics is described by very similar parameters in both years despite a strong turnover in the composition of the pollinator community and different climate conditions, B. There is a drastic change in the temporal behaviour a few days before the end of the season in both years. This change leads to the collapse of the network and does not correlate with weather parameters, C. We estimate that the number of available pollinator species is about 80 species of which 75-80% are observed in each year, D. The network does not reach an equilibrium state (as defined by our model) before the collapse set in and the season is over.


CONCLUSIONS
We have shown that the temporal dynamics of an Arctic plant-pollinator network can be described by a simple mathematical model and that the model allows us to draw biologically interesting conclusions. Our model makes it possible to investigate how the network topology changes with changes in parameter values and might provide means to study the effect of climate on plant-pollinator networks.
Pradal
Clementine
C
Bioinformatics Research Centre, Aarhus University, C, F, Mollers Alle 8, Building 1110, DK-8000 Aarhus C, Denmark.
Olesen
Jens M
JM
Wiuf
Carsten
C
D000818:Animals; D001110:Arctic Regions; D003198:Computer Simulation; D017753:Ecosystem; D007313:Insecta / Q000502:physiology*; D008962:Models, Theoretical; D018521:Plant Physiological Phenomena; D054817:Pollination; D012621:Seasons