10.5061/DRYAD.7ST32
Olito, Colin
University of Calgary
Fox, Jeremy W.
University of Calgary
Data from: Species traits and abundances predict metrics of
plant–pollinator network structure, but not pairwise interactions
Dryad
dataset
2015
Neutrality
Mutualistic Network
2015-06-30T00:00:00Z
2015-06-30T00:00:00Z
en
https://doi.org/10.1111/oik.01439
337052 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Plant–pollinator mutualistic networks represent the ecological context of
foraging (for pollinators) and reproduction (for plants and some
pollinators). Plant–pollinator visitation networks exhibit highly
conserved structural properties across diverse habitats and species
assemblages. The most successful hypotheses to explain these network
properties are the neutrality and biological constraints hypotheses, which
posit that species interaction frequencies can be explained by species
relative abundances, and trait mismatches between potential mutualists
respectively. However, previous network analyses emphasize the prediction
of metrics of qualitative network structure, which may not represent
stringent tests of these hypotheses. Using a newly documented temporally
explicit alpine plant–pollinator visitation network, we show that metrics
of both qualitative and quantitative network structure are easy to
predict, even by models that predict the identity or frequency of species
interactions poorly. A variety of phenological and morphological
constraints as well as neutral interactions successfully predicted all
network metrics tested, without accurately predicting species observed
interactions. Species phenology alone was the best predictor of observed
interaction frequencies. However, all models were poor predictors of
species pairwise interaction frequencies, suggesting that other aspects of
species biology not generally considered in network studies, such as
reproduction for dipterans, play an important role in shaping
plant–pollinator visitation network structure at this site. Future
progress in explaining the structure and dynamics of mutualistic networks
will require new approaches that emphasize accurate prediction of species
pairwise interactions rather than network metrics, and better reflect the
biology underlying species interactions.
SM_A2_rawdata_fullExcel file with separate worksheets including: Raw
visitation data, aggregate network, plant densities, and morphology
classification matrices for plants and pollinators.SM_A3_Rcode_rquantwebsR
code for the algorithm used to generate random interaction frequency
matrices from the different probability models used in the study.
Canada
Alberta
Canadian Rockies
Kananaskis Country