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Title: A new model for ecological networks using species-level traits
Contributor(s): Crea, Catherine (author); Ali, R Ayesha (author); Rader, Romina  (author)orcid 
Publication Date: 2016
DOI: 10.1111/2041-210x.12471
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Abstract: 1. Recent studies on plant-pollinator networks have focused on explaining network structure through linkage rules, including spatio-temporal overlap, and phenotypic trait or phylogenetic signal complementarity. Few studies, however, have quantified the extent to which functional traits affect the probability of plants and pollinators interacting with each other. 2. Dirichlet-multinomial (DM) regression is a consumer-resource model for the interaction probabilities in a mutualistic network. This flexible model accommodates network heterogeneity through random effects and overdispersion and can estimate the contribution of species-level traits to plant-pollinator interactions. 3. Using artificial networks based on linkage rules and neutrality, we evaluate the performance of DM regression and explore the model's parameter space. We also analyse an empirical network in which the interaction probabilities are modelled by species characteristics. 4. Study results show that such random effects models can provide good fits to observed data. The characteristics pollinators seek in plant species may be better anticipated if species interactions are modelled by the functional traits that drive them.
Publication Type: Journal Article
Source of Publication: Methods in Ecology and Evolution, 7(2), p. 232-241
Publisher: Wiley-Blackwell Publishing Ltd
Place of Publication: United Kingdom
ISSN: 2041-210X
Field of Research (FOR): 070301 Agro-ecosystem Function and Prediction
050202 Conservation and Biodiversity
Socio-Economic Outcome Codes: 960504 Ecosystem Assessment and Management of Farmland, Arable Cropland and Permanent Cropland Environments
960804 Farmland, Arable Cropland and Permanent Cropland Flora, Fauna and Biodiversity
960505 Ecosystem Assessment and Management of Forest and Woodlands Environments
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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