DOI: 10.5061/dryad.jq2bvq8hm
title: Data from: Emergence of structure in plant-pollinator networks: Low floral resource constrains network specialisation

description: Specialisation enhances the efficiency of plant-pollinator networks
 through the exchange of conspecific pollen transfer for floral resources.
 Floral resources form the currency of plant-pollinator interactions, but
 the understanding of how floral resources affect the structure of
 plant-pollinator networks remains modest. Previous theory predicts that
 optimally foraging animal species will specialise to improve resource
 acquisition under high resource availability. Although floral resource
 availability depends on both the plant production and animal consumption
 of the resources, previous work has assumed that production and
 availability to be equivalent. This potentially may have led to erroneous
 inferences on the effect of resource availability on specialisation. We
 develop a mutualistic Lotka-Volterra consumer-resource model to
 investigate the influence of floral resource availability on
 plant-pollinator network structure. The model incorporates animal adaptive
 foraging behaviour, floral resource dynamics, and density-dependent
 dynamics. Specialisation, nestedness and modularity of simulated networks
 generated from the model under a wide range of parameters were explained
 using the Generalised Linear Model. We found that the distinction between
 floral resource dynamics and plant density dynamics was necessary for
 partial specialisation of plant-pollinator networks. This is because
 floral resource dynamics constraint animal preference due to its depletion
 by animal species. Floral resource abundance had a positive effect on
 network specialisation, but animal density had a negative effect on
 network specialisation. Floral resource dynamics thus play key roles on
 the structure of plant-pollinator network, distinctive from plant species
 density dynamics.
description: This data was simulated with theoretical model which reperesent
 plant-pollinator community. Parameter are generated abitrarily for each
 networks which correspond to each row in the spread sheet. Network
 structure and species' characteristics were estimated and stored for
 each network. The simulation was carried out with High Performing
 Computing. The simulations were conducted using R language.
description: # Yahaya, M.M., Rodger, J.G., Landi, P., Hui. C., (2024) Emergence of
 structure in plant-pollinator networks: Low floral resource contrains
 network specialisation. **DOI**:10.1111/oik.10533 ## **Data files**
 modelledNet.csv - Speedsheet NetModel.R - R script NetStructurePar.R - R
 script PostModelAnalysis.R - R script ## **Meaning of variables in the
 simulated data and R scripts** \[1] "P" - Number of plant
 species \[2] "A" - Number of animal species \[3] "H2"
 - Specialisation \[4] "WNODA" - Nestedness \[5]
 "modularity" - Modularity \[6] "mean_XP0" - Mean of
 plant density (initial) \[7] "mean_XA0" - Mean of animal density
 (initial) \[8] "mean_rP" - Mean of plant intrinsic growth rate
 \[9] "mean_rA" - Mean of animal intrinsic growth rate \[10]
 "mean_CP" - Mean of plant density dependence \[11]
 "mean_CA" - Mean of animal density dependence \[12]
 "mean_a" - Mean of floral resource production \[13]
 "mean_w" - Mean of floral resource decay rate \[14]
 "mean_Fi0" - Mean of floral resource abundance (initial) \[15]
 "mean_c_sigma_P" - Mean of plant conversion efficiency \[16]
 "mean_c_sigma_A" - Mean of animal conversion efficiency \[17]
 "mean_XPF" - Mean of plant density (final) \[18]
 "mean_XAF" - Mean of animal density (final) \[19]
 "mean_FiF" - Mean of floral resource abundance (final) \[20]
 "mean_G" - Mean of animal adaptaion rate \[21]
 "mean_FA" - Mean of encounter rate (between animal and floral
 resource) \[22] "var_XP0" - Variance of plant density (initial)
 \[23] "var_XA0" - Variance of animal density (initial) \[24]
 "var_rP" - Variance of plant intrinsic growth rate \[25]
 "var_rA" - Variance of animal intrinsic growth rate \[26]
 "var_CP" - Variance of plant density dependence \[27]
 "var_CA" - Variance of animal density dependence \[28]
 "var_a" - Variance of floral resource production rate \[29]
 "var_w" - Variance of floral resource decay rate \[30]
 "var_Fi0" - Variance of floral resource abundance (initial)
 \[31] "var_c_sigma_P" - Variance of plant conversion efficiency
 \[32] "var_c_sigma_A" - Vaariance of animal conversion
 efficiency \[33] "var_XPF" - Variance of plant density (final)
 \[34] "var_XAF" - Variance of animal density (final) \[35]
 "var_FiF" - Variance of floral resource abundance (final) \[36]
 "var_G" - Variance of animal adaption rate \[37]
 "var_FA" - Variance of encounter rate \[38] "S" -
 Specie richness \[39] "P_div_A" - Ratio of plant to animal
 specie richness # Brief description of data modelleNet: A spreadsheet
 containing 3812 simulated plan-pollinator communities. Each row correspond
 to single plant-pollinator community NetModel: R code for simulation of
 plant-pollinator model NetStructurePar: R code for simulation of network
 structure and species characteristics using High Performance Computing
 PostModelAnalysis: R code for post-model statistical analyses ## Software
 version R: R version 4.3.2 (2023-10-31 ucrt) "Eye Holes"
 RStudio: RStudio 2023.09.1+494 "Desert Sunflower" Release
 (cd7011dce393115d3a7c3db799dda4b1c7e88711, 2023-10-16) for windows
 Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like
 Gecko) RStudio/2023.09.1+494 Chrome/116.0.5845.190 Electron/26.2.4
 Safari/537.36