Computational protocol: Diversity protects plant communities against generalist molluscan herbivores

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Protocol publication

[…] The effectiveness of the (–) mollusk treatment was tested by analysing the total mollusk abundance, abundance of the three most common species and the mollusk eggs, using linear mixed effect models (lme) in the package nlme (Pinheiro et al. ), with the three fence treatments and the sown plant number as fixed effects and the twelve wildflower strips as random effect. Again, the function glht (Hothorn et al. ) was used to compute the difference between treatments and years.We then analysed the effects of mollusks on the vegetation. First, the effect of the mollusk treatment and of sown plant number on the plant species richness, effective number of species, vegetation height, plant biomass, and number of invading plant species (species other than those from the sown seed mixture) were analysed for the 3 years separately, with the twelve wildflower strips as random variables. The species richness and cover of the plant functional groups and the individual cover of plant species were then analysed for 2009, the year in which plant diversity differences between the mollusk treatments were significant. We analyzed only the 39 plant species that occurred in more than 20 of the 144 subplots and that had a mean cover >1% over all subplots in this year. We also analyzed the presence/absence data for these plant species using linear mixed effect models with a binomial function and logit link (lmer in the package lme4), again using the mollusk treatments and sown plant number as explanatory variables and the 12 wildflower strips as random variables. To correct for multiple testing, we computed Q-values on the basis of the 39 P-values correcting for the false discovery rate (FDR = No. of false positives/No. of significant tests) using the library q-value (Storey ). We fixed the tuning parameter λ to 0.0 (the most conservative value) for the presence/absence data and to a range between 0 and 0.9 for the cover data. […]

Pipeline specifications

Software tools nlme, lme4
Application Mathematical modeling