Computational protocol: Germination and Seedling Growth of Water Primroses: A Cross Experiment between Two Invaded Ranges with Contrasting Climates

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Protocol publication

[…] Statistical analyses were performing using statistical RTM 3.2.3 software () with packages car (), MuMIn (), lme4 (), AICcmodavg (), and mixtools (). We applied linear models with mixed effects on the MTG, with species, climate, and seed provenance (i.e., invasive range) as fixed effects, and population as random effect. Binomial data such as seed germination, embryo viability, and seedlings survivorship were tested with generalized linear model with mixed effects, species, climate, and seed provenance as fixed effects, and population as random effect. Linear models with mixed effects were used to test the effect of seedling age, species, climate, seed provenance, and the interactions of seedling age, species, and seed provenance with climate (fixed effects), on seedling characteristics. The effects of capsules nested in tank and of populations were included in the model as random effects. Plots were generated from prediction of the linear models for seedling age by species and by range. Confidence intervals around the average predicted per seedling age were calculated as following: +1.96∗ standard deviation and -1.96∗ standard deviation. Variables were considered significantly different when the confidence intervals of the values predicted for the two climates were not overlapping. For both generalized linear models and linear models, the impact of fixed effects was tested with an analysis of deviance performed on the model. Moreover, the variability explained by the model was calculated for fixed and random effects according to the method developed by . […]

Pipeline specifications

Software tools lme4, mixtools
Application Mathematical modeling