Computational protocol: Variation in Seed Germination of 134 Common Species on the Eastern Tibetan Plateau: Phylogenetic, Life History and Environmental Correlates

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[…] Germination percentage (GP) was defined as the proportion of seed germinated, and seed mortality was defined as the proportion of unviable seeds tested with tetrazolium chloride after germination experiments. Mean germination time (GT) was estimated as follows: GT  =  ∑(Gi×i)/∑(G i), where i is the day of germination, counted since the day of sowing, and Gi is the number of seeds germinated on day i . Three species that did not germinate at the end of the experiments were not included in this calculation, i.e., 131 species were used in GT analysis ().First, a composite phylogeny of 134 species was constructed with Phylomatic version 3 (http://phylodiversity.net/phylomatic/) based on the angiosperm megatree (R20120829) . Branch lengths were made proportional to time using the ‘bladj’ function in the program Phylocom 4.0 and divergence time was estimated based on fossil data , . To test the robustness of our results to uncertainties associated with branch length estimates, we also ran our analyses on the same composite tree, but with branch lengths set to 1. The resulting phylogenetic tree was used for subsequent analyses. We tested for the existence of phylogenetic signal by estimating Pagel's λ for GP and GT using “fitContinuous” functions in the R package “geiger” version 1.99-3 , using a maximum likelihood framework to estimate the parameter λ, which can vary from 0 (no influence of phylogeny) to 1 (strong phylogenetic influence) .Then, one-way, two-way and multi-factorial ANOVAs were used to determine the effects of phylogeny and various life history (i.e., seed size, dispersal mode, life form, onset of flowering, duration of flowering) and environmental attributes (i.e., temperature and habitat) on GP and GT. One-way ANOVAs measured the effects of each factor on the variance of GP and GT across all other variables; two-way ANOVAs were conducted to detect significant interactions and associations between factors; multi-factorial ANOVAs tested the effect of each class variable independent of the others. We conducted a series of ANOVAs which include all variables but one (incomplete model). When each of these ANOVAs was compared to the ANOVA including all variables (complete model), the difference between the proportion of the total sum of squares (ss) explained by the complete model (its R2) and the R2 of the incomplete model represented the proportion of the total ss explained by the deleted class variable . Besides, multi-factorial ANOVAs corroborate associations between factors suggested by the two-way ANOVAs. If in the complete ANOVA, a given class variable had a lower R2 value than in the incomplete ANOVA from which a different variable had been deleted, the increase in the R2 value of the first variable would be due to an association (or correlation) or strong interaction with the second variable . To carry out the statistical analysis, we grouped 134 species according to the following categories: 1. Phylogenetic group. Each of the 134 species was assigned to a family and an order according to Angiosperm Phylogeny Group III (). When comparing the GP and GT between families, families containing more than seven species were chosen. 2. Life form. Species were grouped into two classes: annual and perennial. 3. Dispersal mode. Species were classified into four groups according to the morphological features of their seeds : unassisted, ant-dispersed, adhesion-dispersed and wind-dispersed. 4. Seed size. The mean seed size of each species was assigned to 1 of 5 seed size classes according to Baker : 0.032–0.099 mg, 0.100–0.315 mg, 0.316–0.999 mg, 1.000–3.161 mg, 3.162–9.999 mg. 5. Onset of flowering. Each species was grouped based on the Flora of China and field observation records: early, flowering begins in May; middle, flowering begins in June; or late, flowering begins in July and August. 6. Duration of flowering. Each species was grouped based on the Flora of China and field observation records: short, flowering duration of 1 month; median, flowering duration of 2–3 months; or long, flowering duration of ≥4 months. 7. Temperature. Based on temperatures occurring in the species' habitats, rising trend and the optimum alternating temperature regime of the most species , 5/15°C (control treatment), 5/20°C, 5/25°C, 10/20°C and 10/25°C were chosen. 8. Habitat. The habitats were classified into three categories: bottomland, north slope and south slope.Because the data were unbalanced, all ANOVAs were conducted using GLM procedure of SPSS 13.0. The type III sum of squares was used to establish the significance level of each effect. In addition, both GP and mortality were arcsine square root transformed, and GT were log-transformed to improve normality and stabilize variances. […]

Pipeline specifications

Software tools Phylomatic, Phylocom, GEIGER
Application Phylogenetics