The relationships between trait plasticity and canalization, and between phenotypic integration and plasticity, have been under debate, largely because direct evidence is still scarce for their associations, especially in response to environments. To investigate the relationships between canalization, integration, and phenotypic plasticity in response to emergence time, we conducted a field experiment with an annual herbaceous species of Abutilon theophrasti, by subjecting plants to four treatments of emergence time (spring, late spring, summer, and late summer), to measure several morphological traits and analyze correlations of plasticity with canalization and integration in these traits, at two stages of plant growth. Results showed plants with delayed emergence had higher phenotypic integration and more positive correlations between integration and plasticity, but less negative correlations between decreased canalization and plasticity, compared to those that emerged in spring. Results suggested significant environmental changes that induce plastic responses, rather than environmental stress, can result in greater phenotypic integration in plants. Negative correlations between decreased canalization and plasticity occurred more frequently in plants emerging in spring and the least frequently in those emerging in summer, suggesting their relationship depends on specific environmental conditions and the degree of plasticity. Both increased phenotypic integration and decreased canalization might merely be the outcome of plastic responses, rather than mechanisms constraining or facilitating plasticity.

Experimental design

We conducted the field experiment in 2007 at the Pasture Ecological Research Station of Northeast Normal University, Changling, Jilin Province, China (44°45’ N, 123°45’ E). The original soil of the experimental field (aeolian sandy soil, pH = 8.3) at the station had been used annually for many years, with nutrients availability of organic C 3.1 mg kg^–1, available N 21.0 mg kg^–1, and available P 1.1 mg kg^–1 during the growth season of 2007. Seeds of A. theophrasti were collected from local wild populations near the research station in late August 2006 and dry stored at -4°C. We applied a randomized block design, with emergence timing (ET) as the main factor, and block as the sub-factor. The whole plot was divided into twelve 2 × 3 m sub-plots, which were randomly assigned with four ET treatments and three blocks. Plants of A. theophrasti were grown on June 7, June 27, July 17, and August 7, to make them emerge in different periods of the season, as four ET treatments of spring (ET1), late spring (ET2), summer (ET3) and late summer (ET4). The treatments of emergence timing accorded with the time range of emergence of A. theophrasti in its natural habitats in northeast China. Most of the seeds emerged four days after sowing. Seeds were sown at an inter-planting distance of 10 cm, and seedlings were thinned at the four-leaf stage. Plots were hand-weeded when necessary and watered regularly to prevent drought.

Data collection

For each ET treatment, we arranged two times sampling (at days 50 and 70 of growth; Appendix S1; see Supplemental Data with this article), according to the lengths of their life cycles, generally at the stages of vegetative growth, late vegetative or early reproductive growth, and middle to late reproductive growth respectively. For each sampling, five to six individual plants were randomly chosen from each plot, making a maximum total of 6 replicates × 3 blocks × 4 treatments × 2 samplings = 144 samplings. For each plant, the following traits were measured (if applicable): main root length, diameter at the basal of the main root, length and number of lateral roots (above or equal to 1 mm in diameter along the main root), the length of stem, diameter at the base of stem, petiole length and angle, leaf number, leaf size (lamina width), branch length and angle, and branch number (Appendix S1; see Supplemental Data with this article). Each plant individual was then separated into roots, stems, petioles, laminas, reproductive modules, and branches (if there were any), oven-dried at 75°C for two days, and weighed. Reproductive modules consisted of flowers and fruits produced along the main stem and branches, and branches included the stems and leaves on branches. Total mass and mass allocation traits were calculated.

Statistical analysis

Statistical analyses were conducted using IBM SPSS statistics 19. All measured and calculated traits were used for analysis (Appendix S2; see Supplemental Data with this article). To minimize variance heterogeneity, all data were log-transformed, except for petiole angles and branch angles (square root-transformed), before statistical analysis. For plant total mass, we applied two-way ANOVA to analyze the effects of emergence time, growth stage, and their interactions, and one-way ANOVA to analyze the effects of emergence time or growth stage within each or across all of the other treatments. Plant size (e. g. total mass) can have very significant effects on other traits, which may bias the effects of emergence time. Therefore, for all the other traits, we applied two-way ANCOVA to evaluate the overall effects of emergence time, growth stage, and their interactions, and one-way ANCOVAs for effects of emergence time or growth stage within each or across all of the other treatments, with total mass as a covariate. Multiple comparisons used the Least Significant Difference (LSD) method in the General Linear Model (GLM) program.

For each trait, the percent number of significant correlations of it with other traits (NC; p < 0.05) was used as the index of phenotypic integration, and NC values were arcsine- and square-root-transformed before analyses; coefficient of variation (CV) was used to evaluate the level of canalization, which was calculated as the standard deviation divided by the mean value of the trait. Both the level and degree of plasticity (relative plasticity and absolute plasticity, PI_rel and PI_abs) for each trait were calculated with the revised simplified Relative Distance Plasticity Index (RDPI_s, abbreviated as PI), for its strong statistical power in tests of differences in plasticity (Valladares et al., 2006), with the formula as:

PI_rel = (X – Y) / (X + Y)

PI_abs = |X – Y | / (X + Y)

where X was the adjusted mean trait value in the treatment of earlier emergence (ET1, ET2, and ET3), and Y was the adjusted mean value in the treatment of delayed emergence (ET2, ET3, and ET4). The adjusted mean values and standard errors were produced in one-way ANCOVA, with emergence time as effect within each stage, and total mass as a covariate. Since there were four treatments of emergence timing, we calculated the PI in response to each treatment versus another one. Consequently, there were six kinds of plasticity in total, including the responses to ET4 (vs. ET1, ET2, ET3), ET3 (vs. ET1, ET2) and ET2 (vs. ET1).

Correlations between PI and NC, and between PI and CV, were evaluated by Pearson Correlation Coefficients (PCC) produced by PROC CORR (Gianoli and Palacio-López 2009). We then applied regression analyses to quantify the relationships between PI and CV and between PI and NC for plants in different emergence treatments at both stages. Results of correlations and regressions were analyzed with two-way ANOVA for the effects of emergence time and growth stage and their interactions; and one-way ANOVA for the effects of emergence time on these relationships at each stage.