Increased density and delayed emergence are two major biotic factors in nature that have profound and complex effects on plants. No studies have attempt to compare the responses of plants to the two factors via morphological plasticity, particularly in dynamic patterns. We subjected plants of Abutilon theophrasti to four emergence times and three planting densities and measured and analyzed a number of mass and morphological traits at different growth stages. Across both stages, plants emerged in late spring had the highest total mass, and spring and late-spring plants had higher stem mass allocation than later germinants, but plants with delayed emergence had higher leaf and reproductive mass allocation, more leaves and less lateral roots, but lower stem length, stem and root diameter than early-emerged plants. Plants at high density performed lower in total mass and most other traits, but performed better in stem allocation and length, with shorter petioles and lateral roots, than at lower densities. In competition for resources, plants will prefer stem elongation to leaf/root growth, and even at the cost of reproduction to ensure the survival of the present generations when competition is intense or lethal. By contrast, plants will prefer the investment into leaf and reproductive growth to stem/root growth, for offspring persistence, when shortened lifetime does not threaten the contemporary survival. The contrasting strategies revealed the intelligence of plants in balancing between survival, growth and reproduction, depending on environmental contexts.

Experimental design - Two field experiments were conducted in 2007, at the Pasture Ecological Research Station of Northeast Normal University, Changling, Jilin province, China (44°45’ N, 123°45’ E). We collected seeds of A. theophrasti from the small local wild populations near the research station in late August 2006. Seeds were dry stored at -4^oC till using for experiments. We tested effects of emergence timing (ET) and population density (PD) on plants in two experiments respectively. The soil conditions of experimental field in the growth season of 2007 were the same as that in former studies: aeolian sandy soil (pH = 8.3) 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.

For effects of emergence timing, we divided the whole plot into twelve 2 × 3 m sub-plots, which were randomly assigned with four ET treatments and three replicates per treatment. Seeds were grown at an inter-planting distance of 10 cm on June 7, June 27, July 17 and August 7, as four ET treatments of spring (ET1), late spring (ET2), summer (ET3) and late summer (ET4). The treatments accorded with the range of emergence timing of A. theophrasti in its nature habitats in northeast of China (Zhou, Wang et al. 2005). Annually, spring occurs between April and June in northeast of China. Changchun, a city in northeast of China, locates in the middle of Northeast China, where spring starts in late April, summer starts in early July, autumn in mid-August and winter in mid-October. In spite of this, the weather between April and May is often chilling, and precipitation is unpredictable. We did not make plants emerge during this period, to avoid severe stress and mortality early in the season, and instead set up early June as the date of spring emergence, and late June as that of late-spring emergence.

For effects of population density, the whole plot was divided into nine 2 × 3 m sub-plots, which were assigned with three PD treatments and three replicates per treatment randomly. We labeled the treatments as low, medium and high densities, which were created by growing plants with inter-planting distances of 30, 20 and 10 cm, to reach the target densities of 12.8, 27.5, and 108.5 plants·m^-2 respectively. Seeds were grown at initial densities that were a little higher than the target ones on June 7, 2007, the same date of spring-emergence treatment. Most seeds emerged four to five days after planting. When almost all seedlings reached four-leaf stage, they were thinned to the target densities. Plots were hand weeded when necessary and regularly irrigated to prevent drought. 

Data collection - For each ET treatment, we arranged three to four times of sampling at the stages of early vegetative (EV), vegetative (VE), late vegetative (LV) or early reproductive growth (ER), reproductive (RE) and late reproductive (LR) growth of plants respectively, which were defined according to the patterns of plant biomass allocation. Since plants from different ET treatments had different lengths of life cycles and nonsynchronous developments, the intervals between samplings differed for different treatments as well (Table 1). For individuals that emerged in spring (ET1), we sampled four times since they had a prolonged life cycle; and for those emerged in late spring (ET2), the sampling at day 30 were not available due to small plant sizes. At each stage, five to six individual plants were randomly chosen from each plot, making a maximum total of 6 replicates × 3 blocks × 4 treatments × 4 stages = 288 samplings. For each PD treatment, plants were sampled at 30, 50 and 70 days of growth, which represented vegetative stage, early reproductive stage and middle reproductive stage respectively. For each stage, we also randomly sampled five to six individual plants per replicate per density, making a maximum total of 6 replicates × 3 blocks × 3 treatments × 3 stages = 162 samplings. 

For each individual 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, and leaf number (Table 2). Each plant individual was then separated into roots, stems, petioles, laminas, reproductive modules and branches (if there were any), oven-dried at 75^oC 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. The mass and morphological traits of branches were not included in statistical analyses, since plants of many samplings did not grow branches. Total mass and mass allocation traits were calculated.

Statistical analysis - Statistical analyses were conducted using SAS statistical software (SAS Institute 9.0 Incorporation, 2002). Traits used for analysis included allocation traits of root, stem, petiole, lamina, reproductive organs and all morphological traits (Table 2). To minimize variance heterogeneity, all data was 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 effects of emergence time or density, growth stage and their interactions, and one-way ANOVA to analyze the effects of emergence time or density or growth stage within each or across all of the other treatments. Plant size (e. g. total mass) can have substantial effects on other traits, which may bias the environmental effects. Consequently, for all the other traits, we applied two-way ANCOVA for overall effects of emergence time or density, growth stage and their interactions, and one-way ANCOVAs for effects of emergence time or density within each or across all of stages, with total mass as a covariate. For a given trait, the proportion explained by effects of total biomass (plant size) in variation in response to environments indicates apparent plasticity (McConnaughay and Coleman 1999), and the variation due to environmental (ET or PD) effects after removal of size effects in the trait indicates true plasticity (Weiner 2004). Multiple comparisons used the Least Significance Difference (LSD) method in the General Linear Model (GLM) program, which also produced adjusted mean values and standard errors in one-way ANCOVA. To evaluate the plastic responses of plants in a comprehensive perspective, we also performed standard principal component analyses (PCA) on all traits for each treatment and across all treatments at two stages of day 50 and 70 for both ET and PD experiments, to find out the most contributive traits.