Plant leaves exhibit diverse shapes that enable them to utilize a light resource maximally. If there were a general parametric model that could be used to calculate leaf area for different leaf shapes, it would help to elucidate the adaptive evolutional link among plants with the same or similar leaf shapes. We propose a simplified version of the original Gielis equation (SGE), which was developed to describe a variety of object shapes ranging from a droplet to an arbitrary polygon. We used this equation to fit the leaf profiles of 53 species (among which, 48 bamboo plants, 5 woody plants, and 10 geographical populations of a woody plant), totaling 3310 leaves. A third parameter (namely, the floating ratio c in leaf length) was introduced to account for the case when the theoretical leaf length deviates from the observed leaf length. For most datasets, the estimates of c were greater than zero but less than 10%, indicating that the leaf length predicted by the SGE was usually smaller than the actual length. However, the predicted leaf areas approximated their actual values after considering the floating ratios in leaf length. For most datasets, the mean percent errors of leaf areas were lower than 6%, except for a pooled dataset with 42 bamboo species. For the elliptical, lanceolate, linear, obovate, and ovate shapes, although the SGE did not fit the leaf edge perfectly, after adjusting the parameter c, there were small deviations of the predicted leaf areas from the actual values. This illustrates that leaves with different shapes might have similar functional features for photosynthesis, since the leaf areas can be described by the same equation. The anisotropy expressed as a difference in leaf shape for some plants might be an adaptive response to enable them to adapt to different habitats.

Many plant leaves exhibit bilateral symmetry, but such symmetry has rarely been measured because of the lack of practical methods. We propose a simple method for achieving the above objective. A leaf is divided into left and right sides, and several equally-sized strips are generated to intersect each side of that leaf to generate pairwise left and right sub-regions. A standardized index (SI) for measuring bilateral symmetry is built based on the left–right areal differences of those sub-regions. The leaves of 10 species of plants were sampled for testing the method’s validity. Based on the experimental data, we compared the root-mean-squared error (RMSE), SI, and areal ratio (AR) of the left side to the right side of the leaf. The SI measures the bilateral symmetry of plant leaves well, and it is better than the RMSE and AR for eliminating the effect of leaf size on the goodness of fit. The SI proposed here is the best indicator for evaluating the degree of bilateral symmetry and can be potentially used for comparing the difference in the bilateral symmetry of leaves of different plants.

Taylor's power law (TPL) describes the scaling relationship between the temporal or spatial variance and mean of population densities by a simple power law. TPL has been widely testified across space and time in biomedical sciences, botany, ecology, economics, epidemiology, and other fields. In this paper, TPL is analytically reconfirmed by testifying the variance as a function of the mean of the released energy of earthquakes with different magnitudes on varying timescales during the Wenchuan earthquake sequence. Estimates of the exponent of TPL are approximately 2, showing that there is mutual attraction among the events in the sequence. On the other hand, the spatio-temporal distribution of the Wenchuan aftershocks tends to be nonrandom but approximately definite and deterministic, which highly indicates a stable spatio-temporally dependent energy release caused by regional stress adjustment and redistribution during the fault revolution after the mainshock. The effect of different divisions on estimation of the intercept of TPL straight line has been checked, while the exponent is kept to be 2. The result shows that the intercept acts as a logarithm function of the time division. It implies that the mean–variance relationship of the energy release from the earthquakes can be predicted, although we cannot accurately know the occurrence time and locations of imminent events.