Heteroblastic development and the optimal partitioning of traits among contrasting environments in Acacia implexa

Abstract

Background and aims: Optimal partitioning theory (OPT) predicts plants will allocate biomass to organs where resources are limiting. Studies of OPT focus on root, stem and leaf mass ratios where roots and stems are often further sub-divided into organs such as fine roots/tap roots or branches/main stem. Leaves, however, are rarely sub-divided into different organs. Heteroblastic species develop juvenile and adult foliage and provide an opportunity of sub-dividing leaf mass ratio into distinct organs. Acacia implexa (Mimosaceae) is a heteroblastic species that develops compound (juvenile), transitional and phyllode (adult) leaves that differ dramatically in form and function. The aims of the present study were to grow A. implexa to examine patterns of plastic development of whole-plant and leaf traits under the OPT framework.

Methods: Plants were grown in a glasshouse under contrasting nutrient, light and water environments in a full factorial design. Allocation to whole-plant and leaf-level traits was measured and analysed with multivariate statistics.

Key results: Whole-plant traits strongly followed patterns predicted by OPT. Leaf-level traits showed a more complex pattern in response to experimental treatments. Compound leaves on low nutrient plants had significantly lower specific leaf area (SLA) and were retained for longer as quantified by a significantly greater compound leaf mass ratio after 120 d. There was no significant difference in SLA of compound leaves in the light treatment, yet transitional SLA was significantly higher under the low light treatment. The timing of heteroblastic shift from compound to transitional leaves was significantly delayed only in the low light treatment. Therefore, plants in the light treatment responded at the whole-plant level by adjusting allocation to productive compound leaves and at the leaf-level by adjusting SLA. There were no significant SLA differences in the water treatment despite strong trends at the whole-plant level.

Conclusion: Explicitly sub-dividing leaves into different types provided greater insights into OPT.

Fig. 1.

The three types of ‘leaf’ analysed in this experiment: (A) a double compound leaf; (B) a transitional leaf with two pinnae attached to a flattened rachis/petiole; (C) a modified leaf, the phyllode; a flattened rachis/petiole. Leaves were harvested 4 months after sowing from the fourth, eighth and 13th node, respectively, from a non-experimental plant grown in full sunlight. Scale bar = 10 mm.

Fig. 2.

Estimated marginal means and standard errors of whole-plant traits. Traits and their units of measurement are outlined in Table 1. * P < 0·05; ** P < 0·01; *** P < 0·001; **** P < 0·0001.

Fig. 3.

Estimated marginal means and standard errors of heteroblastic traits. Traits and their units of measurement are outlined in Table 1. * P < 0·05; ** P < 0·01; *** P < 0·001; **** P < 0·0001.

Fig. 4.

Grouping of treatments and traits following discriminant function analysis. Variance explained by the first and second discriminant functions are displayed in parentheses. (A, B) Treatments are mean populations, with circles indicating 95 % confidence intervals for (A) whole-plant and (B) heteroblastic traits. Numbers correspond to treatment group (1, high nutrient, high light, high water; 2, high nutrient, high light, low water; 3, high nutrient, low light, high water; 4, high nutrient, low light, low water; 5 low nutrient, high light, high water; 6, low nutrient, high light, low water; 7, low nutrient, low light, high water; 8, low nutrient, low light, low water). The nutrient and light treatments are highlighted due to significant outcomes following MANOVA. (C, D) Factor loadings of (C) whole-plant and (D) heteroblastic traits across the first and second discriminant functions.

Fig. 5.

Number of nodes displaying a compound leaf (CompNodes) with standard error bars. Analysis was performed on log data, but untransformed data are presented. Only the light treatment showed a significant difference (**** P < 0·0001). The full ANCOVA table is presented in the Supplementary Information (available online).

Fig. 6.

Estimated marginal mean and standard errors of total biomass (g) at point of harvest. Analysis was performed on log data, but untransformed data are presented. The nutrient and water treatments showed a significant difference (**** P < 0·0001). The full ANOVA table is presented in the Supplementary Information (available online).