Plant economic strategies in two contrasting forests

Abstract

Background: Predicting relationships between plant functional traits and environmental effects in their habitats is a central issue in terms of classic ecological theories. Yet, only weak correlation with functional trait composition of local plant communities may occur, implying that some essential information might be ignored. In this study, to address this uncertainty, the objective of the study is to test whether and how the consistency of trait relationships occurs by analyzing broad variation in eight traits related to leaf morphological structure, nutrition status and physiological activity, within a large number of plant species in two distinctive but comparable harsh habitats (high-cold alpine fir forest vs. north-cold boreal coniferous forest).

Results: The contrasting and/or consistent relationships between leaf functional traits in the two distinctive climate regions were observed. Higher specific leaf area, photosynthetic rate, and photosynthetic nitrogen use efficiency (PNUE) with lower N concentration occurred in north-cold boreal forest rather than in high-cold alpine forest, indicating the acquisitive vs. conservative resource utilizing strategies in both habitats. The principal component analysis illuminated the divergent distributions of herb and xylophyta groups at both sites. Herbs tend to have a resource acquisition strategy, particularly in boreal forest. The structural equation modeling revealed that leaf density had an indirect effect on PNUE, primarily mediated by leaf structure and photosynthesis. Most of the traits were strongly correlated with each other, highlighting the coordination and/or trade-offs.

Conclusions: We can conclude that the variations in leaf functional traits in north-cold boreal forest were largely distributed in the resource-acquisitive strategy spectrum, a quick investment-return behavior; while those in the high-cold alpine forest tended to be mainly placed at the resource-conservative strategy end. The habitat specificity for the relationships between key functional traits could be a critical determinant of local plant communities. Therefore, elucidating plant economic spectrum derived from variation in major functional traits can provide a fundamental insight into how plants cope with ecological adaptation and evolutionary strategies under environmental changes, particularly in these specific habitats.

Keywords: Alpine fir forest; Boreal coniferous forest; Leaf density; Leaf economics spectrum; Leaf functional traits; Plant functional type.

Fig. 1

Changes in leaf functional traits at the two sites. Points and density curves represent data distribution of leaf functional traits in herbs at Huzhong (HH) and Linzhi (LH), in xylophyta at Huzhong (HX) and Linzhi (LX), and across the two plant functional types at both Huzhong (HZ) and Linzhi (LZ) sites. Leaf functional traits included leaf tissue density (LD, a), leaf thickness (LT, b), specific leaf area (SLA, c), leaf nitrogen concentration per unit mass (N_mass, d), leaf nitrogen concentration per unit area (N_area, e), light-saturated photosynthetic rate per unit mass (A_mass, f), light-saturated photosynthetic rate per unit area (A_area, g), photosynthetic nitrogen use efficiency (PNUE, h). Black points denote means with SD bars. Different capital and lowercase letters indicate significant differences among plant functional types and sites, respectively (p < 0.05)

Fig. 2

Correlations between leaf functional traits at Huzhong (a) and Linzhi (b) sites. *, p < 0.05; **, p < 0.01; ***, p < 0.001. For abbreviations, see Fig. 1

Fig. 3

Regressive relationships of SLA with other leaf functional traits. For abbreviations, see Fig. 1

Fig. 4

Regressive relationships of LD with other leaf functional traits. For abbreviations, see Fig. 1

Fig. 5

Regressive relationships between leaf N content (N_mass and N_area) and light-saturated net photosynthetic rates (A_mass and A_area)

Fig. 6

Principal component analysis (PCA) on plant functional traits for the two plant functional types (PFTs, i.e., herbs and xylophyta) at Huzhong (a) and Linzhi (b) sites, and across the two sits (c). Dim 1 and 2 represent PC factor 1 and PC factor 2, respectively. For abbreviations, see Fig. 1

Fig. 7

Structural equation modeling (SEM) on key leaf functional traits at Huzhong (a, b) and Linzhi (c, d) sites. Direct (DE) and indirect effects (IE) are given at both Huzhong (b) and Linzhi (d) sites, respectively. Solid blue and red arrows represent significant positive or negative relationships at p < 0.05 levels, whereas dashed blue and red arrows represent no significance (p > 0.05). Values above arrows indicate the standard path coefficients, and their significances at 0.05, 0.01, and 0.001 levels are marked by *, **, and ***, respectively. Percentages on rectangles indicate the variance explained by the models. For abbreviations, see Fig. 1; and for SEM statistical information, see Table S7

Fig. 8

A conceptual model related to classical ecological theories based on coordination/balance among leaf functional traits in the two extremely harsh habitats. LES, leaf economics spectrum; PFG, plant functional group; CSR, Grime’s competitive–stress tolerant–ruderal triangle [105]; r vs. K, r - versus K - selection [107]. For other abbreviations (e.g., SLA), see Fig. 1

Fig. 9

The study locations. (a) Map of China; (b) Huzhong site, Greater Khingan, Heilongjiang; (c) Boreal coniferous forest. (d) Linzhi site, Sygera Mountain, Tibet; (e) Alpine fir forest