Dataset Information

Intraspecific variations in leaf functional traits of Cunninghamia lanceolata provenances.

ABSTRACT:

Background

Studies on intra-specific variability in leaf functional traits is important to evaluate adaptation of the species to predicted climate change, and to develop long-term conservation strategy. The main objectives were to investigate the relationship between the functional traits leaves and C, N, P stoichiometry of Chinese fir from different geographical provenances and their relationship with the main environmental factors of provenance.

Results

In this study, we measured 12 leaf functional traits on 36-year-old Cunninghamia lanceolata trees from 13 provenances. Analysis of variance (ANOVA) was performed to examine the variability. Redundancy analysis (RA) was computed to examine the relationship between geo-climatic factors of provenance origin and leaf functional traits while Pearson's correlation coefficient was computed to assess inter-trait correlations. The results showed statistically significant differences (P < 0.01) in intraspecific leaf traits among provenances, except leaf P content. The relationships among leaf traits are consistent with the general trend observed in the leaf economic spectrum. Mean annual temperature appeared to be a key factor that influences intraspecific leaf traits variability compared to mean annual precipitation.

Conclusion

These results provide useful insights about adaptation of leaf trait of Chinese fir in a changing climatic condition. Thus, our findings shed light on the importance of interspecific trait variability in Chinese fir and the potential effect of climate change.

SUBMITTER: Xu R

PROVIDER: S-EPMC9926855 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Intraspecific variations in leaf functional traits of Cunninghamia lanceolata provenances.

Xu Rui R Cheng Shundan S Zhou Jing J Tigabu Mulualem M Ma Xiangqing X Li Ming M

BMC plant biology 20230213 1

<h4>Background</h4>Studies on intra-specific variability in leaf functional traits is important to evaluate adaptation of the species to predicted climate change, and to develop long-term conservation strategy. The main objectives were to investigate the relationship between the functional traits leaves and C, N, P stoichiometry of Chinese fir from different geographical provenances and their relationship with the main environmental factors of provenance.<h4>Results</h4>In this study, we measure ...[more]

PMID: 36782117

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Project description:BackgroundLeaf length and width could be a functioning relationship naturally as plant designs. Single-vein leaves have the simplest symmetrical distribution and structural design, which means that fast-growing single-vein species could interpret the scheme more efficiently. The distribution of leaf length and width can be modulated for better adaptation, providing an informative perspective on the various operational strategies in an emergency, while this mechanism is less clear. Here we selected six age groups of Cunninghamia lanceolata pure forests, including saplings, juveniles, mature, and old-growth trees. We pioneered a tapering model to describe half-leaf symmetric distribution with mathematical approximation based on every measured leaf along developmental sequence, and evaluated the ratio of leaf basal part length to total length (called tipping leaf length ratio).ResultsThe tipping leaf length ratio varied among different tree ages. That means the changes of tipping leaf length ratio and leaf shape are a significant but less-noticed reflection of trees tradeoff strategies at different growth stages. For instance, there exhibited relatively low ratio during sapling and juvenile, then increased with increasing age, showing the highest value in their maturity, and finally decreased on mature to old-growth transition. The tipping leaf length ratio serves as a cost-benefit ratio, thus the subtle changes in the leaf symmetrical distribution within individuals reveal buffering strategy, indicating the selection for efficient design of growth and hydraulic in their developmental sequences.ConclusionsOur model provides a physical explanation of varied signatures for tree operations in hydraulic buffering through growth stages, and the buffering strategy revealed from leaf distribution morphologically provides evidence on the regulation mechanism of leaf biomechanics, hydraulics and physiologies. Our insight contributes greatly to plant trait modeling, policy and management, and will be of interest to some scientists and policy makers who are involved in climate change, ecology and environment protection, as well as forest ecology and management.

Project description:Chinese fir (Cunninghamia lanceolata) is one of southern China's most important native tree species, which has experienced noticeable climate-induced changes. Published papers (1978-2020) on tree growth of Chinese fir forests in China were collected and critically reviewed. After that, a comprehensive growth data set was developed from 482 sites, which are distributed between 102.19° and 130.07°E in longitude, between 21.87° and 37.24°N in latitude and between 5 and 2260 m in altitude. The dataset consists of 2265 entries, including mean DBH (cm), mean H (m), volume (m3), biomass (dry weight) (kg) (stem (over bark) biomass, branches biomass, leaves biomass, bark biomass, aboveground biomass, roots biomass, total trees biomass) and related information, i.e. geographical location (Country, province, study site, longitude, latitude, altitude, slope, and aspect), climate (mean annual precipitation-MAP and mean annual temperature-MAT), stand description (origin, age, canopy density and stand density), and sample regime (plot size, number and investigation year). Our results showed that (1) the best prediction of height was obtained using nonlinear composite model Height = [Formula: see text], (R2 = 0.8715, p < 0.05), (2) the equation Volume = DBH2/(387.8 + 19,190/Height) (R2 = 0.9833, p < 0.05) was observed to be the most suitable model for volume estimation. Meanwhile, when the measurements of the variables are difficult to carry out, the volume model Volume = 0.03957 - 0.01215*DBH + 0.00118*DBH2 (R2 = 0.9573, p < 0.05) is determined from DBH only has a practical advantage, (3) the regression equations of component biomass against DBH explained more significant than 86% variability in almost all biomass data of woody tissues, which were ranked as total trees (97.25%) > aboveground (96.55%) > stems (with bark) (96.17%) > barks (88.95%) > roots (86.71%), and explained greater than 64% variability in branch biomass. The foliage biomass equation was the poorest among biomass components (R2 = 0.6122). The estimation equations derived in this study are particularly suitable for the Chinese fir forests in China. This dataset can provide a theoretical basis for predicting and assessing the potential of carbon sequestration and afforestation activities of Chinese fir forests on a national scale.

Dataset Information

Intraspecific variations in leaf functional traits of Cunninghamia lanceolata provenances.

Background

Results

Conclusion

Publications

Intraspecific variations in leaf functional traits of Cunninghamia lanceolata provenances.

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