Patterns and influencing factors of traits in forest ecosystems: Synthesis and perspectives on the synthetic investigation from the north-east transect of eastern China (NETEC)

Nianpeng, 何念鹏 He; Jiahui, 张佳慧 Zhang; Congcong, 刘聪聪 Liu; Li, 徐丽 Xu; Zhi, 陈智 Chen; Liu, Yuan; Ruili, 王瑞丽 Wang; Ning, 赵宁 Zhao; Zhiwei, 徐志伟 Xu; Jing, 田静 Tian; Qing, 王情 Wang; Jianxing, 朱剑兴 Zhu; Ying, 李颖 Li; Jihua, 侯继华 Hou; Guirui, 于贵瑞 Yu

doi:10.5846/stxb201803140507

Cited by 2 publications

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“…For each shrub species, 1–3 healthy plants were selected in each sample plot, and the top branches of the canopy were intercepted using high‐branch scissors to obtain mixed samples of leaves and branches, respectively; meanwhile, the shrub roots were obtained through excavation. Three mixed samples of leaves, branches, trunks, and roots of different species were obtained for each sample plot (N. P. He, Zhang, Liu, et al., 2018). Within each sample plot, 5–30 plants of each herbaceous species were selected, and above‐ground (leaves and stems) and below‐ground (roots) were collected.…”

Section: Methodsmentioning

confidence: 99%

Biogeographic Patterns of Sulfur in the Vegetation of the Tibetan Plateau

Zhao

Xiao

et al. 2023

JGR Biogeosciences

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Sulfur (S) plays an important role in plant growth and development. However, due to climatic conditions and limited data availability, the variation and allocation of S are largely unknown at regional or global scales. In this study, we systematically evaluated the S distribution patterns and storage in vegetation on the Tibetan Plateau for the first time, based on consistent field‐measured data of 2,040 plant communities. The mean S contents of leaves, branches, trunks, and roots were 1.68, 0.40, 0.19, and 1.45 g kg−1, respectively; corresponding to S densities of 0.40 × 10−2 (9.57%), 1.18 × 10−2 (28.38%), 1.37 × 10−2 (32.90%) and 1.21 × 10−2 t hm−2 (29.15%), respectively. The mean S densities for forests (5.59 ± 0.26 × 10−2 t hm−2) were higher than that of shrublands (4.54 ± 0.51 × 10−2 t hm−2), grasslands (1.03 ± 0.07 × 10−2 t hm−2), and deserts (1.32 ± 0.28 × 10−2 t hm−2). The S density was generally lower in the northwest and higher in the southeast of the Tibetan Plateau and had divergent allocation patterns between different plant organs and vegetation types. Furthermore, we found that S in leaves and roots was more strongly influenced by environmental factors and was particularly sensitive to radiation and atmospheric pressure. Moreover, the total S storage in the vegetation of the Tibetan Plateau was estimated to be 337.32 × 104 t, with 114.32 × 104 (33.89%), 92.36 × 104 (27.38%), 128.77 × 104 (38.17%), and 1.86 × 104 t (0.55%) in the forests, shrublands, grasslands, and deserts, respectively. Our study clarified the S densities of different plant organs and ecosystems on the Tibetan Plateau and compiled 1 × 1 km vegetation S density data sets, which could help determine the key parameters for regional S cycle models in the future.

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Section: Methodsmentioning

confidence: 99%

Biogeographic Patterns of Sulfur in the Vegetation of the Tibetan Plateau

Zhao

Xiao

et al. 2023

JGR Biogeosciences

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Patterns in leaf traits of woody species and their environmental determinants in a humid karstic forest in southwest China

Long

Liang

et al. 2023

Front. Ecol. Evol.

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IntroductionLeaf functional traits constitute a crucial component of plant functionality, providing insights into plants’ adaptability to the environment and their regulatory capacity in complex habitats. The response of leaf traits to environmental factors at the community level has garnered significant attention. Nevertheless, an examination of the environmental factors determining the spatial distribution of leaf traits in the karst region of southwest China remains absent.MethodsIn this study, we established a 25 ha plot within a karst forest and collected leaf samples from 144 woody species. We measured 14 leaf traits, including leaf area (LA), leaf thicknes (LT), specific leaf area (SLA), leaf length to width ratio (LW), leaf tissue density (LTD), leaf carbon concentration (LC), leaf nitrogen concentration (LN), and leaf phosphorus concentration (LP), leaf potassium concentration (LK), leaf calcium concentration (LCa), leaf magnesium Concentration (LMg), leaf carbon to nitrogen ratio (C/N), leaf carbon to phosphorus ratio (C/P), and leaf nitrogen to phosphorus ratio (N/P), to investigate the spatial distribution of community-level leaf traits and the response of the leaf trait community-weighted mean (CWM) to topographic, soil, and spatial factors.ResultsResults showed that the CWM of leaf traits display different spatial patterns, first, the highest CWM values for LT, LTD, C/N, and C/P at hilltops, second, the highest CWM values for LA, SLA, LW, LC, LN, LP, and LK at depressions, and third, the highest CWM values for LCa, LMg, and N/P at slopes. The correlation analysis showed that topographic factors were more correlated with leaf trait CWM than soil factors, with elevation and slope being the strongest correlations. RDA analysis showed that topographic factors explained higher percentage of leaf trait CWM than soil factors, with the highest percentage of 19.96% being explained by elevation among topographic factors. Variance Partitioning Analysis showed that the spatial distribution of leaf traits is predominantly influenced by the combined effects of topography and spatial factors (37%-47% explained), followed by purely spatial factors (24%-36% explained).DiscussionThe results could improve our understanding of community functional traits and their influencing factors in the karst region, which will contribute to a deeper understanding of the mechanisms that shape plant communities.

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Patterns and influencing factors of traits in forest ecosystems: Synthesis and perspectives on the synthetic investigation from the north-east transect of eastern China (NETEC)

Cited by 2 publications

References 0 publications

Biogeographic Patterns of Sulfur in the Vegetation of the Tibetan Plateau

Biogeographic Patterns of Sulfur in the Vegetation of the Tibetan Plateau

Patterns in leaf traits of woody species and their environmental determinants in a humid karstic forest in southwest China

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