Coordination of leaf hydraulic and economic traits in Cinnamomum camphora under impervious pavement

Zhang, Cheng; Liu, Huihui; Huang, Nuo; Zhang, Fengyu; Yu, Mengxi; Wang, Jianan; Li, Yiyong

doi:10.1186/s12870-022-03740-4

Cited by 5 publications

(4 citation statements)

References 59 publications

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“…Plants with lower SLA tend to devote most of their energy and nutrients to building defensive structures or increasing leaf tissue density to prevent excessive dehydration ( Garnier et al., 2001 ). In contrast, Zhang et al. (2022) reported a lower SLA but not leaf size in Cinnamomum camphora under an impervious pavement.…”

Section: Discussionmentioning

confidence: 72%

Responses of tree growth, leaf area and physiology to pavement in Ginkgo biloba and Platanus orientalis

Cui

Wang

Su³

et al. 2022

Front. Plant Sci.

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Trees growing on paved lands endure many environmental stresses in the urban environment. However, the morphological and physiological mechanisms underlying tree adaptation to pavement in the field are less known. In this study, we investigated 40 sites where Ginkgo biloba and Platanus orientalis grow on adjacent pairs of paved and vegetated plots in parks and roadsides in Beijing, China. Relative to the vegetated land, the mean increments in the diameter at breast height and height in the paved land were significantly decreased by 44.5% and 31.9% for G. biloba and 31.7% and 60.1% for P. orientalis, respectively. These decreases are related to both the decrease in assimilation products due to the reductions in leaf area, leaf total nitrogen content, and chlorophyll content and the increase in energy cost due to the synthesis of more soluble sugar and proline for mitigating stress. The increase in leaf soluble sugar content, proline content, and δ13C indicated that trees could adapt to the paved land through the regulation of osmotic balance and the enhancement of water-use efficiency. Piecewise structural equation models showed that trees growing on the paved land are stressed by compounding impacts of the leaf morphological and physiological changes. Therefore, it is critical to explore the complex response of plant morphological and physiological traits to the pavement-induced stress for improving tree health in urban greening.

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Section: Discussionmentioning

confidence: 72%

Responses of tree growth, leaf area and physiology to pavement in Ginkgo biloba and Platanus orientalis

Cui

Wang

Su³

et al. 2022

Front. Plant Sci.

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“…LT measures the distance that water diffuses from the leaf interior to the surface. Plants with a low SLA usually have a high LT, but a low LA ( Abid et al., 2016 ; Wellstein et al., 2017 ; Wright et al., 2017 ; Zhang C. et al., 2022 ). This is inconsistent with our result of SLA being much lower in the dry than the wet season and LT being similar between seasons ( Table S1 ; Figure 2 ).…”

Section: Discussionmentioning

confidence: 99%

Response of leaf functional traits to soil nutrients in the wet and dry seasons in a subtropical forest on an island

Zhang,

Liang,

Tong

et al. 2023

Front. Plant Sci.

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IntroductionIsland ecosystems often have a disproportionate number of endemic species and unique and fragile functional characteristics. However, few examples of this type of ecosystem have been reported.MethodsWe conducted a comprehensive field study on Neilingding Island, southern China. The leaf samples of 79 subtropical forest tree species were obtained and their functional traits were studied in the dry and wet seasons to explain the relationships between plant functional traits and soil nutrients.ResultsWe found a greater availability of soil moisture content (SMC) and nutrients in the wet season than in the dry season. The values of wet season soil available phosphorus (5.97 mg·kg−1), SMC (17.67%), and soil available potassium (SAK, 266.96 mg·kg−1) were significantly higher than those of the dry season. The leaf dry matter content, specific leaf weight, leaf density, leaf total carbon, leaf total nitrogen, leaf total calcium, and the N/P and C/P ratios of leaves were all significantly higher in the dry season than in the wet season, being 18.06%, 12.90%, 12.00%, 0.17%, 3.41%, 9.02%, 26.80%, and 24.14% higher, respectively. In contrast, the leaf area (51.01 cm2), specific leaf area (152.76 cm2·g−1), leaf water content (0.59%), leaf total nitrogen (1.31%), leaf total phosphorus (0.14%), and leaf total magnesium (0.33%) were much lower in the dry season than in the wet one. There were significant pairwise correlations between leaf functional traits, but the number and strength of correlations were significantly different in the dry and wet seasons. The SAK, soil total phosphorus (STP), and pH impacted plant leaf functional traits in the dry season, whereas in the wet season, they were affected by SAK, STP, pH, and NO3− (nitrate).DiscussionBoth soil nutrients and water availability varied seasonally and could cause variation in a number of leaf traits.

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“…Subtropical evergreen broad-leaved species adapted to altitudes below 1800 m, and is light-loving, slightly shade-tolerant, and prefers a warm and humid climate. It is suitable for deep fertile acidic or neutral sandy loam soils [53,54].…”

Section: Cinnamomum Camphoramentioning

confidence: 99%

Individual Tree AGB Estimation of Malania oleifera Based on UAV-RGB Imagery and Mask R-CNN

Gong

Kou

et al. 2023

Forests

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Forest aboveground biomass (AGB) is an important research topic in the field of forestry, with implications for carbon cycles and carbon sinks. Malania oleifera Chun et S. K. Lee (M. oleifera) is a valuable plant species that is listed on the National Second-Class Protected Plant checklist and has received global attention for its conservation and resource utilization. To obtain accurate AGB of individual M. oleifera trees in a fast, low-finance-cost and low-labor-cost way, this study first attempted to estimate individual M. oleifera tree AGB by combining the centimeter-level resolution RGB imagery derived from unmanned aerial vehicles (UAVs) and the deep learning model of Mask R-CNN. Firstly, canopy area (CA) was obtained from the 3.5 cm high-resolution UAV-RGB imagery using the Mask R-CNN; secondly, to establish an allometric growth model between the diameter at breast height (DBH) and CA, the correlation analysis of both was conducted; thirdly, the AGB estimation method of individual M. oleifera trees was presented based on an empirical equation. The study showed that: (1) The deep learning model of Mask R-CNN achieved an average segmentation accuracy of 90% in the mixed forests to the extraction of the canopy of M. oleifera trees from UAV-RGB imagery. (2) The correlation between the extracted CA and field-measured DBH reached an R2 of 0.755 (n = 96). (3) The t-test method was used to verify the predicted and observed values of the CA-DBH model presented in this study, and the difference in deviation was not significant (p > 0.05). (4) AGB of individual M. oleifera was estimated for the first time. This study provides a reference method for the estimation of individual tree AGB of M. oleifera based on centimeter-level resolution UAV-RGB images and the Mask R-CNN deep learning.

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Coordination of leaf hydraulic and economic traits in Cinnamomum camphora under impervious pavement

Cited by 5 publications

References 59 publications

Responses of tree growth, leaf area and physiology to pavement in Ginkgo biloba and Platanus orientalis

Responses of tree growth, leaf area and physiology to pavement in Ginkgo biloba and Platanus orientalis

Response of leaf functional traits to soil nutrients in the wet and dry seasons in a subtropical forest on an island

Individual Tree AGB Estimation of Malania oleifera Based on UAV-RGB Imagery and Mask R-CNN

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