Anatomical changes with needle length are correlated with leaf structural and physiological traits across five<scp><i>Pinus</i></scp>species

Wang, Na; Palmroth, Sari; Maier, Christopher; Domec, Jean‐Christophe; Oren, Ram

doi:10.1111/pce.13516

Cited by 25 publications

(24 citation statements)

References 78 publications

(103 reference statements)

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“…Therefore, it is remarkable that needles form an exception. While the number and diameter of the water‐transporting tracheids in the xylem increase with needle length (Wang et al ., 2006; Zwieniecki et al ., 2006), this is not the case for the phloem SEs, as shown by Rademaker et al . (2017) and here.…”

Section: Discussionmentioning

confidence: 99%

The mechanism of sugar export from long conifer needles

Liesche

Vincent

Han³

et al. 2021

New Phytologist

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 The green leaves of plants are optimized for carbon fixation and the production of sugars, which are used as central units of carbon and energy throughout the plant. However, there are physical limits to this optimization that remain insufficiently understood.  Here, quantitative anatomical analysis combined with mathematical modeling and sugar transport rate measurements were employed to determine how effectively sugars are exported from the needleshaped leaves of conifers in relation to leaf length.  Mathematical modeling indicated that phloem anatomy constrains sugar export in long needles.However, we identified two mechanisms by which this constraint is overcome, even in needles longer than 20 cm: i) the grouping of transport conduits, and ii) a shift in the diurnal rhythm of sugar metabolism and export in needle tips.  The efficiency of sugar transport in the phloem can have a significant influence on leaf function. The constraints on sugar export described here for conifer needles are likely to also be relevant in other groups of plants, such as grasses and angiosperm trees.

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Section: Discussionmentioning

confidence: 99%

The mechanism of sugar export from long conifer needles

Liesche

Vincent

Han³

et al. 2021

New Phytologist

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“…These data suggest a site effect on foliar anatomy, i.e., the ratio of mechanical-tophotosynthetic foliage tissue is altered, where needles with a high DFT (located far from the top of the tree) at the BR site had lower needle density. Wang et al (2019) found that Table 4 Site (S), genotype (G), and density (D) least square means for the non-linear model parameters estimated for the beta model (a sigmoid function) used to describe foliage distribution at absolute and relative scales within the crown. β0, β1, and β2 are the asymptote of foliage in the crown, the point in the crown where the asymptote is achieved and the inflection point at which the increase in leaf area in the crown is maximized, respectively Trees used in this analysis were measured in 2013 and 2017 for crown characteristics at three sites (Virginia, North Carolina, and Brazil) where two genotypes (a clone and an open-pollinated family) of Pinus taeda were planted at 618, 1236, and 1854 tree ha −1 .…”

Section: Leaf Area Distributionmentioning

confidence: 99%

Crown architecture, crown leaf area distribution, and individual tree growth efficiency vary across site, genetic entry, and planting density

Albaugh

Maier

Campoe

et al. 2019

Trees

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We examined crown architecture and within crown leaf area distribution effects on Pinus taeda L. growth in North Carolina (NC), Virginia (VA), and Brazil (BR) to better understand why P. taeda can grow much better in Brazil than in the southeastern United States. The NC, VA, and BR sites were planted in 2009, 2009, and 2011, respectively. At all sites, we planted the same two genetic entries at 618, 1236, and 1854 trees ha −1 . In 2013, when trees were still open grown, the VA and NC sites had greater branch diameter (24%), branch number (14%), live crown length (44%), foliage mass (82%), and branch mass (91%), than the BR site. However, in 2017, after crown closure and when there was no significant difference in tree size, site did not significantly affect these crown variables. In 2013, site significantly affected absolute leaf area distribution, likely due to differences in live crown length and leaf area, such that there was more foliage at a given level in the crown at the VA and NC sites than at the BR site. In 2017, site was still a significant factor explaining leaf area distribution, although at this point, with crown closure and similar sized trees, there was more foliage at the BR site at a given level in the crown compared to the VA and NC sites. In 2013 and 2017, when including site, genetic entry, stand density, and leaf area distribution parameters as independent variables, site significantly affected individual tree growth efficiency, indicating that something other than leaf area distribution was influencing the site effect. Better BR P. taeda growth is likely due to a combination of factors, including leaf area distribution, crown architecture, and other factors that have been identified as influencing the site effect (heat sum), indicating that future work should include a modeling analysis to examine all known contributing factors.

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“…Visual shape description in plants is a very specialized and time-consuming task [1, 2]. The botanist and ecologist require straightforward approaches to communicate relevant information about the plant morphology.…”

Section: Introductionmentioning

confidence: 99%

Contour analysis for interpretable leaf shape category discovery

Victorino

Gómez

2019

Plant Methods

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Background The categorical description of leaf shapes is of paramount importance in ecology, taxonomy and paleobotanical studies. Classification systems proposed by domain experts support these descriptions. Despite the importance of these visual descriptive systems, classifications based on this expert’s knowledge may be ambiguous or limited when representing shapes in unknown scenarios, as expected for biological exploratory domains. This work proposes a novel strategy to automatically discover the shape categories in a set of unlabeled leaves by only using the leaf-shape information. In particular, we overcome the task of discovering shape categories from different plant species for three different biological settings. Results The proposed method may successfully infer the unknown underlying shape categories with an F-score greater than 92%. Conclusions The approach also provided high levels of visual interpretability, an essential requirement in the description of biological objects. This method may support morphological analysis of biological objects in exploratory domains.

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Anatomical changes with needle length are correlated with leaf structural and physiological traits across fivePinusspecies

Cited by 25 publications

References 78 publications

The mechanism of sugar export from long conifer needles

The mechanism of sugar export from long conifer needles

Crown architecture, crown leaf area distribution, and individual tree growth efficiency vary across site, genetic entry, and planting density

Contour analysis for interpretable leaf shape category discovery

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