Leaf heteroblasty in eucalypts: biogeographic evidence of ecological function

2018 ◽  
Vol 66 (3) ◽  
pp. 191 ◽  
Author(s):  
Carolyn Vlasveld ◽  
Benjamin O'Leary ◽  
Frank Udovicic ◽  
Martin Burd
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Unit Area ◽  
Leaf Shape ◽  
Eucalyptus Species ◽  
Canopy Closure ◽  
Area Index ◽  
Leaf Mass ◽  
Adult Leaf ◽  
Shape And Size

Leaves that develop on seedlings, young saplings or regenerative shoots of many eucalypt species are strikingly different in morphology from the typical leaves of more mature plants; a developmental pattern known as heteroblasty. We measured dimorphism between juvenile and adult leaves in shape and size, leaf mass per unit area, and vein frequency in a continent-wide sample of Angophora, Corymbia and Eucalyptus species. We tested whether heteroblasty in this group is an adaptation to shading by comparing the degree of juvenile–adult leaf dimorphism with the canopy closure (measured by the leaf area index) of the habitat in which species occurred. No pattern emerged for heteroblasty in leaf shape and size or leaf mass per unit area, but there was a significant relationship (accounting for phylogenetic relationships) between the degree of juvenile–adult dimorphism in vein frequency and habitat leaf area index. Juvenile leaves tended to have more widely spaced veins than adult leaves of the same species, in regions with more closed vegetative canopies. This evidence suggests that eucalypt heteroblasty is, at least in part, a hydraulic adaptation to the different conditions faced by younger and older plants in higher productivity regions with denser vegetation.

Principal Canopy Factors of Sweet Corn and Relationships to Competitive Ability with Wild-Proso Millet (Panicum miliaceum)

Weed Science ◽  
2009 ◽  
Vol 57 (3) ◽  
pp. 296-303 ◽  
Author(s):  
Yim F. So ◽  
Martin M. Williams ◽  
Jerald K. Pataky ◽  
Adam S. Davis
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Competitive Ability ◽  
Sweet Corn ◽  
Canopy Closure ◽  
Crop Canopy ◽  
Area Index ◽  
Canopy Development ◽  
Proso Millet ◽  
Principal Factors

Univariate analyses fail to account for covariance among phenomorphological traits implicated in crop competitive ability. A more complete analysis of cultivar–weed interactions would reduce a number of important traits to a few underlying principal factors responsible for sweet corn competitiveness. Twenty-three commercial sweet corn hybrids from nine seed companies were grown in the presence and absence of wild-proso millet to (1) quantify the extent to which phenomorphological traits vary in sweet corn, (2) identify underlying principal factors that describe variation in crop canopy development, and (3) determine functional relationships between crop canopy factors and competitive ability. A principal component factor analysis revealed that 7 of the 18 weed-free crop traits measured at silking loaded highly (0.65 to 0.90) into the first factor, including plant height, shoot biomass, per plant leaf area, leaf area index, and intercepted light, as well as thermal time from emergence to silking and emergence to maturity. All seven traits were highly correlated (0.38 to 0.93) and were interpreted as a “late canopy and maturity” factor. Another five traits formed two additional principal factors that were interpreted as an early “seedling quality” factor (e.g., kernel mass, seedling vigor, and height at two-leaf stage) and a mid-season “canopy closure” factor (e.g., leaf area index and intercepted photosynthetically active radiation at six-leaf stage). Relationships between principal factors and competitive abilities were quantified using least-squares linear regression. Cultivars with greater loadings in the late canopy and maturity and canopy closure factors were more competitive with wild-proso millet. In contrast, crop competitive ability declined with cultivars that loaded highly into the seedling quality factor. The analyses showed that sweet corn's ability to endure weed interference and suppress weed fitness relates uniquely to three underlying principal factors that capture crop canopy development around emergence and near canopy closure and during the reproductive phase.

scholarly journals Leaf shape and its relationship with Leaf Area Index in a sugar beet (Beta vulgaris L.) cultivar

2008 ◽  
Vol 46 (1) ◽  
pp. 48-48
Author(s):  
J. T. Tsialtas ◽  
N. Maslaris
Keyword(s):  
Sugar Beet ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Beta Vulgaris ◽  
Leaf Shape ◽  
Area Index

scholarly journals Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model

2022 ◽  
Vol 3 ◽  
Author(s):  
Azbina Rahman ◽  
Xinxuan Zhang ◽  
Paul Houser ◽  
Timothy Sauer ◽  
Viviana Maggioni
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Surface Model ◽  
Random Errors ◽  
Area Index ◽  
Leaf Mass ◽  
The Impact

As vegetation regulates water, carbon, and energy cycles from the local to the global scale, its accurate representation in land surface models is crucial. The assimilation of satellite-based vegetation observations in a land surface model has the potential to improve the estimation of global carbon and energy cycles, which in turn can enhance our ability to monitor and forecast extreme hydroclimatic events, ecosystem dynamics, and crop production. This work proposes the assimilation of a remotely sensed vegetation product (Leaf Area Index, LAI) within the Noah Multi-Parameterization land surface model using an Ensemble Kalman Filter technique. The impact of updating leaf mass along with LAI is also investigated. Results show that assimilating LAI data improves the estimation of transpiration and net ecosystem exchange, which is further enhanced by also updating the leaf mass. Specifically, transpiration anomaly correlation coefficients improve in about 77 and 66% of the global land area thanks to the assimilation of leaf area index with and without updating leaf mass, respectively. Random errors in transpiration are also reduced, with an improvement of the unbiased root mean square error in 70% (74%) of the total area without the update of leaf mass (with the update of leaf mass). Similarly, net ecosystem exchange anomaly correlation coefficients improve from 52 to 75% and random errors improve from 49 to 62% of the total pixels after the update of leaf mass. Better performances for both transpiration and net ecosystem exchange are observed across croplands, but the largest improvement is shown over forests and woodland. The global scope of this work makes it particularly important in data poor regions (e.g., Africa, South Asia), where ground observations are sparse or not available altogether but where an accurate estimation of carbon and energy variables can be critical to improve ecosystem and crop management.

Remote sensing of temperate coniferous forest leaf area index The influence of canopy closure, understory vegetation and background reflectance

1990 ◽  
Vol 11 (1) ◽  
pp. 95-111 ◽  
Author(s):  
MICHAEL A. SPANNER ◽  
LARS L. PIERCE ◽  
DAVID L. PETERSON ◽  
STEVEN W. RUNNING
Keyword(s):  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Coniferous Forest ◽  
Understory Vegetation ◽  
Canopy Closure ◽  
Area Index

scholarly journals Plant Age Has a Minor Effect on Non-Destructive Leaf Area Calculations in Moso Bamboo (Phyllostachys edulis)

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 369
Author(s):  
Lichao Huang ◽  
Ülo Niinemets ◽  
Jianzhong Ma ◽  
Julian Schrader ◽  
Rong Wang ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Leaf Shape ◽  
Age Groups ◽  
Leaf Length ◽  
Moso Bamboo ◽  
Plant Age ◽  
Individual Plant ◽  
Minor Effect ◽  
Area Index

Leaf area is among the most important leaf functional traits, and it determines leaf temperature and alters light harvesting. The calculation of individual leaf area is the basis of calculating the leaf area index (i.e., the total leaf area per unit ground area) that is directly associated with the ability of plants to intercept light for photosynthesis. It is valuable to provide a fast and reliable approach to measuring leaf area. Here, we examined the validity and calculation accuracy of the Montgomery equation (ME), which describes the area of a leaf as a product of leaf length, width and a specific coefficient referred to as the Montgomery parameter, MP. Using ME, we calculated leaf areas of different age groups of bamboo culms. For most broad-leaved plants, leaf area is proportional to the product of leaf length and width, and MP falls within a range of 1/2 to π/4, depending on leaf shape. However, it is unknown whether there is an intra-specific variation in MP resulting from age structure and whether such a variation can significantly reduce the predictability of ME in calculating leaf area. This is relevant as a population of perennial plants usually composes of different age groups. We used Moso bamboos as model as this species is of ecological and economic importance in southern China, and pure stands can cover six to seven plant age groups. We used five age groups of moso bamboo and sampled 260–380 leaves for each group to test whether ME holds true for each group and all groups combined, whether there are significant differences in MP among different age groups, and whether the differences in MP can lead to large prediction errors for leaf area. We observed that for each age group and all groups combined, there were significant proportional relationships between leaf area and the product of leaf length and width. There were small but significant differences in MP among the five age groups (MP values ranged from 0.6738 to 0.7116 for individual plant ages; MP = 0.6936 for all age groups combined), which can be accounted for by the minor intergroup variation of leaf shape (reflected by the leaf width/length ratio). For all age classes, MP estimated for the pooled data resulted in <4% mean absolute percentage error, indicating that the effect of variation in MP among different age groups was small. We conclude that ME can serve as a useful tool for accurate calculations of leaf area in moso bamboo independent of culm age, which is valuable for estimation of leaf area index as well as evaluating the productivity and carbon sequestration capacity of bamboo forests.

Airborne discrete-return LIDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index

2011 ◽  
Vol 115 (4) ◽  
pp. 1065-1080 ◽  
Author(s):  
Lauri Korhonen ◽  
Ilkka Korpela ◽  
Janne Heiskanen ◽  
Matti Maltamo
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Canopy Cover ◽  
Lidar Data ◽  
Canopy Closure ◽  
Area Index

A comparison of four methods for determining leaf area index in successional hardwood forests

1985 ◽  
Vol 15 (6) ◽  
pp. 1154-1158 ◽  
Author(s):  
Thomas W. Jurik ◽  
George M. Briggs ◽  
David M. Gates
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Hardwood Forests ◽  
Litter Fall ◽  
Area Index ◽  
Tree Diameter ◽  
Leaf Mass ◽  
The Vertical Distribution ◽  
Harvest Method ◽  
Do So

Four methods of determining leaf area index of three successional hardwood forests in northern lower Michigan were compared. Direct harvests gave values for leaf area index ranging from 1.4 to 3.6. Estimates of leaf area index derived from litter fall data were consistently higher than the harvest values and were highly dependent on the ratio of leaf area to leaf mass, which had to be estimated. A visual method using sightings through a tube gave values consistently lower (by 27–42%) than the harvest values. Calculations of leaf area index based on regressions of leaf mass versus tree diameter gave results very close to the harvest values for each site as a whole; calculations for smaller plots were more variable. The harvest method allowed measurement of the vertical distribution of leaf area; the other methods could not do so.

Retrieval of Leaf Area Index and Canopy Closure from CASI Data over the BOREAS Flux Tower Sites

2000 ◽  
Vol 74 (2) ◽  
pp. 255-274 ◽  
Author(s):  
Baoxin Hu ◽  
Kris Inannen ◽  
John R Miller
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Canopy Closure ◽  
Area Index ◽  
Flux Tower
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