scholarly journals Contrasting Development of Canopy Structure and Primary Production in Planted and Naturally Regenerated Red Pine Forests

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 566 ◽  
Author(s):  
Laura J. Hickey ◽  
Jeff Atkins ◽  
Robert T. Fahey ◽  
Mark T. Kreider ◽  
Shea B. Wales ◽  
...  
Keyword(s):  
Primary Production ◽  
Canopy Structure ◽  
Structural Complexity ◽  
Red Pine ◽  
Stem Density ◽  
Light Use Efficiency ◽  
Planted Forests ◽  
Area Index ◽  
Use Efficiency ◽  
Naturally Regenerated Stands

Globally, planted forests are rapidly replacing naturally regenerated stands but the implications for canopy structure, carbon (C) storage, and the linkages between the two are unclear. We investigated the successional dynamics, interlinkages and mechanistic relationships between wood net primary production (NPPw) and canopy structure in planted and naturally regenerated red pine (Pinus resinosa Sol. ex Aiton) stands spanning ≥ 45 years of development. We focused our canopy structural analysis on leaf area index (LAI) and a spatially integrative, terrestrial LiDAR-based complexity measure, canopy rugosity, which is positively correlated with NPPw in several naturally regenerated forests, but which has not been investigated in planted stands. We estimated stand NPPw using a dendrochronological approach and examined whether canopy rugosity relates to light absorption and light–use efficiency. We found that canopy rugosity increased similarly with age in planted and naturally regenerated stands, despite differences in other structural features including LAI and stem density. However, the relationship between canopy rugosity and NPPw was negative in planted and not significant in naturally regenerated stands, indicating structural complexity is not a globally positive driver of NPPw. Underlying the negative NPPw-canopy rugosity relationship in planted stands was a corresponding decline in light-use efficiency, which peaked in the youngest, densely stocked stand with high LAI and low structural complexity. Even with significant differences in the developmental trajectories of canopy structure, NPPw, and light use, planted and naturally regenerated stands stored similar amounts of C in wood over a 45-year period. We conclude that widespread increases in planted forests are likely to affect age-related patterns in canopy structure and NPPw, but planted and naturally regenerated forests may function as comparable long-term C sinks via different structural and mechanistic pathways.

scholarly journals Relationship between Light Use Efficiency and Photochemical Reflectance Index Corrected Using a BRDF Model at a Subtropical Mixed Forest

2020 ◽  
Vol 12 (3) ◽  
pp. 550
Author(s):  
Li Ma ◽  
Shaoqiang Wang ◽  
Jinghua Chen ◽  
Bin Chen ◽  
Leiming Zhang ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Mixed Forest ◽  
Canopy Structure ◽  
Terrestrial Laser Scanning ◽  
Light Use Efficiency ◽  
Vegetation Canopy ◽  
Area Index ◽  
Photochemical Reflectance Index ◽  
Use Efficiency ◽  
Point Data

Light use efficiency (LUE) is a key indicator of vegetation photosynthesis, which provides important insights into how vegetation productivity responds to environmental conditions. The photochemical reflectance index (PRI) is based on reflectance at 531 and 570 nm, which reflects the xanthophyll cycle process of plants under different radiation conditions, and makes LUE related to plant optical characteristics. In this study, tower-based PRI and eddy covariance (EC) based LUEs were used to explore the ability of PRI to track LUE variations in a subtropical, evergreen mixed forest in South China. The results indicate that there is a stronger relationship between PRI and LUE, corrected by the bidirectional reflectance distribution function (BRDF), where R2 = 0.46 before correction and R2 = 0.60 after correction. Generally, PRI is able to capture diurnal and seasonal changes in LUE. Simultaneously, this study highlights a significant correlation between LUE and PRI, but there is also a large seasonal difference in its correlation. The correlation in winter was significantly stronger than summer. The strongest correlation is found in November (R2 = 0.91) and the weakest is in July (R2 = 0.34). Photosynthetically active radiation (PAR) had a strong influence on the LUE-PRI relationship, while vapor pressure deficit (VPD) and air temperature (Ta) had negative influences on the relationship between LUE and PRI. Terrestrial laser scanning is used to retrieve the vertical structure of forest crown. Our results show that the vegetation canopy structure (i.e., effective leaf area index, LAIe), extracted from terrestrial laser scanning (TLS) point data in subtropical mixed forests, had a weak influence on LUE. Our research suggests that environmental factors and vegetation canopy structures should be considered when using PRI to accurately estimate LUE.

scholarly journals Efisiensi Penggunaan Cahaya Matahari oleh Tebu pada Berbagai Tingkat Pemupukan Nitrogen dan Fosfor

1970 ◽  
Vol 40 (3) ◽  
Author(s):  
Wawan Pembengo ◽  
, Handoko ◽  
, Suwarto
Keyword(s):  
Dry Matter ◽  
Phosphorus Deficiency ◽  
Block Design ◽  
Canopy Structure ◽  
Leaf Nitrogen ◽  
Light Use Efficiency ◽  
Nitrogen And Phosphorus ◽  
Area Index ◽  
P Fertilizer ◽  
Use Efficiency

Light use efficiency is a crucial parameter in plant growth associated with accumulation of energy interception. Nitrogen and phosphorus deficiency reduce leaf area index (LAI) and specific leaf nitrogen and phosphorus (SLN and SLP) content and reduce efficiency of light intercepted by plant canopy structure. This research was conducted in Kebun Bunga Mayang PTPN VII, North Lampung Regency, Lampung Province (04050’S, 104052’E, 38 m above sea level) from July 2008 to September 2009. Treatments were distributed in the field under a randomized complete block design factorial with three replications. The increase in nitrogen fertilizer (N) improved sugarcane light use efficiency. The light use efficiency of the sugarcane plants fertilized with 225 kg N ha-1 was 2.29 g MJ-1 at maximum stem phase. On the contrary, the increasing of phosphor (P) fertilizer did not affect light use efficiency but increased stem dry matter at maximum seedling phase or about 3 month after planting (3 MAP), at maximum stem phase (9 MAP), and at harvest (11 MAP); total dry matter at seedling phase (5 MAP) and at maximum stem phase (9 MAP). Nitrogen did not interact with P in affecting light use efficiency. Keywords: fertilization N and P, interception radiation, light use efficiency, sugarcane

scholarly journals Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data

2018 ◽  
Vol 10 (9) ◽  
pp. 1346 ◽  
Author(s):  
Joanna Joiner ◽  
Yasuko Yoshida ◽  
Yao Zhang ◽  
Gregory Duveiller ◽  
Martin Jung ◽  
...  
Keyword(s):  
Primary Production ◽  
Eddy Covariance ◽  
Satellite Data ◽  
Gross Primary Production ◽  
Satellite Observation ◽  
Data Driven ◽  
Spatial And Temporal Variability ◽  
Light Use Efficiency ◽  
High Productivity ◽  
Use Efficiency

We estimate global terrestrial gross primary production (GPP) based on models that use satellite data within a simplified light-use efficiency framework that does not rely upon other meteorological inputs. Satellite-based geometry-adjusted reflectances are from the MODerate-resolution Imaging Spectroradiometer (MODIS) and provide information about vegetation structure and chlorophyll content at both high temporal (daily to monthly) and spatial (∼1 km) resolution. We use satellite-derived solar-induced fluorescence (SIF) to identify regions of high productivity crops and also evaluate the use of downscaled SIF to estimate GPP. We calibrate a set of our satellite-based models with GPP estimates from a subset of distributed eddy covariance flux towers (FLUXNET 2015). The results of the trained models are evaluated using an independent subset of FLUXNET 2015 GPP data. We show that variations in light-use efficiency (LUE) with incident PAR are important and can be easily incorporated into the models. Unlike many LUE-based models, our satellite-based GPP estimates do not use an explicit parameterization of LUE that reduces its value from the potential maximum under limiting conditions such as temperature and water stress. Even without the parameterized downward regulation, our simplified models are shown to perform as well as or better than state-of-the-art satellite data-driven products that incorporate such parameterizations. A significant fraction of both spatial and temporal variability in GPP across plant functional types can be accounted for using our satellite-based models. Our results provide an annual GPP value of ∼140 Pg C year - 1 for 2007 that is within the range of a compilation of observation-based, model, and hybrid results, but is higher than some previous satellite observation-based estimates.

Variation in canopy structure, leaf area, light interception and light use efficiency among Eucalyptus clones

2020 ◽  
Vol 463 ◽  
pp. 118038 ◽  
Author(s):  
Eduardo M. de Mattos ◽  
Dan Binkley ◽  
Otavio C. Campoe ◽  
Clayton A. Alvares ◽  
Jose L. Stape
Keyword(s):  
Leaf Area ◽  
Canopy Structure ◽  
Light Interception ◽  
Light Use Efficiency ◽  
Use Efficiency

scholarly journals LINKING PHOTOSYNTHETIC LIGHT USE EFFICIENCY AND OPTICAL VEGETATION ACTIVE INDICATORS: IMPLICATIONS FOR GROSS PRIMARY PRODUCTION ESTIMATION BY REMOTE SENSING

2020 ◽  
Vol V-3-2020 ◽  
pp. 571-578
Author(s):  
S. Wang ◽  
Z. Li ◽  
Y. Zhang ◽  
D. Yang ◽  
C. Ni
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Seasonal Changes ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Canopy Structure ◽  
Remote Sensing Data ◽  
Growing Season ◽  
Light Use Efficiency ◽  
Use Efficiency

Abstract. Over the last 40 years, the light use efficiency (LUE) model has become a popular approach for gross primary productivity (GPP) estimation in the carbon and remote sensing communities. Despite the fact that the LUE model provides a simple but effective way to approximate GPP at ecosystem to global scales from remote sensing data, when implemented in real GPP modelling, however, the practical form of the model can vary. By reviewing different forms of LUE model and their performances at ecosystem to global scales, we conclude that the relationships between LUE and optical vegetation active indicators (OVAIs, including vegetation indices and sun-induced chlorophyll fluorescence-based products) across time and space are key for understanding and applying the LUE model. In this work, the relationships between LUE and OVAIs are investigated at flux-tower scale, using both remotely sensed and simulated datasets. We find that i) LUE-OVAI relationships during the season are highly site-dependent, which is complexed by seasonal changes of leaf pigment concentration, canopy structure, radiation and Vcmax; ii) LUE tends to converge during peak growing season, which enables applying pure OVAI-based LUE models without specifically parameterizing LUE and iii) Chlorophyll-sensitive OVAIs, especially machine-learning-based SIF-like signal, exhibits a potential to represent spatial variability of LUE during the peak growing season.We also show the power of time-series model simulations to improve the understanding of LUE-OVAI relationships at seasonal scale.

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