A Novel Diffuse Fraction‐Based Two‐Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality across 20 AmeriFlux Flux Tower Sites

Yan, Huimin; Wang, Shao Qiang; Yu, Kai; Wang, Bin; Qin, Yu; Bohrer, Gil; Billesbach, D. P.; Bracho, Rosvel; Rahman, Faiz; Shugart, Herman H.

doi:10.1002/2016ms000886

Cited by 39 publications

(44 citation statements)

References 75 publications

(193 reference statements)

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“…Journal of Geophysical Research: Biogeosciences (Yan, Wang, Yu, et al, 2017). In short, diffuse radiation-based enhanced GPP in southern China in dimming years during 2000-2017 was due to higher LAI and D f .…”

Section: 1029/2020jg005735mentioning

confidence: 89%

“…We focused on interannual variations of PAR and its components and related impacts on GPP in China from 2000 to 2017 by using a Dual-leaf Terrestrial Ecosystem Carbon flux (DTEC) model (Yan, Wang, Yu, et al, 2017) driven by climate data and Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) data. These are described in the sections below: (1) estimation of global radiation and diffuse radiation and their evaluation at 13 radiation sites across China;…”

Section: Introductionmentioning

confidence: 99%

“…Motivated by these findings, two leaf‐based LUE models have been developed to treat sunlit and shaded leaves separately. These models incorporate the contrasting impacts of direct and diffuse radiation and simulate GPP better (Chen et al, 1999; He et al, 2013; Mercado et al, 2009a; Yan et al, 2017). Using a diffuse fraction‐based two‐leaf GPP model, Yan, Wang, Yu, et al (2017) found that diffuse radiation is the dominant climatic cause of the unexpected photosynthetic seasonality in Amazon rainforests, that is, the dry season features higher solar radiation but lower GPP compared with the wet season (Saleska et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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Changes of Light Components and Impacts on Interannual Variations of Photosynthesis in China Over 2000–2017 by Using a Two‐Leaf Light Use Efficiency Model

Yan

Wang

et al. 2020

JGR Biogeosciences

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Diffuse radiation produces a higher light use efficiency (LUE) than does direct radiation. However, light components and their impacts on interannual variations of photosynthesis in China have not been intensively studied. We estimated gross primary production (GPP) from a two-leaf LUE model that incorporates a diffuse radiation effect and compared it with a big-leaf LUE model that ignores the diffuse radiation impact. The results show that a dimming occurred in China-the estimated annual photosynthetically active radiation (PAR) declined by −1.79 MJ m −2 yr −1. However, the diffuse fraction and diffuse PAR increased over this interval. Both GPP models simulated an increasing trend of GPP in China from 2000 to 2017. The big-leaf GPP model underestimated the increasing trend of GPP from the two-leaf GPP model by 6.4%. The diffuse fraction change during the dimming exerted an embedded positive impact relative to the big-leaf GPP trend in China. To evaluate the impact of total PAR versus its components on GPP, annual anomaly percentage (A p) of GPP shows that the big-leaf GPP model had a positive correlation between A p of GPP and PAR across China. Considering the diffuse radiation impact, A p of two-leaf GPP was negatively correlated with PAR in southern China, which had a higher leaf area index (2.02) and a greater diffuse fraction (0.63). Strong diffuse radiation effects in southern China produced GPP anomalies in opposition to the direction of the PAR changes. These findings highlight the distinctive impact of light components on interannual variations of plant photosynthesis.

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Section: 1029/2020jg005735mentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Changes of Light Components and Impacts on Interannual Variations of Photosynthesis in China Over 2000–2017 by Using a Two‐Leaf Light Use Efficiency Model

Yan

Wang

et al. 2020

JGR Biogeosciences

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“…The direct and diffuse solar irradiance are essential for estimating solar irradiance under arbitrary surface orientations [3] [4], obstructed environments [5], within interior spaces [6], for building energy simulations, impact on photovoltaic systems and the photosynthesis potentials in agricultural/forestry analysis and planning [7] [8]. Recent studies have shown and measured the positive effect that Diffuse irradiation has on increasing canopy light use efficiency (LUE) in the Amazon Rain Forrest and related vegetative carbon uptake [9][10] [11].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

Claywell¹,

Nádai²,

Felde³

et al. 2020

Preprint

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The accurate prediction of the solar Diffuse Fraction (DF), sometimes called the Diffuse Ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse Irradiance research is discussed and then three robust, Machine Learning (ML) models, are examined using a large dataset (almost 8 years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid Adaptive Network-based Fuzzy Inference System (ANFIS), a single Multi-Layer Perceptron (MLP) and a hybrid Multi-Layer Perceptron-Grey Wolf Optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various Solar and Diffuse Fraction (DF) irradiance data, from Spain. The results were then evaluated using two frequently used evaluation criteria, the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance, in both the training and the testing procedures.

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“…Aerosols can also indirectly affect the vegetation photosynthesis by altering the solar radiation reaching the surface in terms of both of total amount and proportion of diffuse light (Kanniah et al 2012). Regionally, the tropical forest seasonal GPP variations are mostly determined by diffuse radiation (Yan et al 2017); the severe haze in China enhanced the the diffuse radiation and largely stimulate photosynthesis (Yue et al 2017). Globally, the changes in diffuse light are estimated to have increased terrestrial ecosystem uptake of carbon between 1960 and 1980 by 0.44 PgC per year globally (Mercado et al 2009).…”

Section: Feedbacks Between Vegetation and Atmospheric Chemical Processesmentioning

confidence: 99%

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using an Individual-Based Model (IBM)

Wang

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Biosphere-atmosphere interactions (BAIs) are integral to the functioning of the whole Earth System. The complexity of ecological systems profoundly determines these complex, nonlinear, and dynamic interactions. This complexity fundamentally originates from the high degree of biodiversity, resulting in complex interactions among individuals constituting a system and thus emergent system level behaviors. However, biodiversity has long been overlooked either intentionally or unintentionally largely because of methodological limitations. In particular, the currently widely used ecosystem model frameworks of aggregate representation of vegetation using plant functional types (PFTs) have severe deficiencies in integration of biodiversity and ecosystem functions. To address this grand issue, this dissertation primarily focuses on the development of an individual-based forest volatile organic compounds emission model, UVAFME-VOC (v1.0), and applications of this IBM (individual-based model) to addressing questions revolving around the roles of forest system diversity in influencing forest dynamics, biomass production, and isoprene (the most abundant VOC species) emissions responding to climate warming and ozone pollution. Specifically, this dissertation found that ozone may not suppress forest productivity and that climate warming does not necessarily always stimulate isoprene emissions all because of an explicit integration of species diversity and ecological interactions. These findings challenge long-held paradigms that are established on a linear scaleup of plant leaf physiology to the ecosystem level circumventing the community scale. This dissertation is concluded with discussing the deficiencies of IBMs and pointing out the challenges/directions, and advocates the development of IBM in truly integrating biodiversity into biosphere-atmosphere interactions in the Anthropocene Epoch. Volk M et al 2011 Subalpine grassland carbon dioxide fluxes indicate substantial carbon losses under increased nitrogen deposition, but not at elevated ozone concentration Glob. Change

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A Novel Diffuse Fraction‐Based Two‐Leaf Light Use Efficiency Model: An Application Quantifying Photosynthetic Seasonality across 20 AmeriFlux Flux Tower Sites

Cited by 39 publications

References 75 publications

Changes of Light Components and Impacts on Interannual Variations of Photosynthesis in China Over 2000–2017 by Using a Two‐Leaf Light Use Efficiency Model

Changes of Light Components and Impacts on Interannual Variations of Photosynthesis in China Over 2000–2017 by Using a Two‐Leaf Light Use Efficiency Model

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using an Individual-Based Model (IBM)

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