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Journal articles on the topic 'Light use efficiency (LUE) model'

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Published: 9 March 2023

Last updated: 10 March 2023

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1

Zhang, Jun, Xufeng Wang, and Jun Ren. "Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models." Land 10, no. 3 (2021): 329. http://dx.doi.org/10.3390/land10030329.

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Gross primary productivity (GPP) is the most basic variable in a carbon cycle study that determines the carbon that enters the ecosystem. The remote sensing-based light use efficiency (LUE) model is one of the primary tools that is currently used to estimate the GPP at the regional scale. Many remote sensing-based GPP models have been developed in the last several decades, and these models have been well evaluated at some sites. However, an accurate estimation of the GPP remains challenging work using LUE models because of uncertainties in the model caused by model parameters, model forcing, a

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McCallum, I., O. Franklin, E. Moltchanova, et al. "Improved light and temperature responses for light-use-efficiency-based GPP models." Biogeosciences 10, no. 10 (2013): 6577–90. http://dx.doi.org/10.5194/bg-10-6577-2013.

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Abstract. Gross primary production (GPP) is the process by which carbon enters ecosystems. Models based on the theory of light use efficiency (LUE) have emerged as an efficient method to estimate ecosystem GPP. However, problems have been noted when applying global parameterizations to biome-level applications. In particular, model–data comparisons of GPP have shown that models (including LUE models) have difficulty matching estimated GPP. This is significant as errors in simulated GPP may propagate through models (e.g. Earth system models). Clearly, unique biome-level characteristics must be

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McCallum, I., O. Franklin, E. Moltchanova, et al. "Improved light and temperature responses for light use efficiency based GPP models." Biogeosciences Discussions 10, no. 5 (2013): 8919–47. http://dx.doi.org/10.5194/bgd-10-8919-2013.

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Abstract. Gross primary production (GPP) is the process by which carbon enters ecosystems. Diagnostic models, based on the theory of light use efficiency (LUE) have emerged as one method to estimate ecosystem GPP. However, problems have been noted particularly when applying global results at regional levels. We hypothesize that accounting for non-linear light response and temperature acclimation of daily GPP in boreal regions will improve model performance. To test this hypothesis, we have chosen four diagnostic models for comparison, namely: an LUE model (linear in its light response) both wi

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Goerner, A., M. Reichstein, E. Tomelleri, et al. "Remote sensing of ecosystem light use efficiency with MODIS-based PRI." Biogeosciences 8, no. 1 (2011): 189–202. http://dx.doi.org/10.5194/bg-8-189-2011.

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Abstract. Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the effectiveness with which MODIS-based PRI can be used to es

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Xie, Zhiying, Cenliang Zhao, Wenquan Zhu, Hui Zhang, and Yongshuo H. Fu. "A Radiation-Regulated Dynamic Maximum Light Use Efficiency for Improving Gross Primary Productivity Estimation." Remote Sensing 15, no. 5 (2023): 1176. http://dx.doi.org/10.3390/rs15051176.

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The light use efficiency (LUE) model has been widely used in regional and global terrestrial gross primary productivity (GPP) estimation due to its simple structure, few input parameters, and particular theoretical basis. As a key input parameter of the LUE model, the maximum LUE (Ɛmax) is crucial for the accurate estimation of GPP and to the interpretability of the LUE model. Currently, most studies have assumed Ɛmax as a universal constant or constants depending on vegetation type, which means that the spatiotemporal dynamics of Ɛmax were ignored, leading to obvious uncertainties in LUE-base

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Wellington, Michael J., Petra Kuhnert, Luigi J. Renzullo, and Roger Lawes. "Modelling Within-Season Variation in Light Use Efficiency Enhances Productivity Estimates for Cropland." Remote Sensing 14, no. 6 (2022): 1495. http://dx.doi.org/10.3390/rs14061495.

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Gross Primary Productivity (GPP) for cropland is often estimated using a fixed value for maximum light use efficiency (LUEmax) which is reduced to light use efficiency (LUE) by environmental stress scalars. This may not reflect variation in LUE within a crop season, and environmental stress scalars developed for ecosystem scale modelling may not apply linearly to croplands. We predicted LUE on several vegetation indices, crop type, and agroclimatic predictors using supervised random forest regression with training data from flux towers. Using a fixed LUEmax and environmental stress scalars pro

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Goerner, A., M. Reichstein, E. Tomelleri, et al. "Remote sensing of ecosystem light use efficiency with MODIS-based PRI – the DOs and DON'Ts." Biogeosciences Discussions 7, no. 5 (2010): 6935–69. http://dx.doi.org/10.5194/bgd-7-6935-2010.

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Abstract. Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the efficiency with which MODIS-based PRI can be used to estim

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8

Wang, S., Z. Li, Y. Zhang, D. Yang, and C. Ni. "LINKING PHOTOSYNTHETIC LIGHT USE EFFICIENCY AND OPTICAL VEGETATION ACTIVE INDICATORS: IMPLICATIONS FOR GROSS PRIMARY PRODUCTION ESTIMATION BY REMOTE SENSING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2020 (August 3, 2020): 571–78. http://dx.doi.org/10.5194/isprs-annals-v-3-2020-571-2020.

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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 a

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RATJEN, A. M., and H. KAGE. "Nitrogen-limited light use efficiency in wheat crop simulators: comparing three model approaches." Journal of Agricultural Science 154, no. 6 (2015): 1090–101. http://dx.doi.org/10.1017/s0021859615001082.

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SUMMARYThree different explanatory indicators for reduced light use efficiency (LUE) under limited nitrogen (N) supply were evaluated. The indicators can be used to adapt dry matter production of crop simulators to N-limited growth conditions. The first indicator, nitrogen factor (NFAC), originates from the CERES-Wheat model and calculates the critical N concentration of the shoot as a function of phenological development. The second indicator, N nutrition index (NNI), calculates a critical N concentration as a function of shoot dry matter. The third indicator, specific leaf nitrogen (SLN) ind

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Wang, H., I. C. Prentice, and J. Ni. "Primary production in forests and grasslands of China: contrasting environmental responses of light- and water-use efficiency models." Biogeosciences 9, no. 11 (2012): 4689–705. http://dx.doi.org/10.5194/bg-9-4689-2012.

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Abstract. An extensive data set on net primary production (NPP) in China's forests is analysed with the help of two simple theoretically derived models based on the light use efficiency (LUE) and water use efficiency (WUE) concepts, respectively. The two models describe the data equally well, but their implied responses to [CO2] and temperature differ substantially. These responses are illustrated by sensitivity tests in which [CO2] is kept constant or doubled, temperatures are kept constant or increased by 3.5 K, and precipitation is changed by ±10%. Precipitation changes elicit similar respo

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Ma, Li, Shaoqiang Wang, Jinghua Chen, et al. "Relationship between Light Use Efficiency and Photochemical Reflectance Index Corrected Using a BRDF Model at a Subtropical Mixed Forest." Remote Sensing 12, no. 3 (2020): 550. http://dx.doi.org/10.3390/rs12030550.

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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 Chin

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Du, Dandan, Chaolei Zheng, Li Jia, et al. "Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model." Remote Sensing 14, no. 7 (2022): 1722. http://dx.doi.org/10.3390/rs14071722.

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Satellite-based models have been widely used to estimate gross primary production (GPP) of terrestrial ecosystems. Although they have many advantages for mapping spatiotemporal variations of regional or global GPP, the performance in agroecosystems is relatively poor. In this study, a light-use-efficiency model for cropland GPP estimation, named EF-LUE, driven by remote sensing data, was developed by integrating evaporative fraction (EF) as limiting factor accounting for soil water availability. Model parameters were optimized first using CO2 flux measurements by eddy covariance system from fl

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Liu, Linqi, Xiang Gao, Binhua Cao, et al. "Comparing Different Light Use Efficiency Models to Estimate the Gross Primary Productivity of a Cork Oak Plantation in Northern China." Remote Sensing 14, no. 22 (2022): 5905. http://dx.doi.org/10.3390/rs14225905.

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Light use efficiency (LUE) models have been widely used to estimate terrestrial gross primary production (GPP). However, the estimation of GPP still has large uncertainties owing to an insufficient understanding of the complex relationship between water availability and photosynthesis. The plant water stress index (PWSI), which is based on canopy temperature, is very sensitive to the plant stomatal opening and has been regarded as a good indicator for monitoring plant water status at the regional scale. In this study, we selected a cork oak plantation in northern China with an obvious seasonal

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Wang, Mengjia, Rui Sun, Anran Zhu, and Zhiqiang Xiao. "Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches." Remote Sensing 12, no. 6 (2020): 1003. http://dx.doi.org/10.3390/rs12061003.

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Light use efficiency (LUE), which characterizes the efficiency with which vegetation converts captured/absorbed radiation into organic dry matter through photosynthesis, is a key parameter for estimating vegetation gross primary productivity (GPP). Studies suggest that diffuse radiation induces a higher LUE than direct radiation in short-term and site-scale experiments. The clearness index (CI), described as the fraction of solar incident radiation on the surface of the earth to the extraterrestrial radiation at the top of the atmosphere, is added to the parameterization approach to explain th

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Stocker, Benjamin D., Han Wang, Nicholas G. Smith, et al. "P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production." Geoscientific Model Development 13, no. 3 (2020): 1545–81. http://dx.doi.org/10.5194/gmd-13-1545-2020.

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Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farq

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Castro, Saulo, and Arturo Sanchez-Azofeifa. "Testing of Automated Photochemical Reflectance Index Sensors as Proxy Measurements of Light Use Efficiency in an Aspen Forest." Sensors 18, no. 10 (2018): 3302. http://dx.doi.org/10.3390/s18103302.

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Commercially available autonomous photochemical reflectance index (PRI) sensors are a new development in the remote sensing field that offer novel opportunities for a deeper exploration of vegetation physiology dynamics. In this study, we evaluated the reliability of autonomous PRI sensors (SRS-PRI) developed by METER Group Inc. as proxies of light use efficiency (LUE) in an aspen (Populus tremuloides) forest stand. Before comparisons between PRI and LUE measurements were made, the optical SRS-PRI sensor pairs required calibrations to resolve diurnal and seasonal patterns properly. An offline

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Rahman, M. M., D. W. Lamb, J. N. Stanley, and M. G. Trotter. "Use of proximal sensors to evaluate at the sub-paddock scale a pasture growth-rate model based on light-use efficiency." Crop and Pasture Science 65, no. 4 (2014): 400. http://dx.doi.org/10.1071/cp14071.

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Monitoring pasture growth rate is an important component of managing grazing livestock production systems. In this study, we demonstrate that a pasture growth rate (PGR) model, initially designed for NOAA AVHRR normalised difference vegetation index (NDVI) and since adapted to MODIS NDVI, can provide PGR at spatial resolution of ~2 m with an accuracy of ~2 kg DM/ha.day when incorporating in-situ sensor data. A PGR model based on light-use efficiency (LUE) was combined with in-situ measurements from proximal weather (temperature), plant (fraction of absorbed photosynthetically active radiation,

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Wang, H., I. C. Prentice, and J. Ni. "Primary production in forests and grasslands of China: contrasting environmental responses of light- and water-use efficiency models." Biogeosciences Discussions 9, no. 4 (2012): 4285–321. http://dx.doi.org/10.5194/bgd-9-4285-2012.

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Abstract. An extensive data set on net primary production (NPP) in China's forests is analysed with two semi-empirical models based on the light use efficiency (LUE) and water use efficiency (WUE) concepts, respectively. Results are shown to be broadly consistent with other data sets (grassland above-ground NPP; globally extrapolated gross primary production, GPP) and published analyses. But although both models describe the data about equally well, they predict notably different responses to [CO2] and temperature. These are illustrated by sensitivity tests in which [CO2] is kept constant or d

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Zhang, Fengji, Zhijiang Zhang, Yi Long, and Ling Zhang. "Integration of Sentinel-3 OLCI Land Products and MERRA2 Meteorology Data into Light Use Efficiency and Vegetation Index-Driven Models for Modeling Gross Primary Production." Remote Sensing 13, no. 5 (2021): 1015. http://dx.doi.org/10.3390/rs13051015.

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Accurately and reliably estimating total terrestrial gross primary production (GPP) on a large scale is of great significance for monitoring the carbon cycle process. The Sentinel-3 satellite provides the OLCI FAPAR and OTCI products, which possess a higher spatial and temporal resolution than MODIS products. However, few studies have focused on using LUE models and VI-driven models based on the Sentinel-3 satellites to estimate GPP on a large scale. The purpose of this study is to evaluate the performance of Sentinel-3 OLCI FAPAR and OTCI products combined with meteorology reanalysis data in

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Li, Longhui, Yingping Wang, Vivek K. Arora, et al. "Evaluating Global Land Surface Models in CMIP5: Analysis of Ecosystem Water- and Light-Use Efficiencies and Rainfall Partitioning." Journal of Climate 31, no. 8 (2018): 2995–3008. http://dx.doi.org/10.1175/jcli-d-16-0177.1.

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Abstract Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied s

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Kim, Jaewoo, Woo Hyun Kang, and Jung Eek Son. "Interpretation and Evaluation of Electrical Lighting in Plant Factories with Ray-Tracing Simulation and 3D Plant Modeling." Agronomy 10, no. 10 (2020): 1545. http://dx.doi.org/10.3390/agronomy10101545.

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In plant factories, light is fully controllable for crop production but involves a cost. For efficient lighting, light use efficiency (LUE) should be considered as part of light environment design. The objectives of this study were to evaluate and interpret the light interception, photosynthetic rate, and LUE of lettuces under electrical lights using ray-tracing simulation. The crop architecture model was constructed by 3D scanning, and ray-tracing simulation was used to interpret light interception and photosynthesis. For evaluation of simulation reliability, measured light intensities and ph

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Zheng, Yi, Ruoque Shen, Yawen Wang, et al. "Improved estimate of global gross primary production for reproducing its long-term variation, 1982–2017." Earth System Science Data 12, no. 4 (2020): 2725–46. http://dx.doi.org/10.5194/essd-12-2725-2020.

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Abstract. Satellite-based models have been widely used to simulate vegetation gross primary production (GPP) at the site, regional, or global scales in recent years. However, accurately reproducing the interannual variations in GPP remains a major challenge, and the long-term changes in GPP remain highly uncertain. In this study, we generated a long-term global GPP dataset at 0.05∘ latitude by 0.05∘ longitude and 8 d interval by revising a light use efficiency model (i.e., EC-LUE model). In the revised EC-LUE model, we integrated the regulations of several major environmental variables: atmosp

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Yuan, W., S. Liu, W. Cai, et al. "Are vegetation-specific model parameters required for estimating gross primary production?" Geoscientific Model Development Discussions 6, no. 4 (2013): 5475–88. http://dx.doi.org/10.5194/gmdd-6-5475-2013.

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Abstract. Models of gross primary production (GPP) are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameter that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 150 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven li

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Zhang, Helin, Jia Bai, Rui Sun, et al. "Improved Global Gross Primary Productivity Estimation by Considering Canopy Nitrogen Concentrations and Multiple Environmental Factors." Remote Sensing 15, no. 3 (2023): 698. http://dx.doi.org/10.3390/rs15030698.

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The terrestrial gross primary productivity (GPP) plays a crucial role in regional or global ecological environment monitoring and carbon cycle research. Many previous studies have produced multiple products using different models, but there are still significant differences between these products. This study generated a global GPP dataset (NI-LUE GPP) with 0.05° spatial resolution and at 8 day-intervals from 2001 to 2018 based on an improved light use efficiency (LUE) model that simultaneously considered temperature, water, atmospheric CO2 concentrations, radiation components, and nitrogen (N)

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Schull, M. A., M. C. Anderson, R. Houborg, A. Gitelson, and W. P. Kustas. "Thermal-based modeling of coupled carbon, water, and energy fluxes using nominal light use efficiencies constrained by leaf chlorophyll observations." Biogeosciences 12, no. 5 (2015): 1511–23. http://dx.doi.org/10.5194/bg-12-1511-2015.

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Abstract. Recent studies have shown that estimates of leaf chlorophyll content (Chl), defined as the combined mass of chlorophyll a and chlorophyll b per unit leaf area, can be useful for constraining estimates of canopy light use efficiency (LUE). Canopy LUE describes the amount of carbon assimilated by a vegetative canopy for a given amount of absorbed photosynthetically active radiation (APAR) and is a key parameter for modeling land-surface carbon fluxes. A carbon-enabled version of the remote-sensing-based two-source energy balance (TSEB) model simulates coupled canopy transpiration and c

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Schull, M. A., M. C. Anderson, R. Houborg, A. Gitelson, and W. P. Kustas. "Thermal-based modeling of coupled carbon, water and energy fluxes using nominal light use efficiencies constrained by leaf chlorophyll observations." Biogeosciences Discussions 11, no. 10 (2014): 14133–71. http://dx.doi.org/10.5194/bgd-11-14133-2014.

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Abstract. Recent studies have shown that estimates of leaf chlorophyll content (Chl), defined as the combined mass of chlorophyll a and chlorophyll b per unit leaf area, can be useful for constraining estimates of canopy light-use-efficiency (LUE). Canopy LUE describes the amount of carbon assimilated by a vegetative canopy for a given amount of Absorbed Photosynthetically Active Radiation (APAR) and is a key parameter for modeling land-surface carbon fluxes. A carbon-enabled version of the remote sensing-based Two-Source Energy Balance (TSEB) model simulates coupled canopy transpiration and c

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Chen, Jinghua, Qian Zhang, Bin Chen, et al. "Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize." Remote Sensing 12, no. 17 (2020): 2812. http://dx.doi.org/10.3390/rs12172812.

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The photochemical reflectance index (PRI) has been suggested as an indicator of light use efficiency (LUE), and for use in the improvement of estimating gross primary production (GPP) in LUE models. Over the last two decades, solar-induced fluorescence (SIF) observations from remote sensing have been used to evaluate the distribution of GPP over a range of spatial and temporal scales. However, both PRI and SIF observations have been decoupled from photosynthesis under a variety of non-physiological factors, i.e., sun-view geometry and environmental variables. These observations are important f

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Joiner, Joanna, Yasuko Yoshida, Yao Zhang, et al. "Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data." Remote Sensing 10, no. 9 (2018): 1346. http://dx.doi.org/10.3390/rs10091346.

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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 o

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Shu, Yamei, Shuguang Liu, Zhao Wang, et al. "Effects of Aerosols on Gross Primary Production from Ecosystems to the Globe." Remote Sensing 14, no. 12 (2022): 2759. http://dx.doi.org/10.3390/rs14122759.

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Aerosols affect the gross primary productivity (GPP) of plants by absorbing and scattering solar radiation. However, it is still an open question whether and to what extent the effects of aerosol on the diffuse fraction (Df) can enhance GPP globally. We quantified the aerosol diffuse fertilization effect (DFE) and incorporated it into a light use efficiency (LUE) model, EC-LUE. The new model is driven by aerosol optical depth (AOD) data and is referred to as AOD-LUE. The eddy correlation variance (EC) of the FLUXNET2015 dataset was used to calibrate and validate the model. The results showed t

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Xie, Xinyao, Ainong Li, Huaan Jin, Jinhu Bian, Zhengjian Zhang, and Xi Nan. "Comparing Three Remotely Sensed Approaches for Simulating Gross Primary Productivity over Mountainous Watersheds: A Case Study in the Wanglang National Nature Reserve, China." Remote Sensing 13, no. 18 (2021): 3567. http://dx.doi.org/10.3390/rs13183567.

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Light Use Efficiency (LUE), Vegetation Index (VI)-based, and process-based models are the main approaches for spatially continuous gross primary productivity (GPP) estimation. However, most current GPP models overlook the effects of topography on the vegetation photosynthesis process. Based on the structures of a two-leaf LUE model (TL-LUE), a VI-based model (temperature and greenness, TG), and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS), three models, named mountain TL-LUE (MTL-LUE), mountain TG (MTG), and BEPS-TerrainLab, have been proposed to improve GPP estimation

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Ediz; BAYRAMİN, ÜNAL. "Primary production estimation of Çankırı province’s rangelands using light use efficiency (LUE) model with satellite data and agrometshell module." Tarım Bilimleri Dergisi 22, no. 4 (2016): 555–65. http://dx.doi.org/10.1501/tarimbil_0000001414.

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Christina, M., Y. Nouvellon, J. P. Laclau, J. L. Stape, O. C. Campoe, and G. le Maire. "Sensitivity and uncertainty analysis of the carbon and water fluxes at the tree scale in Eucalyptus plantations using a metamodeling approach." Canadian Journal of Forest Research 46, no. 3 (2016): 297–309. http://dx.doi.org/10.1139/cjfr-2015-0173.

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Understanding the consequences of changes in climatic and biological drivers on tree carbon and water fluxes is essential in forestry. Using a metamodeling approach, sensitivity and uncertainty analyses were carried out for a tree-scale model (MAESPA) to isolate the effects of climate, morphological and physiological traits, and intertree competition on the absorption of photosynthetically active radiation (APAR), gross primary production (GPP), transpiration (TR), light use efficiency (LUE), and water use efficiency (WUE) in clonal Eucalyptus plantations. The metamodel predicting daily TR was

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Moore, Caitlin E., Jason Beringer, Bradley Evans, Lindsay B. Hutley, and Nigel J. Tapper. "Tree–grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna." Biogeosciences 14, no. 1 (2017): 111–29. http://dx.doi.org/10.5194/bg-14-111-2017.

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Abstract. The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom–bust seasonal pattern of productivity that follows the wet–dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to u

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Lin, Xiaofeng, Baozhang Chen, Huifang Zhang, et al. "Effects of the Temporal Aggregation and Meteorological Conditions on the Parameter Robustness of OCO-2 SIF-Based and LUE-Based GPP Models for Croplands." Remote Sensing 11, no. 11 (2019): 1328. http://dx.doi.org/10.3390/rs11111328.

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Global retrieval of solar-induced chlorophyll fluorescence (SIF) using remote sensing by means of satellites has been developed rapidly in recent years. Exploring how SIF could improve the characterization of photosynthesis and its role in the land surface carbon cycle has gradually become a very important and active area. However, compared with other gross primary production (GPP) models, the robustness of the parameterization of the SIF model under different circumstances has rarely been investigated. In this study, we examined and compared the effects of temporal aggregation and meteorologi

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Lopez M., Miguel Ángel, Bernardo Chaves C., and Víctor Julio Flórez R. "Potential growing model for the standard carnation cv. Delphi." Agronomía Colombiana 32, no. 2 (2014): 196–204. http://dx.doi.org/10.15446/agron.colomb.v32n2.43737.

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The cut flower business requires exact synchronicity between product offer and demand in consumer countries. Having tools that help to improve this synchronicity through predictions or crop growth monitoring could provide an important advantage to program standards and corrective agronomic practices. At the Centro de Biotecnología Agropecuaria, SENA (SENA's Biotechnology, Agricultural and Livestock Center), located in Mosquera, Cundinamarca, a trial with standard carnation cv. Delphi grown under greenhouse conditions was carried out. The objective of this study was to build a simple model of d

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KAGE, H., C. ALT, and H. STÜTZEL. "Aspects of nitrogen use efficiency of cauliflower II. Productivity and nitrogen partitioning as influenced by N supply." Journal of Agricultural Science 141, no. 1 (2003): 17–29. http://dx.doi.org/10.1017/s0021859603003538.

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Based on studies concerning dry matter (DM) partitioning, DM production, root growth, nitrogen (N) contents of cauliflower organs and soil nitrate availability (first part of the paper Kage et al. 2003b), an integrated simulation model for the cauliflower/soil system is constructed, parameterized and evaluated.Dry matter production of cauliflower is described and predicted using a simple light use efficiency (LUE) based approach assuming a linear decrease of light use efficiency with increasing differences between actual, NCAProt, and ‘optimal’, NCAoptProt area based leaf protein concentration

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Chen, Siyuan, Lichun Sui, Liangyun Liu, and Xinjie Liu. "Effect of the Partitioning of Diffuse and Direct APAR on GPP Estimation." Remote Sensing 14, no. 1 (2021): 57. http://dx.doi.org/10.3390/rs14010057.

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Accurate estimation of gross primary productivity (GPP) is necessary to better understand the interaction of global terrestrial ecosystems with climate change and human activities. Light use efficiency (LUE)-based GPP models are widely used for retrieving several GPP products with various temporal and spatial resolutions. However, most LUE-based models assume a clear-sky condition, and the influence of diffuse radiation on GPP estimations has not been well considered. In this paper, a diffuse and direct (DDA) absorbed photosynthetically active radiation (APAR)-based method is proposed for bett

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Song, Conghe, Matthew P. Dannenberg, and Taehee Hwang. "Optical remote sensing of terrestrial ecosystem primary productivity." Progress in Physical Geography: Earth and Environment 37, no. 6 (2013): 834–54. http://dx.doi.org/10.1177/0309133313507944.

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Terrestrial ecosystem primary productivity is a key indicator of ecosystem functions, including, but not limited to, carbon storage, provision of food and fiber, and sustaining biodiversity. However, measuring terrestrial ecosystem primary productivity in the field is extremely laborious and expensive. Optical remote sensing has revolutionized our ability to map terrestrial ecosystem primary productivity over large areas ranging from regions to the entire globe in a repeated, cost-efficient manner. This progress report reviews the theory and practice of mapping terrestrial primary productivity

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Xu, Wenshuo, Na Lu, Masao Kikuchi, and Michiko Takagaki. "Continuous Lighting and High Daily Light Integral Enhance Yield and Quality of Mass-Produced Nasturtium (Tropaeolum majus L.) in Plant Factories." Plants 10, no. 6 (2021): 1203. http://dx.doi.org/10.3390/plants10061203.

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Nasturtium (Tropaeolum majus L.), as a medicinal plant, has a high phenolic content in its leaves and flowers. It is often used in salads as a dietary vegetable. Attracting strong demand, it could be a good candidate crop for a plant factory with artificial lighting (PFAL) that can achieve the mass production of high-quality crops with high productivity by regulating environmental conditions such as light. In this study, two experiments were conducted to investigate the effects of continuous lighting (CL) and different daily light integrals (DLIs) under CL on the growth, secondary metabolites,

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Balzarolo, M., S. Boussetta, G. Balsamo, et al. "Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network." Biogeosciences 11, no. 10 (2014): 2661–78. http://dx.doi.org/10.5194/bg-11-2661-2014.

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Abstract. This paper reports a comparison between large-scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This

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Zhou, Yanlian, Xiaocui Wu, Weimin Ju, et al. "Modeling the Effects of Global and Diffuse Radiation on Terrestrial Gross Primary Productivity in China Based on a Two-Leaf Light Use Efficiency Model." Remote Sensing 12, no. 20 (2020): 3355. http://dx.doi.org/10.3390/rs12203355.

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Solar radiation significantly affects terrestrial gross primary productivity (GPP). However, the relationship between GPP and solar radiation is nonlinear because it is affected by diffuse radiation. Solar radiation has undergone a shift from darker to brighter values over the past 30 years in China. However, the effects on GPP of variation in solar radiation because of changes in diffuse radiation are unclear. In this study, national global radiation in conjunction with other meteorological data and remotely sensed data were used as input into a two-leaf light use efficiency model (TL-LUE) th

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Gómez-Giráldez, Pedro J., Elisabet Carpintero, Mario Ramos, Cristina Aguilar, and María P. González-Dugo. "Effect of the water stress on gross primary production modeling of a Mediterranean oak savanna ecosystem." Proceedings of the International Association of Hydrological Sciences 380 (December 18, 2018): 37–43. http://dx.doi.org/10.5194/piahs-380-37-2018.

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Abstract. Dehesa ecosystem consists of widely-spaced oak trees combined with crops, pasture and Mediterranean shrubs. It is located in the southwest of the Iberian Peninsula, where water scarcity is recurrent, severely affecting the multiple productions and services of the ecosystem. Upscaling in situ Gross Primary Production (GPP) estimates in these areas is challenging for regional and global studies, given the significant spatial variability of plant functional types and the vegetation stresses usually present. The estimation of GPP is often addressed using light use efficiency models (LUE-

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Zhang, Liangxia, Decheng Zhou, Jiangwen Fan, et al. "Contrasting the Performance of Eight Satellite-Based GPP Models in Water-Limited and Temperature-Limited Grassland Ecosystems." Remote Sensing 11, no. 11 (2019): 1333. http://dx.doi.org/10.3390/rs11111333.

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Models constitute the primary approaches for predicting terrestrial ecosystem gross primary production (GPP) at regional and global scales. Many satellite-based GPP models have been developed due to the simple algorithms and the low requirements of model inputs. The performances of these models are well documented at the biome level. However, their performances among vegetation subtypes limited by different environmental stresses within a biome remains largely unexplored. Taking grasslands in northern China as an example, we compared the performance of eight satellite-based GPP models, includi

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Gamon, J. A. "Reviews and Syntheses: optical sampling of the flux tower footprint." Biogeosciences 12, no. 14 (2015): 4509–23. http://dx.doi.org/10.5194/bg-12-4509-2015.

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Abstract. The purpose of this review is to address the reasons and methods for conducting optical remote sensing within the flux tower footprint. Fundamental principles and conclusions gleaned from over 2 decades of proximal remote sensing at flux tower sites are reviewed. The organizing framework used here is the light-use efficiency (LUE) model, both because it is widely used, and because it provides a useful theoretical construct for integrating optical remote sensing with flux measurements. Multiple ways of driving this model, ranging from meteorological measurements to remote sensing, hav

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Gamon, J. A. "Optical sampling of the flux tower footprint." Biogeosciences Discussions 12, no. 6 (2015): 4973–5014. http://dx.doi.org/10.5194/bgd-12-4973-2015.

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Abstract. The purpose of this review is to address the reasons and methods for conducting optical remote sensing within the flux tower footprint. Fundamental principles and conclusions gleaned from over two decades of proximal remote sensing at flux tower sites are reviewed. An organizing framework is the light-use efficiency (LUE) model, both because it is widely used, and because it provides a useful theoretical construct for integrating optical remote sensing with flux measurements. Multiple ways of driving this model, ranging from meteorological measurements to remote sensing, have emerged

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Dhillon, Maninder Singh, Thorsten Dahms, Carina Kuebert-Flock, Erik Borg, Christopher Conrad, and Tobias Ullmann. "Modelling Crop Biomass from Synthetic Remote Sensing Time Series: Example for the DEMMIN Test Site, Germany." Remote Sensing 12, no. 11 (2020): 1819. http://dx.doi.org/10.3390/rs12111819.

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This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site, Germany. The study focuses on the use of remote sensing (RS) data, acquired in 2015, in CGMs, as they offer spatial information on the actual conditions of the veg

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Lin, Shangrong, Xiaojuan Huang, Yi Zheng, Xiao Zhang, and Wenping Yuan. "An Open Data Approach for Estimating Vegetation Gross Primary Production at Fine Spatial Resolution." Remote Sensing 14, no. 11 (2022): 2651. http://dx.doi.org/10.3390/rs14112651.

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Accurate simulations of the spatial and temporal changes in vegetation gross primary production (GPP) play an important role in ecological studies. Previous studies highlighted large uncertainties in GPP datasets based on satellite data with coarse spatial resolutions (>500 m), and implied the need to produce high-spatial-resolution datasets. However, estimating fine spatial resolution GPP is time-consuming and requires an enormous amount of computing storage space. In this study, based on the Eddy Covariance-Light Use Efficiency (EC-LUE) model, we used Google Earth Engine (GEE) to develop

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Zhou, Xuqiang, Xufeng Wang, Songlin Zhang, Yang Zhang, and Xuejie Bai. "Combining Phenological Camera Photos and MODIS Reflectance Data to Predict GPP Daily Dynamics for Alpine Meadows on the Tibetan Plateau." Remote Sensing 12, no. 22 (2020): 3735. http://dx.doi.org/10.3390/rs12223735.

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Gross primary production (GPP) is the overall photosynthetic fixation of carbon per unit space and time. Due to uncertainties resulting from clouds, snow, aerosol, and topography, it is a challenging task to accurately estimate daily GPP. Daily digital photos from a phenological camera record vegetation daily greenness dynamics with little cloud or aerosol disturbance. It can be fused with satellite remote sensing data to improve daily GPP prediction accuracy. In this study, we combine the two types of datasets to improve the estimation accuracy of GPP for alpine meadow on the Tibetan Plateau.

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Fu, Yangyang, Jianxi Huang, Yanjun Shen, et al. "A Satellite-Based Method for National Winter Wheat Yield Estimating in China." Remote Sensing 13, no. 22 (2021): 4680. http://dx.doi.org/10.3390/rs13224680.

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Satellite-based models have tremendous potential for monitoring crop production because satellite data can provide temporally and spatially continuous crop growth information at large scale. This study used a satellite-based vegetation production model (i.e., eddy covariance light use efficiency, EC-LUE) to estimate national winter wheat gross primary production, and then combined this model with the harvest index (ratio of aboveground biomass to yield) to convert the estimated winter wheat production to yield. Specifically, considering the spatial differences of the harvest index, we used a c

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Chen, T., G. R. van der Werf, N. Gobron, E. J. Moors, and A. J. Dolman. "Global cropland monthly gross primary production in the year 2000." Biogeosciences 11, no. 14 (2014): 3871–80. http://dx.doi.org/10.5194/bg-11-3871-2014.

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Abstract. Croplands cover about 12% of the ice-free terrestrial land surface. Compared with natural ecosystems, croplands have distinct characteristics due to anthropogenic influences. Their global gross primary production (GPP) is not well constrained and estimates vary between 8.2 and 14.2 Pg C yr−1. We quantified global cropland GPP using a light use efficiency (LUE) model, employing satellite observations and survey data of crop types and distribution. A novel step in our analysis was to assign a maximum light use efficiency estimate (&amp;varepsilon;*GPP) to each of the 26 different c

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