Academic literature on the topic 'Light use efficiency (LUE) model'
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Journal articles on the topic "Light use efficiency (LUE) model"
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Zhang, Jun, Xufeng Wang, and Jun Ren. "Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models." Land 10, no. 3 (March 23, 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, and vegetation spatial heterogeneity. In this study, five widely used LUE models, Glo-PEM, VPM, EC-LUE, the MODIS GPP algorithm, and C-fix, were selected to simulate the GPP of the Heihe River Basin forced using in situ measurements. A multiple-model averaging method, Bayesian model averaging (BMA), was used to combine the five models to obtain a more reliable GPP estimation. The BMA was trained using carbon flux data from five eddy covariance towers located at dominant vegetation types in the study area. Generally, the BMA method performed better than any single LUE model. From the case study in the study area, it is indicated that the trained BMA is an efficient method to combine multiple LUE models and can improve the GPP simulation accuracy.
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McCallum, I., O. Franklin, E. Moltchanova, L. Merbold, C. Schmullius, A. Shvidenko, D. Schepaschenko, and S. Fritz. "Improved light and temperature responses for light-use-efficiency-based GPP models." Biogeosciences 10, no. 10 (October 17, 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 accounted for if model accuracy is to be improved. We hypothesize that in boreal regions (which are strongly temperature controlled), accounting for temperature acclimation and non-linear light response of daily GPP 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 with and without temperature acclimation and an LUE model and a big leaf model both with temperature acclimation and non-linear in their light response. All models include environmental modifiers for temperature and vapour pressure deficit (VPD). Initially, all models were calibrated against five eddy covariance (EC) sites within Russia for the years 2002–2005, for a total of 17 site years. Model evaluation was performed via 10-out cross-validation. Cross-validation clearly demonstrates the improvement in model performance that temperature acclimation makes in modelling GPP at strongly temperature-controlled sites in Russia. These results would indicate that inclusion of temperature acclimation in models on sites experiencing cold temperatures is imperative. Additionally, the inclusion of a non-linear light response function is shown to further improve performance, particularly in less temperature-controlled sites.
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McCallum, I., O. Franklin, E. Moltchanova, L. Merbold, C. Schmullius, A. Shvidenko, D. Schepaschenko, and S. Fritz. "Improved light and temperature responses for light use efficiency based GPP models." Biogeosciences Discussions 10, no. 5 (May 29, 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 with and without temperature acclimation and an LUE model and a big leaf model both with temperature acclimation and non-linear in their light response. All models include environmental modifiers for temperature and vapour pressure deficit (VPD). Initially, all models were calibrated against four eddy covariance sites within Russia for the years 2002–2004, for a total of 10 site years. Model evaluation was performed via 10-out cross-validation. This study presents a methodology for comparing diagnostic modeling approaches. Cross validation clearly demonstrates the improvement in model performance that temperature acclimation makes in modeling GPP at strongly temperature controlled sites in Russia. Additionally, the inclusion of a non-linear light response function is shown to further improve performance. Furthermore we demonstrate the parameterization of the big leaf model, incorporating environmental modifiers for temperature and VPD.
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Goerner, A., M. Reichstein, E. Tomelleri, N. Hanan, S. Rambal, D. Papale, D. Dragoni, and C. Schmullius. "Remote sensing of ecosystem light use efficiency with MODIS-based PRI." Biogeosciences 8, no. 1 (January 26, 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 estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependence on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well.
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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 (February 21, 2023): 1176. http://dx.doi.org/10.3390/rs15051176.
Full textAbstract:
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-based GPP estimation. Using quality-screened daily data from the FLUXNET 2015 dataset, this paper proposed a photosynthetically active radiation (PAR)-regulated dynamic Ɛmax (PAR-Ɛmax, corresponding model named PAR-LUE) by considering the nonlinear response of vegetation photosynthesis to solar radiation. The PAR-LUE was compared with static Ɛmax-based (MODIS and EC-LUE) and spatial dynamics Ɛmax-based (D-VPM) models at 171 flux sites. Validation results showed that (1) R2 and RMSE between PAR-LUE GPP and observed GPP were 0.65 (0.44) and 2.55 (1.82) g C m−2 MJ−1 d−1 at the 8-day (annual) scale, respectively; (2) GPP estimation accuracy of PAR-LUE was higher than that of other LUE-based models (MODIS, EC-LUE, and D-VPM), specifically, R2 increased by 29.41%, 2.33%, and 12.82%, and RMSE decreased by 0.36, 0.14, and 0.34 g C m−2 MJ−1 d−1 at the annual scale; and (3) specifically, compared to the static Ɛmax-based model (MODIS and EC-LUE), PAR-LUE effectively relieved the underestimation of high GPP. Overall, the newly developed PAR-Ɛmax provided an estimation method utilizing a spatiotemporal dynamic Ɛmax, which effectively reduced the uncertainty of GPP estimation and provided a new option for the optimization of Ɛmax in the LUE model.
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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 (March 20, 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 produced an overestimation of GPP with a root mean square error (RMSE) of 6.26 gC/m2/day, while using predicted LUE from random forest regression produced RMSEs of 0.099 and 0.404 gC/m2/day for models with and without crop type as a predictor, respectively. Prediction uncertainty was greater for the model without crop type. These results show that LUE varies between crop type, is dynamic within a crop season, and LUE models that reflect this are able to produce much more accurate estimates of GPP over cropland than using fixed LUEmax with stress scalars. Therefore, we suggest a paradigm shift from setting the LUE variable in cropland productivity models based on environmental stress to focusing more on the variation of LUE within a crop season.
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Goerner, A., M. Reichstein, E. Tomelleri, N. Hanan, S. Rambal, D. Papale, D. Dragoni, and C. Schmullius. "Remote sensing of ecosystem light use efficiency with MODIS-based PRI – the DOs and DON'Ts." Biogeosciences Discussions 7, no. 5 (September 14, 2010): 6935–69. http://dx.doi.org/10.5194/bgd-7-6935-2010.
Full textAbstract:
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 estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependance on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well.
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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 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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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 (December 8, 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) index (SLNI), has been newly developed. It compares the actual SLN with the maximum SLN (SLNmax). The latter is calculated as a function of the green area index (GAI). The comparison was based on growth curves and fitted to empirical data, and was carried out independently from a dynamic crop model. The data set included four growing seasons (2004–2006, 2012) in Northern Germany and seven modern bread wheat cultivars with varying N fertilization levels (0–320 kg N/ha). The influence of N shortage on LUE was evaluated from the beginning of stem elongation until flowering. With the exception of 2005, the highest productivity was observed for the highest N level. A moderate N shortage primarily reduced GAI and therefore light interception, while LUE remained stable under moderate N shortage. The relative LUE (rLUE) of a specific day was defined as the ratio of actual to maximal LUE. None of the indicators was proportional to rLUE, but the relationships were described well by quadratic plateau curves. The correlation between simulated and measured rLUE was significant for all explanatory indicators, but different in terms of mean absolute error and coefficient of determination (R2). The performance of SLNI and NNI was similar, but the goodness of prediction was much lower for NFAC. Compared with NNI and NFAC, SLNI corresponded to leaf N and was therefore sensitive to N translocation from leaves to growing grains during the reproductive stage. For this reason, SLNI may have the potential to improve simulation of dry matter production in wheat crop simulators.
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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 (November 22, 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 responses in both models. But NPP in South China, especially, is reduced by warming in the LUE model, whereas it is increased in the WUE model. The [CO2] response of the WUE model is much larger than that of the LUE model. It is argued that the two models provide upper and lower bounds for this response, with the LUE model more realistic for forests. The differences between the two models illustrate some potential causes of the large differences (even in sign) in the global NPP response of different global vegetation models to temperature and [CO2].
Dissertations / Theses on the topic "Light use efficiency (LUE) model"
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GALVAGNO, MARTA RITA. "Carbon dioxide exchange of an alpine grassland: integration of eddy covariance, proximal sensing and models." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/24290.
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The terrestrial biosphere represents a large pool of carbon, whose cycle is governed
by the opposed processes of CO2 uptake (photosynthesis) and release (respiration)
from and to the atmosphere. Considering the role of carbon dioxide in the observed global warming, monitoring, understanding and modeling carbon exchange
of ecosystems is a critical issue in climate change researches. Moreover because
of the multiple implications of vegetation structure dynamics on ecosystem carbon
fluxes, monitoring and modeling plant phenology is also of increasing scientific
interest.
Among terrestrial ecosystem grasslands cover almost 40% of ice-free land surface, nevertheless their role as sources/sinks of atmospheric CO2 is not well clarified.
In this study the eddy covariance method was used to assess CO2 exchange at
an high elevation unmanaged grassland in the North-Western Italian Alps (Aosta
Valley - Torgnon), during three years (2008-2010) of measurements and to evaluate
how environmental factors affect photosynthetic processes.
The seasonal and inter-annual course of net ecosystem CO2 exchange (NEE),
ecosystem respiration (Reco), gross primary production (GPP) and the main meteorological variables was analysed. The three growing seasons had a similar seasonal
dynamic, characterised by a fast rise of photosynthetic activity after snow-melt followed by a gradual autumnal decline. Regarding the meteorological variables, only
precipitation, soil water content and snow depth differed markedly among two of
the studied years (2009-2010) compared to other factors which showed only small
differences in restricted time-periods.
To better interpret how weather variables modulate ecosystem processes at multiple time-scales (day, week, month, year), a quantitative analysis was performed applying wavelet coherence between time-series of GPP and time-series of different
meteorological factors (air and soil temperature, soil water content and photosynthetically active radiation).
Eddy covariance and meteorological data were combined with proximal sensing measurements to identify links between optical indices, canopy development
and fluxes. In particular a colour index derived from continuous digital imagery
(i.e. Greenness Index, (GI), based on RGB channels) and indices derived from an
HyperSpectral System (Hyperspectral Irradiometer, HSI) were used as input to simulate GPP, based on a light use efficiency (LUE) model. Results showed that a LUE
model driven by optical indices and meteorological variables is able to describe the
GPP trend in the two years of study. In particular the use of different model formulations provided insights on the role of the main meteorological factors controlling
grassland photosynthesis. The comprehension of these relationships at stand level
is essential for extrapolating such information at different spatial scales.
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Horn, Judith. "Development and Extrapolation of a General Light Use Efficiency Model for the Gross Primary Production." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-134346.
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Horn, Judith [Verfasser], and Karsten [Akademischer Betreuer] Schulz. "Development and Extrapolation of a General Light Use Efficiency Model for the Gross Primary Production / Judith Horn. Betreuer: Karsten Schulz." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2011. http://d-nb.info/1015500684/34.
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Perez, Denise. "Light-Use Efficiency of Coral-Reef Communities: A Sensitivity Analysis Using an Optically Based Model of Reef Productivity and Calcification." NSUWorks, 2013. http://nsuworks.nova.edu/occ_stuetd/99.
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Biogeochemical processes of reefs have been studied for over fifty years, however, information is still lacking on several fundamental reef processes. This lack of information has been limited essentially by techniques that cannot repeatedly sample large spatial areas. These limitations can be reduced with the use of an optical model to estimate biogeochemical processes. This project applied Monteith's light-use efficiency model to coral reef communities for determining photosynthetic and calcification efficiency of light. Gross primary production and net calcification were pooled from the peer-reviewed literature to calculate efficiency. Process efficiency was then compared across functional types of reef communities (i.e., coral, algae/seagrasses, mixed, and sand), and by year, location, season, and depth. Photosynthetic efficiency was calculated from 19 studies, showing an average of 0.039 mol O2 mol-1 photons. Photosynthetic efficiency differed significantly for mixed communities between studies, and for algae/seagrass communities among depths. Calcification efficiency averaged at 0.007 mol CaCO3 mol-1 photons. Significant differences were found in calcification efficiency of algae/seagrasses and mixed reef communities among studies and localities. Additionally, calcification efficiency of algae/seagrasses varied significantly in accordance with depth. Future use of the light-use efficiency model will require determining the efficiency of each functional type to estimate gross production and calcification. Additionally, further investigation of the light-use efficiency model will require long-term measurements of APAR, which is the fraction of incident light absorbed, and the incorporation of environmental parameters that reduce efficiency.
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Yan, Hao, Shao-Qiang Wang, Rocha Humberto R. da, Alexandru Rap, Damien Bonal, Nathalie Butt, Natalia Restrepo Coupe, and Herman H. Shugart. "Simulation of the Unexpected Photosynthetic Seasonality in Amazonian Evergreen Forests by Using an Improved Diffuse Fraction-Based Light Use Efficiency Model." AMER GEOPHYSICAL UNION, 2017. http://hdl.handle.net/10150/626446.
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Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R-2=0.45-0.69) with a root-mean-square error (RMSE) of 0.67-1.25gCm(-2)d(-1) and a Bias of -0.03-1.04gCm(-2)d(-1) for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. In the transition from dry season to rainy season, incident total radiation (Q) decreased while LUE and diffuse fraction increased, which produced the large seasonal increase (similar to 34%) in GPP of evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R-2=0.40-0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in tropical Amazon. Plain Language Summary Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R2= 0.45-0.69) for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light-use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R2= 0.40 similar to 0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in Amazon.
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Dufbäck, Emma. "Nitrogen Uptake by Vegetation in the Wakkerstroom Wetland, South Africa." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-389981.
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The lack of proper wastewater treatment inhibits the social and economic development in many communities. The South African town Wakkerstroom is an example where wastewater is first treated before it is released. Due to the lack of technical expertise and funding to manage the sewage disposal system, a large part of the wastewater goes directly, without any treatment, into a stream feeding the Wakkerstroom wetland. The wetland purifies the wastewater and provides clean water downstream, thus is indispensable for its detoxification capacity. One relatively cheap method to determine the absorption capacity of a wetland with respect to nitrogen loading is to investigate the nitrogen uptake by the wetland vegetation. In this study, the nitrogen uptake of the vegetation in the Wakkerstroom wetland during the growing seasons between the years 2000-2018 was investigated by using harvested biomass and its nitrogen content as a proxy. The interannual variability of Net Primary Production (NPP) was calculated using a Light Use Efficiency (LUE) model for the period 2000-2018. The NPP derived with LUE-modelling was compared to NPP based on an end-of season harvest of biomass in March 2019. The nitrogen content and carbon and nitrogen (C:N) ratio were determined in the harvested biomass by carbon and nitrogen content analysis. The annual nitrogen uptake of the growing seasons between the years 2000-2018 was subsequently determined by multiplying the calculated NPP by the fraction of nitrogen found in the harvested material. The NPPtot based on harvested biomass (NPPharvest) towards the end of the growing season 2018/2019 was estimated to be 2.01 kg‧m-2‧season-1. The NPPtot calculated from LUE modelling (NPPLUE) varied between 0.49-1.64 kg‧m-2 for the growing seasons between 2000-2018. NPPharvest was between 1.2-4 times higher compared to NPPLUE, probably due to overestimation of NPPharvest because of biomass sampling of more than one-year production, or underestimation of NPPLUE due to a low maximum radiation conversion efficiency factor, εmax. The community mean nitrogen (N) content found in the biomass harvested aboveground was 1.29 % for the Phragmites community and 1.00 % for the Typha community. The nitrogen uptake of the vegetation was estimated to vary between 6.10-20.5 g N∙m-2 per growing season between the years 2000-2018.Bristen på adekvata reningstekniker för att behandla avloppsvatten hämmar den sociala och ekonomiska utvecklingen i många samhällen. Den sydafrikanska staden Wakkerstroom är ett exempel där avloppsvatten först renas innan det släpps ut. På grund av brisen på teknisk kompetens och finansiering att hantera reningsverket som avlägsnar avloppsvatten så läcker en stor del av det orenade avloppsvattnet ut i en våtmark i Wakkerstroom via en närliggande å. Våtmarken är av regional betydelse för sin reningskapacitet då den renar avloppsvattnet och förser användare nedströms med rent vatten. En viktig aspekt för att bestämma en våtmarks reningskapacitet med avseende på kväve (N) är att undersöka växternas kväveupptag i våtmarken. Kväveupptaget hos växterna i våtmarken i Wakkerstroom under växtsäsongerna mellan år 2000–2018 undersöktes genom att använda skördad biomassa och dess kväveinnehåll som proxy. Den årliga variabiliteten hos nettoprimärproduktionen (NPP) beräknades genom att använda en LUE (Light Use Efficiency)-modell för perioden 2000-2018. NPP framtaget med LUE-modellering jämfördes med NPP baserat på biomassa skördad i slutet av växtsäsongen i mars 2019. Kväveinnehållet och kol-kväve (C:N) kvoten bestämdes hos den skördade biomassan genom en kol- och kväveanalys. Det årliga kväveupptaget under växtsäsongerna mellan 2000–2018 togs därefter fram genom att multiplicera beräknad NPP med kvävefraktionen erhållen från den skördade biomassan. NPPtot framtaget med biomassa skördad i slutet av växtsäsongen 2018/2019 (NPPbiomassa) uppskattades vara 2,01 kg‧m-2‧säsong-1. NPPtot beräknat med LUE-modellering (NPPLUE) varierade mellan 0,49–1,64 kg‧m-2 under växtsäsongerna mellan år 2000–2018. NPPbiomassa var 1,2–4 gånger högre i jämförelse med NPPLUE, vilket troligtvis berodde på att NPPbiomassa överskattades på grund av att mer än en årsproduktion av biomassa skördades, eller för att NPPLUE underskattades på grund av ett för lågt värde på den maximala effektivitetsfaktorn εmax valdes. Medelvärdet för kväveinnehållet erhållen i biomassan skördad ovanför vattennivån var 1,29 % för Phragmites-samhället och 1,00 % för Typha-samhället. Kväveupptaget hos växterna varierade mellan 6,10–20,5 g N∙m-2 per växtsäsong mellan år 2000–2018.
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Campoe, Otávio Camargo. "Ecologia da produção e da competição intra-específica do Eucalyptus grandis ao longo de um gradiente de produtividade no estado de São Paulo." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/11/11150/tde-17042012-105858/.
Full textAbstract:
A produtividade dos plantios de eucalipto no Brasil apresentou ganhos significativos nas últimas décadas devido a avanços em melhoramento genético e silvicultura. Contudo, a produção de madeira representa apenas uma fração da produtividade primária bruta (GPP). Avaliar fluxos e partição de carbono (C) entre os diferentes componentes da floresta, e estudar o uso e a eficiência de uso dos recursos disponíveis é essencial para compreender os mecanismos que controlam a produtividade de plantios intensivamente manejados. O estudo quantificou os fluxos e partição de C e a eficiência de uso da luz para a produção de lenho (LUE) em 12 parcelas em um gradiente natural de produtividade, durante o sétimo ano de um plantio comercial de Eucalyptus grandis. Nessas mesmas parcelas, na escala da árvore, foram avaliadas a dominância do crescimento, produção de lenho e LUE, identificando a representatividade de árvores dominantes e suprimidas na produtividade do povoamento. O estudo do balanço de C e a aplicação da teoria da ecologia da produção em diferentes escalas objetivaram ampliar o conhecimento sobre os processos que governam a produtividade florestal. A heterogeneidade espacial dos atributos do solo e a topografia da área experimental influenciaram fortemente os fluxos componentes da GPP e sua partição, gerando um gradiente de produtividade. A produtividade de lenho variou de 554 gC m-2 ano-1 na parcela com menor GPP a 923 gC m-2 ano-1 na parcela com maior GPP. O fluxo de C para o solo variou de 497 gC m-2 ano-1 a 1235 gC m-2 ano-1 sem relação significativa com GPP. A partição do GPP para produção de lenho aumentou de 0,19 a 0,23, com tendência de aumento com o GPP (R2=0,30, p=0,07). A LUE aumentou em 66% (de 0,25 gC MJ-1 para 0,42 gC MJ-1) com a GPP, como resultado da elevação do fluxo e partição de C para produção de lenho. Ao longo do gradiente de produtividade, parcelas com alta eficiência quântica do dossel também mostraram alta LUE. A dominância do crescimento entre árvores teve forte impacto sobre a produtividade do povoamento. As 20% maiores árvores apresentaram em média 38% da biomassa de lenho e representaram 47% da produção de lenho. Características das folhas sugeriram que a maior produtividade de árvores dominantes, em relação às suprimidas, pode resultar de diferenças no controle estomático e não na capacidade fotossintética. A ecologia da produção na escala da árvore mostrou que os indivíduos dominantes produziram mais madeira por terem absorvido mais radiação e pela maior eficiência do uso da luz, comparativamente às árvores suprimidas. Em média, uma árvore suprimida cresceu 1,2 kg ano-1 de lenho, absorveu 2,9 GJ ano-1 de radiação e teve uma LUE de 0,4 g MJ-1. Já uma dominante cresceu 37 kg ano-1, absorveu 38 GJ ano-1 com mais que o dobro da eficiência (1,01 g MJ-1). Estudos sobre o balanço de carbono e ecologia da produção em diferentes escalas são essenciais para aperfeiçoar o conhecimento sobre os processos que controlam a produtividade de madeira e a fixação de carbono, e aprimorar os modelos ecofisiológicos.The productivity of the eucalypt plantations in Brazil showed significant increase over the last decades, due to improvement in breeding and silviculture. However, wood production represents only a fraction of the gross primary production (GPP). Assessing carbon (C) fluxes and partitioning among forest components, and evaluate use and use efficiency of the available resources is essential to understand mechanisms driving productivity of intensively managed plantations. The study quantified fluxes and partitioning of C and light use efficiency for stem production (LUE) in 12 plots across a natural gradient of productivity during the seventh year of a commercial Eucalyptus grandis. Within these plots, at tree level, were evaluated growth dominance, stem production and LUE, identifying representativeness of dominant and suppressed trees to stand productivity. The study of C budget and the application of the production ecology theory at different levels aimed increase the knowledge about the processes driving forest productivity. The spatial heterogeneity of soil attributes and topography across the experimental site strongly influenced the component fluxes of GPP and partitioning, generating a gradient of productivity. Stem production ranged from 554 gC m-2 year-1 at the lowest GPP plot to 923 gC m-2 year-1 at the highest GPP plot. Total below ground carbon flux (TBCF) ranged from 497 g C m-2 year-1 to 1235 g C m-2 year-1, with no relationship to ANPP or GPP. Stem NPP:GPP partitioning ratio increased from 0.19 to 0.23 showing a trend of increase with GPP (R2=0.30, p=0.07). LUE increased by 66% (from 0.25 gC MJ-1 to 0.42 gC MJ-1) with GPP, as a result of the increased C partitioned and flux to stem NPP. Across the gradient of productivity, plots with the highest canopy quantum efficiency also showed the highest LUE. Growth dominance between trees showed a strong impact on stand productivity. The 20% larger trees accounted for 38% of stem biomass and represented 47% stem production. Leaf characteristics suggested that dominant trees were more productive, in relation to suppressed, may result in differences on stomatal control and not on photosynthetic capacity. The production ecology at tree level showed that dominant trees produced more wood by absorbing more radiation and due to higher light use efficiency, comparing to suppressed trees. On average, a suppressed tree grew 1,2 kg year-1 of stem, absorbed 2,9 GJ year-1 of radiation with a LUE of 0.4 g MJ-1. Although, a dominant grew 37 kg year-1 of stem, absorbed 38 GJ year-1 of radiation with the double of efficiency (1.01 g MJ-1). Studies regarding carbon balance and production ecology at different levels are essential to improve the knowledge on processes controlling wood production and carbon uptake, and develop ecophysiological models.
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Spank, Uwe, Barbara Köstner, Uta Moderow, Thomas Grünwald, and Christian Bernhofer. "Surface Conductance of Five Different Crops Based on 10 Years of Eddy-Covariance Measurements." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-214307.
Full textAbstract:
The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).
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Spank, Uwe, Barbara Köstner, Uta Moderow, Thomas Grünwald, and Christian Bernhofer. "Surface Conductance of Five Different Crops Based on 10 Years of Eddy-Covariance Measurements." Schweizerbart Science Publishers, 2016. https://tud.qucosa.de/id/qucosa%3A29981.
Full textAbstract:
The Penman-Monteith (PM) equation is a state-of-the-art modelling approach to simulate evapotranspiration (ET) at site and local scale. However, its practical application is often restricted by the availability and quality of required parameters. One of these parameters is the canopy conductance. Long term measurements of evapotranspiration by the eddy-covariance method provide an improved data basis to determine this parameter by inverse modelling. Because this approach may also include evaporation from the soil, not only the ‘actual’ canopy conductance but the whole surface conductance (gc) is addressed. Two full cycles of crop rotation with five different crop types (winter barley, winter rape seed, winter wheat, silage maize, and spring barley) have been continuously monitored for 10 years. These data form the basis for this study. As estimates of gc are obtained on basis of measurements, we investigated the impact of measurements uncertainties on obtained values of gc. Here, two different foci were inspected more in detail. Firstly, the effect of the energy balance closure gap (EBCG) on obtained values of gc was analysed. Secondly, the common hydrological practice to use vegetation height (hc) to determine the period of highest plant activity (i.e., times with maximum gc concerning CO2-exchange and transpiration) was critically reviewed. The results showed that hc and gc do only agree at the beginning of the growing season but increasingly differ during the rest of the growing season. Thus, the utilisation of hc as a proxy to assess maximum gc (gc,max) can lead to inaccurate estimates of gc,max which in turn can cause serious shortcomings in simulated ET. The light use efficiency (LUE) is superior to hc as a proxy to determine periods with maximum gc. Based on this proxy, crop specific estimates of gc,maxcould be determined for the first (and the second) cycle of crop rotation: winter barley, 19.2 mm s−1 (16.0 mm s−1); winter rape seed, 12.3 mm s−1 (13.1 mm s−1); winter wheat, 16.5 mm s−1 (11.2 mm s−1); silage maize, 7.4 mm s−1 (8.5 mm s−1); and spring barley, 7.0 mm s−1 (6.2 mm s−1).
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Zisheng, Xing. "A simple net ecosystem productivity model for gap filling of tower-based fluxes." Thesis, 2007. http://hdl.handle.net/1882/1053.
Full textAbstract:
In response to global climate change, many important earth-systems-oriented science
programs have been established in the past. One such program, the Fluxnet program, studies
the response of world forests and other natural ecosystems by measuring biospheric fluxes of
carbon dioxide (CO2), water vapour, and energy with eddy-covariance (EC) techniques to
assess the role of world ecosystems in offsetting increases in CO2 emissions and related
impacts on global climate. The EC methodology has its limitations particularly when
weather is inclement and during system stoppages. These limitations create non-trivial
problems by creating data gaps in the monitored data stream, diminishing the integrity of the
dataset and increasing uncertainty with data interpretation.
This Thesis deals with the development of a parsimonious, semi-empirical approach
for gap filling of net ecosystem productivity (NEP) data. The approach integrates the effects
of environmental controls on diurnal NEP. The approach, because of its limited number of
parameters, can be rapidly optimized when appropriate meteorological, site, and NEP target
values are provided. The procedure is verified by applying it to several gap-filling case
studies, including timeseries collected over balsam fir (Abies Balsamea (L.) Mill.) forests in
New Brunswick (NB), Canada and several other forests along a north-south temperaturemoisture
gradient from northern Europe to the Middle East. The evaluation showed that the
model performed relatively well for most sites; i.e., r2 ranged from 0.68-0.83 and modelling
efficiencies, from 0.89-0.97, demonstrating the possibility of applying the model to forests
outside NB. Inferior model performance was associated with sites with less than complete
input datasets.
Book chapters on the topic "Light use efficiency (LUE) model"
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Koncar, Philipp, and Denis Helic. "Employee Satisfaction in Online Reviews." In Lecture Notes in Computer Science, 152–67. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60975-7_12.
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Abstract Employee satisfaction impacts the efficiency of businesses as well as the lives of employees spending substantial amounts of their time at work. As such, employee satisfaction attracts a lot of attention from researchers. In particular, a lot of effort has been previously devoted to the question of how to positively influence employee satisfaction, for example, through granting benefits. In this paper, we start by empirically exploring a novel dataset comprising two million online employer reviews. Notably, we focus on the analysis of the influencing factors for employee satisfaction. In addition, we leverage our empirical insights to predict employee satisfaction and to assess the predictive strengths of individual factors. We train multiple prediction models and achieve accurate prediction performance (ROC AUC of best model $$=0.89$$ = 0.89 ). We find that the number of benefits received and employment status of reviewers are most predictive, while employee position has less predictive strengths for employee satisfaction. Our work complements existing studies and sheds light on the influencing factors for employee satisfaction expressed in online employer reviews. Employers may use these insights, for example, to correct for biases when assessing their reviews.
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Pelli, Afonso, Amanda Rodrigues de Oliveira, Bruna Vilarinho Gonçalves, Carlos Paulino do Santos Júnior, Eliana Mendes de Sousa Rezende, Evylin Sousa dos Santos, Fernanda Coutinho Sartori, et al. "Evaluation of the use of different lamps in light trap model for insect capture." In METHODOLOGY FOCUSED ON THE AREA OF INTERDISCIPLINARITY- V1. Seven Editora, 2023. http://dx.doi.org/10.56238/methofocusinterv1-051.
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Aware of the importance that insects have, as well as their influence, both in ecosystems and human activities, the group has always received prominence in several areas of knowledge. In order to enjoy this immense diversity, the first step is to recognize and classify them. For this, a light trap model was elaborated, using three different lights (black, cold white and warm white). The pitfall-style trap, which in addition to the lights contained a container with alcohol and detergent, was properly assembled. Insects were collected, analyzed and identified. These processes allowed analyzing the efficiency of the trap with different lamps in the capture of insects, as well as the Orders to which they belong. In the end, it was observed that the Order of highest index in the analysis was Homoptera, and that the trap whose light source was black light was the most efficient in quantitative capture, with a total of 497 insects, followed by warm cold white light, respectively.
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Ito, Akihiko, and Takehisa Oikawa. "Chapter 14 Absorption of Photosynthetically Active Radiation, Dry-matter Production, and Light-use Efficiency of Terrestrial Vegetation: A Global Model Simulation." In Elsevier Oceanography Series, 335–505. Elsevier, 2007. http://dx.doi.org/10.1016/s0422-9894(06)73014-8.
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Martínez-Caro, Eva, Juan Gabriel Cegarra-Navarro, and Marcelina Solano-Lorente. "An Extension of the Technology Acceptance Model in Hospital-in-the-Home Units." In Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care, 1191–207. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3990-4.ch062.
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The implementation of a Hospital-in-the-Home Unit (HHU) involves the application of technologies adapted to improve quality of care. The aim of this chapter is to develop a model based on the Technology Acceptance Model, which identifies key success factors for the acceptance of technology systems in HHUs. Qualitative research was carried out in the HHU of a Spanish hospital. Interviews were conducted with the HHU team, the hospital nurse manager, and the medical manager. An extended technology acceptance model is derived from the interviews. While organisational triggers such as accessibility, collaboration, confidentiality, training, and security are the main drivers for perceived usefulness and ease of use; individual processes such as unlearning and openness to address the needs of patients are the main enablers for the participation of practitioners. The results shed light on a possible way for healthcare managers to enhance their subordinates’ acceptance of technologies for HHUs.
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Egi, Yunus, and Engin Eyceyurt. "3D Point Cloud-Based Tree Canopy Visualization for a Smart Deployment of Mobile Communication Systems." In Data Visualization [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96179.
Full textAbstract:
Mobile communication is one of the most important parameters of smart cities in terms of maintaining connectivity and interaction between humans and smart systems. However, In the deployment process of Mobile Communication Systems (MCS), Radio Frequency (RF) engineers use location depended empirical Signal Strength Path Loss (SSPL) models ending up with poor signal strength and slow data connection. This is due to the fact that empirical propagation models usually are restrained by the environment and do not implement state of the art technologies, including Unmanned Aerial Vehicles (UAV), Light Detection and Ranging (LiDAR), Image Processing, and Machine Learning to increase efficiency. Terrains involving buildings, hills, trees, mountains, and human-made structures are considered irregular terrains by telecommunication engineers. Irregular terrains, specifically trees, significantly affect MCS’s efficiency because of their complex pattern resulting in erroneous signal fading via multi-path reflection and absorption. Therefore, a virtual 3D environment is required to extract the required 3D terrain pattern and elevation data from the environment. Once this data is processed in the machine learning algorithm, an adaptive propagation model can be formed and can significantly improve SSPL prediction accuracy for MCS. This chapter presents 3D point cloud visualization via sensor fusion and 2D image color classification techniques, which lead to a novel propagation model for the smart deployment of MCS. The proposed system’s main contribution is to develop an intelligent environment that eliminates limitations and minimizes related signal fading prediction errors. In addition, having better connectivity and efficiency will resolve the communication problem of smart cities. The chapter also provides a case study that significantly outperforms other empirical models with an accuracy of 95.4%.
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Favre, Liliana María. "Software Evolution, MDA and Design Pattern Components." In Advances in Computer and Electrical Engineering, 115–57. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-649-0.ch008.
Full textAbstract:
The success of MDA depends on the definition of model transformations and component libraries which make a significant impact on tools that provide support for MDA. MDA is a young approach and several technical issues are not adequately addressed. For instance, existing MDA-based CASE tools do not provide adequate support to deal with component-based reuse (CASE, 2009). In light of this, we propose a metamodeling technique to reach a high level of reusability and adaptability of components. Reusability is the ability to use software elements for constructing many different applications. An ideal software reusability tehnology should facilitate a consistent system implementation, starting from the adaptation and integration of “implementation pieces” that exist in reusable components library. Software reusability has two main purposes: to increase the reliability of software and to reduce the cost of software development. Most current approaches to object oriented reusability are based on empirical methods. However the most effective forms of reuse are generally found at more abstract levels of design (Krueger, 1992). In MDA, software reusability is difficult because it requires taking many different requirements into account, some of which are abstract and conceptual, while others, such as efficiency are concrete. A good approach for MDA reusability must reconcile models at different abstraction levels. In this chapter, we analyze how to define reusable components in a way that fits with MDA and propose a megamodel for defining MDA components. Considering the relevant role that design patterns take in software evolution we exemplify MDA components for them.
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Sivagami, Arasu, Michael Angelo Kandavalli, and Bhaskarrao Yakkala. "Design and Evaluation of an Automated Monitoring and Control System for Greenhouse Crop Production." In Next-Generation Greenhouses for Food Security. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97316.
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An embedded system integrated with sensors based on nanomaterial is proposed for closely monitoring and control microclimate parameters 24 hours a day to maximise production over the whole crop growth season by introducing greenhouse for the cultivation of plants or specific plant species. The system will also eliminate errors in human intervention to optimise production of crops. This system consists of sensors and actuators, an Analogue to Digital Converter (ADC) and a Raspberry Pi. The system will determine whether a defined threshold is passed by any climate parameter and systematically changes via the controller. The current work reduces human input through automated irrigation to optimally utilize a scarce resource, namely water. Climatic parameters for plant growth such as, moisture, humidity, temperature, water pressure in drip pipe, soil salinity etc. are monitored and optimized. Furthermore, work was extended to include GSM to control the entire farm remotely. For its success, it is very important to choose a greenhouse location. For instance, the problems are quite different when choosing an adjoining greenhouse, for instance a sunroom or greenhouse. The greenhouse location should be chosen for sunlight, proximity to power and water sources, wind, drain and freeze pockets, and the proximity of the garden and house. The intention behind accomplishment and devise of GSM based Fertigation System is to construct and evaluate the requirement of water in the yield as farming is the major resource of production which habitually depends on the water accessibility. Irrigation of water is usually done by manual method. To ease the work of the farmer GSM based automatic Fertigation (includes chemigation too) system can be implemented so that water wastage can be reduced and also the fertilizer can be added accordingly. Also the Soil Salinity can be checked and reduced if exceeds certain limit. By using GSM, only GSM command via GSM mobile can control the start and stop action of a motor that feeds the field with the water. GSM is used for controlling the entire process and the entire system backbone. It can be used from any distance to control irrigation. The results are assessed by electronic simulator PROTEUS using the desired optimised parameters, the design of this automated greenhouse system with PIC controller. As the inputs to the microcontroller and as an LCD screen record the respective outputs, the model produces a soil moisture sensor, light sensor and temperature sensor. The system performance is accurate and repeatable for measuring and controlling the four parameters that are crucial for plant growth - temperature, humidity, soil moisture and light intensity. With the reduction in electricity consumption, maintenance and complexity, and a flexible and precise environment control form for agriculture, the new system successfully cured quite a couple of defects in existing systems. Nano composite film sensors (Graphene and Graphene mixed in order to optimise the input of fertilisers for chemical composition determination. Using nano technology in agriculture enforces the firm bond between the engineer and farmer. Nano material film-based gas sensors were used to measure the presence of oxygen and CO2.using graphene nano composite sensors integrated into an embedded system, to detect the presence and levels of gases. Improve crop growth with combined red and blue light for lighting under the leavened and solar-powered LED lighting modules. This was achieved by graph/solar cells. The light was measured at the photosynthesis flux (PPFD) of 165 μmol m-2 s-1 by 10 cm of its LED module. LED lights were provided between 4:00 a.m. and 4:00 p.m. in the daytime treatments and night treatments from 10 to 10 hours. The use of the nighttime interlumination of LEDs was also economical than the interlumination of charts. Thus, nightlighting LEDs can effectively improve plant growth and output with less energy than the summer and winter times. Solar panels are best functioning during times of strong sunlight today, but begin to wan when they become too hot and cloudy. By allowing Solar Panels to produce electricity during harsh weather conditions and increase efficiency, a breakthrough in graphene-based solar panels can change everything. Ultimately with a fully autonomous system, agricultural productivity and efficiency, the length of the growing season, energy consumption and water consumption were recorded and monitored by exporting the data over GSM environment. With the steady decrease in the cost of high-performing hardware and software, the increased acceptance of self-employed farming systems, and the emerging agricultural system industry, the results will be reliable control systems covering various aspects of quality and production quantity.
Conference papers on the topic "Light use efficiency (LUE) model"
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Boschetti, Mirco, Emanuela Mauri, Chiara Gadda, Lorenzo Busetto, Roberto Confalonieri, Stefano Bocchi, and Pietro A. Brivio. "Monitoring paddy rice crops through remote sensing: productivity estimation by light use efficiency model." In Remote Sensing, edited by Manfred Owe, Guido D'Urso, Ben T. Gouweleeuw, and Anne M. Jochum. SPIE, 2004. http://dx.doi.org/10.1117/12.568106.
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Li, Li, Xiaozhou Xin, Yanhua Gao, Hailong Zhang, Yongming Du, Yong Tang, Bo Zhong, Jianguang Wen, Baocheng DOU, and Qinhuo Liu. "Gpp Estimation in the Heihe River Basin Based on a Light Use Efficiency Model." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518455.
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Du, Xin, Jihua Meng, Igor Savin, and Qiangzi Li. "Wheat yield estimation in Russia with modis time-series data based on light use efficiency model." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723418.
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Zhang, Qian, Weimin Ju, Jing M. Chen, and Fengting Yang. "Application of the photochemical reflectance index to track light use efficiency with a two-leaf model." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730397.
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Chen, Danyan, Pan Gao, Zhisheng Wang, Junhua Zhang, Bin Li, Jin Hu, and Haihui Zhang. "Method for obtaining CO2 limit point of Light-use efficiency model based on U-chord curvature." In 2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2020. http://dx.doi.org/10.13031/aim.202000937.
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Zhang, Helin, Rui Sun, Zhiqiang Xiao, Juanmin Wang, and Mengjia Wang. "Global 500M Spatial Resolution Gross and Net Primary Productivity Products Based on an Improved Light Use Efficiency Model from 2000-2019." In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9884634.
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Lading, Lars, and John Earnshaw. "Surface Light Scattering: Integrated Technology and Signal Processing." In Photon Correlation and Scattering. Washington, D.C.: Optica Publishing Group, 1996. http://dx.doi.org/10.1364/pcs.1996.wb.2.
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Surface light scattering has matured to the extent that it is now possible to envisage the possibility of applying the technique in more demanding environments like microgravity or industrial process monitoring. Such situations will require more compact and robust system designs than the ones that till now have been used in laboratory studies. The generic elements of a system are identified and their impact on system performance is given based on the model presented in.1 We note that proper use of a grating provides a calibration that is independent of the wavelength. This facilitates the use of cheap unstabilised semiconductor lasers2, but the optics may be rather delicate. An implementation with holographic optical elements gives a mechanically very simple and robust system (Fig. 1)3. A concept based on fully integrated optics is obtained by combining a 2D waveguide with diffractive structures for coupling light out of and into the optical “chip”. The waveguide would be combined with the lower hologram. Laser and detectors could be imbedded in the waveguide. Such a system implies a number of conflicting requirements of the integrated optics. A potential solution based on silicon and a rare earth laser is presented. The complexity of the system may be further reduced by the application of intracavity diffractive structures (Fig. 2). By doing this, we essentially eliminate the need for the very high diffraction efficiency required with external diffractive structures and the laser itself may also be used as a detector. However, the simple configuration requires a spacing to the surface that is fixed within a fraction of the optical wavelength.
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Bharath, Anand Nageswaran, Nitya Kalva, Rolf D. Reitz, and Christopher J. Rutland. "Use of Early Exhaust Valve Opening to Improve Combustion Efficiency and Catalyst Effectiveness in a Multi-Cylinder RCCI Engine System: A Simulation Study." In ASME 2014 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icef2014-5534.
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Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) can result in significant improvements of fuel economy and emissions reduction. However, they can produce significant carbon monoxide and unburnt hydrocarbon emissions at low load operating conditions due to poor combustion efficiencies at these operating points, which is a consequence of the low combustion temperatures that cause the oxidation rates of these species to slow down. The exhaust gas temperature is also not high enough at low loads for effective performance of turbocharger systems and diesel oxidation catalysts (DOC). The DOC is extremely sensitive to exhaust gas temperature changes and lights off only when a certain temperature is reached, depending on the catalyst specifications. Uncooled EGR can increase combustion temperatures, thereby improving combustion efficiency, but high EGR concentrations of 50% or more are required, thereby increasing pumping work and reducing volumetric efficiency. However, with early exhaust valve opening, the exhaust gas temperature can be much higher, allowing lower EGR flow rates, and enabling activation of the DOC for more effective oxidization of unburnt hydrocarbons and CO in the exhaust. In this paper, a multi-cylinder engine system simulation of RCCI at low load operation with early exhaust valve opening is presented, along with consideration of the exhaust aftertreatment system. The combustion process is modeled using the 3D CFD code, KIVA, and the heat release rates obtained from this combustion are used in a GT-Power model of a turbocharged, multi-cylinder light-duty RCCI engine for a full system simulation. The post-turbine exhaust gas is fed into GT-Power’s aftertreatment model of the engine’s DOC to determine the catalyst response. It is confirmed that opening the exhaust valve earlier increases the exhaust gas temperature, and hence lower EGR flow rates are needed to improve combustion efficiency. It was also found that exhaust temperatures of around 457 K are required to light off the catalyst and oxidize the unburnt hydrocarbons and CO effectively. Performance of the DOC was drastically improved and higher amounts of unburnt hydrocarbons were oxidized by increasing the exhaust gas temperature.
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Lacin, F., and M. Zhuang. "Optimum Use of Noble Metal Catalysts in Catalytic Converters." In ASME 2002 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/icef2002-534.
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The catalytic converter is an important device for the emission control from spark-ignition engines. Several concurrent physical/chemical processes such as convective heat transfer, gas phase chemical reactions, surface reactions, flow oscillations, water vapor condensation and diffusion mechanisms add complexity to modeling of flows inside catalytic converters. Under cold-start conditions, the fact that catalytic converters do not become operational during the initial operation allows a significant fraction of the overall pollutants to be emitted. In the present study, these complex transient phenomena have been examined using a previously validated numerical model.1 The numerical results suggest new material-dependent designs to improve both the transient conversion characteristics and the steady state conversion efficiency of catalytic converters. Moreover, from our model calculations, we have observed that for a given amount of the noble metal catalysts the light-off time and the monolith temperature are greatly affected by the noble-metal distribution along the honeycomb walls of a monolith. The results of the numerical simulations indicate that the light-off time is shortened by approximately 35% for CO, H2 and C3H6 when replacing a traditional homogeneous noble metal distribution by a simple, step-function distribution.2 The emissions of CO, H2 and C3H6 from the exhaust gas are, therefore, reduced without increasing the cost of noble metal catalysts used in converters. In order to avoid further deterioration of catalysts due to the thermal effects, an optimum noble metal distribution needs to be investigated with the understanding that the optimum noble metal distribution proposed has to be practical for the manufacturing. Since the main source of the exhaust emissions is generated during the cold-start period of the converter operation, the reduction of emissions shown in our model calculations is quite substantial.
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Harry Watson, Harry Watson. "Range Capability as a Significant Variable in Light Duty EVs Life Cycle CO2." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-epv-040.
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"It was recognised by ‘The Club of Rome’ in 1948 that the earth’s resources were limited and by 1971 in the book ‘Fundamentals of Exhaust Emissions’ I concluded that we should also have concern for CO2 levels in the air and consequent global warming caused by transport emissions. So what is the optimum strategy for minimizing energy use and emissions, recognizing that the car is the prime source of personal space for mobility, and that many governments support a focus as EVs as the solution for the future? To demonstrate how range capability has a significant influence on the optimum life for two classes of EVs and to identify the inter relationship with vehicle life. From this to forecast the optimum service life (before scrapping including recycling) against a back drop of steadily improving EV and battery manufacturing energy and efficiency, Using the best available energy production and usage data, life cycle analysis (more than ‘well-to-wheel’ as the energy content and manufacture of consumables and recycling/reuse is included) is performed for electric vehicles accounting for the change in vehicle use with age in vehicle fleets, in which new vehicles replace older, scrapped ones in the market with improvements in energy efficiency (and CO2 emissions). Depending on the vehicle size and configuration, the optimum vehicle life ranges from 17 years to more than thirty. The greater the installed battery kWh and hence range capability the longer is the optimum service life. As the energy efficiency trend for new vehicles entering the market reduces, as it must according to the law of diminishing returns, vehicles need to remain in use for longer to amortize the embedded energy in manufacturing which will also continue to improve. The analysis is only as reliable as the data. However the sensitivity analysis allows the results to remain useful as the user can adjust the scenario according to updated information. Moreover sensitivity analysis allows the reader to apply the results for regional variables such as the proportion of renewable energy in electricity generation and as a consequence of EVs reduced annual travel compared with conventional and hybrid light duty vehicles.. The application of the most recent input data is also novel. Finally, the author is not aware of analyses of this type that recognise reducing annual travel as vehicles age, rather constant km of travel per year has previously been assumed throughout the vehicle life. On the basis of the median results from the projections, short to moderate range EVs offer the path to minimizing CO2 emissions which conflicts with the general consumer desire for reduced ‘range anxiety’ and thus frequency of recharging. EVs life cycle emissions will be considerably worse than those from hybrid vehicles which use the least long term (several model change overs) energy and produce correspondingly low CO2. The sensitivity analysis allows for conclusions to be drawn about many alternative scenarios."
Reports on the topic "Light use efficiency (LUE) model"
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Christopher, David A., and Avihai Danon. Plant Adaptation to Light Stress: Genetic Regulatory Mechanisms. United States Department of Agriculture, May 2004. http://dx.doi.org/10.32747/2004.7586534.bard.
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Original Objectives: 1. Purify and biochemically characterize RB60 orthologs in higher plant chloroplasts; 2. Clone the gene(s) encoding plant RB60 orthologs and determine their structure and expression; 3. Manipulate the expression of RB60; 4. Assay the effects of altered RB60 expression on thylakoid biogenesis and photosynthetic function in plants exposed to different light conditions. In addition, we also examined the gene structure and expression of RB60 orthologs in the non-vascular plant, Physcomitrella patens and cloned the poly(A)-binding protein orthologue (43 kDa RB47-like protein). This protein is believed to a partner that interacts with RB60 to bind to the psbA5' UTR. Thus, to obtain a comprehensive view of RB60 function requires analysis of its biochemical partners such as RB43. Background & Achievements: High levels of sunlight reduce photosynthesis in plants by damaging the photo system II reaction center (PSII) subunits, such as D1 (encoded by the chloroplast tpsbAgene). When the rate of D1 synthesis is less than the rate of photo damage, photo inhibition occurs and plant growth is decreased. Plants use light-activated translation and enhanced psbAmRNA stability to maintain D1 synthesis and replace the photo damaged 01. Despite the importance to photosynthetic capacity, these mechanisms are poorly understood in plants. One intriguing model derived from the algal chloroplast system, Chlamydomonas, implicates the role of three proteins (RB60, RB47, RB38) that bind to the psbAmRNA 5' untranslated leader (5' UTR) in the light to activate translation or enhance mRNA stability. RB60 is the key enzyme, protein D1sulfide isomerase (Pill), that regulates the psbA-RN :Binding proteins (RB's) by way of light-mediated redox potentials generated by the photosystems. However, proteins with these functions have not been described from higher plants. We provided compelling evidence for the existence of RB60, RB47 and RB38 orthologs in the vascular plant, Arabidopsis. Using gel mobility shift, Rnase protection and UV-crosslinking assays, we have shown that a dithiol redox mechanism which resembles a Pill (RB60) activity regulates the interaction of 43- and 30-kDa proteins with a thermolabile stem-loop in the 5' UTR of the psbAmRNA from Arabidopsis. We discovered, in Arabidopsis, the PD1 gene family consists of II members that differ in polypeptide length from 361 to 566 amino acids, presence of signal peptides, KDEL motifs, and the number and positions of thioredoxin domains. PD1's catalyze the reversible formation an disomerization of disulfide bonds necessary for the proper folding, assembly, activity, and secretion of numerous enzymes and structural proteins. PD1's have also evolved novel cellular redox functions, as single enzymes and as subunits of protein complexes in organelles. We provide evidence that at least one Pill is localized to the chloroplast. We have used PDI-specific polyclonal and monoclonal antisera to characterize the PD1 (55 kDa) in the chloroplast that is unevenly distributed between the stroma and pellet (containing membranes, DNA, polysomes, starch), being three-fold more abundant in the pellet phase. PD1-55 levels increase with light intensity and it assembles into a high molecular weight complex of ~230 kDa as determined on native blue gels. In vitro translation of all 11 different Pill's followed by microsomal membrane processing reactions were used to differentiate among PD1's localized in the endoplasmic reticulum or other organelles. These results will provide.1e insights into redox regulatory mechanisms involved in adaptation of the photosynthetic apparatus to light stress. Elucidating the genetic mechanisms and factors regulating chloroplast photosynthetic genes is important for developing strategies to improve photosynthetic efficiency, crop productivity and adaptation to high light environments.
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.
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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.