Automatic Dynamic Aircraft Modeler (ADAM) for the Computer Program NASTRAN

NASA Technical Reports Server (NTRS)

Griffis, H.

1985-01-01

Large general purpose finite element programs require users to develop large quantities of input data. General purpose pre-processors are used to decrease the effort required to develop structural models. Further reduction of effort can be achieved by specific application pre-processors. Automatic Dynamic Aircraft Modeler (ADAM) is one such application specific pre-processor. General purpose pre-processors use points, lines and surfaces to describe geometric shapes. Specifying that ADAM is used only for aircraft structures allows generic structural sections, wing boxes and bodies, to be pre-defined. Hence with only gross dimensions, thicknesses, material properties and pre-defined boundary conditions a complete model of an aircraft can be created.

Chlorophyll Fluorescence Is a Better Proxy for Sunlit Leaf Than Total Canopy Photosynthesis

NASA Astrophysics Data System (ADS)

Chen, J. M.; Wang, Z.; Zhang, F.; Mo, G.

2015-12-01

Chlorophyll fluorescence (CF) results from non-photochemical quenching during plant photosynthesis under excessive radiation. We explore the relationship between gross primary productivity (GPP) and CF using a process ecosystem model, which separates a vegetation canopy into sunlit and shaded leaf groups and simulates the total canopy GPP as the sum of sunlit and shaded leaf GPP. Using GOME-2 and GOSAT data acquired in 2010 over the global land surface, we found that measured CF signals gridded in 1 degree resolution are well correlated with simulated total GPP and its sunlit and shaded components, but the correlation coefficients (R) are largest for the sunlit GPP and smallest for shaded GPP. The seasonal R2 values vary from 0.57 to 0.74, 0.58 to 0.71, and 0.48 to 0.56 for sunlit, total and shaded GPP, respectively. The significance levels for these correlations are all greater than p<0.01. Averaged over the globe, the total simulated shaded GPP is 39% of the total GPP. Theoretically, CF from vegetation comes mostly from sunlit leaves. The significant correlation between measured canopy-level CF and the shaded GPP is likely due to the correlation between shaded and sunlit GPP as both increase with leaf area index. Our simulation confirms the validity of using canopy-level CF measurements to assess the total GPP as the first approximation, although these measurements are a consistently better indicator of sunlit GPP than total GPP. In previous studies, the R2 values for the correlation between CF and total GPP were found to range from 0.76 to 0.88, 0.56 to 0.78, and 0.57 to 0.77 for MPI-BGC, MODIS and CASA model results, respectively. These values are similar or larger than those for sunlit GPP simulated in our study, but are considerably larger than those for total GPP in our study because the correlation for total GPP is contaminated by the inclusion of shaded GPP. All these three models use canopy total light use efficiency without considering the differences between sunlit and shaded leaves, and therefore they mostly capture spatio-temporal variations in sunlit GPP. We therefore argue that solar-induced CF measured from vegetation is a better proxy of sunlit GPP than the total GPP, and the use of CF data for assessing the terrestrial carbon cycle can be improved when sunlit and shaded GPP are modelled separately.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Estimating Per-Pixel GPP of the Contiguous USA Directly from MODIS EVI Data

NASA Astrophysics Data System (ADS)

Rahman, A. F.; Sims, D. A.; El-Masri, B. Z.; Cordova, V. D.

2005-12-01

We estimated gross primary production (GPP) of the contiguous USA using enhanced vegetation index (EVI) data from NASA's moderate resolution imaging spectroradiometer (MODIS). Based on recently published values of correlation coefficients between EVI and GPP of North American vegetations, we derived GPP maps of the contiguous USA for 2001-2004, which included one La Nina year and three moderately El Nino years. The product was a truly per-pixel GPP estimate (named E-GPP), in contrast to the pseudo-continuous MOD17, the standard MODIS GPP product. We compared E-GPP with fine-scale experimental GPP data and MOD17 estimates from three Bigfoot experimental sites, and also with MOD17 estimates from the whole contiguous USA for the above-mentioned four years. For each of the '7 by 7' km Bigfoot experimental sites, E-GPP was able to track the primary production activity during the green-up period while MOD17 failed to do so. The E-GPP estimates during peak production season were similar to those from Bigfoot and MOD17 for most vegetation types except for the deciduous types, where it was lower. Annual E-GPP of the Bigfoot sites compared well with Bigfoot experimental GPP (r = 0.71) and MOD17 (r = 0.78). But for the contiguous USA for 2001-2004, annual E-GPP showed disagreement with MOD17 in both magnitude and seasonal trends for deciduous forests and grass lands. In this study we explored the reasons for this mismatch between E-GPP and MOD17 and also analyzed the uncertainties in E-GPP across multiple spatial scales. Our results show that the E-GPP, based on a simple regression model, can work as a robust alternative to MOD17 for large-area annual GPP estimation. The relative advantages of E-GPP are that it is truly per-pixel, solely dependent on remotely sensed data that is routinely available from NASA, easy to compute and has the potential of being used as an operational product.

The genetic background of generalized pustular psoriasis: IL36RN mutations and CARD14 gain-of-function variants.

PubMed

Sugiura, Kazumitsu

2014-06-01

Generalized pustular psoriasis (GPP) is often present in patients with existing or prior psoriasis vulgaris (PV; "GPP with PV"). However, cases of GPP have been known to arise without a history of PV ("GPP alone"). There has long been debate over whether GPP alone and GPP with PV are distinct subtypes that are etiologically different from each other. We recently reported that the majority of GPP alone cases is caused by recessive mutations of IL36RN. In contrast, only a few exceptional cases of GPP with PV were found to have recessive IL36RN mutations. Very recently, we also reported that CARD14 p.Asp176His, a gain-of-function variant, is a predisposing factor for GPP with PV; in contrast, the variant is not associated with GPP alone in the Japanese population. These results suggest that GPP alone is genetically different from GPP with PV. IL36RN mutations are also found in some patients with severe acute generalized exanthematous pustulosis, palmar-plantar pustulosis, and acrodermatitis continua of hallopeau. CARD14 mutations and variants are causal or disease susceptibility factors of PV, GPP, or pityriasis rubra pilaris, depending on the mutation or variant position of CARD14. It is clinically important to analyze IL36RN mutations in patients with sterile pustulosis. For example, identifying recessive IL36RN mutations leads to early diagnosis of GPP, even at the first episode of pustulosis. In addition, individuals with IL36RN mutations are very susceptible to GPP or GPP-related generalized pustulosis induced by drugs (e.g., amoxicillin), infections, pregnancy, or menstruation. Copyright © 2014 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Evaluation and comparison of gross primary production estimates for the Northern Great Plains grasslands

USGS Publications Warehouse

Zhang, Li; Wylie, Bruce K.; Loveland, Thomas R.; Fosnight, Eugene A.; Tieszen, Larry L.; Ji, Lei; Gilmanov, Tagir

2007-01-01

Two spatially-explicit estimates of gross primary production (GPP) are available for the Northern Great Plains. An empirical piecewise regression (PWR) GPP model was developed from flux tower measurements to map carbon flux across the region. The Moderate Resolution Imaging Spectrometer (MODIS) GPP model is a process-based model that uses flux tower data to calibrate its parameters. Verification and comparison of the regional PWR GPP and the global MODIS GPP are important for the modeling of grassland carbon flux. This study compared GPP estimates from PWR and MODIS models with five towers in the grasslands. Among them, PWR GPP and MODIS GPP showed a good agreement with tower-based GPP at three towers. The global MODIS GPP, however, did not agree well with tower-based GPP at two other towers, probably because of the insensitivity of MODIS model to regional ecosystem and climate change and extreme soil moisture conditions. Cross-validation indicated that the PWR model is relatively robust for predicting regional grassland GPP. However, the PWR model should include a wide variety of flux tower data as the training data sets to obtain more accurate results.In addition, GPP maps based on the PWR and MODIS models were compared for the entire region. In the northwest and south, PWR GPP was much higher than MODIS GPP. These areas were characterized by the higher water holding capacity with a lower proportion of C4 grasses in the northwest and a higher proportion of C4 grasses in the south. In the central and southeastern regions, PWR GPP was much lower than MODIS GPP under complicated conditions with generally mixed C3/C4 grasses. The analysis indicated that the global MODIS GPP model has some limitations on detecting moisture stress, which may have been caused by the facts that C3 and C4 grasses are not distinguished, water stress is driven by vapor pressure deficit (VPD) from coarse meteorological data, and MODIS land cover data are unable to differentiate the sub-pixel cropland components.

Novel (p)ppGpp Binding and Metabolizing Proteins of Escherichia coli.

PubMed

Zhang, Yong; Zborníková, Eva; Rejman, Dominik; Gerdes, Kenn

2018-03-06

The alarmone (p)ppGpp plays pivotal roles in basic bacterial stress responses by increasing tolerance of various nutritional limitations and chemical insults, including antibiotics. Despite intensive studies since (p)ppGpp was discovered over 4 decades ago, (p)ppGpp binding proteins have not been systematically identified in Escherichia coli We applied DRaCALA ( d ifferential ra dial c apillary a ction of l igand a ssay) to identify (p)ppGpp-protein interactions. We discovered 12 new (p)ppGpp targets in E. coli that, based on their physiological functions, could be classified into four major groups, involved in (i) purine nucleotide homeostasis (YgdH), (ii) ribosome biogenesis and translation (RsgA, Era, HflX, and LepA), (iii) maturation of dehydrogenases (HypB), and (iv) metabolism of (p)ppGpp (MutT, NudG, TrmE, NadR, PhoA, and UshA). We present a comprehensive and comparative biochemical and physiological characterization of these novel (p)ppGpp targets together with a comparative analysis of relevant, known (p)ppGpp binding proteins. Via this, primary targets of (p)ppGpp in E. coli are identified. The GTP salvage biosynthesis pathway and ribosome biogenesis and translation are confirmed as targets of (p)ppGpp that are highly conserved between E. coli and Firmicutes In addition, an alternative (p)ppGpp degradative pathway, involving NudG and MutT, was uncovered. This report thus significantly expands the known cohort of (p)ppGpp targets in E. coli IMPORTANCE Antibiotic resistance and tolerance exhibited by pathogenic bacteria have resulted in a global public health crisis. Remarkably, almost all bacterial pathogens require the alarmone (p)ppGpp to be virulent. Thus, (p)ppGpp not only induces tolerance of nutritional limitations and chemical insults, including antibiotics, but is also often required for induction of virulence genes. However, understanding of the molecular targets of (p)ppGpp and the mechanisms by which (p)ppGpp influences bacterial physiology is incomplete. In this study, a systematic approach was used to uncover novel targets of (p)ppGpp in E. coli , the best-studied model bacterium. Comprehensive comparative studies of the targets revealed conserved target pathways of (p)ppGpp in both Gram-positive and -negative bacteria and novel targets of (p)ppGpp, including an alternative degradative pathway of (p)ppGpp. Thus, our discoveries may help in understanding of how (p)ppGpp increases the stress resilience and multidrug tolerance not only of the model organism E. coli but also of the pathogenic organisms in which these targets are conserved. Copyright © 2018 Zhang et al.

How much do different global GPP products agree in distribution and magnitude of GPP extremes?

NASA Astrophysics Data System (ADS)

Kim, S.; Ryu, Y.; Jiang, C.

2016-12-01

To evaluate uncertainty of global Gross Primary Productivity (GPP) extremes, we compare three global GPP datasets derived from different data processing methods (e.g. MPI-BGC: machine-learning, MODIS GPP (MOD17): semi-empirical, Breathing Earth System Simulator (BESS): process based). We preprocess the datasets following the method from Zscheischler et al., (2012) to detect GPP extremes which occur in less than 1% of the number of whole pixels, and to identify 3D-connected spatiotemporal GPP extremes. We firstly analyze global patterns and the magnitude of GPP extremes with MPI-BGC, MOD17, and BESS over 2001-2011. For consistent analysis in the three products, spatial and temporal resolution were set at 50 km and a monthly scale, respectively. Our results indicated that the global patterns of GPP extremes derived from MPI-BGC and BESS agreed with each other by showing hotspots in Northeastern Brazil and Eastern Texas. However, the extreme events detected from MOD17 were concentrated in tropical forests (e.g. Southeast Asia and South America). The amount of GPP reduction caused by climate extremes considerably differed across the products. For example, Russian heatwave in 2010 led to 100 Tg C uncertainty (198.7 Tg C in MPI-BGC, 305.6 Tg C in MOD17, and 237.8 Tg C in BESS). Moreover, the duration of extreme events differ among the three GPP datasets for the Russian heatwave (MPI-BGC: May-Sep, MOD17: Jun-Aug, and BESS: May-Aug). To test whether Sun induced Fluorescence (SiF), a proxy of GPP, can capture GPP extremes, we investigate global distribution of GPP extreme events in BESS, MOD17 and GOME-2 SiF between 2008 and 2014 when SiF data is available. We found that extreme GPP events in GOME-2 SiF and MOD17 appear in tropical forests whereas those in BESS emerged in Northeastern Brazil and Eastern Texas. The GPP extremes by severe 2011 US drought were detected by BESS and MODIS, but not by SiF. Our findings highlight that different GPP datasets could result in varying duration and intensity of GPP extremes and distribution of hotspots, and this study could contribute to quantifying uncertainties in GPP extremes.

[Extraction of temperate vegetation phenology thresholds in North America based on flux tower observation data].

PubMed

Zhao, Jing-Jing; Liu, Liang-Yun

2013-02-01

Flux tower method can effectively monitor the vegetation seasonal and phenological variation processes. At present, the differences in the detection and quantitative evaluation of various phenology extraction methods were not well validated and quantified. Based on the gross primary productivity (GPP) and net ecosystem productivity (NEP) data of temperate forests from 9 forest FLUXNET sites in North America, and by using the start dates (SOS) and end dates (EOS) of the temperate forest growth seasons extracted by different phenology threshold extraction methods, in combining with the forest ecosystem carbon source/sink functions, this paper analyzed the effects of different threshold standards on the extraction results of the vegetations phenology. The results showed that the effects of different threshold standards on the stability of the extracted results of deciduous broadleaved forest (DBF) phenology were smaller than those on the stability of the extracted results of evergreen needleleaved forest (ENF) phenology. Among the extracted absolute and relative thresholds of the forests GPP, the extracted threshold of the DBF daily GPP= 2 g C.m-2.d-1 had the best agreement with the DBF daily GPP = 20% maximum GPP (GPPmax) , the phenological metrics with a threshold of daily GPP = 4 g C.m-2.d-1 was close to that between daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, and the start date of ecosystem carbon sink function was close to the SOS metrics between daily GPP = 4 g C.m-2.d-1 and daily GPP= 20% GPPmax. For ENF, the phenological metrics with a threshold of daily GPP = 2 g C.m-2.d-1 and daily GPP = 4 g C.m-2.d-1 had the best agreement with the daily GPP = 20% GPPmax and daily GPP = 50% GPPmax, respectively, and the start date of the ecosystem carbon sink function was close to the SOS metrics between daily GPP = 2 g C.m-2.d-1 and daily GPP= 10% GPPmax.

Regional contribution to variability and trends of global gross primary productivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less

Regional contribution to variability and trends of global gross primary productivity

NASA Astrophysics Data System (ADS)

Chen, Min; Rafique, Rashid; Asrar, Ghassem R.; Bond-Lamberty, Ben; Ciais, Philippe; Zhao, Fang; Reyer, Christopher P. O.; Ostberg, Sebastian; Chang, Jinfeng; Ito, Akihiko; Yang, Jia; Zeng, Ning; Kalnay, Eugenia; West, Tristram; Leng, Guoyong; Francois, Louis; Munhoven, Guy; Henrot, Alexandra; Tian, Hanqin; Pan, Shufen; Nishina, Kazuya; Viovy, Nicolas; Morfopoulos, Catherine; Betts, Richard; Schaphoff, Sibyll; Steinkamp, Jörg; Hickler, Thomas

2017-10-01

Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr-1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products

NASA Astrophysics Data System (ADS)

Martínez, B.; Sanchez-Ruiz, S.; Gilabert, M. A.; Moreno, A.; Campos-Taberner, M.; García-Haro, F. J.; Trigo, I. F.; Aurela, M.; Brümmer, C.; Carrara, A.; De Ligne, A.; Gianelle, D.; Grünwald, T.; Limousin, J. M.; Lohila, A.; Mammarella, I.; Sottocornola, M.; Steinbrecher, R.; Tagesson, T.

2018-03-01

The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m-2 day-1; MBE = -0.63 g m-2 day-1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m-2 day-1) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m-2 day-1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to -3.0 g m-2 day-1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.

Differential binding of ppGpp and pppGpp to E. coli RNA polymerase: photo-labeling and mass spectral studies.

PubMed

Syal, Kirtimaan; Chatterji, Dipankar

2015-12-01

(p)ppGpp, a secondary messenger, is induced under stress and shows pleiotropic response. It binds to RNA polymerase and regulates transcription in Escherichia coli. More than 25 years have passed since the first discovery was made on the direct interaction of ppGpp with E. coli RNA polymerase. Several lines of evidence suggest different modes of ppGpp binding to the enzyme. Earlier cross-linking experiments suggested that the β-subunit of RNA polymerase is the preferred site for ppGpp, whereas recent crystallographic studies pinpoint the interface of β'/ω-subunits as the site of action. With an aim to validate the binding domain and to follow whether tetra- and pentaphosphate guanosines have different location on RNA polymerase, this work was initiated. RNA polymerase was photo-labeled with 8-azido-ppGpp/8-azido-pppGpp, and the product was digested with trypsin and subjected to mass spectrometry analysis. We observed three new peptides in the trypsin digest of the RNA polymerase labeled with 8-azido-ppGpp, of which two peptides correspond to the same pocket on β'-subunit as predicted by X-ray structural analysis, whereas the third peptide was mapped on the β-subunit. In the case of 8-azido-pppGpp-labeled RNA polymerase, we have found only one cross-linked peptide from the β'-subunit. However, we were unable to identify any binding site of pppGpp on the β-subunit. Interestingly, we observed that pppGpp at high concentration competes out ppGpp bound to RNA polymerase more efficiently, whereas ppGpp cannot titrate out pppGpp. The competition between tetraphosphate guanosine and pentaphosphate guanosine for E. coli RNA polymerase was followed by gel-based assay as well as by a new method known as DRaCALA assay. © 2015 The Molecular Biology Society of Japan and Wiley Publishing Asia Pty Ltd.

Canopy and physiological controls of GPP during drought and heat wave

NASA Astrophysics Data System (ADS)

Zhang, Yao; Xiao, Xiangming; Zhou, Sha; Ciais, Philippe; McCarthy, Heather; Luo, Yiqi

2016-04-01

Vegetation indices (VIs) derived from satellite reflectance measurements are often used as proxies of canopy activity to evaluate the impacts of drought and heat wave on gross primary production (GPP) through production efficiency models. However, GPP is also regulated by physiological processes that cannot be directly detected using reflectance measurements. This study analyzes the co-limitation of canopy and plant physiology (represented by VIs and climate anomalies, respectively) on GPP during the 2003 European summer drought and heat wave for 15 Euroflux sites. During the entire drought period, spatial pattern of GPP anomalies can be quantified by relative changes in VIs. We also find that GPP sensitivity to relative canopy changes is higher for nonforest ecosystems (1.81 ± 0.32%GPP/%enhanced vegetation index), while GPP sensitivity to physiological changes is higher for forest ecosystems (-0.18 ± 0.05 g C m-2 d-1/hPa). A conceptual model is further built to better illustrate the canopy and physiological controls on GPP during drought periods.

Motivating green public procurement in China: an individual level perspective.

PubMed

Zhu, Qinghua; Geng, Yong; Sarkis, Joseph

2013-09-15

Green public procurement (GPP) practices have been recognized as an effective policy tool for sustainable production and consumption. However, GPP practices adoption, especially in developing countries, is still an issue. Seeking to help understand these adoption issues, we develop a conceptual model which hypothesizes moderation effects of GPP knowledge on the relationships between GPP drivers and practices. Using primary data collected from 193 Chinese government officials, we find that regulations, rewards & incentive gains, and stakeholders exert pressure to motivate adoption of GPP practices. Knowledge of GPP regulations, responsibilities and experiences in developed countries is found to be limited. The study also found that voluntary regulations may actually be demotivating GPP practices. This study contributes to further theoretical and practical understanding of GPP practices. The findings can be helpful for policy makers, especially those in developing countries, to establish promotion and diffusion mechanisms for GPP practices as an important sustainable development tool. Copyright © 2013 Elsevier Ltd. All rights reserved.

Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

NASA Astrophysics Data System (ADS)

Ma, M., II; Yuan, W.; Dong, J.; Zhang, F.; Cai, W.; Li, H.

2017-12-01

Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from twelve eddy covariance (EC) sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. The EC-LUE model explained 85.4% of the daily observed GPP variations through all of the twelve EC sites, and characterized very well the seasonal changes of GPP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature TA increase had a greater influence than solar radiation and PREC changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014.

PubMed

Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin

2018-10-15

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2  > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.

Cytosolic ppGpp accumulation induces retarded plant growth and development.

PubMed

Ihara, Yuta; Masuda, Shinji

2016-01-01

In bacteria a second messenger, guanosine 5'-diphosphate 3'-diphosphate (ppGpp), synthesized upon nutrient starvation, controls many gene expressions and enzyme activities, which is necessary for growth under changeable environments. Recent studies have shown that ppGpp synthase and hydrolase are also conserved in eukaryotes, although their functions are not well understood. We recently showed that ppGpp-overaccumulation in Arabidopsis chloroplasts results in robust growth under nutrient-limited conditions, demonstrating that the bacterial-like stringent response at least functions in plastids. To test if ppGpp also functions in the cytosol, we constructed the transgenic Arabidopsis expressing Bacillus subtilis ppGpp synthase gene yjbM. Upon induction of the gene, the mutant synthesizes ∼10-20-fold higher levels of ppGpp, and its fresh weight was reduced to ˜80% that of the wild type. These results indicate that cytosolic ppGpp negatively regulates plant growth and development.

Temporal variability of the NPP-GPP ratio at seasonal and interannual time scales in a temperate beech forest

NASA Astrophysics Data System (ADS)

Campioli, M.; Gielen, B.; Göckede, M.; Papale, D.; Bouriaud, O.; Granier, A.

2011-09-01

The allocation of carbon (C) taken up by the tree canopy for respiration and production of tree organs with different construction and maintenance costs, life span and decomposition rate, crucially affects the residence time of C in forests and their C cycling rate. The carbon-use efficiency, or ratio between net primary production (NPP) and gross primary production (GPP), represents a convenient way to analyse the C allocation at the stand level. In this study, we extend the current knowledge on the NPP-GPP ratio in forests by assessing the temporal variability of the NPP-GPP ratio at interannual (for 8 years) and seasonal (for 1 year) scales for a young temperate beech stand, reporting dynamics for both leaves and woody organs, in particular stems. NPP was determined with biometric methods/litter traps, whereas the GPP was estimated via the eddy covariance micrometeorological technique. The interannual variability of the proportion of C allocated to leaf NPP, wood NPP and leaf plus wood NPP (on average 11% yr-1, 29% yr-1 and 39% yr-1, respectively) was significant among years with up to 12% yr-1 variation in NPP-GPP ratio. Studies focusing on the comparison of NPP-GPP ratio among forests and models using fixed allocation schemes should take into account the possibility of such relevant interannual variability. Multiple linear regressions indicated that the NPP-GPP ratio of leaves and wood significantly correlated with environmental conditions. Previous year drought and air temperature explained about half of the NPP-GPP variability of leaves and wood, respectively, whereas the NPP-GPP ratio was not decreased by severe drought, with large NPP-GPP ratio on 2003 due mainly to low GPP. During the period between early May and mid June, the majority of GPP was allocated to leaf and stem NPP, whereas these sinks were of little importance later on. Improved estimation of seasonal GPP and of the contribution of previous-year reserves to stem growth, as well as reduction of data uncertainty, will be of relevance to increase the accuracy of the seasonal assessment of the NPP-GPP ratio in forests.

Molecular mechanism and evolution of guanylate kinase regulation by (p)ppGpp

DOE PAGES

Liu, Kuanqing; Myers, Angela R.; Pisithkul, Tippapha; ...

2015-02-05

The nucleotide (p)ppGpp mediates bacterial stress responses, but its targets and underlying mechanisms of action vary among bacterial species and remain incompletely understood. In this paper, we characterize the molecular interaction between (p)ppGpp and guanylate kinase (GMK), revealing the importance of this interaction in adaptation to starvation. Combining structural and kinetic analyses, we show that (p)ppGpp binds the GMK active site and competitively inhibits the enzyme. The (p)ppGpp-GMK interaction prevents the conversion of GMP to GDP, resulting in GMP accumulation upon amino acid downshift. Abolishing this interaction leads to excess (p)ppGpp and defective adaptation to amino acid starvation. A surveymore » of GMKs from phylogenetically diverse bacteria shows that the (p)ppGpp-GMK interaction is conserved in members of Firmicutes, Actinobacteria, and Deinococcus-Thermus, but not in Proteobacteria, where (p)ppGpp regulates RNA polymerase (RNAP). Finally, we propose that GMK is an ancestral (p)ppGpp target and RNAP evolved more recently as a direct target in Proteobacteria.« less

Joint control of terrestrial gross primary productivity by plant phenology and physiology

PubMed Central

Xia, Jianyang; Niu, Shuli; Ciais, Philippe; Janssens, Ivan A.; Chen, Jiquan; Ammann, Christof; Arain, Altaf; Blanken, Peter D.; Cescatti, Alessandro; Bonal, Damien; Buchmann, Nina; Curtis, Peter S.; Chen, Shiping; Dong, Jinwei; Flanagan, Lawrence B.; Frankenberg, Christian; Georgiadis, Teodoro; Gough, Christopher M.; Hui, Dafeng; Kiely, Gerard; Li, Jianwei; Lund, Magnus; Magliulo, Vincenzo; Marcolla, Barbara; Merbold, Lutz; Olesen, Jørgen E.; Piao, Shilong; Raschi, Antonio; Roupsard, Olivier; Suyker, Andrew E.; Vaccari, Francesco P.; Varlagin, Andrej; Vesala, Timo; Wilkinson, Matthew; Weng, Ensheng; Yan, Liming; Luo, Yiqi

2015-01-01

Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space. PMID:25730847

40 CFR 747.195 - Triethanolamine salt of a substituted organic acid.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., commerce, importer, impurity, Inventory, manufacturer, person, process, processor, and small quantities... control of the processor. (ii) Distribution in commerce is limited to purposes of export. (iii) The processor or distributor may not use the substance except in small quantities solely for research and...

Estimating gross primary productivity (GPP) of forests across southern England at high spatial and temporal resolution using the FLIGHT model

NASA Astrophysics Data System (ADS)

Pankaew, Prasan; Milton, Edward; Dawson, Terry; Dash, Jadu

2013-04-01

Forests and woodlands play an important role in CO2 flux and in the storage of carbon, therefore it is important to be able to estimate gross primary productivity (GPP) and its change over time. The MODIS GPP product (MOD17) provides near-global GPP, but at relatively coarse spatial resolution (1km pixel size) and only every eight days. In order to study the dynamics of GPP over shorter time periods and over smaller areas it is necessary to make ground measurements or use a plant canopy model. The most reliable ground-based GPP data are those from the FLUXNET network, which comprises over 500 sites worldwide, each of which measures GPP using the eddy covariance method. Each FLUXNET measurement corresponds to GPP from an area around the sampling tower, the size and shape of which varies with weather conditions, notably wind speed and direction. The FLIGHT forest light simulation model (North, 1996) is a Monte Carlo based model to estimate the GPP from forest canopies, which does not take into account the spatial complexity of the site or the wind conditions at the time. Forests in southern England are small and embedded in a matrix of other land cover types (agriculture, urban etc.), so GPP estimated from FLIGHT needs to be adjusted to match that measured from a FLUXNET tower. The aim of this paper is to develop and test a method to adjust FLIGHT GPP so that it matches FLUXNET GPP. The advantage of this is that GPP can then be estimated over many other forests which do not possess FLUXNET sites. The study was based on data from two mixed broadleaf forests in southern England (Wytham Woods and Alice Holt forest), both of which have FLUXNET sites located within them. The FLUXNET meteorological data were prepared for use in the FLIGHT model by converting broadband irradiance to photosynthetically active radiance (PAR) and estimating diffuse PAR, using methods developed in previous work by the authors. The standard FLIGHT model tended to overestimate GPP in the winter and spring period and under-estimate GPP in the summer months. Correction factors were computed based on the midday GPP for each month of the year. The modified FLIGHT model was used to estimate GPP from each of the two forest sites at hourly intervals over a year. Both sites showed a strong linear relationship between GPP estimated from FLIGHT and GPP measured by FLUXNET (Alice Holt forest, R2=0.96, RMSE = 2.39 μmol m-2 s-1, MBE = 1.32 μmol m-2 s-1 , Wytham Wood R2 = 0.97, RMSE = 1.42 μmol m-2 s-1, MBE = 0.57 μmol m-2 s-1). The results suggest that the modified FLIGHT model could be used to estimate GPP at hourly intervals over non-instrumented forest sites across southern England, and thereby obtain regional estimates of GPP at high spatial and temporal resolution. Reference North, P. R. J. (1996). Three-Dimensional Forest Light Interaction Model Using a Monte Carlo Method. IEEE Transactions on Geoscience and Remote Sensing, 34(4), 946-956.

Juvenile generalized pustular psoriasis is a chronic recalcitrant disease: an analysis of 27 patients seen in a tertiary hospital in Johor, Malaysia.

PubMed

Lau, Bi-Wen; Lim, Dee-Zhen; Capon, Francesca; Barker, Jonathan N; Choon, Siew-Eng

2017-04-01

Limited information exists regarding juvenile generalized pustular psoriasis (GPP). We aim to determine the clinical profile and outcome of Malaysians with juvenile GPP. Review of hospital case notes on patients with juvenile GPP. Twenty-seven patients with juvenile GPP were identified. Female to male ratio was 1.4:1. The median age at onset of GPP was 6.5 years. Ten patients had prior psoriasis with a median pre-pustular duration of 2.7 years. Onset of GPP was earlier in patients without prior psoriasis (5.1 years vs. 12.0 years, P = 0.002). Precipitating factors identified included stress, upper respiratory tract infection, systemic steroid use, vaccination, and pregnancy. A positive family history of psoriasis and GPP was present in six and one patient(s), respectively. Twenty-one patients had acute, five annular, and one localized variant of GPP. Arthritis was present in 22.2%. Fever, leukocytosis, and transaminitis were mainly seen in patients with acute GPP at 80.9, 72.2, and 11.1%, respectively. Among 20 patients screened, eight carry IL36RN variants and one has CARD14 mutation. IL36RN-positive patients have more severe disease characterized by early onset, low prevalence of prior plaque psoriasis, high prevalence of systemic inflammation, and need for continuous long-term systemic therapy. Acitretin and cyclosporine were effective in aborting acute GPP in 100% of 16 and 66.7% of six patients treated, respectively. However, relapses were common. Only three of the 17 patients whose initial acute GPP was controlled with systemic agents were successfully weaned off treatment. Juvenile GPP is a chronic recalcitrant disease. IL36RN-positive patients have more severe disease. © 2017 The International Society of Dermatology.

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing.

PubMed

Feng, X; Liu, G; Chen, J M; Chen, M; Liu, J; Ju, W M; Sun, R; Zhou, W

2007-11-01

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.

Prediction of Gross Primary Production during the Drought and Normal Years over the US Using Solar-Induced Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Halubok, M.; Yang, Z. L.

2016-12-01

This study investigates how gross primary production (GPP) estimates can be improved with the use of solar-induced chlorophyll fluorescence (SIF) and presents an effort to produce GPP predictions based on the interdependence between SIF, precipitation, soil moisture and GPP using Global Ozone Monitoring Experiment-2 (GOME-2), Tropical Rainfall Measuring Mission (TRMM), European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) datasets and FLUXNET observations. We found that considering the relationships between SIF, precipitation and soil moisture, isolating SIF-GPP relationships for different plant functional types (PFTs), and using precipitation and soil moisture conditions pertinent to the continental US provides the most accurate GPP estimates over the Great Plains and Texas. We found that there exists a lag between a precipitation event and corresponding fluorescence levels, ranging from about 2 weeks for grasses to a month for crops. Using these lead-lag relationships, we estimate GPP using SIF, precipitation and soil moisture data for two different PFTs (C3 non-arctic grass and crop) over the US applying the multiple linear regression technique. GPP values estimated from our lead-lag based SIF show the closest possible match with the observational data from the FLUXNET stations. During the drought 2011 year over Texas, our GPP values show a decrease by 100 gC/m2/month as compared to the reference year of 2007. In 2012 (drought year over the Great Plains), we observe significant decrease in GPP, especially in the area of high production (>500 gC/m2/month) that is reduced in July and August 2012. Hence, estimating GPP using specific SIF-GPP relationships, considering the differences in biomes and their interactions with precipitation and soil moisture pertinent to a certain region can detect the drought trends and produce reasonable GPP estimates. Thus, this simple and computationally efficient method based on derived linear equations can be used to obtain GPP predictions.

Remote sensing evaluation of CLM4 GPP for the period 2000 to 2009

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying

2012-01-01

The ability of a process-based ecosystem model like Version 4 of the Community Land Model (CLM4) to provide accurate estimates of CO2 flux is a top priority for researchers, modelers and policy makers. Remote sensing can provide long-term and large scale products suitable for ecosystem model evaluation. Global estimations of gross primary production (GPP) at the 1 km spatial resolution from years 2000 to 2009 from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor offer a unique opportunity for evaluating the temporal and spatial patterns of global GPP and its relationship with climate for CLM4. We compare monthly GPP simulated bymore » CLM4 at half-degree resolution with satellite estimates of GPP from the MODIS GPP (MOD17) dataset for the 10-yr period, January 2000 December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intra-annual and inter-annual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and later decline of GPP in autumn. Empirical Orthogonal Function (EOF) analysis of the monthly GPP changes indicates that on the intra-annual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and the very dry region in central Australia. For 2000-2009, CLM4 simulates increases in annual averaged GPP over both hemispheres, however estimates from MODIS suggest a reduction in the Southern Hemisphere (-0.2173 PgC/year) balancing the significant increase over the Northern Hemisphere (0.2157 PgC/year).« less

Physicochemical properties and antioxidant activities of polysaccharides from Gynura procumbens leaves by fractional precipitation.

PubMed

Li, Jing-En; Wang, Wen-Jun; Zheng, Guo-Dong; Li, Lin-Yan

2017-02-01

Four new polysaccharides (GPP-20, GPP-40, GPP-60 and GPP-80) were fractionated from Gynura procumbens leaves by 20%, 40%, 60% and 80% (v/v) ethanol, successively. Their physicochemical properties including the contents of neutral sugar, uronic acid and protein, as well as the monosaccharide composition were determined. In addition, the antioxidant activities of them were investigated via the reducing power assay and scavenging capacities of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radicals and hydroxyl free radicals, respectively. The results indicated that apart from neutral sugar, they all contained uronic acids and proteins in their structures, which were further proved by the UV-vis and FT-IR spectra. Monosaccharide composition analysis implied that they all belonged to heteropolysaccharides consisted of arabinose, galactose, glucose, xylose and galacturonic acid with different types and ratios. What's more, GPP-20, GPP-40 and GPP-80 always exhibited better antioxidant activities than GPP-60 among these three antioxidant assays in vitro. Copyright © 2016 Elsevier B.V. All rights reserved.

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

Rsd balances (p)ppGpp level by stimulating the hydrolase activity of SpoT during carbon source downshift in Escherichia coli.

PubMed

Lee, Jae-Woo; Park, Young-Ha; Seok, Yeong-Jae

2018-06-18

Bacteria respond to nutritional stresses by changing the cellular concentration of the alarmone (p)ppGpp. This control mechanism, called the stringent response, depends on two enzymes, the (p)ppGpp synthetase RelA and the bifunctional (p)ppGpp synthetase/hydrolase SpoT in Escherichia coli and related bacteria. Because SpoT is the only enzyme responsible for (p)ppGpp hydrolysis in these bacteria, SpoT activity needs to be tightly regulated to prevent the uncontrolled accumulation of (p)ppGpp, which is lethal. To date, however, no such regulation of SpoT (p)ppGpp hydrolase activity has been documented in E. coli In this study, we show that Rsd directly interacts with SpoT and stimulates its (p)ppGpp hydrolase activity. Dephosphorylated HPr, but not phosphorylated HPr, of the phosphoenolpyruvate-dependent sugar phosphotransferase system could antagonize the stimulatory effect of Rsd on SpoT (p)ppGpp hydrolase activity. Thus, we suggest that Rsd is a carbon source-dependent regulator of the stringent response in E. coli . Copyright © 2018 the Author(s). Published by PNAS.

Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data.

PubMed

MacBean, Natasha; Maignan, Fabienne; Bacour, Cédric; Lewis, Philip; Peylin, Philippe; Guanter, Luis; Köhler, Philipp; Gómez-Dans, Jose; Disney, Mathias

2018-01-31

Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr -1 to 166 ± 10 PgCyr -1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr -1 . Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections.

Case for a field-programmable gate array multicore hybrid machine for an image-processing application

NASA Astrophysics Data System (ADS)

Rakvic, Ryan N.; Ives, Robert W.; Lira, Javier; Molina, Carlos

2011-01-01

General purpose computer designers have recently begun adding cores to their processors in order to increase performance. For example, Intel has adopted a homogeneous quad-core processor as a base for general purpose computing. PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high level. Can modern image-processing algorithms utilize these additional cores? On the other hand, modern advancements in configurable hardware, most notably field-programmable gate arrays (FPGAs) have created an interesting question for general purpose computer designers. Is there a reason to combine FPGAs with multicore processors to create an FPGA multicore hybrid general purpose computer? Iris matching, a repeatedly executed portion of a modern iris-recognition algorithm, is parallelized on an Intel-based homogeneous multicore Xeon system, a heterogeneous multicore Cell system, and an FPGA multicore hybrid system. Surprisingly, the cheaper PS3 slightly outperforms the Intel-based multicore on a core-for-core basis. However, both multicore systems are beaten by the FPGA multicore hybrid system by >50%.

Stanford Hardware Development Program

NASA Technical Reports Server (NTRS)

Peterson, A.; Linscott, I.; Burr, J.

1986-01-01

Architectures for high performance, digital signal processing, particularly for high resolution, wide band spectrum analysis were developed. These developments are intended to provide instrumentation for NASA's Search for Extraterrestrial Intelligence (SETI) program. The real time signal processing is both formal and experimental. The efficient organization and optimal scheduling of signal processing algorithms were investigated. The work is complemented by efforts in processor architecture design and implementation. A high resolution, multichannel spectrometer that incorporates special purpose microcoded signal processors is being tested. A general purpose signal processor for the data from the multichannel spectrometer was designed to function as the processing element in a highly concurrent machine. The processor performance required for the spectrometer is in the range of 1000 to 10,000 million instructions per second (MIPS). Multiple node processor configurations, where each node performs at 100 MIPS, are sought. The nodes are microprogrammable and are interconnected through a network with high bandwidth for neighboring nodes, and medium bandwidth for nodes at larger distance. The implementation of both the current mutlichannel spectrometer and the signal processor as Very Large Scale Integration CMOS chip sets was commenced.

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production

NASA Astrophysics Data System (ADS)

Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julia; Dong, Jinwei; Kato, Etsushi; Jain, Atul K.; Wiltshire, Andy; Stocker, Benjamin D.

2016-12-01

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

Precipitation and Carbon-Water Coupling Jointly Control the Interannual Variability of Global Land Gross Primary Production

NASA Technical Reports Server (NTRS)

Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julian; Dong, Jinwei;

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.

Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less

Estimating of gross primary production in an Amazon-Cerrado transitional forest using MODIS and Landsat imagery.

PubMed

Danelichen, Victor H M; Biudes, Marcelo S; Velasque, Maísa C S; Machado, Nadja G; Gomes, Raphael S R; Vourlitis, George L; Nogueira, José S

2015-09-01

The acceleration of the anthropogenic activity has increased the atmospheric carbon concentration, which causes changes in regional climate. The Gross Primary Production (GPP) is an important variable in the global carbon cycle studies, since it defines the atmospheric carbon extraction rate from terrestrial ecosystems. The objective of this study was to estimate the GPP of the Amazon-Cerrado Transitional Forest by the Vegetation Photosynthesis Model (VPM) using local meteorological data and remote sensing data from MODIS and Landsat 5 TM reflectance from 2005 to 2008. The GPP was estimated using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) calculated by MODIS and Landsat 5 TM images. The GPP estimates were compared with measurements in a flux tower by eddy covariance. The GPP measured in the tower was consistent with higher values during the wet season and there was a trend to increase from 2005 to 2008. The GPP estimated by VPM showed the same increasing trend observed in measured GPP and had high correlation and Willmott's coefficient and low error metrics in comparison to measured GPP. These results indicated high potential of the Landsat 5 TM images to estimate the GPP of Amazon-Cerrado Transitional Forest by VPM.

Novel pppGpp binding site at the C-terminal region of the Rel enzyme from Mycobacterium smegmatis.

PubMed

Syal, Kirtimaan; Joshi, Himanshu; Chatterji, Dipankar; Jain, Vikas

2015-10-01

Mycobacterium tuberculosis elicits the stringent response under unfavorable growth conditions, such as those encountered by the pathogen inside the host. The hallmark of this response is production of guanosine tetra- and pentaphosphates, collectively termed (p)ppGpp, which have pleiotropic effects on the bacterial physiology. As the stringent response is connected to survival under stress, it is now being targeted for developing inhibitors against bacterial persistence. The Rel enzyme in mycobacteria has two catalytic domains at its N-terminus that are involved in the synthesis and hydrolysis of (p)ppGpp, respectively. However, the function of the C-terminal region of the protein remained unknown. Here, we have identified a binding site for pppGpp in the C-terminal region of Rel. The binding affinity of pppGpp was quantified by isothermal titration calorimetry. The binding site was determined by crosslinking using the nucleotide analog azido-pppGpp, and examining the crosslink product by mass spectrometry. Additionally, mutations in the Rel protein were created to confirm the site of pppGpp binding by isothermal titration calorimetry. These mutants showed increased pppGpp synthesis and reduced hydrolytic activity. We believe that binding of pppGpp to Rel provides a feedback mechanism that allows the protein to detect and adjust the (p)ppGpp level in the cell. Our work suggests that such sites should also be considered while designing inhibitors to target the stringent response. © 2015 FEBS.

Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon

USGS Publications Warehouse

Hall, Robert O.; Yackulic, Charles B.; Kennedy, Theodore A.; Yard, Michael D.; Rosi-Marshall, Emma J.; Voichick, Nicholas; Behn, Kathrine E.

2015-01-01

Dams and river regulation greatly alter the downstream environment for gross primary production (GPP) because of changes in water clarity, flow, and temperature regimes. We estimated reach-scale GPP in five locations of the regulated Colorado River in Grand Canyon using an open channel model of dissolved oxygen. Benthic GPP dominates in Grand Canyon due to fast transport times and low pelagic algal biomass. In one location, we used a 738 days time series of GPP to identify the relative contribution of different physical controls of GPP. We developed both linear and semimechanistic time series models that account for unmeasured temporal covariance due to factors such as algal biomass dynamics. GPP varied from 0 g O2 m−2 d−1 to 3.0 g O2 m−2 d−1 with a relatively low annual average of 0.8 g O2 m−2d−1. Semimechanistic models fit the data better than linear models and demonstrated that variation in turbidity primarily controlled GPP. Lower solar insolation during winter and from cloud cover lowered GPP much further. Hydropeaking lowered GPP but only during turbid conditions. Using the best model and parameter values, the model accurately predicted seasonal estimates of GPP at 3 of 4 upriver sites and outperformed the linear model at all sites; discrepancies were likely from higher algal biomass at upstream sites. This modeling approach can predict how changes in physical controls will affect relative rates of GPP throughout the 385 km segment of the Colorado River in Grand Canyon and can be easily applied to other streams and rivers.

Sensitivity of gross primary production of irrigation-permitted and non-permitted grassland and croplands to drought and pluvial conditions during 2010-2016

NASA Astrophysics Data System (ADS)

Doughty, R.; Xiao, X.; Qin, Y.; Wu, X.; Zhang, Y.; Zou, Z.; Bajgain, R.; Zhou, Y.; Basara, J. B.; McCarthy, H. R.; Friedman, J. R.

2017-12-01

To accurately estimate carbon cycling and food production, it is essential to understand how gross primary production (GPP) of irrigated and non-irrigated grasslands and croplands respond to drought and pluvial conditions. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in 2015, thus providing an opportunity to study such changes in GPP of grasslands and croplands. This study analyzes annual GPP of irrigation-permitted and non-permitted grasslands, winter wheat, other C3 croplands, and C4 croplands in Caddo County of western Oklahoma from 2010 through 2016. For each land class, annual GPP from the 2011 drought and pluvial 2015 were compared with the combined, 5-year mean GPP from the other years of the study period. The results show that for the 2011 drought: 1) non-permitted C4 croplands had the largest percentage decrease (-41%) in GPP from the 5-year mean, but irrigation-permitted C4 croplands had no significant decrease; 2) GPP was significantly lower than the 5-year mean for all non-C4 vegetation types, regardless of water rights; 3) non-permitted lands were more sensitive to drought than irrigation-permitted lands, except for grasslands, which had similar percentage reductions in GPP (-35%). Results for the pluvial year 2015 indicate that: 1) GPP was significantly higher for grasslands, winter wheat, and non-permitted C3 croplands than the 5-year mean; 2) there was no significant difference in GPP for irrigation-permitted C3 croplands or non-permitted C4 croplands; 3) GPP for C4 irrigation-permitted croplands was 9% lower than the 5-year mean.

Diversity in Guanosine 3′,5′-Bisdiphosphate (ppGpp) Sensitivity among Guanylate Kinases of Bacteria and Plants*

PubMed Central

Nomura, Yuhta; Izumi, Atsushi; Fukunaga, Yoshinori; Kusumi, Kensuke; Iba, Koh; Watanabe, Seiya; Nakahira, Yoichi; Weber, Andreas P. M.; Nozawa, Akira; Tozawa, Yuzuru

2014-01-01

The guanosine 3′,5′-bisdiphosphate (ppGpp) signaling system is shared by bacteria and plant chloroplasts, but its role in plants has remained unclear. Here we show that guanylate kinase (GK), a key enzyme in guanine nucleotide biosynthesis that catalyzes the conversion of GMP to GDP, is a target of regulation by ppGpp in chloroplasts of rice, pea, and Arabidopsis. Plants have two distinct types of GK that are localized to organelles (GKpm) or to the cytosol (GKc), with both enzymes being essential for growth and development. We found that the activity of rice GKpm in vitro was inhibited by ppGpp with a Ki of 2.8 μm relative to the substrate GMP, whereas the Km of this enzyme for GMP was 73 μm. The IC50 of ppGpp for GKpm was ∼10 μm. In contrast, the activity of rice GKc was insensitive to ppGpp, as was that of GK from bakers' yeast, which is also a cytosolic enzyme. These observations suggest that ppGpp plays a pivotal role in the regulation of GTP biosynthesis in chloroplasts through specific inhibition of GKpm activity, with the regulation of GTP biosynthesis in chloroplasts thus being independent of that in the cytosol. We also found that GKs of Escherichia coli and Synechococcus elongatus PCC 7942 are insensitive to ppGpp, in contrast to the ppGpp sensitivity of the Bacillus subtilis enzyme. Our biochemical characterization of GK enzymes has thus revealed a novel target of ppGpp in chloroplasts and has uncovered diversity among bacterial GKs with regard to regulation by ppGpp. PMID:24722991

Benchmarking global land surface models in CMIP5: analysis of ecosystem water use efficiency (WUE) and Budyko framework

NASA Astrophysics Data System (ADS)

Li, Longhui

2015-04-01

Twelve Earth System Models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated in terms of ecosystem water use efficiency (WUE) and Budyko framework. Simulated values of GPP and ET from ESMs were validated against with FLUXNET measurements, and the slope of linear regression between the measurement and the model ranged from 0.24 in CanESM2 to 0.8 in GISS-E2 for GPP, and from 0.51 to 0.86 for ET. The performances of 12 ESMs in simulating ET are generally better than GPP. Compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11), all ESMs could capture the latitudinal variations of GPP and ET, but the majority of models extremely overestimated GPP and ET, particularly around the equator. The 12 ESMs showed much larger variations in latitudinal WUE. 4 of 12 ESMs predicted global annual GPP of higher than 150 Pg C year-1, and the other 8 ESMs predicted global GPP with ±15% error of the JU11 GPP. In contrast, all EMSs predicted moderate bias for global ET. The coefficient of variation (CV) of ET (0.11) is significantly less than that of GPP (0.25). More than half of 12 ESMs generally comply with the Budyko framework but some models deviated much. Spatial analysis of error in GPP and ET indicated that model results largely differ among models at different regions. This study suggested that the estimate of ET was much better than GPP. Incorporating the convergence of WUE and the Budyko framework into ESMs as constraints in the next round of CMIP scheme is expected to decrease the uncertainties of carbon and water fluxes estimates.

MS_RHII-RSD, a Dual-Function RNase HII-(p)ppGpp Synthetase from Mycobacterium smegmatis

PubMed Central

Murdeshwar, Maya S.

2012-01-01

In the noninfectious soil saprophyte Mycobacterium smegmatis, intracellular levels of the stress alarmones guanosine tetraphosphate and guanosine pentaphosphate, together termed (p)ppGpp, are regulated by the enzyme RelMsm. This enzyme consists of a single, bifunctional polypeptide chain that is capable of both synthesizing and hydrolyzing (p)ppGpp. The relMsm knockout strain of M. smegmatis (ΔrelMsm) is expected to show a (p)ppGpp null [(p)ppGpp0] phenotype. Contrary to this expectation, the strain is capable of synthesizing (p)ppGpp in vivo. In this study, we identify and functionally characterize the open reading frame (ORF), MSMEG_5849, that encodes a second functional (p)ppGpp synthetase in M. smegmatis. In addition to (p)ppGpp synthesis, the 567-amino-acid-long protein encoded by this gene is capable of hydrolyzing RNA·DNA hybrids and bears similarity to the conventional RNase HII enzymes. We have classified this protein as actRelMsm in accordance with the recent nomenclature proposed and have named it MS_RHII-RSD, indicating the two enzymatic activities present [RHII, RNase HII domain, originally identified as domain of unknown function 429 (DUF429), and RSD, RelA_SpoT nucleotidyl transferase domain, the SYNTH domain responsible for (p)ppGpp synthesis activity]. MS_RHII-RSD is expressed and is constitutively active in vivo and behaves like a monofunctional (p)ppGpp synthetase in vitro. The occurrence of the RNase HII and (p)ppGpp synthetase domains together on the same polypeptide chain is suggestive of an in vivo role for this novel protein as a link connecting the essential life processes of DNA replication, repair, and transcription to the highly conserved stress survival pathway, the stringent response. PMID:22636779

MS_RHII-RSD, a dual-function RNase HII-(p)ppGpp synthetase from Mycobacterium smegmatis.

PubMed

Murdeshwar, Maya S; Chatterji, Dipankar

2012-08-01

In the noninfectious soil saprophyte Mycobacterium smegmatis, intracellular levels of the stress alarmones guanosine tetraphosphate and guanosine pentaphosphate, together termed (p)ppGpp, are regulated by the enzyme Rel(Msm). This enzyme consists of a single, bifunctional polypeptide chain that is capable of both synthesizing and hydrolyzing (p)ppGpp. The rel(Msm) knockout strain of M. smegmatis (Δrel(Msm)) is expected to show a (p)ppGpp null [(p)ppGpp(0)] phenotype. Contrary to this expectation, the strain is capable of synthesizing (p)ppGpp in vivo. In this study, we identify and functionally characterize the open reading frame (ORF), MSMEG_5849, that encodes a second functional (p)ppGpp synthetase in M. smegmatis. In addition to (p)ppGpp synthesis, the 567-amino-acid-long protein encoded by this gene is capable of hydrolyzing RNA·DNA hybrids and bears similarity to the conventional RNase HII enzymes. We have classified this protein as actRel(Msm) in accordance with the recent nomenclature proposed and have named it MS_RHII-RSD, indicating the two enzymatic activities present [RHII, RNase HII domain, originally identified as domain of unknown function 429 (DUF429), and RSD, RelA_SpoT nucleotidyl transferase domain, the SYNTH domain responsible for (p)ppGpp synthesis activity]. MS_RHII-RSD is expressed and is constitutively active in vivo and behaves like a monofunctional (p)ppGpp synthetase in vitro. The occurrence of the RNase HII and (p)ppGpp synthetase domains together on the same polypeptide chain is suggestive of an in vivo role for this novel protein as a link connecting the essential life processes of DNA replication, repair, and transcription to the highly conserved stress survival pathway, the stringent response.

Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data.

PubMed

Ogutu, Booker O; Dash, Jadunandan; Dawson, Terence P

2013-09-01

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2)  > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2)  > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution. © 2013 John Wiley & Sons Ltd.

Consistency Between Sun-Induced Chlorophyll Fluorescence and Gross Primary Production of Vegetation in North America

NASA Technical Reports Server (NTRS)

Zhang, Yao; Xiao, Xiangming; Jin, Cui; Dong, Jinwei; Zhou, Sha; Wagle, Pradeep; Joiner, Joanna; Guanter, Luis; Zhang, Yongguang; Zhang , Geli;

Assessing the relationship between microwave vegetation optical depth and gross primary production

NASA Astrophysics Data System (ADS)

Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Liu, Yi Y.; Miralles, Diego G.; Parinussa, Robert; van der Schalie, Robin; Vreugdenhil, Mariette; Schwalm, Christopher R.; Tramontana, Gianluca; Camps-Valls, Gustau; Dorigo, Wouter A.

2018-03-01

At the global scale, the uptake of atmospheric carbon dioxide by terrestrial ecosystems through photosynthesis is commonly estimated through vegetation indices or biophysical properties derived from optical remote sensing data. Microwave observations of vegetated areas are sensitive to different components of the vegetation layer than observations in the optical domain and may therefore provide complementary information on the vegetation state, which may be used in the estimation of Gross Primary Production (GPP). However, the relation between GPP and Vegetation Optical Depth (VOD), a biophysical quantity derived from microwave observations, is not yet known. This study aims to explore the relationship between VOD and GPP. VOD data were taken from different frequencies (L-, C-, and X-band) and from both active and passive microwave sensors, including the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS) mission, the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) and a merged VOD data set from various passive microwave sensors. VOD data were compared against FLUXCOM GPP and Solar-Induced chlorophyll Fluorescence (SIF) from the Global Ozone Monitoring Experiment-2 (GOME-2). FLUXCOM GPP estimates are based on the upscaling of flux tower GPP observations using optical satellite data, while SIF observations present a measure of photosynthetic activity and are often used as a proxy for GPP. For relating VOD to GPP, three variables were analyzed: original VOD time series, temporal changes in VOD (ΔVOD), and positive changes in VOD (ΔVOD≥0). Results show widespread positive correlations between VOD and GPP with some negative correlations mainly occurring in dry and wet regions for active and passive VOD, respectively. Correlations between VOD and GPP were similar or higher than between VOD and SIF. When comparing the three variables for relating VOD to GPP, correlations with GPP were higher for the original VOD time series than for ΔVOD or ΔVOD≥0 in case of sparsely to moderately vegetated areas and evergreen forests, while the opposite was true for deciduous forests. Results suggest that original VOD time series should be used jointly with changes in VOD for the estimation of GPP across biomes, which may further benefit from combining active and passive VOD data.

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide rangemore » of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.« less

The bacterial alarmone (p)ppGpp activates the type III secretion system in Erwinia amylovora.

PubMed

Ancona, Veronica; Lee, Jae Hoon; Chatnaparat, Tiyakhon; Oh, Jinrok; Hong, Jong-In; Zhao, Youfu

2015-04-01

The hypersensitive response and pathogenicity (hrp) type III secretion system (T3SS) is a key pathogenicity factor in Erwinia amylovora. Previous studies have demonstrated that the T3SS in E. amylovora is transcriptionally regulated by a sigma factor cascade. In this study, the role of the bacterial alarmone ppGpp in activating the T3SS and virulence of E. amylovora was investigated using ppGpp mutants generated by Red recombinase cloning. The virulence of a ppGpp-deficient mutant (ppGpp(0)) as well as a dksA mutant of E. amylovora was completely impaired, and bacterial growth was significantly reduced, suggesting that ppGpp is required for full virulence of E. amylovora. Expression of T3SS genes was greatly downregulated in the ppGpp(0) and dksA mutants. Western blotting showed that accumulations of the HrpA protein in the ppGpp(0) and dksA mutants were about 10 and 4%, respectively, of that in the wild-type strain. Furthermore, higher levels of ppGpp resulted in a reduced cell size of E. amylovora. Moreover, serine hydroxamate and α-methylglucoside, which induce amino acid and carbon starvation, respectively, activated hrpA and hrpL promoter activities in hrp-inducing minimal medium. These results demonstrated that ppGpp and DksA play central roles in E. amylovora virulence and indicated that E. amylovora utilizes ppGpp as an internal messenger to sense environmental/nutritional stimuli for regulation of the T3SS and virulence. The type III secretion system (T3SS) is a key pathogenicity factor in Gram-negative bacteria. Fully elucidating how the T3SS is activated is crucial for comprehensively understanding the function of the T3SS, bacterial pathogenesis, and survival under stress conditions. In this study, we present the first evidence that the bacterial alarmone ppGpp-mediated stringent response activates the T3SS through a sigma factor cascade, indicating that ppGpp acts as an internal messenger to sense environmental/nutritional stimuli for the regulation of the T3SS and virulence in plant-pathogenic bacteria. Furthermore, the recovery of an spoT null mutant, which displayed very unique phenotypes, suggested that small proteins containing a single ppGpp hydrolase domain are functional. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

The Bacterial Alarmone (p)ppGpp Activates the Type III Secretion System in Erwinia amylovora

PubMed Central

Ancona, Veronica; Lee, Jae Hoon; Chatnaparat, Tiyakhon; Oh, Jinrok; Hong, Jong-In

2015-01-01

ABSTRACT The hypersensitive response and pathogenicity (hrp) type III secretion system (T3SS) is a key pathogenicity factor in Erwinia amylovora. Previous studies have demonstrated that the T3SS in E. amylovora is transcriptionally regulated by a sigma factor cascade. In this study, the role of the bacterial alarmone ppGpp in activating the T3SS and virulence of E. amylovora was investigated using ppGpp mutants generated by Red recombinase cloning. The virulence of a ppGpp-deficient mutant (ppGpp0) as well as a dksA mutant of E. amylovora was completely impaired, and bacterial growth was significantly reduced, suggesting that ppGpp is required for full virulence of E. amylovora. Expression of T3SS genes was greatly downregulated in the ppGpp0 and dksA mutants. Western blotting showed that accumulations of the HrpA protein in the ppGpp0 and dksA mutants were about 10 and 4%, respectively, of that in the wild-type strain. Furthermore, higher levels of ppGpp resulted in a reduced cell size of E. amylovora. Moreover, serine hydroxamate and α-methylglucoside, which induce amino acid and carbon starvation, respectively, activated hrpA and hrpL promoter activities in hrp-inducing minimal medium. These results demonstrated that ppGpp and DksA play central roles in E. amylovora virulence and indicated that E. amylovora utilizes ppGpp as an internal messenger to sense environmental/nutritional stimuli for regulation of the T3SS and virulence. IMPORTANCE The type III secretion system (T3SS) is a key pathogenicity factor in Gram-negative bacteria. Fully elucidating how the T3SS is activated is crucial for comprehensively understanding the function of the T3SS, bacterial pathogenesis, and survival under stress conditions. In this study, we present the first evidence that the bacterial alarmone ppGpp-mediated stringent response activates the T3SS through a sigma factor cascade, indicating that ppGpp acts as an internal messenger to sense environmental/nutritional stimuli for the regulation of the T3SS and virulence in plant-pathogenic bacteria. Furthermore, the recovery of an spoT null mutant, which displayed very unique phenotypes, suggested that small proteins containing a single ppGpp hydrolase domain are functional. PMID:25666138

Gross primary production of a semiarid grassland is enhanced by six years of exposure to elevated atmospheric CO2, warming, and irrigation.

NASA Astrophysics Data System (ADS)

Ryan, E.; Ogle, K.; Peltier, D.; Williams, D. G.; Pendall, E.

2014-12-01

The goal of this study was to quantify interannual variation of gross primary production (GPP) and evaluate potential drivers of GPP with global change using the Prairie Heating and CO2 Enrichment (PHACE) experiment in semiarid grassland in southeastern Wyoming. PHACE consists of the treatments: control, warming only, elevated CO2 (eCO2) only, eCO2 and warming, and irrigation only. We expected that GPP would be most strongly influenced by interannual variability in precipitation under all PHACE treatments, soil water availability under eCO2, and nitrogen availability. GPP data were obtained from paired measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco; GPP = Reco - NEE) made on 2-4 week intervals over six growing seasons (2007-2012). Soil temperature (T), soil water content (SWC), vapor pressure deficit (VPD), and photosynthetically active radiation (PAR) were continuously recorded at the plot (T, SWC) and site (VPD, PAR) scales. Annual, plot-level aboveground plant nitrogen content (N) was measured during peak biomass. We fit a non-linear light-response model to the GPP data within a Bayesian framework, and modeled the maximum GPP rate (Gmax) and canopy light-use efficiency (Q) as functions of N and current and antecedent SWC, T, and VPD. The model fit the GPP data well (R2 = 0.64), and regardless of the PHACE treatment the most important drivers of GPP were N (for Gmax), VPD (Gmax and Q), antecedent T (Gmax), and antecedent VPD (Q). Model simulations predicted that annual GPP increased on average by about 16% with eCO2, 14% with warming, 12% with eCO2 and warming, and 23% with irrigation. For four of the six years, annual GPP was significantly affected by either eCO2 alone or when combined with warming. The increase in annual GPP under irrigation was similar to the increase under eCO2 during a dry year (2012), but irrigation stimulated GPP to a greater degree than eCO2 during wet years (2008, 2009). Hence, increases in GPP under eCO2 appear to be indirectly due to increases in SWC, especially under dry conditions. These results suggest that future climate scenarios will lead to more productive grasslands in semiarid regions, but the overall response of the C cycle and the potential for these systems to sequester greater C will depend on the magnitude and direction of both the Reco and GPP responses.

Implementation of kernels on the Maestro processor

NASA Astrophysics Data System (ADS)

Suh, Jinwoo; Kang, D. I. D.; Crago, S. P.

Currently, most microprocessors use multiple cores to increase performance while limiting power usage. Some processors use not just a few cores, but tens of cores or even 100 cores. One such many-core microprocessor is the Maestro processor, which is based on Tilera's TILE64 processor. The Maestro chip is a 49-core, general-purpose, radiation-hardened processor designed for space applications. The Maestro processor, unlike the TILE64, has a floating point unit (FPU) in each core for improved floating point performance. The Maestro processor runs at 342 MHz clock frequency. On the Maestro processor, we implemented several widely used kernels: matrix multiplication, vector add, FIR filter, and FFT. We measured and analyzed the performance of these kernels. The achieved performance was up to 5.7 GFLOPS, and the speedup compared to single tile was up to 49 using 49 tiles.

Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia

NASA Astrophysics Data System (ADS)

Dass, P.; Rawlins, M. A.; Kimball, J. S.; Kim, Y.

2016-01-01

Terrestrial ecosystems of northern Eurasia are demonstrating an increasing gross primary productivity (GPP), yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness, and forest fires individually contribute to changes in GPP derived from satellite data across northern Eurasia using a light-use- efficiency-based model, for the period 1982-2010. We find that annual satellite-derived GPP is most sensitive to the temperature, precipitation and cloudiness of summer, which is the peak of the growing season and also the period of the year when the GPP trend is maximum. Considering the regional median, the summer temperature explains as much as 37.7 % of the variation in annual GPP, while precipitation and cloudiness explain 20.7 and 19.3 %. Warming over the period analysed, even without a sustained increase in precipitation, led to a significant positive impact on GPP for 61.7 % of the region. However, a significant negative impact on GPP was also found, for 2.4 % of the region, primarily the dryer grasslands in the south-west of the study area. For this region, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. While our results further advance the notion that air temperature is the dominant environmental control for recent GPP increases across northern Eurasia, the role of precipitation and cloudiness can not be ignored.

Hypercluster - Parallel processing for computational mechanics

NASA Technical Reports Server (NTRS)

Blech, Richard A.

1988-01-01

An account is given of the development status, performance capabilities and implications for further development of NASA-Lewis' testbed 'hypercluster' parallel computer network, in which multiple processors communicate through a shared memory. Processors have local as well as shared memory; the hypercluster is expanded in the same manner as the hypercube, with processor clusters replacing the normal single processor node. The NASA-Lewis machine has three nodes with a vector personality and one node with a scalar personality. Each of the vector nodes uses four board-level vector processors, while the scalar node uses four general-purpose microcomputer boards.

The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax ) on global gross primary production.

PubMed

Walker, Anthony P; Quaife, Tristan; van Bodegom, Peter M; De Kauwe, Martin G; Keenan, Trevor F; Joiner, Joanna; Lomas, Mark R; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan; Woodward, F Ian

2017-09-01

The maximum photosynthetic carboxylation rate (V cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr -1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.

Development of an analytical model for estimating global terrestrial carbon assimilation using a rate-limitation framework

NASA Astrophysics Data System (ADS)

Donohue, Randall; Yang, Yuting; McVicar, Tim; Roderick, Michael

2016-04-01

A fundamental question in climate and ecosystem science is "how does climate regulate the land surface carbon budget?" To better answer that question, here we develop an analytical model for estimating mean annual terrestrial gross primary productivity (GPP), which is the largest carbon flux over land, based on a rate-limitation framework. Actual GPP (climatological mean from 1982 to 2010) is calculated as a function of the balance between two GPP potentials defined by the climate (i.e., precipitation and solar radiation) and a third parameter that encodes other environmental variables and modifies the GPP-climate relationship. The developed model was tested at three spatial scales using different GPP sources, i.e., (1) observed GPP from 94 flux-sites, (2) modelled GPP (using the model-tree-ensemble approach) at 48654 (0.5 degree) grid-cells and (3) at 32 large catchments across the globe. Results show that the proposed model could account for the spatial GPP patterns, with a root-mean-square error of 0.70, 0.65 and 0.3 g C m-2 d-1 and R2 of 0.79, 0.92 and 0.97 for the flux-site, grid-cell and catchment scales, respectively. This analytical GPP model shares a similar form with the Budyko hydroclimatological model, which opens the possibility of a general analytical framework to analyze the linked carbon-water-energy cycles.

The Impact of Alternative Trait-Scaling Hypotheses for the Maximum Photosynthetic Carboxylation Rate (V (sub cmax)) on Global Gross Primary Production

NASA Technical Reports Server (NTRS)

Walker, Anthony P.; Quaife, Tristan; Van Bodegom, Peter M.; De Kauwe, Martin G.; Keenan, Trevor F.; Joiner, Joanna; Lomas, Mark R.; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan;

Does physiological acclimation to climate warming stabilize the ratio of canopy respiration to photosynthesis?

PubMed

Drake, John E; Tjoelker, Mark G; Aspinwall, Michael J; Reich, Peter B; Barton, Craig V M; Medlyn, Belinda E; Duursma, Remko A

2016-08-01

Given the contrasting short-term temperature dependences of gross primary production (GPP) and autotrophic respiration, the fraction of GPP respired by trees is predicted to increase with warming, providing a positive feedback to climate change. However, physiological acclimation may dampen or eliminate this response. We measured the fluxes of aboveground respiration (Ra ), GPP and their ratio (Ra /GPP) in large, field-grown Eucalyptus tereticornis trees exposed to ambient or warmed air temperatures (+3°C). We report continuous measurements of whole-canopy CO2 exchange, direct temperature response curves of leaf and canopy respiration, leaf and branch wood respiration, and diurnal photosynthetic measurements. Warming reduced photosynthesis, whereas physiological acclimation prevented a coincident increase in Ra . Ambient and warmed trees had a common nonlinear relationship between the fraction of GPP that was respired above ground (Ra /GPP) and the mean daily temperature. Thus, warming significantly increased Ra /GPP by moving plants to higher positions on the shared Ra /GPP vs daily temperature relationship, but this effect was modest and only notable during hot conditions. Despite the physiological acclimation of autotrophic respiration to warming, increases in temperature and the frequency of heat waves may modestly increase tree Ra /GPP, contributing to a positive feedback between climate warming and atmospheric CO2 accumulation. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis

Treesearch

Kevin Schaefer; Christopher R. Schwalm; Chris Williams; M. Altaf Arain; Alan Barr; Jing M. Chen; Kenneth J. Davis; Dimitre Dimitrov; Timothy W. Hilton; David Y. Hollinger; Elyn Humphreys; Benjamin Poulter; Brett M. Raczka; Andrew D. Richardson; Alok Sahoo; Peter Thornton; Rodrigo Vargas; Hans Verbeeck; Ryan Anderson; Ian Baker; T. Andrew Black; Paul Bolstad; Jiquan Chen; Peter S. Curtis; Ankur R. Desai; Michael Dietze; Danilo Dragoni; Christopher Gough; Robert F. Grant; Lianhong Gu; Atul Jain; Chris Kucharik; Beverly Law; Shuguang Liu; Erandathie Lokipitiya; Hank A. Margolis; Roser Matamala; J. Harry McCaughey; Russ Monson; J. William Munger; Walter Oechel; Changhui Peng; David T. Price; Dan Ricciuto; William J. Riley; Nigel Roulet; Hanqin Tian; Christina Tonitto; Margaret Torn; Ensheng Weng; Xiaolu Zhou

2012-01-01

Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States...

Peak growing season gross uptake of carbon in North America is largest in the Midwest USA

NASA Astrophysics Data System (ADS)

Hilton, Timothy W.; Whelan, Mary E.; Zumkehr, Andrew; Kulkarni, Sarika; Berry, Joseph A.; Baker, Ian T.; Montzka, Stephen A.; Sweeney, Colm; Miller, Benjamin R.; Elliott Campbell, J.

2017-06-01

Gross primary production (GPP) is a first-order uncertainty in climate predictions. Large-scale CO2 observations can provide information about the carbon cycle, but are not directly useful for GPP. Recently carbonyl sulfide (COS or OCS) has been proposed as a potential tracer for regional and global GPP. Here we present the first regional assessment of GPP using COS. We focus on the North American growing season--a global hotspot for COS air-monitoring and GPP uncertainty. Regional variability in simulated vertical COS concentration gradients was driven by variation in GPP rather than other modelled COS sources and sinks. Consequently we are able to show that growing season GPP in the Midwest USA significantly exceeds that of any other region of North America. These results are inconsistent with some ecosystem models, but are supportive of new ecosystem models from CMIP6. This approach provides valuable insight into the accuracy of various ecosystem land models.

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

NASA Astrophysics Data System (ADS)

Yan, Hao; Wang, Shao-Qiang; Yu, Kai-Liang; Wang, Bin; Yu, Qin; Bohrer, Gil; Billesbach, Dave; Bracho, Rosvel; Rahman, Faiz; Shugart, Herman H.

2017-10-01

Diffuse radiation can increase canopy light use efficiency (LUE). This creates the need to differentiate the effects of direct and diffuse radiation when simulating terrestrial gross primary production (GPP). Here, we present a novel GPP model, the diffuse-fraction-based two-leaf model (DTEC), which includes the leaf response to direct and diffuse radiation, and treats maximum LUE for shaded leaves (ɛmsh defined as a power function of the diffuse fraction (Df)) and sunlit leaves (ɛmsu defined as a constant) separately. An Amazonian rainforest site (KM67) was used to calibrate the model by simulating the linear relationship between monthly canopy LUE and Df. This showed a positive response of forest GPP to atmospheric diffuse radiation, and suggested that diffuse radiation was more limiting than global radiation and water availability for Amazon rainforest GPP on a monthly scale. Further evaluation at 20 independent AmeriFlux sites showed that the DTEC model, when driven by monthly meteorological data and MODIS leaf area index (LAI) products, explained 70% of the variability observed in monthly flux tower GPP. This exceeded the 51% accounted for by the MODIS 17A2 big-leaf GPP product. The DTEC model's explicit accounting for the impacts of diffuse radiation and soil water stress along with its parameterization for C4 and C3 plants was responsible for this difference. The evaluation of DTEC at Amazon rainforest sites demonstrated its potential to capture the unique seasonality of higher GPP during the diffuse radiation-dominated wet season. Our results highlight the importance of diffuse radiation in seasonal GPP simulation.