Comparison of simulation modeling and satellite techniques for monitoring ecological processes

NASA Technical Reports Server (NTRS)

Box, Elgene O.

1988-01-01

In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.

Attributing regional trends of evapotranspiration and gross primary productivity with remote sensing: a case study in the North China Plain

NASA Astrophysics Data System (ADS)

Mo, Xingguo; Chen, Xuejuan; Hu, Shi; Liu, Suxia; Xia, Jun

2017-01-01

Attributing changes in evapotranspiration (ET) and gross primary productivity (GPP) is crucial for impact and adaptation assessment of the agro-ecosystems to climate change. Simulations with the VIP model revealed that annual ET and GPP slightly increased from 1981 to 2013 over the North China Plain. The tendencies of both ET and GPP were upward in the spring season, while they were weak and downward in the summer season. A complete factor analysis illustrated that the relative contributions of climatic change, CO2 fertilization, and management to the ET (GPP) trend were 56 (-32) %, -28 (25) %, and 68 (108) %, respectively. The decline of global radiation resulted from deteriorated aerosol and air pollution was the principal cause of GPP decline in summer, while air warming intensified the water cycle and advanced the plant productivity in the spring season. Generally, agronomic improvements were the principal drivers of crop productivity enhancement.

Uncertainty analysis of gross primary production partitioned from net ecosystem exchange measurements

NASA Astrophysics Data System (ADS)

Raj, Rahul; Hamm, Nicholas Alexander Samuel; van der Tol, Christiaan; Stein, Alfred

2016-03-01

Gross primary production (GPP) can be separated from flux tower measurements of net ecosystem exchange (NEE) of CO2. This is used increasingly to validate process-based simulators and remote-sensing-derived estimates of simulated GPP at various time steps. Proper validation includes the uncertainty associated with this separation. In this study, uncertainty assessment was done in a Bayesian framework. It was applied to data from the Speulderbos forest site, The Netherlands. We estimated the uncertainty in GPP at half-hourly time steps, using a non-rectangular hyperbola (NRH) model for its separation from the flux tower measurements. The NRH model provides a robust empirical relationship between radiation and GPP. It includes the degree of curvature of the light response curve, radiation and temperature. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. We defined the prior distribution of each NRH parameter and used Markov chain Monte Carlo (MCMC) simulation to estimate the uncertainty in the separated GPP from the posterior distribution at half-hourly time steps. This time series also allowed us to estimate the uncertainty at daily time steps. We compared the informative with the non-informative prior distributions of the NRH parameters and found that both choices produced similar posterior distributions of GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications.

Assessment of SMAP soil moisture for global simulation of gross primary production

NASA Astrophysics Data System (ADS)

He, Liming; Chen, Jing M.; Liu, Jane; Bélair, Stéphane; Luo, Xiangzhong

2017-07-01

In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun-induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment-2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p < 0.05). Significant improvement in r appears in single-cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater-stressed areas are included.

Copula Multivariate analysis of Gross primary production and its hydro-environmental driver; A BIOME-BGC model applied to the Antisana páramos

NASA Astrophysics Data System (ADS)

Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Galarraga, Remigio; Mynett, Arthur

2014-05-01

Simulations of carbon cycling are prone to uncertainties from different sources, which in general are related to input data, parameters and the model representation capacities itself. The gross carbon uptake in the cycle is represented by the gross primary production (GPP), which deals with the spatio-temporal variability of the precipitation and the soil moisture dynamics. This variability associated with uncertainty of the parameters can be modelled by multivariate probabilistic distributions. Our study presents a novel methodology that uses multivariate Copulas analysis to assess the GPP. Multi-species and elevations variables are included in a first scenario of the analysis. Hydro-meteorological conditions that might generate a change in the next 50 or more years are included in a second scenario of this analysis. The biogeochemical model BIOME-BGC was applied in the Ecuadorian Andean region in elevations greater than 4000 masl with the presence of typical vegetation of páramo. The change of GPP over time is crucial for climate scenarios of the carbon cycling in this type of ecosystem. The results help to improve our understanding of the ecosystem function and clarify the dynamics and the relationship with the change of climate variables. Keywords: multivariate analysis, Copula, BIOME-BGC, NPP, páramos

Partitioning net ecosystem exchange of CO2 into gross primary production and ecosystem respiration in northern high-latitude ecosystems

NASA Astrophysics Data System (ADS)

Lund, M.; Zona, D.; Jackowicz-Korczynski, M.; Xu, X.

2017-12-01

The eddy covariance methodology is the primary tool for studying landscape-scale land-atmosphere exchange of greenhouse gases. Since the choice of instrumental setup and processing algorithms may influence the results, efforts within the international flux community have been made towards methodological harmonization and standardization. Performing eddy covariance measurements in high-latitude, Arctic tundra sites involves several challenges, related not only to remoteness and harsh climate conditions but also to the choice of processing algorithms. Partitioning of net ecosystem exchange (NEE) of CO2 into gross primary production (GPP) and ecosystem respiration (Reco) in the FLUXNET2015 dataset is made using either Nighttime or Daytime methods. These variables, GPP and Reco, are essential for calibration and validation of Earth system models. North of the Arctic Circle, sun remains visible at local midnight for a period of time, the number of days per year with midnight sun being dependent on latitude. The absence of nighttime conditions during Arctic summers renders the Nighttime method uncertain, however, no extensive assessment on the implications for flux partitioning has yet been made. In this study, we will assess the performance and validity of both partitioning methods along a latitudinal transect of northern sites included in the FLUXNET2015 dataset. We will evaluate the partitioned flux components against model simulations using the Community Land Model (CLM). Our results will be valuable for users interested in simulating Arctic and global carbon cycling.

Observations-based GPP estimates

NASA Astrophysics Data System (ADS)

Joiner, J.; Yoshida, Y.; Jung, M.; Tucker, C. J.; Pinzon, J. E.

2017-12-01

We have developed global estimates of gross primary production based on a relatively simple satellite observations-based approach using reflectance data from the MODIS instruments in the form of vegetation indices that provide information about photosynthetic capacity at both high temporal and spatial resolution and combined with information from chlorophyll solar-induced fluorescence from the Global Ozone Monitoring Experiment-2 instrument that is noisier and available only at lower temporal and spatial scales. We compare our gross primary production estimates with those from eddy covariance flux towers and show that they are competitive with more complicated extrapolated machine learning gross primary production products. Our results provide insight into the amount of variance in gross primary production that can be explained with satellite observations data and also show how processing of the satellite reflectance data is key to using it for accurate GPP estimates.

Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

PubMed

Barman, Rahul; Jain, Atul K; Liang, Miaoling

2014-05-01

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework. © 2013 John Wiley & Sons Ltd.

Fine and gross motor skills: The effects on skill-focused dual-tasks.

PubMed

Raisbeck, Louisa D; Diekfuss, Jed A

2015-10-01

Dual-task methodology often directs participants' attention towards a gross motor skill involved in the execution of a skill, but researchers have not investigated the comparative effects of attention on fine motor skill tasks. Furthermore, there is limited information about participants' subjective perception of workload with respect to task performance. To examine this, the current study administered the NASA-Task Load Index following a simulated shooting dual-task. The task required participants to stand 15 feet from a projector screen which depicted virtual targets and fire a modified Glock 17 handgun equipped with an infrared laser. Participants performed the primary shooting task alone (control), or were also instructed to focus their attention on a gross motor skill relevant to task execution (gross skill-focused) and a fine motor skill relevant to task execution (fine skill-focused). Results revealed that workload was significantly greater during the fine skill-focused task for both skill levels, but performance was only affected for the lesser-skilled participants. Shooting performance for the lesser-skilled participants was greater during the gross skill-focused condition compared to the fine skill-focused condition. Correlational analyses also demonstrated a significant negative relationship between shooting performance and workload during the gross skill-focused task for the higher-skilled participants. A discussion of the relationship between skill type, workload, skill level, and performance in dual-task paradigms is presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon

2005-01-01

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...

Internal performance of a 10 deg conical plug nozzle with a multispoke primary and translating external shroud

NASA Technical Reports Server (NTRS)

Bresnahan, D. L.

1972-01-01

An experimental investigation was conducted in a nozzle static test facility to determine the performance characteristics of a cold-flow, 21.59-centimeter-diameter plug nozzle with a multispoke primary. Two multispoke primary nozzles, a 12-spoke and a 24-spoke, were tested and compared with an annular plug nozzle. The supersonic cruise configurations for both spoke primaries performed about the same, with a gross thrust coefficient of 0.974, a decrease of approximately 1.5 percent from the reference nozzle. The takeoff configuration for the 12-spoke primary had a gross thrust coefficient of 0.957, a decrease of 1.5 percent from the reference nozzle, and the 24-spoke primary had a gross thrust coefficient of 0.95.

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.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

PubMed Central

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale. PMID:22399948

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

PubMed

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Improved estimations of gross primary production using satellite-derived photosynthetically active radiation

NASA Astrophysics Data System (ADS)

Cai, Wenwen; Yuan, Wenping; Liang, Shunlin; Zhang, Xiaotong; Dong, Wenjie; Xia, Jiangzhou; Fu, Yang; Chen, Yang; Liu, Dan; Zhang, Qiang

2014-01-01

Terrestrial vegetation gross primary production (GPP) is an important variable in determining the global carbon cycle as well as the interannual variability of the atmospheric CO2 concentration. The accuracy of GPP simulation is substantially affected by several critical model drivers, one of the most important of which is photosynthetically active radiation (PAR) which directly determines the photosynthesis processes of plants. In this study, we examined the impacts of uncertainties in radiation products on GPP estimates in China. Two satellite-based radiation products (GLASS and ISCCP), three reanalysis products (MERRA, ECMWF, and NCEP), and a blended product of reanalysis and observations (Princeton) were evaluated based on observations at hundreds of sites. The results revealed the highest accuracy for two satellite-based products over various temporal and spatial scales. The three reanalysis products and the Princeton product tended to overestimate radiation. The GPP simulation driven by the GLASS product exhibited the highest consistency with those derived from site observations. Model validation at 11 eddy covariance sites suggested the highest model performance when utilizing the GLASS product. Annual GPP in China driven by GLASS was 5.55 Pg C yr-1, which was 68.85%-94.87% of those derived from the other products. The results implied that the high spatial resolution, satellite-derived GLASS PAR significantly decreased the uncertainty of the GPP estimates at the regional scale.

Model aerodynamic test results for two variable cycle engine coannular exhaust systems at simulated takeoff and cruise conditions. Comprehensive data report. Volume 3: Graphical data book 1

NASA Technical Reports Server (NTRS)

Nelson, D. P.

1981-01-01

A graphical presentation of the aerodynamic data acquired during coannular nozzle performance wind tunnel tests is given. The graphical data consist of plots of nozzle gross thrust coefficient, fan nozzle discharge coefficient, and primary nozzle discharge coefficient. Normalized model component static pressure distributions are presented as a function of primary total pressure, fan total pressure, and ambient static pressure for selected operating conditions. In addition, the supersonic cruise configuration data include plots of nozzle efficiency and secondary-to-fan total pressure pumping characteristics. Supersonic and subsonic cruise data are given.

Interplay of drought and tropical cyclone activity in SE U.S. gross primary productivity

NASA Astrophysics Data System (ADS)

Lowman, Lauren E. L.; Barros, Ana P.

2016-06-01

Tropical cyclones (TCs), often associated with massive flooding and landslides in the Southeast U.S. (SE U.S.), provide a significant input of freshwater to the hydrologic system, and their timing and trajectory significantly impact drought severity and persistence. This manuscript investigates the sensitivity of gross primary productivity (GPP) in the SE U.S. to TC activity using the 1-D column implementation of the Duke Coupled Hydrology Model with Vegetation (DCHM-V) including coupled water and energy cycles and a biochemical representation of photosynthesis. Decadal-scale simulations of water, energy, and carbon fluxes were conducted at high temporal (30 min) and spatial (4 km) resolution over the period 2002-2012. At local scales, model results without calibration compare well against AmeriFlux tower data. At regional scales, differences between the DCHM-V estimates and the Moderate Resolution Imaging Spectroradiometer GPP product reflect the spatial organization of soil hydraulic properties and soil moisture dynamics by physiographic region, highlighting the links between the water and carbon cycles. To isolate the contribution of TC precipitation to SE U.S. productivity, control forcing simulations are contrasted with simulations where periods of TC activity in the atmospheric forcing data were replaced with climatology. During wet years, TC activity impacts productivity in 40-50% of the SE U.S. domain and explains a regional GPP increase of 3-5 Mg C/m2 that is 9% of the warm season total. In dry years, 23-34% of the domain exhibits a smaller positive response that corresponds to 4-8% of the seasonal carbon uptake, depending on TC timing and trajectory.

Curriculum Guide for Day Care Primary.

ERIC Educational Resources Information Center

Radke, Mary Ann

This curriculum, designed for severely retarded children in a primary day care setting, is divided into three sections: (1) Awareness of Body Parts, (2) Gross Motor Skills, and (3) Language Arts. Detailed activities are suggested to develop and reinforce various gross motor coordinations and learning skills. (CS)

Multiscale analyses of solar-induced florescence and gross primary production

USDA-ARS?s Scientific Manuscript database

Remotely sensed solar induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground-based GPP have posed challenges toward...

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger

2003-01-01

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...

Modeling gross primary production of an evergreen needleleaf forest using MODIS and climate data

Treesearch

Xiangming Xiao; Qingyuan Zhang; David Hollinger; John Aber; Berrien, III Moore

2005-01-01

Forest canopies are composed of photosynthetically active vegetation (PAV, chloroplasts) and nonphotosynthetic vegetation (NPV, e.g., cell wall, vein, branch). The fraction of photosynthetically active radiation (PAR) absorbed by the canopy (FAPAR) should be partitioned into FAPARPAV and FAPARNPV. Gross primary production (...

Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation ...

Integrating solar induced flourescence and the photochemical reflectance index for estimating gross primary production in a cornfield

USDA-ARS?s Scientific Manuscript database

The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four ...

Simulation of homogeneous condensation of small polyatomic systems in high pressure supersonic nozzle flows using Bhatnagar-Gross-Krook model

NASA Astrophysics Data System (ADS)

Kumar, Rakesh; Levin, Deborah A.

2011-03-01

In the present work, we have simulated the homogeneous condensation of carbon dioxide and ethanol using the Bhatnagar-Gross-Krook based approach. In an earlier work of Gallagher-Rogers et al. [J. Thermophys. Heat Transfer 22, 695 (2008)], it was found that it was not possible to simulate condensation experiments of Wegener et al. [Phys. Fluids 15, 1869 (1972)] using the direct simulation Monte Carlo method. Therefore, in this work, we have used the statistical Bhatnagar-Gross-Krook approach, which was found to be numerically more efficient than direct simulation Monte Carlo method in our previous studies [Kumar et al., AIAA J. 48, 1531 (2010)], to model homogeneous condensation of two small polyatomic systems, carbon dioxide and ethanol. A new weighting scheme is developed in the Bhatnagar-Gross-Krook framework to reduce the computational load associated with the study of homogeneous condensation flows. The solutions obtained by the use of the new scheme are compared with those obtained by the baseline Bhatnagar-Gross-Krook condensation model (without the species weighting scheme) for the condensing flow of carbon dioxide in the stagnation pressure range of 1-5 bars. Use of the new weighting scheme in the present work makes the simulation of homogeneous condensation of ethanol possible. We obtain good agreement between our simulated predictions for homogeneous condensation of ethanol and experiments in terms of the point of condensation onset and the distribution of mass fraction of ethanol condensed along the nozzle centerline.

Responses of gross primary production of grasslands and croplands under drought, pluvial, and irrigation conditions during 2010-2016, Oklahoma, USA

USDA-ARS?s Scientific Manuscript database

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 events. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in...

Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography

NASA Astrophysics Data System (ADS)

Sonnentag, O.; Chen, J. M.; Roulet, N. T.; Ju, W.; Govind, A.

2008-06-01

Carbon dynamics in peatlands are controlled, in large part, by their wetness as defined by water table depth and volumetric liquid soil moisture content. A common type of peatland is raised bogs that typically have a multiple-layer canopy of vascular plants over a Sphagnum moss ground cover. Their convex form restricts water supply to precipitation and water is shed toward the margins, usually by lateral subsurface flow. The hydraulic gradient for lateral subsurface flow is governed by the peat surface topography at the mesoscale (˜200 m to 5 km). To investigate the influence of mesoscale topography on wetness, evapotranspiration (ET), and gross primary productivity (GPP) in a bog during the snow-free period, we compare the outputs of a further developed version of the daily Boreal Ecosystem Productivity Simulator (BEPS) with observations made at the Mer Bleue peatland, located near Ottawa, Canada. Explicitly considering mesoscale topography, simulated total ET and GPP correlate well with measured ET (r = 0.91) and derived gross ecosystem productivity (GEP; r = 0.92). Both measured ET and derived GEP are simulated similarly well when mesoscale topography is neglected, but daily simulated values are systematically underestimated by about 10% and 12% on average, respectively, due to greater wetness resulting from the lack of lateral subsurface flow. Owing to the differences in moss surface conductances of water vapor and carbon dioxide with increasing moss water content, the differences in the spatial patterns of simulated total ET and GPP are controlled by the mesotopographic position of the moss ground cover.

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

Understanding the Dynamics of Soil Carbon in CMIP5 Models

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Luo, Y.; Randerson, J. T.; Allison, S. D.; Smith, M. J.

2014-12-01

Soil carbon stocks have the potential to be a strong source or sink for carbon dioxide over the next century, playing a critical role in climate change. These stocks are the result of small differences between much larger primary carbon fluxes: gross primary production, litter fall, autotrophic respiration and heterotrophic respiration. There was little agreement on predicted soil carbon stocks between Earth system models (ESMs) in the most recent Climate Model Intercomparison Project. Predicted present-day stocks ranged from roughly 500 Pg to over 3000 Pg and predicted changes over the 21st century ranged from -70 Pg to +250 Pg). The primary goal of this study was to understand why such large differences exist. We constructed four reduced complexity models to describe the primary carbon fluxes, making different assumptions about how soil carbon fluxes are modelled in ESMs. For each of these reduced complexity models we statistically inferred the most likely model parameters given the gridded ESM simulation outputs. Gross primary production was best explained by incoming short wave radiation, CO2 concentration, and leaf area index (global GPP comparison of simulation vs reduced complexity model of R2>0.9 (p < 1e-4) with slopes between 0.65 and 1.2 and intercepts between -13 and 67 Pg C yr-1). Autotrophic respiration was best explained as a proportion of GPP (R2 > 0.9 (p < 1e-4) with slopes between 0.78 and 1.1 and intercepts between -15 and 14 Pg C yr-1). Flux between the vegetation and soil pools were best explained as a proportion of the vegetation carbon stock (R2 > 0.9 (p < 1e-4) with slopes between 0.9 and 2.1 and intercepts between -65 and 25 Pg C yr-1). Finally heterotrophic respiration was best explained as a function of soil carbon stocks and soil temperature (R2 > 0.9 (p < 1e-4) with slopes between 0.7 and 1.5 and intercepts between -40 and 15 Pg C yr-1). This research suggests three main lines of decomposition model improvement: 1) improve connecting sub-models, 2) data integration to improve parameterization, 3) modification of model structure. The implied variation in RCM parameterization suggests that data integration could constrain model simulation results. However, the similarity in model structure may lead to systematic biases in the simulations without the introduction of new model structures.

The Potential of Carbonyl Sulfide as a Tracer for Gross Primary Productivity at Flux Tower Sites

USDA-ARS?s Scientific Manuscript database

Regional/continental scale studies of atmospheric carbonyl sulfide (OCS) seasonal dynamics and leaf level studies of plant OCS uptake have shown a close relationship to CO2 dynamics and uptake, suggesting potential for OCS as a tracer for gross primary productivity (GPP). Canopy CO2 and OCS differen...

Responses of gross primary production of grasslands and croplands to drought and pluvial events and irrigation during 2010-2016, Oklahoma, USA

USDA-ARS?s Scientific Manuscript database

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 events. Oklahoma experienced extreme drought in 2011 and record-breaking precipitation in...

Linking climate, gross primary productivity, and site index across forests of the western United States

Treesearch

Aaron R. Weiskittel; Nicholas L. Crookston; Philip J. Radtke

2011-01-01

Assessing forest productivity is important for developing effective management regimes and predicting future growth. Despite some important limitations, the most common means for quantifying forest stand-level potential productivity is site index (SI). Another measure of productivity is gross primary production (GPP). In this paper, SI is compared with GPP estimates...

Impacts of droughts and extreme-temperature events on gross primary production and ecosystem respiration: a systematic assessment across ecosystems and climate zones

USDA-ARS?s Scientific Manuscript database

Extreme climatic events, such as droughts and heat stress induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underl...

Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI

USDA-ARS?s Scientific Manuscript database

Quantifying global carbon and water balances requires accurate estimation of gross primary production (GPP) and evapotranspiration (ET), respectively, across space and time. Models that are based on the theory of light use efficiency (LUE) and water use efficiency (WUE) have emerged as efficient met...

Uncertainty analysis of gross primary production partitioned from net ecosystem exchange measurements

NASA Astrophysics Data System (ADS)

Raj, R.; Hamm, N. A. S.; van der Tol, C.; Stein, A.

2015-08-01

Gross primary production (GPP), separated from flux tower measurements of net ecosystem exchange (NEE) of CO2, is used increasingly to validate process-based simulators and remote sensing-derived estimates of simulated GPP at various time steps. Proper validation should include the uncertainty associated with this separation at different time steps. This can be achieved by using a Bayesian framework. In this study, we estimated the uncertainty in GPP at half hourly time steps. We used a non-rectangular hyperbola (NRH) model to separate GPP from flux tower measurements of NEE at the Speulderbos forest site, The Netherlands. The NRH model included the variables that influence GPP, in particular radiation, and temperature. In addition, the NRH model provided a robust empirical relationship between radiation and GPP by including the degree of curvature of the light response curve. Parameters of the NRH model were fitted to the measured NEE data for every 10-day period during the growing season (April to October) in 2009. Adopting a Bayesian approach, we defined the prior distribution of each NRH parameter. Markov chain Monte Carlo (MCMC) simulation was used to update the prior distribution of each NRH parameter. This allowed us to estimate the uncertainty in the separated GPP at half-hourly time steps. This yielded the posterior distribution of GPP at each half hour and allowed the quantification of uncertainty. The time series of posterior distributions thus obtained allowed us to estimate the uncertainty at daily time steps. We compared the informative with non-informative prior distributions of the NRH parameters. The results showed that both choices of prior produced similar posterior distributions GPP. This will provide relevant and important information for the validation of process-based simulators in the future. Furthermore, the obtained posterior distributions of NEE and the NRH parameters are of interest for a range of applications.

Continuous estimation of evapotranspiration and gross primary productivity from an Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Wang, S.; Bandini, F.; Jakobsen, J.; J Zarco-Tejada, P.; Liu, X.; Haugård Olesen, D.; Ibrom, A.; Bauer-Gottwein, P.; Garcia, M.

2017-12-01

Model prediction of evapotranspiration (ET) and gross primary productivity (GPP) using optical and thermal satellite imagery is biased towards clear-sky conditions. Unmanned Aerial Systems (UAS) can collect optical and thermal signals at unprecedented very high spatial resolution (< 1 meter) under sunny and cloudy weather conditions. However, methods to obtain model outputs between image acquisitions are still needed. This study uses UAS based optical and thermal observations to continuously estimate daily ET and GPP in a Danish willow forest for an entire growing season of 2016. A hexacopter equipped with multispectral and thermal infrared cameras and a real-time kinematic Global Navigation Satellite System was used. The Normalized Differential Vegetation Index (NDVI) and the Temperature Vegetation Dryness Index (TVDI) were used as proxies for leaf area index and soil moisture conditions, respectively. To obtain continuously daily records between UAS acquisitions, UAS surface temperature was assimilated by the ensemble Kalman filter into a prognostic land surface model (Noilhan and Planton, 1989), which relies on the force-restore method, to simulate the continuous land surface temperature. NDVI was interpolated into daily time steps by the cubic spline method. Using these continuous datasets, a joint ET and GPP model, which combines the Priestley-Taylor Jet Propulsion Laboratory ET model (Fisher et al., 2008; Garcia et al., 2013) and the Light Use Efficiency GPP model (Potter et al., 1993), was applied. The simulated ET and GPP were compared with the footprint of eddy covariance observations. The simulated daily ET has a RMSE of 14.41 W•m-2 and a correlation coefficient of 0.83. The simulated daily GPP has a root mean square error (RMSE) of 1.56 g•C•m-2•d-1 and a correlation coefficient of 0.87. This study demonstrates the potential of UAS based multispectral and thermal mapping to continuously estimate ET and GPP for both sunny and cloudy weather conditions.

Asymmetric Responses of Primary Productivity to Altered Precipitation Simulated by Land Surface Models across Three Long-term Grassland Sites

NASA Astrophysics Data System (ADS)

Wu, D.; Ciais, P.; Viovy, N.; Knapp, A.; Wilcox, K.; Bahn, M.; Smith, M. D.; Ito, A.; Arneth, A.; Harper, A. B.; Ukkola, A.; Paschalis, A.; Poulter, B.; Peng, C.; Reick, C. H.; Hayes, D. J.; Ricciuto, D. M.; Reinthaler, D.; Chen, G.; Tian, H.; Helene, G.; Zscheischler, J.; Mao, J.; Ingrisch, J.; Nabel, J.; Pongratz, J.; Boysen, L.; Kautz, M.; Schmitt, M.; Krohn, M.; Zeng, N.; Meir, P.; Zhang, Q.; Zhu, Q.; Hasibeder, R.; Vicca, S.; Sippel, S.; Dangal, S. R. S.; Fatichi, S.; Sitch, S.; Shi, X.; Wang, Y.; Luo, Y.; Liu, Y.; Piao, S.

2017-12-01

Changes in precipitation variability including the occurrence of extreme events strongly influence plant growth in grasslands. Field measurements of aboveground net primary production (ANPP) in temperate grasslands suggest a positive asymmetric response with wet years resulting in ANPP gains larger than ANPP declines in dry years. Whether land surface models used for historical simulations and future projections of the coupled carbon-water system in grasslands are capable to simulate such non-symmetrical ANPP responses remains an important open research question. In this study, we evaluate the simulated responses of grassland primary productivity to altered precipitation with fourteen land surface models at the three sites of Colorado Shortgrass Steppe (SGS), Konza prairie (KNZ) and Stubai Valley meadow (STU) along a rainfall gradient from dry to wet. Our results suggest that: (i) Gross primary production (GPP), NPP, ANPP and belowground NPP (BNPP) show nonlinear response curves (concave-down) in all the models, but with different curvatures and mean values. In contrast across the sites, primary production increases and then saturates along increasing precipitation with a flattening at the wetter site. (ii) Slopes of spatial relationships between modeled primary production and precipitation are steeper than the temporal slopes (obtained from inter-annual variations). (iii) Asymmetric responses under nominal precipitation range with modeled inter-annual primary production show large uncertainties, and model-ensemble median generally suggests negative asymmetry (greater declines in dry years than increases in wet years) across the three sites. (iv) Primary production at the drier site is predicted to more sensitive to precipitation compared to wetter site, and median sensitivity consistently indicates greater negative impacts of reduced precipitation than positive effects of increased precipitation under extreme conditions. This study implies that most models overemphasize the drought effects or underestimate the watering impacts on primary production in the normal-state, with the direct consequence that carbon-water interactions need to be improved in future model generations with improved mechanistic representations.

Satellite-based modeling of gross primary production in an evergreen needleleaf forest

Treesearch

Xiangming Xiao; David Hollinger; John Aber; Mike Goltz; Eric A. Davidson; Qingyuan Zhang; Berrien Moore III

2004-01-01

The eddy covariance technique provides valuable information on net ecosystem exchange (NEE) of CO2, between the atmosphere and terrestrial ecosystems, ecosystem respiration, and gross primary production (GPP) at a variety of C02 eddy flux tower sites. In this paper, we develop a new, satellite-based Vegetation Photosynthesis Model (VPM) to estimate the seasonal dynamcs...

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process-based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process- based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

Sensitivity of Crop Gross Primary Production Simulations to In-situ and Reanalysis Meteorological Data

NASA Astrophysics Data System (ADS)

Jin, C.; Xiao, X.; Wagle, P.

2014-12-01

Accurate estimation of crop Gross Primary Production (GPP) is important for food securityand terrestrial carbon cycle. Numerous publications have reported the potential of the satellite-based Production Efficiency Models (PEMs) to estimate GPP driven by in-situ climate data. Simulations of the PEMs often require surface reanalysis climate data as inputs, for example, the North America Regional Reanalysis datasets (NARR). These reanalysis datasets showed certain biases from the in-situ climate datasets. Thus, sensitivity analysis of the PEMs to the climate inputs is needed before their application at the regional scale. This study used the satellite-based Vegetation Photosynthesis Model (VPM), which is driven by solar radiation (R), air temperature (T), and the satellite-based vegetation indices, to quantify the causes and degree of uncertainties in crop GPP estimates due to different meteorological inputs at the 8-day interval (in-situ AmeriFlux data and NARR surface reanalysis data). The NARR radiation (RNARR) explained over 95% of the variability in in-situ RAF and TAF measured from AmeriFlux. The bais of TNARR was relatively small. However, RNARR had a systematical positive bias of ~3.5 MJ m-2day-1 from RAF. A simple adjustment based on the spatial statistic between RNARR and RAF produced relatively accurate radiation data for all crop site-years by reducing RMSE from 4 to 1.7 MJ m-2day-1. The VPM-based GPP estimates with three climate datasets (i.e., in-situ, and NARR before and after adjustment, GPPVPM,AF, GPPVPM,NARR, and GPPVPM,adjNARR) showed good agreements with the seasonal dynamics of crop GPP derived from the flux towers (GPPAF). The GPPVPM,AF differed from GPPAF by 2% for maize, and -8% to -12% for soybean on the 8-day interval. The positive bias of RNARR resulted in an overestimation of GPPVPM,NARR at both maize and soybean systems. However, GPPVPM,adjNARR significantly reduced the uncertainties of the maize GPP from 25% to 2%. The results from this study revealed that the errors of the NARR surface reanalysis data introduced significant uncertainties of the PEMs-based GPP estimates. Therefore, it is important to develop more accurate radiation datasets at the regional and global scales to estimate gross and net primary production of terrestrial ecosystems at the regional and global scales.

Curricular Guidelines in Gross Anatomy.

ERIC Educational Resources Information Center

Horn, Stanton D.; And Others

1981-01-01

An outline of AADS curricular guidelines for gross anatomy in dental education includes primary educational goals, prerequisites, core content, specific course objectives for each section of content, sequencing, faculty requirements, and facility and equipment needs. (MSE)

Seasonal and Inter-Annual Variations in Carbon Dioxide Exchange over an Alpine Grassland in the Eastern Qinghai-Tibetan Plateau.

PubMed

Shang, Lunyu; Zhang, Yu; Lyu, Shihua; Wang, Shaoying

2016-01-01

This work analyzed carbon dioxide exchange and its controlling factors over an alpine grassland on the eastern Qinghai-Tibetan Plateau. The main results show that air temperature and photosynthetically active radiation are two dominant factors controlling daily gross primary production. Soil temperature and soil water content are the main factors controlling ecosystem respiration. Canopy photosynthetic activity is also responsible for the variation of daily ecosystem respiration other than environmental factors. No clear correlation between net ecosystem exchange and environmental factors was observed at daily scale. Temperature sensitive coefficient was observed to increase with larger soil water content. High values of temperature sensitive coefficient occurred during the periods when soil water content was high and grass was active. Annual integrated net ecosystem exchange, gross primary production and ecosystem respiration were -191, 1145 and 954 g C m-2 for 2010, and -250, 975 and 725 g C m-2 for 2011, respectively. Thus, this alpine grassland was a moderate carbon sink in both of the two years. Compared to alpine grasslands on the Qinghai-Tibetan Plateau, this alpine grassland demonstrated a much greater potential for carbon sequestration than others. Annual precipitation is a dominant factor controlling the variation of annual net ecosystem exchange over this grassland. The difference in gross primary production between the two years was not caused by the variation in annual precipitation. Instead, air temperature and the length of growing season had an important impact on annual gross primary production. Variation of annual ecosystem respiration was closely related to annual gross primary production and soil water content during the growing season.

Seasonal and Inter-Annual Variations in Carbon Dioxide Exchange over an Alpine Grassland in the Eastern Qinghai-Tibetan Plateau

PubMed Central

Shang, Lunyu; Zhang, Yu; Lyu, Shihua; Wang, Shaoying

2016-01-01

This work analyzed carbon dioxide exchange and its controlling factors over an alpine grassland on the eastern Qinghai-Tibetan Plateau. The main results show that air temperature and photosynthetically active radiation are two dominant factors controlling daily gross primary production. Soil temperature and soil water content are the main factors controlling ecosystem respiration. Canopy photosynthetic activity is also responsible for the variation of daily ecosystem respiration other than environmental factors. No clear correlation between net ecosystem exchange and environmental factors was observed at daily scale. Temperature sensitive coefficient was observed to increase with larger soil water content. High values of temperature sensitive coefficient occurred during the periods when soil water content was high and grass was active. Annual integrated net ecosystem exchange, gross primary production and ecosystem respiration were -191, 1145 and 954 g C m-2 for 2010, and -250, 975 and 725 g C m-2 for 2011, respectively. Thus, this alpine grassland was a moderate carbon sink in both of the two years. Compared to alpine grasslands on the Qinghai-Tibetan Plateau, this alpine grassland demonstrated a much greater potential for carbon sequestration than others. Annual precipitation is a dominant factor controlling the variation of annual net ecosystem exchange over this grassland. The difference in gross primary production between the two years was not caused by the variation in annual precipitation. Instead, air temperature and the length of growing season had an important impact on annual gross primary production. Variation of annual ecosystem respiration was closely related to annual gross primary production and soil water content during the growing season. PMID:27861616

[Collaborative application of BEPS at different time steps.

PubMed

Lu, Wei; Fan, Wen Yi; Tian, Tian

2016-09-01

BEPSHourly is committed to simulate the ecological and physiological process of vegetation at hourly time steps, and is often applied to analyze the diurnal change of gross primary productivity (GPP), net primary productivity (NPP) at site scale because of its more complex model structure and time-consuming solving process. However, daily photosynthetic rate calculation in BEPSDaily model is simpler and less time-consuming, not involving many iterative processes. It is suitable for simulating the regional primary productivity and analyzing the spatial distribution of regional carbon sources and sinks. According to the characteristics and applicability of BEPSDaily and BEPSHourly models, this paper proposed a method of collaborative application of BEPS at daily and hourly time steps. Firstly, BEPSHourly was used to optimize the main photosynthetic parameters: the maximum rate of carboxylation (V c max ) and the maximum rate of photosynthetic electron transport (J max ) at site scale, and then the two optimized parameters were introduced into BEPSDaily model to estimate regional NPP at regional scale. The results showed that optimization of the main photosynthesis parameters based on the flux data could improve the simulate ability of the model. The primary productivity of different forest types in descending order was deciduous broad-leaved forest, mixed forest, coniferous forest in 2011. The collaborative application of carbon cycle models at different steps proposed in this study could effectively optimize the main photosynthesis parameters V c max and J max , simulate the monthly averaged diurnal GPP, NPP, calculate the regional NPP, and analyze the spatial distribution of regional carbon sources and sinks.

Gross Motor Activities: Movement for Fun and Learning.

ERIC Educational Resources Information Center

Lowenthal, Barbara

1983-01-01

Examples are provided of ways in which gross motor activities are integrated into mathematics, language arts, social studies, art, and music and creative movement concepts for preschool- and primary-age children with special needs. (CL)

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

Treesearch

Heather L. Kimball; Paul C. Selmants; Alvaro Moreno; Steve W. Running; Christian P. Giardina; Benjamin Poulter

2017-01-01

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the...

Intercomparison of terrestrial carbon fluxes and carbon use efficiency simulated by CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Kim, Dongmin; Lee, Myong-In; Jeong, Su-Jong; Im, Jungho; Cha, Dong Hyun; Lee, Sanggyun

2017-12-01

This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

Description and validation of the Simple, Efficient, Dynamic, Global, Ecological Simulator (SEDGES v.1.0)

NASA Astrophysics Data System (ADS)

Paiewonsky, Pablo; Elison Timm, Oliver

2018-03-01

In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.

Modeling of carbon dioxide condensation in the high pressure flows using the statistical BGK approach

NASA Astrophysics Data System (ADS)

Kumar, Rakesh; Li, Zheng; Levin, Deborah A.

2011-05-01

In this work, we propose a new heat accommodation model to simulate freely expanding homogeneous condensation flows of gaseous carbon dioxide using a new approach, the statistical Bhatnagar-Gross-Krook method. The motivation for the present work comes from the earlier work of Li et al. [J. Phys. Chem. 114, 5276 (2010)] in which condensation models were proposed and used in the direct simulation Monte Carlo method to simulate the flow of carbon dioxide from supersonic expansions of small nozzles into near-vacuum conditions. Simulations conducted for stagnation pressures of one and three bar were compared with the measurements of gas and cluster number densities, cluster size, and carbon dioxide rotational temperature obtained by Ramos et al. [Phys. Rev. A 72, 3204 (2005)]. Due to the high computational cost of direct simulation Monte Carlo method, comparison between simulations and data could only be performed for these stagnation pressures, with good agreement obtained beyond the condensation onset point, in the farfield. As the stagnation pressure increases, the degree of condensation also increases; therefore, to improve the modeling of condensation onset, one must be able to simulate higher stagnation pressures. In simulations of an expanding flow of argon through a nozzle, Kumar et al. [AIAA J. 48, 1531 (2010)] found that the statistical Bhatnagar-Gross-Krook method provides the same accuracy as direct simulation Monte Carlo method, but, at one half of the computational cost. In this work, the statistical Bhatnagar-Gross-Krook method was modified to account for internal degrees of freedom for multi-species polyatomic gases. With the computational approach in hand, we developed and tested a new heat accommodation model for a polyatomic system to properly account for the heat release of condensation. We then developed condensation models in the framework of the statistical Bhatnagar-Gross-Krook method. Simulations were found to agree well with the experiment for all stagnation pressure cases (1-5 bar), validating the accuracy of the Bhatnagar-Gross-Krook based condensation model in capturing the physics of condensation.

Relationship between habitual physical activity and gross motor skills is multifaceted in 5- to 8-year-old children.

PubMed

Laukkanen, A; Pesola, A; Havu, M; Sääkslahti, A; Finni, T

2014-04-01

Adequate motor skills are essential for children participating in age-related physical activities, and gross motor skills may play an important role for maintaining sufficient level of physical activity (PA) during life course. The purpose of this study was to examine the relationship between gross motor skills and PA in children when PA was analyzed by both metabolic- and neuromuscular-based methods. Gross motor skills (KTK--Körperkoordinationstest für Kinder and APM inventory--manipulative skill test) of 84 children aged 5-8 years (53 preschoolers, 28 girls; 31 primary schoolers, 18 girls) were measured, and accelerometer-derived PA was analyzed using in parallel metabolic counts and neuromuscular impact methods. The gross motor skills were associated with moderate-to-high neuromuscular impacts, PA of vigorous metabolic intensity, and mean level of PA in primary school girls (0.5 < r < 0.7, P < 0.05), and with high impacts in preschool girls (0.3 < r < 0.5, P < 0.05). In preschool boys, moderate impacts, light-to-vigorous PA, and mean level of PA were associated with gross motor skills (0.4 < r < 0.7, P < 0.05). In conclusion, the result emphasizes an important relationship between gross motor skills and PA stressing both metabolic and neuromuscular systems in children. Furthermore, PA highly stressing neuromuscular system interacts with gross motor proficiency in girls especially. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone

USGS Publications Warehouse

Liu, Shu-Guang; Reiners, William A.; Keller, Michael; Schimel, Davis S.

2000-01-01

WFPS is the dominant determinant of the fraction of gross N mineralization that is emitted from the soil as N2O and NO. If WFPS were not limiting during part of the year, this fraction would be 4.2%. With some periods of lower WFPS, the realized fraction is 2.2%. Because of the strong relationships between N2O and NO emission rates and rainfall and its derivative, WFPS, these moisture variables can be used to scale up nitrogen trace gas fluxes from sites to larger spatial scales.

Respiration of new and old carbon in the surface ocean: Implications for estimates of global oceanic gross primary productivity

NASA Astrophysics Data System (ADS)

Carvalho, Matheus C.; Schulz, Kai G.; Eyre, Bradley D.

2017-06-01

New respiration (Rnew, of freshly fixated carbon) and old respiration (Rold, of storage carbon) were estimated for different regions of the global surface ocean using published data on simultaneous measurements of the following: (1) primary productivity using 14C (14PP); (2) gross primary productivity (GPP) based on 18O or O2; and (3) net community productivity (NCP) using O2. The ratio Rnew/GPP in 24 h incubations was typically between 0.1 and 0.3 regardless of depth and geographical area, demonstrating that values were almost constant regardless of large variations in temperature (0 to 27°C), irradiance (surface to 100 m deep), nutrients (nutrient-rich and nutrient-poor waters), and community composition (diatoms, flagellates, etc,). As such, between 10 and 30% of primary production in the surface ocean is respired in less than 24 h, and most respiration (between 55 and 75%) was of older carbon. Rnew was most likely associated with autotrophs, with minor contribution from heterotrophic bacteria. Patterns were less clear for Rold. Short 14C incubations are less affected by respiratory losses. Global oceanic GPP is estimated to be between 70 and 145 Gt C yr-1.