Science.gov

Sample records for primary production gpp

  1. Improving North American gross primary production (GPP) estimates using atmospheric measurements of carbonyl sulfide (COS)

    NASA Astrophysics Data System (ADS)

    Chen, Huilin; Montzka, Steve; Andrews, Arlyn; Sweeney, Colm; Jacobson, Andy; Miller, Ben; Masarie, Ken; Jung, Martin; Gerbig, Christoph; Campbell, Elliott; Abu-Naser, Mohammad; Berry, Joe; Baker, Ian; Tans, Pieter

    2013-04-01

    Understanding the responses of gross primary production (GPP) to climate change is essential for improving our prediction of climate change. To this end, it is important to accurately partition net ecosystem exchange of carbon into GPP and respiration. Recent studies suggest that carbonyl sulfide is a useful tracer to provide a constraint on GPP, based on the fact that both COS and CO2 are simultaneously taken up by plants and the quantitative correlation between GPP and COS plant uptake. We will present an assessment of North American GPP estimates from the Simple Biosphere (SiB) model, the Carnegie-Ames-Stanford Approach (CASA) model, and the MPI-BGC model through atmospheric transport simulations of COS in a receptor oriented framework. The newly upgraded Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) will be employed to compute the influence functions, i.e. footprints, to link the surface fluxes to the concentration changes at the receptor observations. The HYSPLIT is driven by the 3-hourly archived NAM 12km meteorological data from NOAA NCEP. The background concentrations are calculated using empirical curtains along the west coast of North America that have been created by interpolating in time and space the observations at the NOAA/ESRL marine boundary layer stations and from aircraft vertical profiles. The plant uptake of COS is derived from GPP estimates of biospheric models. The soil uptake and anthropogenic emissions are from Kettle et al. 2002. In addition, we have developed a new soil flux map of COS based on observations of molecular hydrogen (H2), which shares a common soil uptake term but lacks a vegetative sink. We will also improve the GPP estimates by assimilating atmospheric observations of COS in the receptor oriented framework, and then present the assessment of the improved GPP estimates against variations of climate variables such as temperature and precipitation.

  2. Global 4 km resolution monthly gridded Gross Primary Productivity (GPP) data set derived from FLUXNET2015

    DOE Data Explorer

    Kumar, Jitendra; Hoffman, Forrest M.; Hargrove, William W.; Collier, Nathan

    2016-08-01

    This data set contain global gridded surfaces of Gross Primary Productivity (GPP) at 2 arc minute (approximately 4 km) spatial resolution monthly for the period of 2000-2014 derived from FLUXNET2015 (released July 12, 2016) observations using a representativeness based upscaling approach.

  3. Estimation of Crop Gross Primary Production (GPP). 2; Do Scaled (MODIS) Vegetation Indices Improve Performance?

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.

    2015-01-01

    Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the

  4. 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

  5. How drought severity constrains gross primary production(GPP) and its partitioning among carbon pools in a Quercus ilex coppice?

    NASA Astrophysics Data System (ADS)

    Rambal, S.; Lempereur, M.; Limousin, J. M.; Martin-StPaul, N. K.; Ourcival, J. M.; Rodríguez-Calcerrada, J.

    2014-12-01

    The partitioning of photosynthates toward biomass compartments plays a crucial role in the carbon (C) sink function of forests. Few studies have examined how carbon is allocated toward plant compartments in drought-prone forests. We analyzed the fate of gross primary production (GPP) in relation to yearly water deficit in an old evergreen Mediterranean Quercus ilex coppice severely affected by water limitations. Carbon fluxes between the ecosystem and the atmosphere were measured with an eddy covariance flux tower running continuously since 2001. Discrete measurements of litterfall, stem growth and fAPAR allowed us to derive annual productions of leaves, wood, flowers and acorns, and an isometric relationship between stem and belowground biomass has been used to estimate perennial belowground growth. By combining eddy covariance fluxes with annual net primary productions (NPP), we managed to close a C budget and derive values of autotrophic, heterotrophic respirations and carbon-use efficiency (CUE; the ratio between NPP and GPP). Average values of yearly net ecosystem production (NEP), GPP and Reco were 282, 1259 and 977 g C m-2. The corresponding aboveground net primary production (ANPP) components were 142.5, 26.4 and 69.6 g C m-2 for leaves, reproductive effort (flowers and fruits) and stems, respectively. NEP, GPP and Reco were affected by annual water deficit. Partitioning to the different plant compartments was also impacted by drought, with a hierarchy of responses going from the most affected - the stem growth - to the least affected - the leaf production. The average CUE was 0.40, which is well in the range for Mediterranean-type forest ecosystems. CUE tended to decrease less drastically in response to drought than GPP and NPP did, probably due to drought acclimation of autotrophic respiration. Overall, our results provide a baseline for modeling the inter-annual variations of carbon fluxes and allocation in this widespread Mediterranean ecosystem, and

  6. Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Xiao, Xiangming; Suyker, Andrew; Verma, Shashi; Tan, Bin; Middleton, Elizabeth M.

    2014-01-01

    Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) = 35? to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA = 35?. The fourth experiment included only backscatter observations with VZA = 35?. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation

  7. Evaluating drought effect on MODIS Gross Primary Production (GPP) with an eco-hydrological model in the mountainous forest, East Asia.

    NASA Astrophysics Data System (ADS)

    Hwang, T.; Kang, S.; Kim, J.; Kim, Y.; Lee, D.; Band, L.

    2008-05-01

    Surface soil moisture dynamics is a key link between climate fluctuation and vegetation dynamics in space and time. In East Asia, precipitation is concentrated in the short monsoon season which reduces plants water availability in the dry season. Furthermore, most forests are located in mountainous areas because of high demand for agricultural land, which results in increased lateral water flux and uneven distribution of plant available water. These climatic and topographic features of the forests make them more vulnerable to drought conditions. In this study, the eco-hydrological model (RHESSys) is validated with various water and carbon flux measurements in a small catchment in Korea. The model is then extended to the regional scale with fine- resolution remote sensing data to evaluate the Moderate Resolution Imaging Radiometer (MODIS) leaf area index (LAI) and gross primary productivity (GPP) products. Long-term model runs simulated severe drought effect in 2001 well, which is clearly shown in the ring increment data. However, MODIS GPP does not capture this drought effect in 2001 which might be from a simplified treatment of water stress in the MODIS GPP algorithm. This study shows that the MODIS GPP products can potentially overestimate carbon uptake specifically during drought conditions driven by soil water stress.

  8. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

    NASA Astrophysics Data System (ADS)

    Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

    2010-12-01

    Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

  9. Comparison of Modeling Approaches for Carbon Partitioning: Impact on Estimates of Global Net Primary Production and Equilibrium Biomass of Woody Vegetation from MODIS GPP

    NASA Astrophysics Data System (ADS)

    Ise, T.; Litton, C. M.; Giardina, C. P.; Ito, A.

    2009-12-01

    Plant partitioning of carbon (C) to above- vs. belowground, to growth vs. respiration, and to short vs. long lived tissues exerts a large influence on ecosystem structure and function with implications for the global C budget. Importantly, outcomes of process-based terrestrial vegetation models are likely to vary substantially with different C partitioning algorithms. However, controls on C partitioning patterns remain poorly quantified, and studies have yielded variable, and at times contradictory, results. A recent meta-analysis of forest studies suggests that the ratio of net primary production (NPP) and gross primary production (GPP) is fairly conservative across large scales. To illustrate the effect of this unique meta-analysis-based partitioning scheme (MPS), we compared an application of MPS to a terrestrial satellite-based (MODIS) GPP to estimate NPP vs. two global process-based vegetation models (Biome-BGC and VISIT) to examine the influence of C partitioning on C budgets of woody plants. Due to the temperature dependence of maintenance respiration, NPP/GPP predicted by the process-based models increased with latitude while the ratio remained constant with MPS. Overall, global NPP estimated with MPS was 17 and 27% lower than the process-based models for temperate and boreal biomes, respectively, with smaller differences in the tropics. Global equilibrium biomass of woody plants was then calculated from the NPP estimates and tissue turnover rates from VISIT. Since turnover rates differed greatly across tissue types (i.e., metabolically active vs. structural), global equilibrium biomass estimates were sensitive to the partitioning scheme employed. The MPS estimate of global woody biomass was 7-21% lower than that of the process-based models. In summary, we found that model output for NPP and equilibrium biomass was quite sensitive to the choice of C partitioning schemes. Carbon use efficiency (CUE; NPP/GPP) by forest biome and the globe. Values are means

  10. Estimation of crop gross primary production (GPP): fAPAR_chl versus MOD15A2 FPAR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Within leaf chloroplasts chlorophylls absorb photosynthetically active radiation (PAR) for photosynthesis (PSN). The MOD15A2 FPAR (fraction of PAR absorbed by canopy, i.e., fAPARcanopy) product has been widely used to compute absorbed PAR for PSN (APARPSN). The MOD17A2 algorithm uses MOD15A2 FPAR i...

  11. A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation

    NASA Astrophysics Data System (ADS)

    Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.

    2003-12-01

    Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.

  12. GPP estimates in a biodiesel crop using MERIS products

    NASA Astrophysics Data System (ADS)

    Sánchez, M. L.; Pardo, N.; Pérez, I.; García, M. A.; Paredes, V.

    2012-04-01

    Greenhouse gas emissions in Spain in 2008-2009 were 34.3 % higher than the base-year level, significantly above the burden-sharing target of 15 % for the period 2008-2012. Based on this result, our country will need to make a major effort to meet the committed target on time using domestic measures as well as others foreseen in the Kyoto Protocol, such as LULUFC activities. In this framework, agrofuels, in other words biofuels produced by crops that contain high amounts of vegetable oil such as sorghum, sunflower, rape seed and jatropha, appear to be an interesting mitigation alternative. Bearing in mind the meteorological conditions in Spain, sunflower and rape seed in particular are considered the most viable crops. Sunflower cultivated surface in Spain has remained fairly constant in recent years, in contrast to rapeseed crop surface which, although still scarce, has followed an increasing trend. In order to assess rape seed ability as a CO2 sink as well as to describe GPP dynamic evolution, we installed an eddy correlation station in an agricultural plot of the Spanish plateau. Measurements at the plot consisted of 30-min NEE flux measurements (using a LI-7500 and a METEK USA-1 sonic anemometer) as well as other common meteorological variables. Measurements were performed from March to October. This paper presents the results of the GPP 8-d estimated values using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MERIS, the PAR in situ measurements, and a scalar f varying, between 0 and 1, to take into account the reduction of the maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. The f values were assumed to be dependent on air temperature and the evaporative fraction, EF, which was considered as a proxy of soil moisture. ɛ0, a key parameter, which depends on biome types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites

  13. The architecture and ppGpp-dependent expression of the primary transcriptome of Salmonella Typhimurium during invasion gene expression

    PubMed Central

    2012-01-01

    Background Invasion of intestinal epithelial cells by Salmonella enterica serovar Typhimurium (S. Typhimurium) requires expression of the extracellular virulence gene expression programme (STEX), activation of which is dependent on the signalling molecule guanosine tetraphosphate (ppGpp). Recently, next-generation transcriptomics (RNA-seq) has revealed the unexpected complexity of bacterial transcriptomes and in this report we use differential RNA sequencing (dRNA-seq) to define the high-resolution transcriptomic architecture of wild-type S. Typhimurium and a ppGpp null strain under growth conditions which model STEX. In doing so we show that ppGpp plays a much wider role in regulating the S. Typhimurium STEX primary transcriptome than previously recognised. Results Here we report the precise mapping of transcriptional start sites (TSSs) for 78% of the S. Typhimurium open reading frames (ORFs). The TSS mapping enabled a genome-wide promoter analysis resulting in the prediction of 169 alternative sigma factor binding sites, and the prediction of the structure of 625 operons. We also report the discovery of 55 new candidate small RNAs (sRNAs) and 302 candidate antisense RNAs (asRNAs). We discovered 32 ppGpp-dependent alternative TSSs and determined the extent and level of ppGpp-dependent coding and non-coding transcription. We found that 34% and 20% of coding and non-coding RNA transcription respectively was ppGpp-dependent under these growth conditions, adding a further dimension to the role of this remarkable small regulatory molecule in enabling rapid adaptation to the infective environment. Conclusions The transcriptional architecture of S. Typhimurium and finer definition of the key role ppGpp plays in regulating Salmonella coding and non-coding transcription should promote the understanding of gene regulation in this important food borne pathogen and act as a resource for future research. PMID:22251276

  14. Remote estimation of crop gross primary production with Landsat data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An accurate and synoptic quantification of gross primary productivity (GPP) in crops is essential for studies of carbon budgets at regional and global scales. In this study, we developed a model relating crop GPP to a product of total canopy chlorophyll (Chl) content and potential incident photosynt...

  15. Gross Primary Productivity

    NASA Technical Reports Server (NTRS)

    2002-01-01

    NASA's new Moderate-resolution Imaging Spectroradiometer (MODIS) allows scientists to gauge our planet's metabolism on an almost daily basis. GPP, gross primary production, is the technical term for plant photosynthesis. This composite image over the continental United States, acquired during the period March 26-April 10, 2000, shows regions where plants were more or less productive-i.e., where they 'inhaled' carbon dioxide and then used the carbon from photosynthesis to build new plant structures. This false-color image provides a map of how much carbon was absorbed out of the atmosphere and fixed within land vegetation. Areas colored blue show where plants used as much as 60 grams of carbon per square meter. Areas colored green and yellow indicate a range of anywhere from 40 to 20 grams of carbon absorbed per square meter. Red pixels show an absorption of less than 10 grams of carbon per square meter and white pixels (often areas covered by snow or masked as urban) show little or no absorption. This is one of a number of new measurements that MODIS provides to help scientists understand how the Earth's landscapes are changing over time. Scientists' goal is use of these GPP measurements to refine computer models to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. The GPP will be an integral part of global carbon cycle source and sink analysis, an important aspect of Kyoto Protocol assessments. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana

  16. Modeling gross primary production of deciduous forest using remotely sensed radiation and ecosystem variables

    NASA Astrophysics Data System (ADS)

    Jahan, Nasreen; Gan, Thian Yew

    2009-12-01

    We explored the potential application of two remotely sensed (RS) variables, the Global Vegetation Moisture Index (GVMI) and the near-infrared albedo (AlbedoNIR), in modeling the gross primary production (GPP) of three deciduous forests. For the Harvard Forest (deciduous) of Massachusetts, it was found that GPP is strongly correlated with GVMI (coefficient of determination, R2 = 0.60) during the growing season, and with AlbedoNIR (R2 = 0.82) throughout the year. Subsequently, a statistical model called the Remotely Sensed GPP (R-GPP) model was developed to estimate GPP using remotely sensed radiation (land surface temperature (LST), AlbedoNIR) and ecosystem variables (enhanced vegetation index (EVI) and GVMI). The R-GPP model, calibrated and validated against the GPP estimates derived from the eddy covariance flux tower of the Harvard Forest, could explain 95% and 92% of the observed GPP variability for the study site during the calibration (2000-2003) and the validation (2004-2005) periods, respectively. It outperformed the primary RS-based GPP algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS), which explained 80% and 77% of the GPP variability during 2000-2003 and 2004-2005, respectively. The calibrated R-GPP model also explained 93% and 94% of the observed GPP variation for two other independent validation sites, the Morgan Monroe State Forest and the University of Michigan Biological Station, respectively, which demonstrates its transferability to other deciduous ecoregions of northeastern United States.

  17. RelA-Dependent (p)ppGpp Production Controls Exoenzyme Synthesis in Erwinia carotovora subsp. atroseptica▿

    PubMed Central

    Wang, Jinhong; Gardiol, Noemie; Burr, Tom; Salmond, George P. C.; Welch, Martin

    2007-01-01

    In this report, we investigate the link between nutrient limitation, RelA-mediated (p)ppGpp production, and virulence in the phytopathogen Erwinia carotovora subsp. atroseptica. A relA null mutant (JWC7) was constructed by allelic exchange, and we confirmed that, unlike the wild-type progenitor, this mutant did not produce elevated levels of (p)ppGpp upon nutrient downshift. However, (p)ppGpp production could be restored in strain JWC7 during nutrient limitation by supplying relA in trans. During growth on exoenzyme-inducing minimal medium, the relA mutant showed a diminution in secreted pectate lyase and protease activities and a severe defect in motility. The relA mutant was also impaired in its ability to cause rot in potato tubers. In the presence of serine hydroxamate (a competitive inhibitor of seryl tRNA synthase and a potent inducer of the stringent response in wild-type E. carotovora subsp. atroseptica), exoenzyme production was essentially abolished in JWC7 but could be restored in the presence of plasmid-borne relA. The inhibition of exoenzyme production in JWC7 caused by serine hydroxamate could not be overcome by addition of the quorum-sensing signal molecule, N-3-oxohexanoyl-l-homoserine lactone. Quantitative reverse transcription-PCR analysis of selected RNA species confirmed that the effects of relA on secreted pectate lyase activity and motility could be attributed to a reduction in transcription of the corresponding genes. We conclude that nutrient limitation is a potent environmental cue that triggers (p)ppGpp-dependent exoenzyme production in E. carotovora subsp. atroseptica. Furthermore, our data suggest that nutrient limitation [or rather, (p)ppGpp accumulation] is a prerequisite for effective quorum-sensing-dependent activation of exoenzyme production. PMID:17766416

  18. Global GPP based on Plant Functional Types

    NASA Astrophysics Data System (ADS)

    Veroustraete, Frank; Balzarolo, Manuela

    2016-04-01

    Vegetation variables like Gross Primary productivity (GPP) and the Normalized Difference Vegetation Index (NDVI) are key variables in vegetation carbon exchange studies. Field measurements of the NDVI are time consuming due to landscape heterogeneity across time. Typically a sampling protocol adopted during field campaigns is based on the VALERI protocol in that case toe estimate LAI. Field campaign GPP or NDVI measurements can be scaled up to using in-situ FLUXNET radiation raster maps. Regression analysis can then be applied to construct transfer functions for the determination of GPP raster maps raster imagery from Normalized Difference Vegetation Index (NDVI) raster maps derived from in-situ FLUXNET radiation raster maps. Subsequently, in the VALERI approach the scaling up of raster maps is performed by aggregation of high resolution in-situ FLUXNET radiation raster maps data into high resolution raster maps and subsequently aggregating these to 1x1 km MODIS NDVI raster maps by calculating average NDVI values for the low resolution data. The up-scaled 1x1 km pixels are then used to validate the MODIS GPP and NVI products. Hence up scaling based on in-situ FLUXNET radiation measurements are not a luxury for large and heterogeneous sites. Therefore this paper tackles the problem of up scaling using in-situ FLUXNET radiation measurements. Key Words: FLUXNET, GPP, Plant Functional Types, Up-scaling

  19. 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

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

    PubMed

    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; Montagnani, Leonardo; Moors, Eddy J; Olesen, Jørgen E; Piao, Shilong; Raschi, Antonio; Roupsard, Olivier; Suyker, Andrew E; Urbaniak, Marek; Vaccari, Francesco P; Varlagin, Andrej; Vesala, Timo; Wilkinson, Matthew; Weng, Ensheng; Wohlfahrt, Georg; Yan, Liming; Luo, Yiqi

    2015-03-01

    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 (r(2) = 0.90) and GPP recovery after a fire disturbance in South Dakota (r(2) = 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

  1. A spatial implementation of the BIOME-BGC to model grassland GPP production and water budgets in the Ecuadorian Andean Region

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Many terrestrial biogeochemistry process models have been applied around the world at different scales and for a large range of ecosystems. Grasslands, and in particular the ones located in the Andean Region are essential ecosystems that sustain important ecological processes; however, just a few efforts have been made to estimate the gross primary production (GPP) and the hydrological budgets for this specific ecosystem along an altitudinal gradient. A previous study, which is one of the few available in the region, considered the heterogeneity of the main properties of the páramo vegetation and showed significant differences in plant functional types, site/soil parameters and daily meteorology. This study extends the work above mentioned and uses spatio-temporal analysis of the BIOME-BGC model results. This was done to simulate the GPP and the water fluxes in space and time, by applying altitudinal analysis. The catchment located at the southwestern slope of the Antisana volcano in Ecuador was selected as a representative area of the Andean páramos and its hydrological importance as one of the main sources of a water supply reservoir in the region. An accurate estimation of temporal changes in GPP in the region is important for carbon budget assessments, evaluation of the impact of climate change and biomass productivity. This complex and yet interesting problem was integrated by the ecosystem process model BIOME-BGC, the results were evaluated and associated to the land cover map where the growth forms of vegetation were identified. The responses of GPP and the water fluxes were not only dependent on the environmental drivers but also on the ecophysiology and the site specific parameters. The model estimated that the GPP at lower elevations doubles the amount estimated at higher elevations, which might have a large implication during extrapolations at larger spatio-temporal scales. The outcomes of the stand hydrological processes demonstrated a wrong

  2. 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.

  3. Variability in light-use efficiency for gross primary productivity on Great Plains grasslands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Gross primary productivity (GPP) often is estimated at regional scales by multiplying the amount of photosynthetically active radiation (PAR) absorbed by the plant canopy (PARa) by light-use efficiency (eg; GPP/PARa). Mass flux techniques are being used to calculate eg. Flux-based estimates of eg ...

  4. Primary Productivity in Meduxnekeag River, Maine, 2005

    USGS Publications Warehouse

    Goldstein, Robert M.; Schalk, Charles W.; Kempf, Joshua P.

    2009-01-01

    During August and September 2005, dissolved oxygen, temperature, pH, specific conductance, streamflow, and light intensity (LI) were determined continuously at six sites defining five reaches on Meduxnekeag River above and below Houlton, Maine. These data were collected as input for a dual-station whole-stream metabolism model to evaluate primary productivity in the river above and below Houlton. The river receives nutrients and organic matter from tributaries and the Houlton wastewater treatment plant (WWTP). Model output estimated gross and net primary productivity for each reach. Gross primary productivity (GPP) varied in each reach but was similar and positive among the reaches. GPP was correlated to LI in the four reaches above the WWTP but not in the reach below. Net primary productivity (NPP) decreased in each successive downstream reach and was negative in the lowest two reaches. NPP was weakly related to LI in the upper two reaches and either not correlated or negatively correlated in the lower three reaches. Relations among GPP, NPP, and LI indicate that the system is heterotrophic in the downstream reaches. The almost linear decrease in NPP (the increase in metabolism and respiration) indicates a cumulative effect of inputs of nutrients and organic matter from tributaries that drain agricultural land, the town of Houlton, and the discharges from the WWTP.

  5. Estimation of gross primary production capacity from global satellite observations

    NASA Astrophysics Data System (ADS)

    Muramatsu, Kanako; Thanyapraneedkul, Juthasinee; Furumi, Shinobu; Soyama, Noriko; Daigo, Motomasa

    2012-10-01

    To estimate gross primary production (GPP), the process of photosynthesis was considered as two separate phases: capacity and reduction. The reduction phase is influenced by environmental conditions such as soil moisture and weather conditions such as vapor pressure differences. For a particular leaf, photosynthetic capacity mainly depends on the amount of chlorophyll and the RuBisCO enzyme. The chlorophyll content can be estimated by the color of the leaf, and leaf color can be detected by optical sensors. We used the chlorophyll content of leaves to estimate the level of GPP. A previously developed framework for GPP capacity estimation employs a chlorophyll index. The index is based on the linear relationship between the chlorophyll content of a leaf and the maximum photosynthesis at PAR =2000 (μmolm -2s-1) on a light-response curve under low stress conditions. As a first step, this study examined the global distribution of the index and found that regions with high chlorophyll index values in winter corresponded to tropical rainforest areas. The seasonal changes in the chlorophyll index differed from those shown by the normalized difference vegetation index. Next, the capacity of GPP was estimated from the light-response curve using the index. Most regions exhibited a higher GPP capacity than that estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, except in areas of tropical rainforest, where the GPP capacity and the MODIS GPP estimates were almost identical.

  6. Evaluation of the Empirical Piecewise Regression Model in Simulating GPP in the Northern Great Plains

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Wylie, B. K.; Fosnight, E. A.

    2005-12-01

    For better understanding the carbon fluxes in the grassland ecosystems, an empirical piecewise regression (PWR) model was developed to estimate gross primary production (GPP) for the grassland ecosystems in the Northern Great Plains and Northern Kazakhstan. The PWR model spatially scales up the localized flux tower measurements across an ecoregion at 1-km resolution. In this study, we compared the PWR GPP and the MODIS GPP with five grassland flux tower measurements. Then we employed cross-validation to evaluate the PWR GPP values. We also compared PWR GPP and MODIS GPP for grasslands for the entire study area. Factors that may explain the spatial pattern of the GPP differences between the two models were explored using decision tree technique. The results indicated that the PWR modeling approach was robust with a good agreement (agreement coefficient d=0.71-0.97) between PWR model and tower measurements. Cross-validation showed a relatively low agreement (d=0.71-0.78) at two influential flux tower sites. We also observed that the PWR GPP was lower than or similar to the MODIS GPP in the east and higher in the west and south. Further analysis suggested that percentage of C4 grasses, soil water holding capacity, percentage of clay, and percentage of crop mixed in the grassland contributed to the GPP difference of the PWR and MODIS models.

  7. Exact evaluation of gross photosynthetic production from the oxygen triple-isotope composition of O2: Implications for the net-to-gross primary production ratios

    NASA Astrophysics Data System (ADS)

    Prokopenko, Maria G.; Pauluis, Olivier M.; Granger, Julie; Yeung, Laurence Y.

    2011-07-01

    The oxygen triple-isotope composition of dissolved O2 provides an integrative method to estimate the rates of Gross Photosynthetic Production (GPP) in the upper ocean, and combined with estimates of Net Community Production (NCP) yields an estimate of the net-to-gross (NCP/GPP) production ratios. However, derivations of GPP from oxygen triple-isotope measurements have involved some mathematical approximations. We derive an exact expression for calculating GPP, and show that small errors associated with approximations result in a relative error of up to ˜38% in GPP, and up to ˜50% in N/G. In open ocean regimes with low primary production, the observed magnitude of the error is comparable to the combined methodological uncertainties. In highly productive ecosystems, the error arising from approximations becomes significant. Using data collected on the Bering Sea shelf, we illustrate the differences in GPP estimates in both high and low productivity regimes that arise from exact and approximated formulations.

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

    SciTech Connect

    Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying; Zhao, Maosheng; Post, Wilfred M

    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 by 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).

  9. Comparing Temporal Variations in LUE and GPP across Evergreen and Deciduous Forest Types

    NASA Astrophysics Data System (ADS)

    Zhou, Y.; Hilker, T.; Ju, W.; Coops, N. C.; Black, T. A.; Chen, J.

    2015-12-01

    Estimating gross primary production (GPP) is an important goal of global change research. However, the relationship between GPP and its environmental drivers is highly complex and as a result, accurate modeling of GPP is difficult. One possible technique to help constrain the uncertainties is by using remote sensing data to try and determine the factors driving GPP directly from satellite imagery. In this study, we used GPP from flux data (GPP_EC) and meteorological observations of a deciduous (SOA) and a coniferous evergreen forest (DF-49) to optimize light use efficiency of sunlit (LUEsun) and shaded (LUEshaded) canopies. We based our analysis on the two-leave light use efficiency model (TL-LUE) at daily, 8 day, and 16 day scales by using the Markov chain Monte Carlo (MCMC). The photochemical reflectance index (PRI) of sunlit (PRIsun) and shaded (PRIshaded) leaves was calculated from spectral observations and related to tower based GPP at the three temporal scales. We found that the coefficient of determination (R2) between PRIsun and LUEsun, as well as PRIshaded and LUEshaded at the evergreen forest was lower than that at the deciduous forest. The modeled GPP was closely to the GPP_EC at the three temporal scales. The R2 between the GPP_EC and modeled daily GPP was the highest when using daily measures of LUE, and lowest when uisng16-day LUEsun and LUEshaded. The results indicated that LUE is an important parameter when modeling instantaneous GPP and the short term variations of it. The results help to obtain a better understanding of how many satellite observations are needed to reliably constrain existing GPP models from remote sensing data.

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

    USGS Publications Warehouse

    Zhang, L.; Wylie, B.; Loveland, T.; Fosnight, E.; Tieszen, L.L.; Ji, L.; Gilmanov, T.

    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

  11. The global role of ppGpp synthesis in morphological differentiation and antibiotic production in Streptomyces coelicolor A3(2)

    PubMed Central

    Hesketh, Andrew; Chen, Wenqiong Joan; Ryding, Jamie; Chang, Sherman; Bibb, Mervyn

    2007-01-01

    Background Regulation of production of the translational apparatus via the stringent factor ppGpp in response to amino acid starvation is conserved in many bacteria. However, in addition to this core function, it is clear that ppGpp also exhibits genus-specific regulatory effects. In this study we used Affymetrix GeneChips to more fully characterize the regulatory influence of ppGpp synthesis on the biology of Streptomyces coelicolor A3(2), with emphasis on the control of antibiotic biosynthesis and morphological differentiation. Results Induction of ppGpp synthesis repressed transcription of the major sigma factor hrdB, genes with functions associated with active growth, and six of the thirteen conservons present in the S. coelicolor genome. Genes induced following ppGpp synthesis included the alternative sigma factor SCO4005, many for production of the antibiotics CDA and actinorhodin, the regulatory genes SCO4198 and SCO4336, and two alternative ribosomal proteins. Induction of the CDA and actinorhodin clusters was accompanied by an increase in transcription of the pathway regulators cdaR and actII-ORF4, respectively. Comparison of transcriptome profiles of a relA null strain, M570, incapable of ppGpp synthesis with its parent M600 suggested the occurrence of metabolic stress in the mutant. The failure of M570 to sporulate was associated with a stalling between production of the surfactant peptide SapB, and of the hydrophobins: it overproduced SapB but failed to express the chaplin and rodlin genes. Conclusion In S. coelicolor, ppGpp synthesis influences the expression of several genomic elements that are particularly characteristic of streptomycete biology, notably antibiotic gene clusters, conservons, and morphogenetic proteins. PMID:17683547

  12. Change of outlook for the forest productivity estimated with remote sensing using the new Collection 6 GPP/NPP MODIS product

    NASA Astrophysics Data System (ADS)

    Marjanović, Hrvoje; Kern, Anikó; Anić, Mislav; Zorana Ostrogović Sever, Maša; Balenović, Ivan; Alberti, Giorgio; Kovač, Goran; Barcza, Zoltán

    2016-04-01

    Estimates of forest productivity from remote sensing data, such as the MOD17 GPP and NPP values derived from MODIS data, are becoming increasingly important tools for monitoring forest productivity in light of the climate change. Hence, small sensor degradation, like the one in the case of MODIS sensor on-board satellite Terra could lead so significant bias in results and false conclusions of the path that the ecosystem is on. In new Collection 6 (C6) of the MOD17 product, the sensor degradation problem has been addressed compared to the previous version Collection 5.5 (C5.5) products, offering a new outlook on the trends in forest productivity. In our work we compared the C5.5 and C6 for MOD17 GPP and NPP products against estimates from eddy covariance and field measurements ('ground truth') at young Pedunculate oak site in Jastrebarsko forest. In order to assess the outlook of forest productivity at larger scale we intersected in GIS maps of forest areas under management and MODIS pixels with 1km spatial resolution. After selecting only those pixels that have at least 90% forest coverage according to the management plans, we analysed the temporal trends and variability in MODIS derived GPP and NPP both from C5.5 and C6 products. Analysis was performed for four main forests classes according to the dominant tree species (Pedunculate oak, Sessile oak, Common beech and Silver fir).

  13. Extreme events in gross primary production: a characterization across continents

    NASA Astrophysics Data System (ADS)

    Zscheischler, J.; Mahecha, M. D.; Harmeling, S.; Rammig, A.; Tomelleri, E.; Reichstein, M.

    2014-01-01

    Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented. Here we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive (increase in uptake) and negative extremes (decrease in uptake) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Most extremes in GPP start in early summer. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role than durations or maximal GPP anomaly when it comes to the overall impact of GPP extremes. An analysis of possible causes implies that across continents most extremes in GPP can best be explained by water scarcity rather than by extreme temperatures. However, for Europe, South America and Oceania we identify also fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

  14. Assessment of CO2 fluxes and forest productivity (NPP/GPP) estimates from eddy covariance measurement and field observations

    NASA Astrophysics Data System (ADS)

    Anić, Mislav; Marjanović, Hrvoje; Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Večenaj, Željko

    2016-04-01

    Eddy covariance (EC) measurements were carried out at the Jastrebarsko site, Croatia, in lowland forest dominated by pedunculate oak. For validation of CO2 fluxes measured with EC method bi-weekly field measurements of increment of 640 trees in 24 plots set in a 100m x 100m grid, height increment and litterfall have been used. In our work we compared annual productivity (GPP and NPP) assessments from EC measurements with field measurements. The comparison was made on a seven year dataset of measurements, spanning from 2008 to 2014. Also, flux dependence on groundwater level has been investigated. Results are showing that forest productivity estimates with EC method are in good agreement with the estimates from field measurements in the dry years. Agreement is slightly lower for years with high precipitation.

  15. 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; Qin, Yuanwei; Wang, Jie; Moore, Berrien, III

    2016-01-01

    Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study,we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS (Moderate Resolution Imaging Spectrometer) images at 8-day temporal and 500 meter spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPP (sub VPM)) agrees well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPP (sub VPM) in 2010 is spatially aggregated to 0.5 by 0.5-degree grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPP (sub VPM) and GOME-2 SIF show good consistency. At the biome scale, GPP (sub VPM) and SIF shows strong linear relationships (R (sup 2) is greater than 0.95) and small variations in regression slopes ((4.60-5.55 grams Carbon per square meter per day) divided by (milliwatts per square meter per nanometer per square radian)). The total annual GPP (sub VPM) in NA in 2010 is approximately 13.53 petagrams Carbon per year, which accounts for approximately 11.0 percent of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35-22.23 petagrams Carbon per year). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models.

  16. 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.

  17. Extreme events in gross primary production: a characterization across continents

    NASA Astrophysics Data System (ADS)

    Zscheischler, J.; Reichstein, M.; Harmeling, S.; Rammig, A.; Tomelleri, E.; Mahecha, M. D.

    2014-06-01

    Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.

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

    USGS Publications Warehouse

    Hall, Robert O., Jr.; 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.

  19. Ozone vegetation damage effects on gross primary productivity in the United States

    NASA Astrophysics Data System (ADS)

    Yue, X.; Unger, N.

    2014-09-01

    We apply an off-line process-based vegetation model (the Yale Interactive Terrestrial Biosphere model) to assess the impacts of ozone (O3) vegetation damage on gross primary productivity (GPP) in the United States during the past decade (1998-2007). The model's GPP simulation is evaluated at 40 sites of the North American Carbon Program (NACP) synthesis. The ecosystem-scale model version reproduces interannual variability and seasonality of GPP at most sites, especially in croplands. Inclusion of the O3 damage impact decreases biases of simulated GPP at most of the NACP sites. The simulation with the O3 damage effect reproduces 64% of the observed variance in summer GPP and 42% on the annual average. Based on a regional gridded simulation over the US, summertime average O3-free GPP is 6.1 g C m-2 day-1 (9.5 g C m-2 day-1 in the east of 95° W and 3.9 g C m-2 day-1 in the west). O3 damage decreases GPP by 4-8% on average in the eastern US and leads to significant decreases of 11-17% in east coast hot spots. Sensitivity simulations show that a 25% decrease in surface O3 concentration halves the average GPP damage to only 2-4%, suggesting the substantial co-benefits to ecosystem health that may be achieved via O3 air pollution control.

  20. Terrestrial gross primary production inferred from satellite fluorescence and vegetation models.

    PubMed

    Parazoo, Nicholas C; Bowman, Kevin; Fisher, Joshua B; Frankenberg, Christian; Jones, Dylan B A; Cescatti, Alessandro; Pérez-Priego, Oscar; Wohlfahrt, Georg; Montagnani, Leonardo

    2014-10-01

    Determining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth's carbon budget. Dynamical global vegetation models (DGVMs) provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar-induced chlorophyll fluorescence (SIF) opens up a new possibility to provide direct global observational constraints for GPP. Here, we apply an optimal estimation approach to infer the global distribution of GPP from an ensemble of eight DGVMs constrained by global measurements of SIF from the Greenhouse Gases Observing SATellite (GOSAT). These estimates are compared to flux tower data in N. America, Europe, and tropical S. America, with careful consideration of scale differences between models, GOSAT, and flux towers. Assimilation of GOSAT SIF with DGVMs causes a redistribution of global productivity from northern latitudes to the tropics of 7-8 Pg C yr(-1) from 2010 to 2012, with reduced GPP in northern forests (~3.6 Pg C yr(-1) ) and enhanced GPP in tropical forests (~3.7 Pg C yr(-1) ). This leads to improvements in the structure of the seasonal cycle, including earlier dry season GPP loss and enhanced peak-to-trough GPP in tropical forests within the Amazon Basin and reduced growing season length in northern croplands and deciduous forests. Uncertainty in predicted GPP (estimated from the spread of DGVMs) is reduced by 40-70% during peak productivity suggesting the assimilation of GOSAT SIF with models is well-suited for benchmarking. We conclude that satellite fluorescence augurs a new opportunity to quantify the GPP response to climate drivers and the potential to constrain predictions of carbon cycle evolution. PMID:24909755

  1. Large-scale estimation and uncertainty analysis of gross primary production in Tibetan alpine grasslands

    NASA Astrophysics Data System (ADS)

    He, Honglin; Liu, Min; Xiao, Xiangming; Ren, Xiaoli; Zhang, Li; Sun, Xiaomin; Yang, Yuanhe; Li, Yingnian; Zhao, Liang; Shi, Peili; Du, Mingyuan; Ma, Yaoming; Ma, Mingguo; Zhang, Yu; Yu, Guirui

    2014-03-01

    Gross primary production (GPP) is an important parameter for carbon cycle and climate change research. Previous estimations of GPP on the Tibetan Plateau were usually reported without quantitative uncertainty analyses. This study sought to quantify the uncertainty and its partitioning in GPP estimation across Tibetan alpine grasslands during 2003-2008 with the modified Vegetation Photosynthesis Model (VPM). Monte Carlo analysis was used to provide a quantitative assessment of the uncertainty in model simulations, and Sobol' variance decomposition method was applied to determine the relative contribution of each source of uncertainty to the total uncertainty. The results showed that the modified VPM successfully reproduced the seasonal dynamics and magnitude of GPP of 10 flux tower sites on the plateau (R2 = 0.77 - 0.95, p < 0.001). The 6 year mean GPP in Tibetan alpine grasslands was estimated at 223.3 Tg C yr-1 (312.3 g C m-2 yr-1). The mean annual GPP increased from western to eastern plateau, with the increase of annual temperature and precipitation and the decrease of elevation, while the decrease of GPP from southern to northern plateau was primarily driven by air temperature. Furthermore, the mean relative uncertainty of the annual GPP was 18.30%, with larger uncertainty occurring in regions with lower GPP. Photosynthetic active radiation, enhanced vegetation index, and the maximum light use efficiency (LUE) are the primary sources of uncertainty in GPP estimation, contributing 36.84%, 26.86%, and 21.99%, respectively. This emphasizes the importance of uncertainty in driving variables as well as that of maximum LUE in LUE model simulation.

  2. 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. PMID:23687009

  3. 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. PMID:26221990

  4. Modeling Gross Primary Production in North America with MODIS Images and Reanalysis Climate Data

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Xiao, X.; Jin, C.; Dong, J.; Zhou, S.; Wagle, P.; Joiner, J.; Guanter, L.; Zhang, Y.; Zhang, G.; Qin, Y.; Wang, J.; Moore, B., III

    2015-12-01

    Accurate estimation of gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study we estimated GPP in North America (NA), using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS images at 8-day temporal and 500 m spatial resolution, and NCEP-NARR reanalysis climate data. The simulated GPP (GPPVPM) agreed well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPPVPM in 2010 was spatially aggregated to 0.5 by 0.5 degree grid cell, and then evaluated with solar-induced chlorophyll fluorescence (SIF) data from GOME-2, which is often regarded as the proxy of direct measurement of vegetation photosynthesis. There were good agreements in spatial distribution and seasonal dynamics between GPPVPM and SIF. At biome scale, the relationship between GPPVPM and SIF showed strong linear correlations (R2 > 0.95) and small variations of slopes (4.60 - 5.55 g C m-2 year-1 / (mW m-2 nm-1 sr-1)). The total annual GPPVPM in NA in 2010 was approximately 13.53 Pg C year-1, which accounted for ~11.0% of the global terrestrial GPP and was within the range of annual GPP estimates from several other process-based and data-driven models (11.35 - 22.23 Pg C year-1). Forests contributed most (4.17 Pg C year-1) to the annual GPP in NA. Evergreen broadleaf forests were most productive with an average annual GPP exceeding 2000 g C m-2 year-1. The results from this study has demonstrated the reliable performance of VPM at the continental scale, and the resultant GPP product at 500-m spatial resolution provides more opportunities to improve the studies of carbon cycle, model inter-comparison, and benchmarking.

  5. Remote Estimation of Gross Primary Production in Crops at Field and Regional Levels

    NASA Astrophysics Data System (ADS)

    Gitelson, A. A.; Vina, A.; Verma, S. B.; Rundquist, D. C.

    2007-12-01

    Accurate estimation of spatially distributed CO2 fluxes is of great importance for regional and global studies of carbon balance. We have found that in irrigated and rainfed crops (maize and soybean), GPP is closely related to total crop chlorophyll content. The finding allowed development of a new technique for remote estimation of crop chlorophyll specifically for assessing gross primary production. The technique is based on reflectance in two spectral channels: the near-infrared and either the green or the red-edge. The technique provided accurate estimations of daily GPP in both crops. Validation using independent datasets for irrigated and rainfed maize and soybean documented the robustness of the technique. We report also about applying the developed technique for GPP retrieval from data acquired by both an airborne imaging spectrometer (AISA-Eagle) and Landsat ETM+. The Chlorophyll Index, retrieved from Landsat ETM+ data, was found to be an accurate surrogate measure for daily crop GPP with a root mean square error of GPP prediction of less than 1.58 g C m-2d-1 in a GPP range of 1.88 g C m-2d-1 to 23.1 g C m-2d-1. These results suggest new possibilities for analyzing the spatio-temporal variation of the GPP of crops using not only the extensive archive of Landsat Thematic Mapper imagery acquired since the early 1980s but also the 500-m/pixel data currently being acquired by MODIS.

  6. The ppGpp synthetase gene (relA) of Streptomyces coelicolor A3(2) plays a conditional role in antibiotic production and morphological differentiation.

    PubMed Central

    Chakraburtty, R; Bibb, M

    1997-01-01

    Deletion of most of the coding region of the ppGpp synthetase gene (relA) of Streptomyces coelicolor A3(2) resulted in loss of ppGpp synthesis, both upon entry into stationary phase under conditions of nitrogen limitation and following amino acid starvation during exponential growth, but had no effect on growth rate. The relA mutant, which showed continued rRNA synthesis upon amino acid depletion (the relaxed response), failed to produce the antibiotics undecylprodigiosin (Red) and actinorhodin (Act) under conditions of nitrogen limitation. The latter appears to reflect diminished transcription of pathway-specific regulatory genes for Red and Act production, redD and actII-ORF4, respectively. In addition to the changes in secondary metabolism, the relA mutant showed a marked delay in the onset and extent of morphological differentiation, resulting in a conspicuously altered colony morphology. PMID:9294445

  7. Primary production of coral ecosystems in the Vietnamese coastal and adjacent marine waters

    NASA Astrophysics Data System (ADS)

    Tac-An, Nguyen; Minh-Thu, Phan; Cherbadji, I. I.; Propp, M. V.; Odintsov, V. S.; Propp, L. H.

    2013-11-01

    Coral reef ecosystems in coastal waters and islands of Vietnam have high primary production. Average gross primary production (GPP) in coral reef waters was 0.39 g C m-2 day-1. GPP of corals ranged from 3.12 to 4.37 g C m-2 day-1. GPP of benthic microalgae in coral reefs ranged from 2 to 10 g C m-2 day-1. GPP of macro-algae was 2.34 g C m-2 day-1. Therefore, the total of GPP of whole coral reef ecosystems could reach 7.85 to 17.10 g C m-2 day-1. Almost all values of the ratio of photosynthesis to respiration in the water bodies are higher than 1, which means these regions are autotrophic systems. Wire variation of GPP in coral reefs was contributed by species abundance of coral and organisms, nutrient supports and environmental characteristics of coral ecosystems. Coral reefs play an important ecological role of biogeochemical cycling of nutrients in waters around the reefs. These results contribute valuable information for the protection, conservation and sustainable exploitation of the natural resources in coral reef ecosystems in Vietnam.

  8. 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

  9. 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.

  10. 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.

  11. A multi-sites analysis on the ozone effects on Gross Primary Production of European forests.

    PubMed

    Proietti, C; Anav, A; De Marco, A; Sicard, P; Vitale, M

    2016-06-15

    Ozone (O3) is both a greenhouse gas and a secondary air pollutant causing adverse impacts on forests ecosystems at different scales, from cellular to ecosystem level. Specifically, the phytotoxic nature of O3 can impair CO2 assimilation that, in turn affects forest productivity. This study aims to evaluate the effects of tropospheric O3 on Gross Primary Production (GPP) at 37 European forest sites during the time period 2000-2010. Due to the lack of carbon assimilation data at O3 monitoring stations (and vice-versa) this study makes a first attempt to combine high resolution MODIS Gross Primary Production (GPP) estimates and O3 measurement data. Partial Correlations, Anomalies Analysis and the Random Forests Analysis (RFA) were used to quantify the effects of tropospheric O3 concentration and its uptake on GPP and to evaluate the most important factors affecting inter-annual GPP changes. Our results showed, along a North-West/South-East European transect, a negative impact of O3 on GPP ranging from 0.4% to 30%, although a key role of meteorological parameters respect to pollutant variables in affecting GPP was found. In particular, meteorological parameters, namely air temperature (T), soil water content (SWC) and relative humidity (RH) are the most important predictors at 81% of test sites. Moreover, it is interesting to highlight a key role of SWC in the Mediterranean areas (Spanish, Italian and French test sites) confirming that, soil moisture and soil water availability affect vegetation growth and photosynthesis especially in arid or semi-arid ecosystems such as the Mediterranean climate regions. Considering the pivotal role of GPP in the global carbon balance and the O3 ability to reduce primary productivity of the forests, this study can help in assessing the O3 impacts on ecosystem services, including wood production and carbon sequestration. PMID:26971205

  12. Gross primary production of global forest ecosystems has been overestimated

    PubMed Central

    Ma, Jianyong; Yan, Xiaodong; Dong, Wenjie; Chou, Jieming

    2015-01-01

    Coverage rate, a critical variable for gridded forest area, has been neglected by previous studies in estimating the annual gross primary production (GPP) of global forest ecosystems. In this study, we investigated to what extent the coverage rate could impact forest GPP estimates from 1982 to 2011. Here we show that the traditional calculation without considering the coverage rate globally overestimated the forest gross carbon dioxide uptake by approximately 8.7%, with a value of 5.12 ± 0.23 Pg C yr−1, which is equivalent to 48% of the annual emissions from anthropogenic activities in 2012. Actually, the global annual GPP of forest ecosystems is approximately 53.71 ± 4.83 Pg C yr−1 for the past 30 years by taking the coverage rate into account. Accordingly, we argue that forest annual GPP calculated by previous studies has been overestimated due to the exaggerated forest area, and therefore, coverage rate may be a required factor to further quantify the global carbon cycle. PMID:26027557

  13. Developing a gross primary production model for coniferous forests of northeastern USA from MODIS data

    NASA Astrophysics Data System (ADS)

    Jahan, Nasreen; Gan, Thian Yew

    2013-12-01

    Accurate estimation of ecosystem carbon fluxes is crucial for understanding the feedbacks between the terrestrial biosphere and the atmosphere and for making climate-policy decisions. A statistical model is developed to estimate the gross primary production (GPP) of coniferous forests of northeastern USA using remotely sensed (RS) radiation (land surface temperature and near-infra red albedo) and ecosystem variables (enhanced vegetation index and global vegetation moisture index) acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This GPP model (called R-GPP-Coni), based only on remotely sensed data, was first calibrated with GPP estimates derived from the eddy covariance flux tower of the Howland forest main tower site and then successfully transferred and validated at three other coniferous sites: the Howland forest west tower site, Duke pine forest and North Carolina loblolly pine site, which demonstrate its transferability to other coniferous ecoregions of northeastern USA. The proposed model captured the seasonal dynamics of the observed 8-day GPP successfully by explaining 84-94% of the observed variations with a root mean squared error (RMSE) ranging from 1.10 to 1.64 g C/m2/day over the 4 study sites and outperformed the primary RS-based GPP algorithm of MODIS.

  14. MODIS-Derived Terrestrial Primary Production

    NASA Astrophysics Data System (ADS)

    Zhao, Maosheng; Running, Steven; Heinsch, Faith Ann; Nemani, Ramakrishna

    Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of all the acronyms is available in the appendix at the end of the chapter) by the human population accounts for about 14-26% of global NPP (Imhoff et al. 2004). Rapid global climate change is induced by increased atmospheric greenhouse gas concentration, especially CO2, which results from human activities such as fossil fuel combustion and deforestation. This directly impacts terrestrial NPP, which continues to change in both space and time (Melillo et al. 1993; Prentice et al. 2001; Nemani et al. 2003), and ultimately impacts the well-being of human society (Milesi et al. 2005). Additionally, substantial evidence show that the oceans and the biosphere, especially terrestrial ecosystems, currently play a major role in reducing the rate of the atmospheric CO2 increase (Prentice et al. 2001; Schimel et al. 2001). NPP is the first step needed to quantify the amount of atmospheric carbon fixed by plants and accumulated as biomass. Continuous and accurate measurements of terrestrial NPP at the global scale are possible using satellite data. Since early 2000, for the first time, the MODIS sensors onboard the Terra and Aqua satellites, have operationally provided scientists with near real-time global terrestrial gross primary production (GPP) and net photosynthesis (PsnNet) data. These data are provided at 1 km spatial resolution and an 8-day interval, and annual NPP covers 109,782,756 km2 of vegetated land. These GPP, PsnNet and NPP products are collectively known as MOD17 and are part of a larger suite of MODIS land products (Justice et al. 2002), one of the core Earth System or Climate Data Records (ESDR or

  15. Exogenous N addition enhances the responses of gross primary productivity to individual precipitation events in a temperate grassland.

    PubMed

    Guo, Qun; Hu, Zhong-Min; Li, Sheng-Gong; Yu, Gui-Rui; Sun, Xiao-Min; Li, Ling-Hao; Liang, Nai-Shen; Bai, Wen-Ming

    2016-01-01

    Predicted future shifts in the magnitude and frequency (larger but fewer) of precipitation events and enhanced nitrogen (N) deposition may interact to affect grassland productivity, but the effects of N enrichment on the productivity response to individual precipitation events remain unclear. In this study, we quantified the effects of N addition on the response patterns of gross primary productivity (GPP) to individual precipitation events of different sizes (Psize) in a temperate grassland in China. The results showed that N enrichment significantly increased the time-integrated amount of GPP in response to an individual precipitation event (GPPtotal), and the N-induced stimulation of GPP increased with increasing Psize. N enrichment rarely affected the duration of the GPP response, but it significantly stimulated the maximum absolute GPP response. Higher foliar N content might play an important role in the N-induced stimulation of GPP. GPPtotal in both the N-addition and control treatments increased linearly with Psize with similar Psize intercepts (approximately 5 mm, indicating a similar lower Psize threshold to stimulate the GPP response) but had a steeper slope under N addition. Our work indicates that the projected larger precipitation events will stimulate grassland productivity, and this stimulation might be amplified by increasing N deposition. PMID:27264386

  16. Exogenous N addition enhances the responses of gross primary productivity to individual precipitation events in a temperate grassland

    NASA Astrophysics Data System (ADS)

    Guo, Qun; Hu, Zhong-Min; Li, Sheng-Gong; Yu, Gui-Rui; Sun, Xiao-Min; Li, Ling-Hao; Liang, Nai-Shen; Bai, Wen-Ming

    2016-06-01

    Predicted future shifts in the magnitude and frequency (larger but fewer) of precipitation events and enhanced nitrogen (N) deposition may interact to affect grassland productivity, but the effects of N enrichment on the productivity response to individual precipitation events remain unclear. In this study, we quantified the effects of N addition on the response patterns of gross primary productivity (GPP) to individual precipitation events of different sizes (Psize) in a temperate grassland in China. The results showed that N enrichment significantly increased the time-integrated amount of GPP in response to an individual precipitation event (GPPtotal), and the N-induced stimulation of GPP increased with increasing Psize. N enrichment rarely affected the duration of the GPP response, but it significantly stimulated the maximum absolute GPP response. Higher foliar N content might play an important role in the N-induced stimulation of GPP. GPPtotal in both the N-addition and control treatments increased linearly with Psize with similar Psize intercepts (approximately 5 mm, indicating a similar lower Psize threshold to stimulate the GPP response) but had a steeper slope under N addition. Our work indicates that the projected larger precipitation events will stimulate grassland productivity, and this stimulation might be amplified by increasing N deposition.

  17. Exogenous N addition enhances the responses of gross primary productivity to individual precipitation events in a temperate grassland

    PubMed Central

    Guo, Qun; Hu, Zhong-min; Li, Sheng-gong; Yu, Gui-rui; Sun, Xiao-min; Li, Ling-hao; Liang, Nai-shen; Bai, Wen-ming

    2016-01-01

    Predicted future shifts in the magnitude and frequency (larger but fewer) of precipitation events and enhanced nitrogen (N) deposition may interact to affect grassland productivity, but the effects of N enrichment on the productivity response to individual precipitation events remain unclear. In this study, we quantified the effects of N addition on the response patterns of gross primary productivity (GPP) to individual precipitation events of different sizes (Psize) in a temperate grassland in China. The results showed that N enrichment significantly increased the time-integrated amount of GPP in response to an individual precipitation event (GPPtotal), and the N-induced stimulation of GPP increased with increasing Psize. N enrichment rarely affected the duration of the GPP response, but it significantly stimulated the maximum absolute GPP response. Higher foliar N content might play an important role in the N-induced stimulation of GPP. GPPtotal in both the N-addition and control treatments increased linearly with Psize with similar Psize intercepts (approximately 5 mm, indicating a similar lower Psize threshold to stimulate the GPP response) but had a steeper slope under N addition. Our work indicates that the projected larger precipitation events will stimulate grassland productivity, and this stimulation might be amplified by increasing N deposition. PMID:27264386

  18. Remote estimation of gross primary productivity in crops: from close range to satellite observations

    NASA Astrophysics Data System (ADS)

    Peng, Y.; Gitelson, A. A.; Sakamoto, T.; Masek, J. G.; Rundquist, D.; Nguy-Robertson, A. L.; Verma, S.; Suyker, A.

    2013-12-01

    An accurate estimation of crop gross primary productivity (GPP) is essential for monitoring regional and global carbon exchanges. In this study, with ten-year observations throughout 2001 to 2010 at three irrigated and rainfed AmerFlux sites in Mead, Nebraska, a simple model was tested to estimate crop GPP using a product of chlorophyll-related vegetation index and photosynthetically active radiation (PAR). Vegetation indices (VI), a proxy of canopy chlorophyll, were calculated from canopy reflectance at various spatial and temporal resolution, including daily observations of four-band radiance 6 m above the ground, weekly in-situ measurements of hyperspectral reflectance, and satellite data (Landsat and MODIS). This model was able to estimate GPP accurately in croplands with different crop species, field managements and climatic conditions. It showed that the used VI was quite sensitive to detect daily GPP variation in crops even under stressed conditions when total Chl content is closely tied to seasonal dynamic of GPP. To minimize the uncertainty of GPP variations, which do not follow fluctuations of incoming PAR, potential PAR was introduced into the model as a better representative of radiation absorbed by canopy for photosynthesis. The model using satellite data and potential PAR is entirely based on remotely sensed data not requiring any ground-based observation. The indices using green and NIR Landsat bands were found to be the most accurate in GPP estimation with coefficients of variation below 13% for maize and 15% for soybean. Using MODIS 250 m data, EVI2 and WDRVI were accurate estimating GPP with coefficient of variation below 20% in maize and 25% in soybean.

  19. Estimation and Analysis of Gross Primary Production of Soybean Under Various Management Practices and Drought Conditions

    NASA Astrophysics Data System (ADS)

    Wagle, P.; Xiao, X.; Suyker, A.

    2014-12-01

    Gross primary production (GPP) of croplands may be used to quantify crop productivity and evaluate a range of management practices. Eddy flux data from three soybean (Glycine max L.) fields under different management practices (no-till vs till; rainfed vs irrigated) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices (VIs) were used to evaluate the biophysical performance of VIs and crop phenology, and to model GPP using a satellite-based vegetation photosynthesis model (VPM). The VIs tracked soybean phenology well and delineated the growing season length. The results show that the carbon uptake period and seasonal sums of net ecosystem CO2 exchange (NEE) and GPP can be inferred from the length of the vegetation activity period from satellite remote sensing data. Land surface water index (LSWI) tracked drought-impacted vegetation well. On a seasonal scale, NEE of the soybean sites ranged from -37 to -264 g C m-2. The result suggests that rainfed soybean fields needed about 450-500 mm of well-distributed seasonal rainfall to maximize the net carbon sink. During non-drought conditions, VPM accurately estimated seasonal dynamics and interannual variation of GPP of soybean under different management practices. However, some large discrepancies between GPPVPM and GPPEC were observed under drought conditions as the VI did not reflect the corresponding decrease in GPP. Diurnal GPP dynamics showed a bimodal distribution with a pronounced midday depression at the period of higher water vapor pressure deficit (> 1.2 kPa). A modified Wscalar based on LSWI, to account for the water stress, in VPM helped quantify the reduction in GPP during severe drought and the model's performance improved substantially. The results of this study demonstrate the potential use of remotely sensed VIs for better understanding of carbon dynamics and extrapolation of GPP of soybean croplands.

  20. Attributing Changes in Gross Primary Productivity from 1901 to 2010

    NASA Astrophysics Data System (ADS)

    Schwalm, C. R.; Huntzinger, D. N.; Michalak, A. M.; Cook, R. B.; El Masri, B.; Hayes, D. J.; Huang, M.; Jacobson, A. R.; Jain, A. K.; Lei, H.; Lu, C.; Tian, H.; Schaefer, K. M.; Wei, Y.

    2014-12-01

    Model-based studies are foundational to perform diagnosis (has there been a change?) and attribution (what caused this change?) in the context of global environmental change. Here we employ a dual method approach using machine learning and simulation differencing across an ensemble of terrestrial biosphere models (TBM) to attribute changes in gross primary productivity (GPP) from 1901 to 2010. The simulations are taken from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). For each TBM MsTMIP prescribes a semi-factorial set of five runs (globally at 0.5º spatial resolution) where time-varying controls on carbon metabolism are sequentially enabled. MsTMIP has a constrained simulation protocol -driving data, vegetation cover, boundary conditions, and steady-state spin up protocol are all standardized- such that only model structure varies and ensemble spread addresses process uncertainty. Applying this dual method to MsTMIP simulation output we attribute changes in GPP to changes in climate, land cover/land use change, atmospheric CO2, nitrogen deposition, near-surface air temperature, precipitation, and downwelling shortwave radiation as well as climate sigma (irreducible climate noise) and nonlinearity (interactions). Globally, the key factor associated with the Anthropocene, namely the sustained increase in atmospheric CO2, dominates changes in GPP across the full time period. Climate factors are of secondary importance and, along with land cover/land use change, may act to decrease GPP depending on decade and reference period. Despite differences in model structure attribution results across the full ensemble are generally consistent. Spatial morphologies, replicating the same dual approach by grid cell, exhibit high variability but with an atmospheric CO2 fertilization effect dominating the tropical zone. Our results suggest that the modern era of global warming, when viewed through the prism of GPP attribution, reaches back at

  1. A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data

    SciTech Connect

    Xiao, Jingfeng; Zhuang, Qianlai; Law, Beverly E.; Chen, Jiquan; Baldocchi, D. D.; Ma, Siyan; Cook, David R.; Oren, Ram; Katul, G. G.; Gu, Lianhong

    2010-03-01

    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 range 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 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 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

  2. Temperature sensitivity of stream gross primary production and respiration from the tropics to the arctic

    NASA Astrophysics Data System (ADS)

    Song, C.; Argerich, A.; Baker, C.; Bowden, W. B.; Dodds, W. K.; Douglas, M.; Farrell, K.; Flinn, M. B.; Garcia, E.; Gido, K. B.; Harms, T.; Jones, J.; Koenig, L.; Kominoski, J. S.; McDonald, K. S.; McDowell, W. H.; McMaster, D.; Parker, S.; Rosemond, A.; Rüegg, J.; Sheehan, K.; Trentman, M. T.; Wollheim, W. M.; Ballantyne, F.

    2015-12-01

    Understanding the temperature dependence of gross primary production (GPP) and ecosystem respiration (ER) in streams is critical to predict the carbon balance in stream ecosystems under global warming. We collected dissolved oxygen (DO) concentration, photosynthetically active radiation (PAR), channel hydrology and geomorphology, and temperature from multiple locations throughout stream networks in seven sites across six biomes, specifically tropical forest, temperate deciduous forest, temperate coniferous forest, tallgrass prairie, boreal forest, and arctic tundra. We estimated the activation energy (Ea) of GPP and ER from diel changes in DO, temperature and PAR for each stream reach. We showed the relationship between Ea and environmental variables, such as temperature, light availability and discharge. In addition, we found that Ea of GPP and ER were highly variable from reach to reach within each biome. The estimated Ea of GPP and ER was generally higher than predicted by metabolic theory. Ea of GPP ranges from 20 to 140 KJ/mol and Ea of ER ranges from 50 to 150 KJ/mol. There was no consistent trend of larger Ea for GPP or ER. This suggests that the changes in carbon balance in streams caused directly by warming is likely to be site specific.

  3. Remote sensing of annual terrestrial gross primary productivity from MODIS: an assessment using the FLUXNET La Thuile data set

    NASA Astrophysics Data System (ADS)

    Verma, M.; Friedl, M. A.; Richardson, A. D.; Kiely, G.; Cescatti, A.; Law, B. E.; Wohlfahrt, G.; Gielen, B.; Roupsard, O.; Moors, E. J.; Toscano, P.; Vaccari, F. P.; Gianelle, D.; Bohrer, G.; Varlagin, A.; Buchmann, N.; van Gorsel, E.; Montagnani, L.; Propastin, P.

    2014-04-01

    Gross primary productivity (GPP) is the largest and most variable component of the global terrestrial carbon cycle. Repeatable and accurate monitoring of terrestrial GPP is therefore critical for quantifying dynamics in regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is widely used to monitor and model spatiotemporal variability in ecosystem properties and processes that affect terrestrial GPP. We used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and FLUXNET to assess how well four metrics derived from remotely sensed vegetation indices (hereafter referred to as proxies) and six remote sensing-based models capture spatial and temporal variations in annual GPP. Specifically, we used the FLUXNET La Thuile data set, which includes several times more sites (144) and site years (422) than previous studies have used. Our results show that remotely sensed proxies and modeled GPP are able to capture significant spatial variation in mean annual GPP in every biome except croplands, but that the percentage of explained variance differed substantially across biomes (10-80%). The ability of remotely sensed proxies and models to explain interannual variability in GPP was even more limited. Remotely sensed proxies explained 40-60% of interannual variance in annual GPP in moisture-limited biomes, including grasslands and shrublands. However, none of the models or remotely sensed proxies explained statistically significant amounts of interannual variation in GPP in croplands, evergreen needleleaf forests, or deciduous broadleaf forests. Robust and repeatable characterization of spatiotemporal variability in carbon budgets is critically important and the carbon cycle science community is increasingly relying on remotely sensing data. Our analyses highlight the power of remote sensing-based models, but also provide bounds on the uncertainties associated with these models. Uncertainty in flux

  4. Uncertainty Analysis of Gross Primary Production Separated from Net Ecosystem Exchange Measurements at Speulderbos Forest, The Netherlands

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Gross primary production (GPP), separated from the 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 scales. Proper implementation of validation requires knowledge of the uncertainty associated with the separated GPP at different time scales so that the propagated uncertainty can be determined. We estimate the uncertainty in GPP at half-hourly to yearly time scales. Flux tower measurements of NEE results from two major fluxes GPP and ecosystem respiration (Reco) as NEE = GPP - Reco and therefore GPP can be separated from NEE. We used a non-rectangular hyperbola (NRH) model to separate half-hourly GPP from the three years of continuous flux tower measurements of half-hourly NEE at the Speulderbos forest site, The Netherlands. NRH includes the variables that influence GPP, in particular radiation, vapor pressure deficit, and temperature. In addition, NRH model provides a robust empirical relationship between radiation and GPP by including the degree of curvature of light response curve. NRH was fitted to the measured NEE data on a daily basis. Variation in the parameters of this model was studied within each year. We did not obtain a single optimized value of each parameter of NRH model, instead we defined the prior distribution of each parameters based on literature search. We adopted a Bayesian approach, which was implemented using Markov chain Monte Carlo (MCMC) simulation to update the prior distribution of each parameter on a daily basis. This allowed us to estimate the uncertainty in the separated GPP at the half-hourly time scale. The results of this approach generated the empirical distribution of GPP at each half-hour, which are a measure of uncertainty. The time series of empirical distributions of half-hourly GPP values also allowed us to estimate the uncertainty at daily, monthly and yearly time scales. Our research

  5. Diagnostic extrapolation of gross primary production from flux tower sites to the globe

    NASA Astrophysics Data System (ADS)

    Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Baldocchi, Dennis; Luyssaert, Sebastiaan; Papale, Dario

    2010-05-01

    The uptake of atmospheric CO2 by plant photosynthesis is the largest global carbon flux and is thought of driving most terrestrial carbon cycle processes. While the photosynthesis processes at the leaf and canopy levels are quite well understood, so far only very crude estimates of its global integral, the Gross Primary Production (GPP) can be found in the literature. Existing estimates have been lacking sound empirical basis. Reasons for such limitations lie in the absence of direct estimates of ecosystem-level GPP and methodological difficulties in scaling local carbon flux measurements to global scale across heterogeneous vegetation. Here, we present global estimates of GPP based on different diagnostic approaches. These up-scaling schemes integrated high-resolution remote sensing products, such as land cover, the fraction of photosynthetically active radiation (fAPAR) and leaf-area index, with carbon flux measurements from the global network of eddy covariance stations (FLUXNET). In addition, meteorological datasets from diverse sources and river runoff observations were used. All the above-mentioned approaches were also capable of estimating uncertainties. With six novel or newly parameterized and highly diverse up-scaling schemes we consistently estimated a global GPP of 122 Pg C y-1. In the quantification of the total uncertainties, we considered uncertainties arising from the measurement technique and data processing (i.e. partitioning into GPP and respiration). Furthermore, we accounted for the uncertainties of drivers and the structural uncertainties of the extrapolation approach. The total propagation led to a global uncertainty of 15 % of the mean value. Although our mean GPP estimate of 122 Pg C y-1 is similar to the previous postulate by Intergovernmental Panel on Climate Change in 2001, we estimated a different variability among ecoregions. The tropics accounted for 32 % of GPP showing a greater importance of tropical ecosystems for the global carbon

  6. Comparison of solar-induced chlorophyll fluorescence, light-use efficiency, and process-based GPP models in maize.

    PubMed

    Wagle, Pradeep; Zhang, Yongguang; Jin, Cui; Xiao, Xiangming

    2016-06-01

    Accurately quantifying cropland gross primary production (GPP) is of great importance to monitor cropland status and carbon budgets. Satellite-based light-use efficiency (LUE) models and process-based terrestrial biosphere models (TBMs) have been widely used to quantify cropland GPP at different scales in past decades. However, model estimates of GPP are still subject to large uncertainties, especially for croplands. More recently, space-borne solar-induced chlorophyll fluorescence (SIF) has shown the ability to monitor photosynthesis from space, providing new insights into actual photosynthesis monitoring. In this study, we examined the potential of SIF data to describe maize phenology and evaluated three GPP modeling approaches (space-borne SIF retrievals, a LUE-based vegetation photosynthesis model [VPM], and a process-based soil canopy observation of photochemistry and energy flux [SCOPE] model constrained by SIF) at a maize (Zea mays L.) site in Mead, Nebraska, USA. The result shows that SIF captured the seasonal variations (particularly during the early and late growing season) of tower-derived GPP (GPP_EC) much better than did satellite-based vegetation indices (enhanced vegetation index [EVI] and land surface water index [LSWI]). Consequently, SIF was strongly correlated with GPP_EC than were EVI and LSWI. Evaluation of GPP estimates against GPP_EC during the growing season demonstrated that all three modeling approaches provided reasonable estimates of maize GPP, with Pearson's correlation coefficients (r) of 0.97, 0.94, and 0.93 for the SCOPE, VPM, and SIF models, respectively. The SCOPE model provided the best simulation of maize GPP when SIF observations were incorporated through optimizing the key parameter of maximum carboxylation capacity (Vcmax). Our results illustrate the potential of SIF data to offer an additional way to investigate the seasonality of photosynthetic activity, to constrain process-based models for improving GPP estimates, and to

  7. Diagnostic Up-scaling of GPP from Eddy Covariance to Global Estimates

    NASA Astrophysics Data System (ADS)

    Tomelleri, E.; Beer, C.; Carvalhais, N.; Jung, M.; Papale, D.; Reichstein, M.; Ciais, P.; Peylin, P.; Pis, F.

    2009-12-01

    The uptake of atmospheric CO2 by plant photosynthesis is the largest global carbon flux and drives all terrestrial carbon cycle processes. While the photosynthesis processes at the leaf and canopy levels are quite well understood, so far only very crude estimates of its global integral, the Gross Primary Production (GPP) can be found in the literature. Existing estimates have been lacking sound empirical basis. Reasons for such limitations lie in the absence of direct estimates of ecosystem-level GPP and methodological difficulties in scaling local carbon flux measurements to global scale across heterogeneous vegetation. Here, we present global estimates of GPP based on different diagnostic approaches. All these up-scaling schemes integrated high-resolution remote sensing products, such as land cover, the fraction of photosynthetically active radiation (fAPAR) and leaf-area index, with carbon flux measurements from the global network of eddy covariance stations (FLUXNET). In addition, meteorological datasets from diverse sources and river runoff observations were used. All the above-mentioned approaches were also capable of estimating uncertainties. With six novel or newly parameterized and highly diverse up-scaling schemes we consistently estimated a global GPP of 122 Pg C y-1. This value is 5 % higher than estimates from inversions of 18O and CO2 atmospheric concentration. In the quantification of the total uncertainties, we considered uncertainties arising from the measurement technique and data processing (i.e. partitioning into GPP and respiration). Furthermore, we accounted for the uncertainties of drivers and the structural uncertainties of the extrapolation approach. The total propagation led to a global uncertainty of 15 % of the mean value. Although our mean GPP estimate of 122 Pg C y-1 is similar to the previous postulate by Intergovernmental Panel on Climate Change in 2001, we estimated a different variability among ecoregions. The tropics accounted for

  8. Variability in light-use efficiency for gross primary productivity on Great Plains grasslands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Gross primary productivity (GPP) often is estimated at regional and global scales by multiplying the amount of photosynthetically active radiation (PAR) absorbed by the plant canopy (PARa) by a light-use efficiency (eg) which is modeled as a function of air temperature (Ta) and other environmental c...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  10. An Evaluation of the MOD17 Gross Primary Production Algorithm in a Mangrove Forest

    NASA Astrophysics Data System (ADS)

    Wells, H.; Najjar, R.; Herrmann, M.; Fuentes, J. D.; Ruiz-Plancarte, J.

    2015-12-01

    Though coastal wetlands occupy a small fraction of the Earth's surface, they are extremely active ecosystems and play a significant role in the global carbon budget. However, coastal wetlands are still poorly understood, especially when compared to open-ocean and terrestrial ecosystems. This is partly due to the limited in situ observations in these areas. One of the ways around the limited in situ data is to use remote sensing products. Here we present the first evaluation of the MOD17 remote sensing algorithm of gross primary productivity (GPP) in a mangrove forest using data from a flux tower in the Florida Everglades. MOD17 utilizes remote sensing products from the Moderate Resolution Imaging Spectroradiometer and meteorological fields from the NCEP/DOE Reanalysis 2. MOD17 is found to capture the long-term mean and seasonal amplitude of GPP but has significant errors describing the interannual variability, intramonthly variability, and the phasing of the annual cycle in GPP. Regarding the latter, MOD17 overestimates GPP when salinity is high and underestimates it when it is low, consistent with the fact that MOD17 ignores salinity and salinity tends to decrease GPP. Including salinity in the algorithm would then most likely improve its accuracy. MOD17 also assumes that GPP is linear with respect to PAR (photosynthetically active radiation), which does not hold true in the mangroves. Finally, the estimated PAR and air temperature inputs to MOD17 were found to be significantly lower than observed. In summary, while MOD17 captures some aspects of GPP variability at this mangrove site, it appears to be doing so for the wrong reasons.

  11. Evaluation of optical remote sensing parameters to improve modeling of gross primary productivity in a heterogeneous agricultural area

    NASA Astrophysics Data System (ADS)

    Schickling, A.; Damm, A.; Schween, J.; Rascher, U.; Crewell, S.; Wahner, A.

    2011-12-01

    Terrestrial photosynthesis greatly determines plant mediated exchange processes in the vegetation atmosphere system and substantially influences patterns in atmospheric carbon dioxide (CO2) concentrations and water vapor. Therefore, an accurate quantification of photosynthetic CO2 uptake, commonly referred to as gross primary productivity (GPP), is a key parameter to distinguish those atmospheric patterns on various spatio-temporal scales. Remote sensing (RS) offers the unique possibility to determine GPP at different spatial scales ranging from the local to the global scale. Attempts to estimate GPP from RS data focus on the light use efficiency (LUE) concept of Monteith which relates GPP to the absorbed photosynthetically active radiation and the efficiency of plant canopies to utilize the absorbed radiation for photosynthesis. To reliably predict GPP on different spatio-temporal scales LUE has to be linked to optical RS parameters which detect changes in photosynthetic efficiency due to environmental conditions. In this study we evaluated two optical RS parameters, namely the sun-induced fluorescence (Fs) and the photochemical reflectance index (PRI), for their potential to serve as a proxy for LUE. The parameters were derived from two ASD FieldSpec spectrometers which were operated in parallel. During several days one instrument was installed on the ground above the vegetation canopy of either a winter wheat or a sugar beet field. The second instrument was operated from a small research aircraft continuously crossing the observation sites at low altitude (< 300 m). GPP was calculated on a diurnal basis including optical parameters in Monteith's LUE concept. The calculated GPP was compared to simultaneously acquired GPP data from eddy covariance measurements. The diurnal behavior of calculated and measured GPP corresponded well indicating that optical RS parameters are able to track the diurnal response of physiological regulation of photosynthesis to changing

  12. Seasonality of primary and secondary production in an Arctic river

    NASA Astrophysics Data System (ADS)

    Kendrick, M.; Huryn, A.; Deegan, L.

    2011-12-01

    Rivers and streams that freeze solid for 8-9 months each year provide excellent examples of the extreme seasonality of arctic habitats. The communities of organisms inhabiting these rivers must complete growth and development during summer, resulting in a rapid ramp-up and down of production over the short ice-free period. The effects of recent shifts in the timing of the spring thaw and autumn freeze-up on the duration and pattern of the period of active production are poorly understood. We are currently investigating: 1) the response of the biotic community of the Kuparuk River (Arctic Alaska) to shifts in the seasonality of the ice-free period, and 2) the community response to increases in phosphorous (P) supply anticipated as the volume of the permafrost active-layer increases in response to climate warming. Here algal production supports a 2-tier web of consumers. We tracked primary and secondary production from the spring thaw through mid-August in a reference reach and one receiving low-level P fertilization. Gross primary production/community respiration (GPP/R) ratios for both reaches were increasing through mid-July, with higher GPP/R in response to the P addition. Understanding the degree of synchrony between primary and secondary production in this Arctic river system will enhance further understanding of how shifts in seasonality affect trophic dynamics.

  13. Estimating Vegetation Primary Production in the Heihe River Basin of China with Multi-Source and Multi-Scale Data

    PubMed Central

    Cui, Tianxiang; Wang, Yujie; Sun, Rui; Qiao, Chen; Fan, Wenjie; Jiang, Guoqing; Hao, Lvyuan; Zhang, Lei

    2016-01-01

    Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m-2 d-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m-2 d-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our modelling

  14. Estimating Vegetation Primary Production in the Heihe River Basin of China with Multi-Source and Multi-Scale Data.

    PubMed

    Cui, Tianxiang; Wang, Yujie; Sun, Rui; Qiao, Chen; Fan, Wenjie; Jiang, Guoqing; Hao, Lvyuan; Zhang, Lei

    2016-01-01

    Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m(-2) d(-1) and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m(-2) d(-1) and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our

  15. 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

  16. Fruit development, not GPP, drives seasonal variation in NPP in a tropical palm plantation.

    PubMed

    Navarro, M N V; Jourdan, C; Sileye, T; Braconnier, S; Mialet-Serra, I; Saint-Andre, L; Dauzat, J; Nouvellon, Y; Epron, D; Bonnefond, J M; Berbigier, P; Rouziere, A; Bouillet, J P; Roupsard, O

    2008-11-01

    We monitored seasonal variations in net primary production (NPP), estimated by allometric equations from organ dimensions, gross primary production (GPP), estimated by the eddy covariance method, autotrophic respiration (R(a)), estimated by a model, and fruit production in a coconut (Cocos nucifera L.) plantation located in the sub-tropical South Pacific archipelago of Vanuatu. Net primary production of the vegetative compartments of the trees accumulated steadily throughout the year. Fruits accounted for 46% of tree NPP and showed large seasonal variations. On an annual basis, the sum of estimated NPP (16.1 Mg C ha(-1) year(-1)) and R(a) (24.0 Mg C ha(-1) year(-1)) for the ecosystem (coconut trees and herbaceous understory) closely matched GPP (39.0 Mg C ha(-1) year(-1)), suggesting adequate cross-validation of annual C budget methods. However, seasonal variations in NPP + R(a) were smaller than the seasonal variations in GPP, and maximum tree NPP occurred 6 months after the midsummer peak in GPP and solar radiation. We propose that this discrepancy reflects seasonal variation in the allocation of dry mass to carbon reserves and new plant tissue, thus affecting the allometric relationships used for estimating NPP. PMID:18765371

  17. Remote sensing evaluation of CLMCN GPP

    NASA Astrophysics Data System (ADS)

    Mao, J.; Thornton, P. E.; Shi, X.; Levis, S.

    2010-12-01

    CLMCN is the carbon-nitrogen biogeochemical component of the CESM1, which is one of the major fully coupled earth system models for the IPCC AR5. Accurate simulation and prediction of terrestrial carbon cycles are considerably important to reduce the uncertainty of the carbon-climate feedbacks to global warming. In comparison with other estimations and models, recent work (Beer et al., 2010) showed the systematic overestimation of GPP from CLMCN particularly over the tropical ecosystem. Remote sensing is a versatile tool that is suited to provide the long-term and large scale geography products for model evaluation. In this research, we calibrated and evaluated the CLMCN GPP by the use of improved MODIS GPP and LAI between 2001 and 2009. Compared to the remote sensing data, we found earlier growing timing for most deciduous PFTs, which partly accounts for the errors of global GPP. After modifications of phenology parameters, we improved the GPP and related carbon variables over different temporal and spatial scales.

  18. Influences of seasonality, geomorphology, and hydrology on primary production and respiration in Arctic stream ecosystems

    NASA Astrophysics Data System (ADS)

    Herstand, M. R.; Bowden, W. B.; Gooseff, M. N.; Whittinghill, K. A.; Wlostowski, A. N.; Wollheim, W. M.

    2011-12-01

    Stream ecosystem processes in the Arctic are poorly understood in the spring and fall 'shoulder' seasons. We hypothesize that seasonal changes in solar radiation, hydrologic conditions, and landscape inputs are all reflected in the seasonal patterns of Gross Primary Productivity (GPP) and Community Respiration (CR). We continuously monitored the GPP and CR of three streams with different geomorphic characteristics (alluvial lake inlet, alluvial lake outlet, and beaded peat) near Toolik Lake Field Station, Alaska from breakup to freeze-up during 2011. We used open-system whole stream metabolism (WSM) methods, with dissolved oxygen estimates every five minutes. Dissolved and particulate nutrient chemistry, benthic chlorophyll, and nutrient uptake rates from solute injections were also measured across the seasons, and had correlations with GPP and CR. The fall freeze-up season was especially productive, as the well-developed benthic community responded to either lower flows (preventing sloughing) and/or increasing dissolved nutrient loads during landscape plant senescence. Storm events and high flow conditions (observed throughout seasons) decreased the GPP:CR ratio. Average monthly air temperatures have increased on the North Slope, especially during the shoulder seasons, increasing the duration of the ice-free stream season. Increasing the fall shoulder season may increase the annual stream GPP and nutrient uptake, with uncertain impacts on nutrient loading to the Arctic Ocean.

  19. Vegetation canopy and physiological control of GPP decline during drought and heat wave

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Xiao, X.; Zhou, S.; McCarthy, H. R.; Ciais, P.; Luo, Y.

    2015-12-01

    Different vegetation indices derived from satellites were often used as a proxy of vegetation activity to monitor and evaluate the impacts of drought and heat wave on ecosystem carbon fluxes (gross primary production, respiration) through the production efficiency models (PEMs). However, photosynthesis is also regulated by a series of physiological processes which cannot be directly observed through satellites. In this study, we analyzed the response of drought and heat wave induced GPP and climate anomaly from 15 Euroflux sites and the corresponding vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Correlation analysis suggests that the vegetation indices are more responsive to GPP variation in grasslands and open shrublands, but less responsive in forest ecosystems. Physiology control can be up to 20% of the total GPP during the drought period without changing the canopy structure. At temporal scale for each site, VPD and vegetation indices can be used to track the GPP for forest and non-forest, respectively. However, different stand characteristics should be taken into consideration for forest ecosystems. Based on the above findings, a conceptual model is built to illuminate the physiological and canopy control on the GPP during the drought period. Improvement for future PEMs should incorporate better indicators to deal with drought conditions for different ecosystems.

  20. Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

    USGS Publications Warehouse

    Yuan, W.; Liu, S.; Yu, G.; Bonnefond, J.-M.; Chen, J.; Davis, K.; Desai, A.R.; Goldstein, Allen H.; Gianelle, D.; Rossi, F.; Suyker, A.E.; Verma, S.B.

    2010-01-01

    The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively. Global patterns of ET and GPP at a spatial resolution of 0.5?? latitude by 0.6?? longitude during the years 2000-2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP

  1. Seasonality of Ecosystem Respiration and Gross Primary Production as Derived from Fluxnet Measurements

    NASA Astrophysics Data System (ADS)

    Falge, E.; Baldocchi, D.; Tenhunen, J.

    2001-12-01

    Differences in the seasonal pattern of assimilatory and respiratory processes are responsible for divergences in seasonal net carbon exchange among ecosystems. Using FLUXNET data (http://www-eosdis.ornl.gov/FLUXNET) we have analyzed seasonal patterns of gross primary productivity (GPP), and ecosystem respiration (RE) of boreal and temperate, deciduous and coniferous forests, mediterranean evergreen systems, rainforest, temperate grasslands, and C3 and C4 crops. Based on generalized seasonal patterns classifications of ecosystems into vegetation functional types can be evaluated for use in global productivity and climate change models. The results of this study contribute to our understanding of respiratory costs of assimilated carbon in various ecosystems. Seasonal variability of GPP and RE increased in the order tropical, Mediterranean, temperate coniferous, temperate deciduous, boreal forests. Together with boreal forests, managed grasslands and crops show the largest seasonal variability. In temperate coniferous forests, seasonal patterns of GPP and RE are in phase, in temperate deciduous and boreal coniferous forests RE was delayed compared to GPP, resulting in the greatest imbalance between respiratory and assimilatory fluxes early in the growing season. Gross primary productivity adjusted for the length of the growing season decreased across functional types in the order C4 crops, and temperate and boreal deciduous forests (7.5-8.3 g C m-2 d-1), temperate conifers, C3 grassland and crops (5.7-6.9 g C m-2 d-1), rainforest and boreal conifers (4.6-4.9 g C m-2 d-1). Annual GPP and NEP decreased across climate zones in the order tropical, temperate, boreal. However, the decrease in NEP was greater than the decrease in GPP, indicating a larger contribution of respiratory (especially heterotrophic) processes in boreal systems.

  2. Terrestrial ecosystem model performance for net primary productivity and its vulnerability to climate change in permafrost regions

    NASA Astrophysics Data System (ADS)

    Xia, J.; McGuire, A. D.; Lawrence, D. M.; Burke, E.; Chen, X.; Delire, C. L.; Koven, C. D.; MacDougall, A. H.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D. P.; Miller, P. A.; Moore, J. C.; Smith, B.; Sueyoshi, T.; Shi, Z.; Yan, L.; Liang, J.; Jiang, L.; Luo, Y.

    2014-12-01

    A more accurate prediction of future climate-carbon (C) cycle feedbacks requires better understanding and improved representation of the carbon cycle in permafrost regions within current earth system models. Here, we evaluated 10 terrestrial ecosystem models for their estimated net primary productivity (NPP) and its vulnerability to climate change in permafrost regions in the Northern Hemisphere. Those models were run retrospectively between 1960 and 2009. In comparison with MODIS satellite estimates, most models produce higher NPP (310 ± 12 g C m-2 yr-1) than MODIS (240 ± 20 g C m-2 yr-1) over the permafrost regions during 2000‒2009. The modeled NPP was then decomposed into gross primary productivity (GPP) and the NPP/GPP ratio (i.e., C use efficiency; CUE). By comparing the simulated GPP with a flux-tower-based database [Jung et al. Journal of Geophysical Research 116 (2011) G00J07] (JU11), we found although models only produce 10.6% higher mean GPP than JU11 over 1982‒2009, there was a two-fold disparity among models (397 to 830 g C m-2 yr-1). The model-to-model variation in GPP mainly resulted from the seasonal peak GPP and in low-latitudinal permafrost regions such as the Tibetan Plateau. Most models overestimate the CUE in permafrost regions in comparison to calculated CUE from the MODIS NPP and JU11 GPP products and observation-based estimates at 8 forest sites. The models vary in their sensitivities of NPP, GPP and CUE to historical changes in air temperature, atmospheric CO2 concentration and precipitation. For example, climate warming enhanced NPP in four models via increasing GPP but reduced NPP in two other models by decreasing both GPP and CUE. The results indicate that the model predictability of C cycle in permafrost regions can be improved by better representation of those processes controlling the seasonal maximum GPP and the CUE as well as their sensitivity to climate change.

  3. Modelling GPP and chlorophyll fluorescence using SCOPE (Invited)

    NASA Astrophysics Data System (ADS)

    van der Tol, C.; Verhoef, W.

    2009-12-01

    Chlorophyll fluorescence of Photosystem II (PSII) is a measure for photosynthetic processes and the functional state of the vegetation. Research in the past has focused on the active (light-induced) measurement of fluorescence at leaf and field scale. Current research focuses on the potential of satellite remote sensing of passive (solar-induced) chlorophyll fluorescence of PSII to monitor photosynthetic processes of terrestrial vegetation at large spatial scales. This research includes the relationship between top-of-canopy (TOC) fluorescence and gross primary production (GPP). The recently developed model SCOPE simulates this relationship using three sub-models. The first sub-model (FLUSPECT) is based on PROSPECT and describes leaf fluorescence spectra as a function of their chemical composition. The second sub-model describes the effects of leaf temperature, humidity and irradiance on these spectra and on actual photosynthesis. The third sub-model is a canopy level radiative transfer model, which calculates the scattering and absorption of solar radiation and fluorescence within a canopy, and computes the TOC spectrum of fluorescence in observation direction. A sensitivity analysis of the model shows a strong relationship between solar induced fluorescence and GPP at canopy level. This relationship is consistent with data from field campaigns. Fluorescence and GPP are sensitive to stress conditions including high leaf temperatures and water stress.

  4. An algorithm of gross primary production capacity from GCOM-C1/SGLI

    NASA Astrophysics Data System (ADS)

    Muramatsu, Kanako; Soyama, Noriko; Furumi, Shinobu; Daigo, Motomasa; Mineshita, Yukiko

    An algorithm of gross primary production (GPP) capacity from GCOM-C1/SGLI is presented. GCOM-C1 satellite will be launched in 2016. The characteristics of this method corresponds to photosynthesis process, and was to use light-response curves. The photosynthesis velocity depends on it's capacity and depression because of weather conditions. The capacity part depends on one of plant physiological parameters of chlorophyll contents of a leaf. In the previous study ( J. Thanyapraneedkul et al., 2013 ), the framework of estimation method was developed how to determine the two parameters, initial slope and maximum of GPP capacity in the light saturation, of light-response curves of GPP capacity using FLUX data and satellite data. The initial slope was used as fixed values for each plant functional types. The maximum of GPP capacity at the light saturation was determined from the linear relationship between GPP capacity at 2000 (mumol/m2/s) and Chlorophyll index (CIgreen) using green band developed by Gitelson et al. (1996). The relationship determined for five plant functional types of needleleaf deciduous trees, broadleaf deciduous trees, needleleaf evergreen trees, C3 grass, and crops were determined. For applying the method, other plant functional types were needed. In this study, additional four plant functional types were studied for open shrub, closed shrub, mixed forest and tropical rain forest, and the initial slopes and the relationship between GPP capacity at 2000 (umol/m2/s) and CIgreen for each plant functional types were determined. From the results, the relationship were divided into three groups. One was grass, and open shrubs, and second one was forest types except for tropical rain forest, and third one was tropical rain forest. For each group, the slope of the relationship was almost same value, and only the intercept was different. Whether the rules were extracted for determination of the intercept was discussed and the estimation results of GPP

  5. Estimating Daytime Ecosystem Respiration to Improve Estimates of Gross Primary Production of a Temperate Forest

    PubMed Central

    Sun, Jinwei; Wu, Jiabing; Guan, Dexin; Yao, Fuqi; Yuan, Fenghui; Wang, Anzhi; Jin, Changjie

    2014-01-01

    Leaf respiration is an important component of carbon exchange in terrestrial ecosystems, and estimates of leaf respiration directly affect the accuracy of ecosystem carbon budgets. Leaf respiration is inhibited by light; therefore, gross primary production (GPP) will be overestimated if the reduction in leaf respiration by light is ignored. However, few studies have quantified GPP overestimation with respect to the degree of light inhibition in forest ecosystems. To determine the effect of light inhibition of leaf respiration on GPP estimation, we assessed the variation in leaf respiration of seedlings of the dominant tree species in an old mixed temperate forest with different photosynthetically active radiation levels using the Laisk method. Canopy respiration was estimated by combining the effect of light inhibition on leaf respiration of these species with within-canopy radiation. Leaf respiration decreased exponentially with an increase in light intensity. Canopy respiration and GPP were overestimated by approximately 20.4% and 4.6%, respectively, when leaf respiration reduction in light was ignored compared with the values obtained when light inhibition of leaf respiration was considered. This study indicates that accurate estimates of daytime ecosystem respiration are needed for the accurate evaluation of carbon budgets in temperate forests. In addition, this study provides a valuable approach to accurately estimate GPP by considering leaf respiration reduction in light in other ecosystems. PMID:25419844

  6. Application of MODIS GPP to Forecast Risk of Hantavirus Pulmonary Syndrome Based on Fluctuations in Reservoir Population Density

    NASA Astrophysics Data System (ADS)

    Loehman, R.; Heinsch, F. A.; Mills, J. N.; Wagoner, K.; Running, S.

    2003-12-01

    Recent predictive models for hantavirus pulmonary syndrome (HPS) have used remotely sensed spectral reflectance data to characterize risk areas with limited success. We present an alternative method using gross primary production (GPP) from the MODIS sensor to estimate the effects of biomass accumulation on population density of Peromyscus maniculatus (deer mouse), the principal reservoir species for Sin Nombre virus (SNV). The majority of diagnosed HPS cases in North America are attributed to SNV, which is transmitted to humans through inhalation of excretions and secretions from infected rodents. A logistic model framework is used to evaluate MODIS GPP, temperature, and precipitation as predictors of P. maniculatus density at established trapping sites across the western United States. Rodent populations are estimated using monthly minimum number alive (MNA) data for 2000 through 2002. Both local meteorological data from nearby weather stations and 1.25 degree x 1 degree gridded data from the NASA DAO were used in the regression model to determine the spatial sensitivity of the response. MODIS eight-day GPP data (1-km resolution) were acquired and binned to monthly average and monthly sum GPP for 3km x 3km grids surrounding each rodent trapping site. The use of MODIS GPP to forecast HPS risk may result in a marked improvement over past reflectance-based risk area characterizations. The MODIS GPP product provides a vegetation dynamics estimate that is unique to disease models, and targets the fundamental ecological processes responsible for increased rodent density and amplified disease risk.

  7. Improving the estimation of terrestrial gross primary productivity by downscaling global sun-induced chlorophyll fluorescence

    NASA Astrophysics Data System (ADS)

    Cescatti, A.; Duveiller, G.

    2015-12-01

    The synoptic nature of satellite remote sensing makes this technique a key tool to contribute to estimating the amount of Carbon fixed by vegetation at global scale. From the various types of information that can be derived from space, the recent capacity to create global datasets of sun-induced chlorophyll fluorescence (SIF) may prove to be a game-changer. SIF is a signal emitted by the photosynthetic machinery itself that, under the illumination conditions in which it can be estimated by satellite, has been shown to be proportional to gross primary productivity (GPP). However, this relationship is dependent on vegetation types that are typically spatially mixed at the coarse spatial resolution of SIF datasets (at best 0.5°), which in turn is a consequence of the complexity of the SIF retrieval itself. This study demonstrates how 0.5° SIF derived from GOME-2 data can be downscaled to a more adequate spatial resolution of 0.05° by combining 3 explanatory biophysical variables derived from the MODIS sensor (NDVI, land surface temperature and evapotranspiration) under a semi-empirical light-use efficiency framework. The finer spatial resolution results in a cleaner signal when aggregating it per land cover type. The signal is also better correlated in time with GPP estimated from flux towers, reaching the same level of performance than global GPP products calibrated on such flux towers and driven by meteorological and remote sensing variables (other than SIF). Establishing linear relationships between SIF and flux-tower GPP at vegetation type level allows to estimate values of global terrestrial vegetation gross productivity that have different magnitude but similar temporal patterns as other GPP products. Based on downscaled SIF, the mean global GPP values over the period 2007 to 2013 are (for deciduous broadleaf and mixed forests) 13.7, (for evergreen needleleaf forests) 2.5, (for grasslands) 12.5 and (savannahs and woody savannas) 36.8 Pg of Carbon per year.

  8. Modeling the Impacts of Long-Term Warming Trends on Gross Primary Productivity Across North America

    NASA Astrophysics Data System (ADS)

    Mekonnen, Z. A.; Grant, R. F.

    2014-12-01

    There is evidence of warming over recent decades in most regions of North America (NA) that affects ecosystem productivity and the past decade has been the warmest since instrumental records of global surface temperatures began. In this study, we examined the spatial and temporal variability and trends of warming across NA using climate data from the North America Regional Reanalysis (NARR) from 1979 to 2010 with a 3-hourly time-step and 0.250 x 0.250 spatial resolution as part of the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). A comprehensive mathematical process model, ecosys was used to simulate impacts of this variability in warming on gross primary productivity (GPP). In a test of model results, annual GPP modeled for pixels which corresponded to the locations of 25 eddy covariance towers correlated well (R2=0.76) with annual GPP derived from the flux towers in 2005. At the continental scale long-term (2000 - 2010) annual average modeled GPP for NA correlated well (geographically weighed regression R2 = 0.8) with MODIS GPP, demonstrating close similarities in spatial patterns. Results from the NARR indicated that most areas of NA, particularly high latitude regions, have experienced warming but changes in precipitation vary spatially over the last three decades. GPP modeled in most areas with lower mean annual air temperature (Ta), such as those in boreal climate zones, increased due to early spring and late autumn warming observed in NARR. However modeled GPP declined in most southwestern regions of NA, due to water stress from rising Ta and declining precipitation. Overall, GPP modeled across NA had a positive trend of +0.025 P g C yr-1 with a range of -1.16 to 0.87 P g C yr-1 from the long-term mean. Interannual variability of GPP was the greatest in southwest of US and part of the Great Plains, which could be as a result of frequent El Niño-Southern Oscillation' (ENSO) events that led to major droughts.

  9. On Extrapolating Nighttime Ecosystem Respiration To Daytime Conditions and Implications for Gross Primary Productivity Estimation

    NASA Astrophysics Data System (ADS)

    Galvagno, M.; Wohlfahrt, G.

    2015-12-01

    Gross primary productivity (GPP) is a key term in the carbon cycle science. Being difficult or even impossible, at the ecosystem scale to directly quantify, various methods are used to estimate GPP, such as: eddy covariance CO2 flux partitioning, carbonyl sulfide exchange, sun-induced fluorescence, isotopes of CO2, and the photochemical reflectance index. The primary source of global GPP estimates is the FLUXNET project within which GPP is estimated in a consistent fashion through eddy covariance flux partitioning at more than 700 sites globally. Since the net ecosystem CO2 exchange (NEE) reflects net uptake during daytime, when photosynthesis exceeds respiration, and net emission during nighttime due to ecosystem respiration (RECO), the eddy covariance flux partitioning is based on the idea that daytime RECO may be inferred from nighttime NEE direct measurements, and consequently GPP can be obtained by subtracting RECO from NEE. However, the main assumption underlying this approach, which is that a temperature-dependent model of RECO parametrised based on nighttime temperatures may be extrapolated to daytime temperatures, has not been conclusively tested. This study investigates whether nighttime measurements of RECO provide unbiased estimates of daytime RECO. To this end we used ecosystem respiration chambers in a mountain grassland which, by keeping the vegetation in the dark during the measurement, allowed us to directly quantify RECO during both day and night. These data, pooled by day, night or day and night, were then used to parametrise temperature dependent models of RECO. Results show that day and night RECO do not follow the same relationship with temperature and that RECO inferred by using the nighttime parametrisation overestimates the true respiration. Potential reasons of this observed bias, like the overestimation of daytime mitochondrial respiration and implications for the quantification of GPP are discussed.

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

    SciTech Connect

    Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.; Chen, Jiquan; Baldocchi, Dennis D.; Cook, David R.; Oren, Ram; Richardson, Andrew D.; Wharton, Sonia; Ma, Siyan; Martin, Timothy A.; Verma, Shashi B.; Suyker, Andrew E.; Scott, Russell L.; Monson, Russell K.; Litvak, Marcy; Hollinger, David Y.; Sun, Ge; Davis, Kenneth J.; Bolstad, Paul V.; Burns, Sean P.; Curtis, Peter S.; Drake, Bert G.; Falk, Matthias; Fischer, Marc L.; Foster, David R.; Gu, Lianhong; Hadley, Julian L.; Katul, Gabriel G.; Matamala, Roser; McNulty, Steve; Meyers, Tilden P.; Munger, J. William; Noormets, Asko; Oechel, Walter C.; U, Kyaw Tha Paw; Schmid, Hans Peter; Starr, Gregory; Torn, Margaret S.; Wofsy, Steven C.

    2009-01-28

    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 range 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

  11. Modeling gross primary production and ecosystem respiration for terrestrial ecosystems in North China and Tibet Plateau using MODIS imagery

    NASA Astrophysics Data System (ADS)

    Gao, Y.; Yu, G.; Yan, H.; Zhu, X.; Li, S.; Wang, Q.; Zhang, J.; Wang, Y.; Li, Y.; Zhao, L.; Shi, P.

    2013-12-01

    Gross primary production (GPP) and ecosystem respiration (Re) are two large components in the studying of regional and global carbon cycles. Accurate quantification of spatio-temporal variations of GPP and Re for terrestrial ecosystems is of great importance to research carbon budget on regional and global scales. In this study, we proposed two satellite-based models, i.e. Photosynthetic Capacity Model (PCM) and Ecosystem Respiration Model (ERM), to simulate GPP and Re of terrestrial ecosystems, respectively. Multi-year eddy CO2 flux data from five vegetation types in North China (temperate mixed forest, temperate steppe) and Tibet Plateau (alpine shrubland, alpine marsh and alpine meadow-steppe) were used for assessing the model performances. The PCM model was driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI) from MODIS imagery. In most cases, the PCM-simulated GPP and the observed GPP displayed very consistent seasonal and inter-seasonal variability regardless of vegetation types. The PCM predicted versus observed GPP performed better than the MODIS GPP products, and was compatible with the Vegetation Photosynthesis Model (VPM). Moreover, the model parameter of the PCM could be gained from the linear function of mean annual remote sensing data. Based on this linear function, the PCM model simulated 93% variations of the observed GPP across all five vegetation types. The ERM model was developed based on both GPP and temperature, and was driven by EVI, LSWI and the Land Surface Temperature (LST) from MODIS imagery. In most cases, the seasonal and interannual variations of the simulated Re matched well with the observed Re. Compared with the model driven by temperature, and the model further added GPP in the reference respiration, the ERM model was optimal in each vegetation type. The model parameters of the ERM could also be presented by the liner functions of mean annual remote sensing data. Based on these linear functions, 90

  12. Estimation of terrestrial carbon fluxes over East Asia through AsiaFlux and improved MODIS gross primary production data

    NASA Astrophysics Data System (ADS)

    Kim, Miae; Im, Jungho; Lee, Junghee; Shin, Minso; Lee, Sanggyun

    2014-05-01

    The accurate estimation of carbon fluxes over terrestrial ecosystems provides useful information in studying the global carbon cycle. Estimates of carbon fluxes such as gross primary production (GPP) and net ecosystem exchanges (NEE) have been commonly used as indicators of the global carbon budgets. Eddy covariance (EC) flux towers are operating all over the world, networking each other. The towers provide temporally continuous measurements of carbon, water and energy over terrestrial ecosystems as being the best way to estimate ecosystem fluxes up to date. However, the EC flux towers only cover the scale of footprint, having difficulty in representing fluxes at the regional or continental scale. For upscaling flux tower data, satellite products that cover vast areas at high temporal resolution can be used. While many studies were conducted to estimate carbon fluxes from satellite products using process-based modeling and empirical modeling approaches, there are still great uncertainties in carbon flux estimation due to biases and errors associated with in-situ measurements, spatio-temporal discrepancy between satellite products and in-situ measurements, and relatively less accurate satellite products. In this paper, NEE and GPP were estimated using machine learning techniques including random forest, Cubist, and support vector regression. Various satellite products were used as independent variables such as land surface temperature, normalized difference vegetation index, enhanced vegetation index, leaf area index, fraction of photosynthetically active radiation, GPP, evapotranspiration, rainfall, normalized difference water index obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM). However, MODIS GPP based on the light use efficiency (LUE) model has some uncertainties derived from input data used in this model such as coarse spatial resolution of the Data Assimilation Office (DAO) meteorological

  13. Mapping cropland GPP in the north temperate region with space measurements of chlorophyll fluorescence

    NASA Astrophysics Data System (ADS)

    Guanter, L.; Zhang, Y.; Jung, M.; Joiner, J.; Voigt, M.; Huete, A. R.; Zarco-Tejada, P.; Frankenberg, C.; Lee, J.; Berry, J. A.; Moran, S. M.; Ponce-Campos, G.; Beer, C.; Camps-Valls, G.; Buchmann, N. C.; Gianelle, D.; Klumpp, K.; Cescatti, A.; Baker, J. M.; Griffis, T.

    2013-12-01

    Monitoring agricultural productivity is important for optimizing management practices in a world under a continuous increase of food and biofuel demand. We used new space measurements of sun-induced chlorophyll fluorescence (SIF), a vegetation parameter intrinsically linked to photosynthesis, to capture photosynthetic uptake of the crop belts in the north temperate region. The following data streams and procedures have been used in this analysis: (1) SIF retrievals have been derived from measurements of the MetOp-A / GOME-2 instrument in the 2007-2011 time period; (2) ensembles of process-based and data-driven biogeochemistry models have been analyzed in order to assess the capability of global models to represent crop gross primary production (GPP); (3) flux tower-based GPP estimates covering the 2007-2011 time period have been extracted over 18 cropland and grassland sites in the Midwest US and Western Europe from the Ameriflux and the European Fluxes Database networks; (4) large-scale NPP estimates have been derived by the agricultural inventory data sets developed by USDA-NASS and Monfreda et al. The strong linear correlation between the SIF space retrievals and the flux tower-based GPP, found to be significantly higher than that between reflectance-based vegetation indices (EVI, NDVI and MTCI) and GPP, has enabled the direct upscaling of SIF to cropland GPP maps at the synoptic scale. The new crop GPP estimates we derive from the scaling of SIF space retrievals are consistent with both flux tower GPP estimates and agricultural inventory data. These new GPP estimates show that crop productivity in the US Western Corn Belt, and most likely also in the rice production areas in the Indo-Gangetic plain and China, is up to 50-75% higher than estimates by state-of-the-art data-driven and process-oriented biogeochemistry models. From our analysis we conclude that current carbon models have difficulties in reproducing the special conditions of those highly productive

  14. Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current

    PubMed Central

    Reimer, Janet J.; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J. Martin; Lara-Lara, Ruben

    2015-01-01

    Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could

  15. Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current.

    PubMed

    Reimer, Janet J; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J Martin; Lara-Lara, Ruben

    2015-01-01

    Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  18. Estimation of gross primary production over burned black spruce forests in interior Alaska using MODIS data

    NASA Astrophysics Data System (ADS)

    Otsuki, M.; Iwata, H.; Harazono, Y.; Iwata, T.

    2012-12-01

    Black spruce forests, which are distributed widely in Alaska and Canada, have been reported to be sinks of carbon dioxide (CO2) under the current climate. However, an increasing trend of wildfire occurrence, and its magnitude, in interior Alaska, may alter the future CO2 budget in regional scale. The goal of this study is to estimate the gross primary production (GPP) in burned area using the light-use efficiency model with MODerate resolution Imaging Spectroradiometer (MODIS) data. Accuracy of GPP estimation was improved by explicitly treating burned area with a new parameterization of light-use efficiency and fraction of absorbed photosynthetically active radiation (FPAR). To parameterize the model, we started a CO2flux observation at a burned black spruce site (65°07N, 147°26W) in interior Alaska in 2008. At this site, a severe wildfire occurred in late June 2004, and almost all vegetation were burned. The vegetation is recovering and saplings of deciduous tree are currently starting to dominate. In order to parameterize the light-use efficiency for burned area, we observed absorption of photosynthetically active radiation (PAR) along with the CO2flux. The obtained maximum light-use efficiency gradually increased over 2009-2011 with the vegetation recovery. In calculating spatial distribution of GPP with satellite data, we estimated PAR distribution using a model developed by Nishida (2006, SOLA). FPAR and the maximum light-use efficiency were estimated from the relationships with satellite NDVI data. A comparison with GPP calculated using MOD15, total GPP can be over estimated by 7% if the burned areas are not considered. This overestimation will lead to a significant error in regional GPP estimation in severe fire years.

  19. 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.

  20. Seasonal controls of canopy chlorophyll content on forest carbon uptake: Implications for GPP modeling

    NASA Astrophysics Data System (ADS)

    Croft, H.; Chen, J. M.; Froelich, N. J.; Chen, B.; Staebler, R. M.

    2015-08-01

    Forested ecosystems represent an important part of the global carbon cycle, with accurate estimates of gross primary productivity (GPP) crucial for understanding ecosystem response to environmental controls and improving global carbon models. This research investigated the relationships between leaf area index (LAI) and leaf chlorophyll content (ChlLeaf) with forest carbon uptake. Ground measurements of LAI and ChlLeaf were taken approximately every 9 days across the 2013 growing season from day of year (DOY) 130 to 290 at Borden Forest, Ontario. These biophysical measurements were supported by on-site eddy covariance flux measurements. Differences in the temporal development of LAI and ChlLeaf were considerable, with LAI reaching maximum values within approximately 10 days of bud burst at DOY 141. In contrast, ChlLeaf accumulation only reached maximum values at DOY 182. This divergence has important implications for GPP models which use LAI to represent the fraction of light absorbed by a canopy (fraction of absorbed photosynthetic active radiation (fAPAR)). Daily GPP values showed the strongest relationship with canopy chlorophyll content (ChlCanopy; R2 = 0.69, p < 0.001), with the LAI and GPP relationship displaying nonlinearity at the start and end of the growing season (R2 = 0.55, p < 0.001). Modeled GPP derived from LAI × PAR and ChlCanopy × PAR was tested against measured GPP, giving R2 = 0.63, p < 0.001 and R2 = 0.82, p < 0.001, respectively. This work demonstrates the importance of considering canopy pigment status in deciduous forests, with models that use fAPARLAI rather than fAPARChl neglecting to account for the importance of leaf photosynthetic potential.

  1. Mapping net primary production and related biophysical variables with remote sensing: Application to the BOREAS region

    NASA Astrophysics Data System (ADS)

    Goetz, Scott J.; Prince, Stephen D.; Goward, Samuel N.; Thawley, Michelle M.; Small, Jennifer; Johnston, Andrew

    1999-11-01

    Maps of net and gross primary production, autotrophic respiration, biomass, and other biophysical variables were generated for 106 km2 of boreal forest in central Canada (the Boreal Ecosystem-Atmosphere (BOREAS) region) using a production efficiency model (PEM) driven with remotely sensed observations at 1 km2 spatial resolution. The PEM was based on carbon yields of absorbed photosynthetically active radiation for both gross and net primary production (GPP and NPP), accounting for environmental stress and autotrophic respiration (Ra). Physiological control was modeled using remotely sensed maps of air temperature, vapor pressure deficit, and soil moisture. The accuracy of the inferred variables was generally within 10-30% of point measurements at the surface and independent model results (both at the stand level). Biomass maps were derived from visible reflectance measurements and were also compared to independently derived maps. Area-averaged GPP was 604 g C m-2 yr-1 compared with average canopy respiration of 428 g C m-2 yr-1 and NPP of 235 g C m-2 yr-1. Net annual carbon uptake in net primary production for the region totaled 175 teragrams. Canopy carbon exchange (GPP and Ra) differed widely between land cover types even though the model does not use land cover information. Extensive areas of the least productive cover types (e.g., lowland needleleaf species) accounted for the greatest amount of NPP.

  2. MODIS GPP/NPP for complex land use area: a case study of comparison between MODIS GPP/NPP and ground-based measurements over Korea

    NASA Astrophysics Data System (ADS)

    Shim, C.

    2013-12-01

    The Moderate Resolution Imaging Radiometer (MODIS) Gross Primary Productivity (GPP)/Net Primary Productivity (NPP) has been widely used for the study on global terrestrial ecosystem and carbon cycle. The current MODIS product with ~ 1 km spatial resolution, however, has limitation on the information on local scale environment (< 1km), particularly on the regions with complex land-use types. Here we try to test the performance of MODIS annual GPP/NPP for a case of Korea, where the vegetation types are mostly heterogeneous within a size of MODIS products (~1km). We selected the sites where the ground/tower flux measurements and MODIS retrievals were simultaneously available and the land classification of sites agreed the forest type map (~71m) (1 site over Gwangneung flux tower (GDK) for 2006-2008 and 2 sites of ground measurements over Cheongju (CJ1 and CJ2) for 2011). The MODIS GPP are comparable to that of GDK (largely deciduous forest) within -6.3 ~ +2.3% of bias (-104.5 - 37.9 gCm-2yr-1). While the MODIS NPP of CJ1 at Cheongju (largely Larix leptolepis) underestimated NPP by 34% (-224.5 gCm-2yr-1), the MODIS NPP of CJ2 (largely Pinus densiflora) agreed well with -0.2% of bias (1.6 gCm-2yr-1). The fairly comparable values of the MODIS here however, cannot assure the quality of the MOD17 over the complex vegetation area of Korea since the ground measurements except the eddy covariance tower flux measurements are highly inconsistent. Therefore, the comprehensive experiments to represents GPP/NPP over diverse vegetation types for a comparable scale of MODIS with a consistent measurement technique are necessary in order to evaluate the MODIS vegetation productivity data over Korea, which contains a large portion of highly heterogeneous vegetation area.

  3. Estimating the Capacity of Gross Primary Production from Global Observation Satellite

    NASA Astrophysics Data System (ADS)

    Muramatsu, Kanako; Soyama, Noriko; Thanyaparaneedkul, Juthasinee; Furumi, Shinobu; Daigo, Motomasa

    2012-07-01

    Estimation of Gross Primary Production with high accuracy is important for understanding the carbon cycle. For estimating gross primary production, photosynthesis process was considers into two parts. One is the capacity and another is the reduction which is influenced by environmental conditions such as weather conditions of vapor pressure difference and soil moisture. The capacity estimation part is reported in this conference. For a leaf, it is well known photosynthesis capacity is mainly depend on amount of chlorophyll and enzyme. Chlorophyll contents reflect the color of a leaf. Since we focus on the chlorophyll contents for estimating the capacity of the gross primary production. It was reported by J. Thanyapraneedkul (2012) that vegetation index of the ratio of green band and near infrared was linear relationship with chlorophyll contents of a leaf, and was a linear relationship with the maximum photosynthesis at light saturation of light response curve with less stress conditions using flux data. The index is suitable for global observing satellite, because the spectral bands are available. Using the index and empirical relationship developed by J. Thanyapraneedkul, the light response curve with less stress can be estimated from the vegetation index. In this study, firstly, the global distribution of the index was studied. The regions of high index value in winter time were correspond to tropical rainforest. Next, the capacity of gross primary production was estimated using the light response curve using the index. The GPP capacity of the almost all regions was higher than MODIS GPP. For the tropical rain forest regions, the GPP capacity value was similar with MODIS GPP product.

  4. Improvement of satellite-based gross primary production through incorporation of high resolution input data over east asia

    NASA Astrophysics Data System (ADS)

    Park, Haemi; Im, Jungho; Kim, Miae

    2016-04-01

    Photosynthesis of plants is the main mechanism of carbon absorption from the atmosphere into the terrestrial ecosystem and it contributes to remove greenhouse gases such as carbon dioxide. Annually, 120 Gt of C is supposed to be assimilated through photosynthetic activity of plants as the gross primary production (GPP) over global land area. In terms of climate change, GPP modelling is essential to understand carbon cycle and the balance of carbon budget over various ecosystems. One of the GPP modelling approaches uses light use efficiency that each vegetation type has a specific efficiency for consuming solar radiation related with temperature and humidity. Satellite data can be used to measure various meteorological and biophysical factors over vast areas, which can be used to quantify GPP. NASA Earth Observing System (EOS) program provides Moderate Resolution Imaging Spectroradiometer (MODIS)-derived global GPP product, namely MOD17A2H, on a daily basis. However, significant underestimation of MOD17A2H has been reported in Eastern Asia due to its dense forest distribution and humid condition during monsoon rainy season in summer. The objective of this study was to improve underestimation of MODIS GPP (MOD17A2H) by incorporating meteorological data-temperature, relative humidity, and solar radiation-of higher spatial resolution than data used in MOD17A2H. Landsat-based land cover maps of finer resolution observation and monitoring - global land cover (FROM-GLC) at 30m resolution were used for selection of light use efficiency (LUE). GPP (eq1. GPP = APAR×LUE) is computed by multiplication of APAR (IPAR×fPAR) and LUE (ɛ= ɛmax×T(°C)scalar×VPD(Pa)scalar, where, T is temperature, VPD is vapour pressure deficit) in this study. Meteorological data of Japanese 55-year Reanalysis (JRA-55, 0.56° grid, 3hr) were used for calculation of GPP in East Asia, including Eastern part of China, Korean peninsula, and Japan. Results were validated using flux tower-observed GPP

  5. Evaluating post-disaster ecosystem resilience using MODIS GPP data

    NASA Astrophysics Data System (ADS)

    Frazier, Amy E.; Renschler, Chris S.; Miles, Scott B.

    2013-04-01

    An integrated community resilience index (CRI) quantifies the status, exposure, and recovery of the physical, economic, and socio-cultural capital for a specific target community. However, most CRIs do not account for the recovery of ecosystem functioning after extreme events, even though many aspects of a community depend on the services provided by the natural environment. The primary goal of this study was to monitor the recovery of ecosystem functionality (ecological capital) using remote sensing-derived gross primary production (GPP) as an indicator of 'ecosystem-wellness' and assess the effect of resilience of ecological capital on the recovery of a community via an integrated CRI. We developed a measure of ecosystem resilience using remotely sensed GPP data and applied the modeling prototype ResilUS in a pilot study for a four-parish coastal community in southwestern Louisiana, USA that was impacted by Hurricane Rita in 2005. The results illustrate that after such an extreme event, the recovery of ecological capital varies according to land use type and may take many months to return to full functionality. This variable recovery can potentially impact the recovery of certain businesses that rely heavily on ecosystem services such as agriculture, forestry, fisheries, and tourism.

  6. Effects of the partitioning of diffuse and direct solar radiation on satellite-based modeling of crop gross primary production

    NASA Astrophysics Data System (ADS)

    Xin, Qinchuan; Gong, Peng; Suyker, Andrew E.; Si, Yali

    2016-08-01

    Modeling crop gross primary production (GPP) is critical to understanding the carbon dynamics of agro-ecosystems. Satellite-based studies have widely used production efficiency models (PEM) to estimate cropland GPP, wherein light use efficiency (LUE) is a key model parameter. One factor that has not been well considered in many PEMs is that canopy LUE could vary with illumination conditions. This study investigates how the partitioning of diffuse and direct solar radiation influences cropland GPP using both flux tower and satellite data. The field-measured hourly LUE under cloudy conditions was 1.50 and 1.70 times higher than that under near clear-sky conditions for irrigated corn and soybean, respectively. We applied a two-leaf model to simulate the canopy radiative transfer process, where modeled photosynthetically active radiation (PAR) absorbed by canopy agreed with tower measurements (R2 = 0.959 and 0.914 for corn and soybean, respectively). Derived canopy LUE became similar after accounting for the impact of light saturation on leaf photosynthetic capacity under varied illumination conditions. The impacts of solar radiation partitioning on satellite-based modeling of crop GPP was examined using vegetation indices (VI) derived from MODIS data. Consistent with the field modeling results, the relationship between daily GPP and PAR × VI under varied illumination conditions showed different patterns in terms of regression slope and intercept. We proposed a function to correct the influences of direct and diffuse radiation partitioning and the explained variance of flux tower GPP increased in all experiments. Our results suggest that the non-linear response of leaf photosynthesis to light absorption contributes to higher canopy LUE on cloudy days than on clear days. We conclude that accounting for the impacts of solar radiation partitioning is necessary for modeling crop GPP on a daily or shorter basis.

  7. 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

  8. The new product fAPARchl is better than fAPARcanopy to describe terrestrial ecosystem photosynthesis (GPP)

    NASA Astrophysics Data System (ADS)

    Zhang, Q.; Middleton, E.; Cheng, Y.; Wei, J.

    2011-12-01

    Existing global climate models have been unable to accurately describe the intensity of photosynthetic activity or to discriminate this functionality among terrestrial vegetation canopies/ecosystems. Many satellite-based production efficiency models (PEMs), land-atmosphere interaction models and biogeochemical models (e.g., SiB, CLM and CASA) have used the concept of the fraction of photosynthetically active radiation (PAR) absorbed for vegetation photosynthesis (fAPARPSN) in their modeling work. These models typically use fAPAR for the whole canopy (fAPARcanopy) (usually denoted as FPAR or fAPAR) to represent fAPARPSN. However, this widely used FPAR parameter has proved to be physiologically insufficient to describe or retrieve terrestrial ecosystem photosynthesis. A much better alternative is to utilize the fraction of PAR absorbed by chlorophyll throughout a canopy/ecosystem (i.e., fAPARchl) to replace FPAR in these calculations. In this study, we present examples of fAPARchl, leaf fAPARNPV (the non-photosynthetic canopy fraction, without chlorophyll) and fAPARcanopy at 30 m spatial resolution for deciduous forests, evergreen forests and crops, obtained from Earth Observing One (EO-1) Hyperion satellite imagery. The differences obtained between fAPARchl and fAPARcanopy are significant for all of these vegetation types across the whole growing season. For instance, for the evergreen forests, fAPARchl changes seasonally, whereas the seasonal trend for fAPARcanopy is flat. Consequently, these differences translate into significant differences in estimates of fAPARPSN. We suggest modeling scientists should compare simulation outputs using fAPARcanopy versus fAPARchl, to check whether the differences are significant.

  9. Predicting gross primary production with high spatio-temporal resolution remote sensing datasets at regional scale

    NASA Astrophysics Data System (ADS)

    Fu, D.; Chen, B.

    2012-04-01

    Remote sensing has great potential for estimating gross primary production (GPP) without resorting to interpolation of many surface observations. Meanwhile, it can be applied to analyzing the variation of GPP at different ecosystems across a wide range of spatial, temporal, and spectral resolutions. However, the availability of input data for remote-sensing-based GPP models is the bottleneck. The input data of remote-sensing-based greenness and radiation (GR) model is more independent on climate or ground-based observations, and the result is promising. Previous work using this modeling approach only used coarse spatial resolution data (e.g. MODerate resolution Imaging Spectroradiometer, MODIS), the estimated spatio-temporal distributions of GPP with higher resolution remains unclear. To overcome this limitation, a modified image fusion method was developed based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (mESTARFM), producing images with high spatial and temporal resolutions based on Landsat Thematic Mapper (TM) / Enhanced TM Plus (ETM+) (high spatial resolution, low temporal resolution) and MODIS (low spatial resolution, high temporal resolution). Meanwhile, the Simple Analytical Footprint model on Eulerian coordinates (SAFE) model to estimate the flux tower's footprint, which will be helpful for GR model's calibration, and improve the accuracy of GPP estimate. In the study, twelve flux sites belonging to Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) were selected, covering grassland, forest, and wetland biomes. The remote sensing dataset acquired in this study for each site include MODIS reflectance product (MOD09A1, 500 m), Landsat TM /ETM+ (30 m), MODIS BRDF/ Albedo model parameter product (MCD43A1, 500 m), MODIS BRDF/ Albedo quality product (MCD43A2, 500 m). The steps are as follows:: (i) Landsat TM /ETM+ and MODIS data were used as mESTARFM inputs to produce reflectance datasets with high spatio

  10. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes

    USGS Publications Warehouse

    Yuan, W.; Liu, S.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, Allen H.; Goulden, M.L.; Hollinger, D.Y.; Hu, Y.; Law, B.E.; Stoy, P.C.; Vesala, T.; Wofsy, S.C.

    2007-01-01

    The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks. ?? 2007 Elsevier B.V. All rights reserved.

  11. Assessing soil fluxes of carbonyl sulfide to aid in ecosystem estimates of GPP

    NASA Astrophysics Data System (ADS)

    Whelan, M.; Rhew, R. C.; Campbell, J. E.; Hilton, T. W.; Berkelhammer, M. B.; Zumkehr, A. L.; Berry, J. A.

    2014-12-01

    Measuring the draw down of carbonyl sulfide (chemical formula: COS) over ecosystems can provide a new tool for estimating gross primary production (GPP) at important temporal and spatial scales. COS is a gas ubiquitous in the atmosphere that shares many characteristics with CO2: both are taken up by enzymes in plant leaves at a predictable ratio and in proportion to their ambient concentrations. While CO2 is simultaneously respired by soil and plant roots, the dominant flux of COS is foliar absorption. Previously, ecosystem soil fluxes of COS were thought to be negligible in the application of this COS-GPP proxy. Here we present new data describing controls on soil fluxes as a way to anticipate COS soil exchange over heterogeneous landscapes. Using soil samples from two agricultural sites in the Great Plains and one site in the Colorado Desert, we captured data from the extremes of ecosystem GPP in the United States. We then built a model describing COS soil fluxes with inputs of soil temperature and soil water content based on characterized soil behavior. This study provides an essential refinement in applying COS-GPP estimates over the continents.

  12. Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: implications for remote sensing of crop primary production.

    PubMed

    Gitelson, Anatoly A; Peng, Yi; Arkebauer, Timothy J; Suyker, Andrew E

    2015-04-01

    Vegetation productivity metrics such as gross primary production (GPP) at the canopy scale are greatly affected by the efficiency of using absorbed radiation for photosynthesis, or light use efficiency (LUE). Thus, close investigation of the relationships between canopy GPP and photosynthetically active radiation absorbed by vegetation is the basis for quantification of LUE. We used multiyear observations over irrigated and rainfed contrasting C3 (soybean) and C4 (maize) crops having different physiology, leaf structure, and canopy architecture to establish the relationships between canopy GPP and radiation absorbed by vegetation and quantify LUE. Although multiple LUE definitions are reported in the literature, we used a definition of efficiency of light use by photosynthetically active "green" vegetation (LUE(green)) based on radiation absorbed by "green" photosynthetically active vegetation on a daily basis. We quantified, irreversible slowly changing seasonal (constitutive) and rapidly day-to-day changing (facultative) LUE(green), as well as sensitivity of LUE(green) to the magnitude of incident radiation and drought events. Large (2-3-fold) variation of daily LUE(green) over the course of a growing season that is governed by crop physiological and phenological status was observed. The day-to-day variations of LUE(green) oscillated with magnitude 10-15% around the seasonal LUE(green) trend and appeared to be closely related to day-to-day variations of magnitude and composition of incident radiation. Our results show the high variability of LUE(green) between C3 and C4 crop species (1.43 g C/MJ vs. 2.24 g C/MJ, respectively), as well as within single crop species (i.e., maize or soybean). This implies that assuming LUE(green) as a constant value in GPP models is not warranted for the crops studied, and brings unpredictable uncertainties of remote GPP estimation, which should be accounted for in LUE models. The uncertainty of GPP estimation due to facultative and

  13. Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations

    PubMed Central

    Liu, Dan; Cai, Wenwen; Xia, Jiangzhou; Dong, Wenjie; Zhou, Guangsheng; Chen, Yang; Zhang, Haicheng; Yuan, Wenping

    2014-01-01

    Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year−1 (mean value ± standard deviation) across the vegetated area for the period 2000–2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year−1). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year−1, indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization. PMID:25375227

  14. 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. PMID:26606426

  15. High spatial resolution remote sensing imagery improves GPP predictions in disturbed, semi-arid woodlands

    NASA Astrophysics Data System (ADS)

    Krofcheck, D. J.; Eitel, J.; Vierling, L. A.; Schulthess, U.; Litvak, M. E.

    2012-12-01

    Climate across the globe is changing and consequently the productivity of terrestrial vegetation is changing with it. Gross primary productivity (GPP) is an integral part of the carbon cycle, yet challenging to measure everywhere, all the time. Efforts to estimate GPP in the context of climate change are becoming continually more salient of the need for models sensitive to the heterogeneous nature of drought and pest induced disturbance. Given the increased availability of high spatial resolution remotely sensed imagery, their use in ecosystem scale GPP estimation is becoming increasingly viable. We used a simple linear model with inputs derived from RapidEye time series data (5 meter spatial resolution) as compared to MODIS inputs (250 meter spatial resolution) to estimate GPP in intact and girdled PJ woodland to simulate drought and pest induced disturbance. An area equal to the MODIS pixels measured was aggregated using RapidEye data centered on the flux towers for comparison purposes. We generated four model runs, two using only MODIS or RapidEye spectral vegetation indices (VIs) and two using MODIS and RapidEye VIs combined at both the control and disturbed tower site. Our results suggest that for undisturbed regions, MODIS derived VIs perform better than the higher spatial resolution RapidEye VIs when a moisture sensitive index is incorporated into the model (RMSE of 17.51for MODIS vs. 22.71 for RapidEye). Modeling GPP in disturbed regions however benefits from the inclusion of high spatial resolution data (RMSE of 14.83 for MODIS vs. 14.70 for RapidEye). This discrepancy may have to do with the disparate scale of a MODIS pixel and the size of the tower fetch. Our results suggest that the best source of VI's for the modeling GPP in semi-arid woodlands depends on the level of disturbance in the landscape. Given that the rate and extent of drought and insect induced mortality events in terrestrial forests are projected to increase with our changing climate

  16. Modeling Gross Primary Production in Maize and Soybean Using Four Parameters: Light Quality, Temperature, Water Stress, and Phenology

    NASA Astrophysics Data System (ADS)

    Nguy-Robertson, A. L.; Suyker, A.; Xiao, X.; Thomas, T.

    2014-12-01

    Light use efficiency (LUE) models are used to estimate gross and net primary production (GPP, NPP). Earlier approaches have used one or more of the following factors impacting LUE to model GPP: (i) light climate, (ii) temperature, (iii) water stress, and (iv) phenology. In this study we seek to incorporate all four inputs as scalars for up- or down-regulating LUE in a daily GPP model. Traditional methods using satellite data are limited by cloudy conditions and revisit times. They require the use of interpolation to achieve daily estimates of GPP. Some parameters can vary greatly within a few days (i.e. light climate, temperature) and thus, reduce the accuracy of interpolations between scenes. Alternatively, methods that can combine spatially interpolated gridded meteorological and satellite data for parameters that change over the course of days to weeks (i.e. phenology) provide the best opportunity for a continuous daily estimate of GPP. This study seeks to develop the framework for such a model. Three Nebraska AmeriFlux sites between 2001 and 2012 (maize: 26 field-years; soybean: 10 field-years) were used to develop and validate a daily GPP model based on ground measurements of incoming photosynthetically active radiation, temperature, vapor pressure deficit, and leaf area index. This model was calibrated using eddy covariance data from 2001 to 2008 (RMSE = 2.2 g C m-2 d-1; MNB = 4.7%) and validated with 2009 to 2012 data (RMSE = 2.6 g C m-2 d-1; MNB = 1.7%). Modeled GPP was generally within 10% of measured growing season totals in each year from 2009 to 2012. Cumulatively, over the same four years, the sum of error and the sum of absolute error between the measured and modeled GPP, which provide measures of long-term bias, was ±5% and 2 to 9%, respectively, among the three sites. The inclusion of AmeriFlux cropland sites in Iowa, Illinois, and Minnesota will support this approach and provide additional validation sites for a daily GPP model using gridded

  17. Quantifying subtropical North Pacific gyre mixed layer primary productivity from Seaglider observations of diel oxygen cycles

    NASA Astrophysics Data System (ADS)

    Nicholson, David P.; Wilson, Samuel T.; Doney, Scott C.; Karl, David M.

    2015-05-01

    Using autonomous underwater gliders, we quantified diurnal periodicity in dissolved oxygen, chlorophyll, and temperature in the subtropical North Pacific near the Hawaii Ocean Time-series (HOT) Station ALOHA during summer 2012. Oxygen optodes provided sufficient stability and precision to quantify diel cycles of average amplitude of 0.6 µmol kg-1. A theoretical diel curve was fit to daily observations to infer an average mixed layer gross primary productivity (GPP) of 1.8 mmol O2 m-3 d-1. Cumulative net community production (NCP) over 110 days was 500 mmol O2 m-2 for the mixed layer, which averaged 57 m in depth. Both GPP and NCP estimates indicated a significant period of below-average productivity at Station ALOHA in 2012, an observation confirmed by 14C productivity incubations and O2/Ar ratios. Given our success in an oligotrophic gyre where biological signals are small, our diel GPP approach holds promise for remote characterization of productivity across the spectrum of marine environments.

  18. 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

  19. Temperature dependence of CO2-enhanced primary production in the European Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Holding, J. M.; Duarte, C. M.; Sanz-Martín, M.; Mesa, E.; Arrieta, J. M.; Chierici, M.; Hendriks, I. E.; García-Corral, L. S.; Regaudie-de-Gioux, A.; Delgado, A.; Reigstad, M.; Wassmann, P.; Agustí, S.

    2015-12-01

    The Arctic Ocean is warming at two to three times the global rate and is perceived to be a bellwether for ocean acidification. Increased CO2 concentrations are expected to have a fertilization effect on marine autotrophs, and higher temperatures should lead to increased rates of planktonic primary production. Yet, simultaneous assessment of warming and increased CO2 on primary production in the Arctic has not been conducted. Here we test the expectation that CO2-enhanced gross primary production (GPP) may be temperature dependent, using data from several oceanographic cruises and experiments from both spring and summer in the European sector of the Arctic Ocean. Results confirm that CO2 enhances GPP (by a factor of up to ten) over a range of 145-2,099 μatm however, the greatest effects are observed only at lower temperatures and are constrained by nutrient and light availability to the spring period. The temperature dependence of CO2-enhanced primary production has significant implications for metabolic balance in a warmer, CO2-enriched Arctic Ocean in the future. In particular, it indicates that a twofold increase in primary production during the spring is likely in the Arctic.

  20. Evaluation of MODIS GPP over a complex ecosystem in East Asia: A case study at Gwangneung flux tower in Korea

    NASA Astrophysics Data System (ADS)

    Shim, Changsub; Hong, Jiyoun; Hong, Jinkyu; Kim, Youngwook; Kang, Minseok; Malla Thakuri, Bindu; Kim, Yongwon; Chun, Junghwa

    2014-12-01

    Moderate Resolution Imaging Radiometer (MODIS) gross primary productivity (GPP) has been used widely to study the global carbon cycle associated with terrestrial ecosystems. The retrieval of the current MODIS productivity with a 1 × 1 km2 resolution has limitations when presenting subgrid scale processes in terrestrial ecosystems, specifically when forests are located in mountainous areas, and shows heterogeneity in vegetation type due to intensive land use. Here, we evaluate MODIS GPP (MOD17) at Gwangneung deciduous forest KoFlux tower (deciduous forest; GDK) for 2006-2010 in Korea, where the forests comprise heterogeneous vegetation cover over complex terrain. The monthly MODIS GPP data overestimated the GDK measurements in a range of +15% to +34% and was fairly well correlated (R = 0.88) with the monthly variability at GDK during the growing season. In addition, the MODIS data partly represented the sharp GPP reduction during the Asian summer monsoon (June-September) when intensive precipitation considerably reduces solar radiation and disturbs the forest ecosystem. To examine the influence of subgrid scale heterogeneity on GPP estimates over the MODIS scale, the individual vegetation type and its area within a corresponding MODIS pixel were identified using a national forest type map (∼71-m spatial resolution), and the annual GPP in the same area as the MODIS pixel was estimated. This resulted in a slight reduction in the positive MODIS bias by ∼10%, with a high degree of uncertainty in the estimation. The MODIS discrepancy for GDK suggests further investigation is necessary to determine the MODIS errors associated with the site-specific aerodynamic and hydrological characteristics that are closely related to the mountainous topography. The accuracy of meteorological variables and the impact of the very cloudy conditions in East Asia also need to be assessed.

  1. Microbial production of primary metabolites

    NASA Astrophysics Data System (ADS)

    Demain, Arnold L.

    1980-12-01

    Microbial production of primary metabolites contributes significantly to the quality of life. Through fermentation, microorganisms growing on inexpensive carbon sources can produce valuable products such as amino acids, nucleotides, organic acids, and vitamins which can be added to food to enhance its flavor or increase its nutritive value. The contribution of microorganisms will go well beyond the food industry with the renewed interest in solvent fermentations. Microorganisms have the potential to provide many petroleum-derived products as well as the ethanol necessary for liquid fuel. The role of primary metabolites and the microbes which produce them will certainly increase in importance.

  2. Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

    NASA Astrophysics Data System (ADS)

    Westergaard-Nielsen, Andreas; Lund, Magnus; Hansen, Birger Ulf; Tamstorf, Mikkel Peter

    2013-12-01

    The Arctic is experiencing disproportionate warming relative to the global average, and the Arctic ecosystems are as a result undergoing considerable changes. Continued monitoring of ecosystem productivity and phenology across temporal and spatial scales is a central part of assessing the magnitude of these changes. This study investigates the ability to use automatic digital camera images (DCIs) as proxy data for gross primary production (GPP) in a complex low Arctic wetland site. Vegetation greenness computed from DCIs was found to correlate significantly (R2 = 0.62, p < 0.001) with a normalized difference vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid functions for each plant community. GPP at light saturation modeled from eddy covariance (EC) flux measurements were found to correlate significantly with vegetation greenness for all plant communities in the studied year (i.e., 2010), and the highest correlation was found between modeled fen greenness and GPP (R2 = 0.85, p < 0.001). Finally, greenness computed within modeled EC footprints were used to evaluate the influence of individual plant communities on the flux measurements. The study concludes that digital cameras may be used as a cost-effective proxy for potential GPP in remote Arctic regions.

  3. Primary productivity in the sea

    SciTech Connect

    Falkowski, P.G.

    1980-01-01

    Recent progress in primary productivity is discussed in the book based on 27 symposia texts and 19 poster abstracts. Most papers deal with particular cellular processes in pelagic phytoplankton and their relationship to whole plant photosynthesis and growth. In addition, presentations on the productivity of the seaweed, Laminaria, zooxanthellae and whole corals are included. Other articles discuss predictive modeling, new developments in remote sensing, nutrient regeneration within the sea, grazing effects, and carbon cycling. (JMT)

  4. Impacts of Light Use Efficiency and fPAR Parameterization on Gross Primary Production Modeling

    NASA Technical Reports Server (NTRS)

    Cheng, Yen-Ben; Zhang, Qingyuan; Lyapustin, Alexei I.; Wang, Yujie; Middleton, Elizabeth M.

    2014-01-01

    This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially

  5. Evaluation of terrestrial primary production using biosphere models and space-based measurements of fluorescence

    NASA Astrophysics Data System (ADS)

    Parazoo, N.; Bowman, K. W.; Frankenberg, C.; Sitch, S.; Fisher, J. B.; Jones, D. B.; Friedlingstein, P.; Poulter, B.

    2013-12-01

    Changes in the processes that control terrestrial carbon uptake are highly uncertain but likely to have a significant influence on future atmospheric CO2 levels. RECCAP aims to improve process understanding by reconciling fluxes from top-down CO2 inversions and bottom-up estimates from an ensemble of dynamical global vegetation models (DGVMs). As these models are typically used in projections of climate change a key part of this effort is evaluating drivers of net carbon exchange within the current climate. Of particular importance are the spatial distribution and time rate of change of gross primary productivity (GPP). Recent advances in the remote sensing of solar-induced chlorophyll fluorescence opens up a new possibility to directly measure planetary photosynthesis on spatially resolved scales. Here, we discuss a new methodology for estimating GPP from an optimal combination of an ensemble of DGVMs from the TRENDY project with satellite-based observations of chlorophyll fluorescence from GOSAT. We evaluate optimized fluxes against flux tower and semi-empirical data in N. America, Europe, and S. America, then examine the period 2009-2010 to identify critical regions (i.e., regions with high annual GPP) where optimized and model fluxes diverge.

  6. Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data

    NASA Astrophysics Data System (ADS)

    Muramatsu, Kanako; Furumi, Shinobu; Daigo, Motomasa

    2015-10-01

    We plan to estimate gross primary production (GPP) using the SGLI sensor on-board the GCOM-C1 satellite after it is launched in 2017 by the Japan Aerospace Exploration Agency, as we have developed a GPP estimation algorithm that uses SGLI sensor data. The characteristics of this GPP estimation method correspond to photosynthesis. The rate of plant photosynthesis depends on the plant's photosynthesis capacity and the degree to which photosynthesis is suppressed. The photosynthesis capacity depends on the chlorophyll content of leaves, which is a plant physiological parameter, and the degree of suppression of photosynthesis depends on weather conditions. The framework of the estimation method to determine the light-response curve parameters was developed using ux and satellite data in a previous study[1]. We estimated one of the light-response curve parameters based on the linear relationship between GPP capacity at 2000 (μmolm-2s-1) of photosynthetically active radiation and a chlorophyll index (CIgreen [2;3] ). The relationship was determined for seven plant functional types. Decreases in the photosynthetic rate are controlled by stomatal opening and closing. Leaf stomatal conductance is maximal during the morning and decreases in the afternoon. We focused on daily changes in leaf stomatal conductance. We used open shrub flux data and MODIS reflectance data to develop an algorithm for a canopy. We first evaluated the daily changes in GPP capacity estimated from CIgreen and photosynthesis active radiation using light response curves, and GPP observed during a flux experiment. Next, we estimated the canopy conductance using flux data and a big-leaf model using the Penman-Monteith equation[4]. We estimated GPP by multiplying GPP capacity by the normalized canopy conductance at 10:30, the time of satellite observations. The results showed that the estimated daily change in GPP was almost the same as the observed GPP. From this result, we defined a normalized canopy

  7. Sensitivity of global terrestrial gross primary production to hydrologic states simulated by the Community Land Model using two runoff parameterizations

    NASA Astrophysics Data System (ADS)

    Lei, Huimin; Huang, Maoyi; Leung, L. Ruby; Yang, Dawen; Shi, Xiaoying; Mao, Jiafu; Hayes, Daniel J.; Schwalm, Christopher R.; Wei, Yaxing; Liu, Shishi

    2014-09-01

    Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simulations of the carbon cycle, numerical experiments were performed using version 4 of the Community Land Model with two widely adopted runoff generation parameterizations from the TOPMODEL and Variable Infiltration Capacity (VIC) model under the same protocol. The results showed that differences in the runoff generation schemes caused a relative difference of 36% and 34% in global mean total runoff and soil moisture, respectively, with substantial differences in their spatial distribution and seasonal variability. Changes in the simulated gross primary production (GPP) were found to correlate well with changes in soil moisture through its effects on leaf photosynthesis (An) and leaf area index (LAI), which are the two dominant components determining GPP. Soil temperature, which is influenced by soil moisture, also affects LAI and GPP for the seasonal-deciduous and stress-deciduous plant functional types that dominate in cold regions. Consequently, the simulated global mean GPP differs by 20.4% as a result of differences in soil moisture and soil temperature simulated between the two models. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.

  8. Integrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfield

    NASA Technical Reports Server (NTRS)

    Cheng, Yen-Ben; Middleton, Elizabeth M.; Zhang, Qingyuan; Huemmrich, Karl F.; Campbell, Petya K. E.; Corp, Lawrence A.; Cook, Bruce D.; Kustas, William P.; Daughtry, Criag S.

    2013-01-01

    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 growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2 = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2 = 0.80, RMSE = 0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations.

  9. Magic spot: (p) ppGpp.

    PubMed

    Wu, Jun; Xie, Jianping

    2009-08-01

    Guanosine 5'-(tri)diphosphate, 3'-diphosphate [(p) ppGpp] is a small nucleic acid that helps bacteria survive in limited environments. Gene chip shows that (p) ppGpp is a global transcription-regulator of genes related to important bacterial metabolic processes. Therefore, more attention should be focused on the molecular mechanisms of (p) ppGpp, as it is the foundation to understanding how bacteria adapt to extreme circumstances through the stringent response. PMID:19391118

  10. Modeling climate change impacts on primary production by the terrestrial biosphere

    NASA Astrophysics Data System (ADS)

    Davis, T. W.; Prentice, I. C.; Evans, B. J.; Gilbert, X.

    2013-12-01

    A modelling system is under development for the global hindcasting and analysis of spatial and temporal patterns in terrestrial gross primary production (GPP). The aim is to produce the simplest possible model that makes good use of observational data (from flux towers, meteorological stations, and remote-sensing satellites) while defensibly representing the principal ecophysiological processes that govern GPP. The first modelling step consists of partitioning high time-resolution carbon dioxide flux data, using in situ photosynthetically active radiation (PAR) measurements. The second step estimates monthly light-use efficiency (LUE) from monthly aggregated GPP and gap-filled, monthly aggregated PAR, and analyses the empirical dependencies of LUE on vegetational and environmental factors in order to yield a simple predictive model for LUE. The third and final stage generates spatial fields of monthly GPP based on remotely sensed reflectances and predicted LUE. The basis of the system is an efficient database structure, which is the "tool chest" for modelling. The tool chest is designed to hold the variety of observational data necessary to complete each stage of the model including point measurements of CO2 fluxes and PAR, and gridded measurements of surface reflectances and downwelling radiation. The Python programming language is used to upload, retrieve and process data. Although the model as currently developed is a data-driven, 'diagnostic' model, the intention is to use its basic elements in the construction of a next-generation vegetation and land-surface model based on a new theoretical approach to predict the light use efficiency of ecosystems. The model will strive for clarity and uniformity so that it may be used by researchers across disciplines. The use of an open-source programming language allows for portability and transparency. The model will invite a range of applications to the analysis of climate and CO2 change impacts on ecosystem processes.

  11. Atmospheric COS measurements and satellite-derived vegetation fluorescence data to evaluate the terrestrial gross primary productivity of CMIP5 model

    NASA Astrophysics Data System (ADS)

    Peylin, Philippe; MacBean, Natasha; Launois, Thomas; Belviso, Sauveur; Cadule, Patricia; Maignan, Fabienne

    2016-04-01

    Predicting the fate of the ecosystem carbon stocks and their sensitivity to climate change strongly relies on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. The Gross Primary Productivity (GPP) simulated by the different terrestrial models used in CMIP5 show large differences however, not only in terms of mean value but also in terms of phase and amplitude, thus hampering accurate investigations into carbon-climate feedbacks. While the net C flux of an ecosystem (NEE) can be measured in situ with the eddy covariance technique, the GPP is not directly accessible at larger scales and usually estimates are based on indirect measurements combining different tracers. Recent measurements of a new atmospheric tracer, the Carbonyl sulphide (COS), as well as the global measurement of Solar Induced Fluorescence (SIF) from satellite instruments (GOSAT, GOME2) open a new window for evaluating the GPP of earth system models. The use of COS relies on the fact that it is absorbed by the leaves in a similar manner to CO2, while there seems to be nothing equivalent to respiration for COS. Following recent work by Launois et al. (ACP, 2015), there is a potential to evaluate model GPP from atmospheric COS and CO2 measurements, using a transport model and recent parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of COS. Vegetation uptake of COS is modeled as a linear function of GPP and the ratio of COS to CO2 rate of uptake by plants. For the fluorescence, recent measurements of SIF from space appear to be highly correlated with monthly variations of data-driven GPP estimates (Guanter et al., 2012), following a strong dependence of vegetation SIF on photosynthetic activity. These global measurements thus provide new indications on the timing of canopy carbon uptake. In this work, we propose a dual approach that combines the strength of both COS and SIF

  12. Evaluating the potential of Southampton Carbon flux (SCARF) model to predict terrestrial gross primary productivity over Africa.

    NASA Astrophysics Data System (ADS)

    Dash, Jadunandan; Chiwara, Phibion; Milton, Edward; Ardo, Jonas; Saunders, Matthew; Nicolini, Giacomo

    The amount of carbon uptake by vegetation is an important component to understand the functioning of ecosystem processes and their response/feedback to climate. Recently a new diagnostic model called the Southampton Carbon flux (SCARF) model was develop to predict terrestrial gross primary productivity at regional to global scale using satellite data. The model based on the quantum yield of vegetation improves on the previous diagnostic model by (i) using the fraction of photosynthetic active radiation absorbed by the photosynthetic pigment (FAPAR _{ps}) and (ii) using direct quantum yield by classifying the vegetation into C3 or C4 classes. Initial results suggest a very good agreement with expected results for ecosystems where the growth is controlled by temperature (e.g. Northern higher latitude). In this paper we calibrated and validated the model for a range of vegetation types across Africa, in order to test the performance of vegetation over a water limiting ecosystem. The vapour pressure deficit term (VPD) was modified to quantify the water loss and in turn reduced carbon assimilation through Evapotranspiration. The performance of the model was evaluated with GPP measured at eight eddy covariance flux tower data across Africa. Overall, the modelled GPP values show good agreement with observed GPP at most sites (except tropical rainforest site) in terms of their seasonality and absolute values. Mean daily GPP across the investigated period varied significantly across sites depending on the vegetation types from a minimum of 0.64 gC m (2) day (-1) for the dry savannah grassland at Demokeya to a maximum of 7.83 gC m (2) day (-1) for tropical rain forest at Ankasa. The model results have modest to very strong positive agreement with observed GPP at most sites (r (2) values ranging from 0.58 for Kruger and 0.84 for Mongu). Generally, strong correlation is observed in woodlands and grasslands where vegetation follows a prescribed seasonal cycle as determined by

  13. Estimation and analysis of gross primary production of soybean under various management practices and drought conditions

    NASA Astrophysics Data System (ADS)

    Wagle, Pradeep; Xiao, Xiangming; Suyker, Andrew E.

    2015-01-01

    Gross primary production (GPP) of croplands may be used to quantify crop productivity and evaluate a range of management practices. Eddy flux data from three soybean (Glycine max L.) fields under different management practices (no-till vs. till; rainfed vs. irrigated) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices (VIs) were used to test the capabilities of remotely sensed VIs and soybean phenology to estimate the seasonal dynamics of carbon fluxes. The modeled GPP (GPPVPM) using vegetation photosynthesis model (VPM) was compared with the GPP (GPPEC) estimated from eddy covariance measurements. The VIs tracked soybean phenology well and delineated the growing season length (GSL), which was closely related to carbon uptake period (CUP, R2 = 0.84), seasonal sums of net ecosystem CO2 exchange (NEE, R2 = 0.78), and GPPEC (R2 = 0.54). Land surface water index (LSWI) tracked drought-impacted vegetation well, as the LSWI values were positive during non-drought periods and negative during severe droughts within the soybean growing season. On a seasonal scale, NEE of the soybean sites ranged from -37 to -264 g C m-2. The result suggests that rainfed soybean fields needed about 450-500 mm of well-distributed seasonal rainfall to maximize the net carbon sink. During non-drought conditions, VPM accurately estimated seasonal dynamics and interannual variation of GPP of soybean under different management practices. However, some large discrepancies between GPPVPM and GPPEC were observed under drought conditions as the VI did not reflect the corresponding decrease in GPPEC. Diurnal GPPEC dynamics showed a bimodal distribution with a pronounced midday depression at the period of higher water vapor pressure deficit (>1.2 kPa). A modified Wscalar based on LSWI to account for the water stress in VPM helped quantify the reduction in GPP during severe drought and the model's performance improved substantially. In conclusion, this study demonstrates

  14. [Characteristics of terrestrial ecosystem primary productivity in East Asia based on remote sensing and process-based model].

    PubMed

    Zhang, Fang-Min; Ju, Wei-Min; Chen, Jing-Ming; Wang, Shao-Qiang; Yu, Gui-Rui; Han, Shi-Jie

    2012-02-01

    Based on the bi-linearly interpolated meteorological reanalysis data from National Centers for Environmental Prediction, USA and by using the leaf area index data derived from the GIMMS NDVI to run the process-based Boreal Ecosystems Productivity Simulator (BEPS) model, this paper simulated and analyzed the spatiotemporal characteristics of the terrestrial ecosystem gross primary productivity (GPP) and net primary productivity (NPP) in East Asia in 2000-2005. Before regional simulating and calculating, the observation GPP data of different terrestrial ecosystem in 15 experimental stations of AsiaFlux network and the inventory measurements of NPP at 1300 sampling sites were applied to validate the BEPS GPP and NPP. The results showed that BEPS could well simulate the changes in GPP and NPP of different terrestrial ecosystems, with the R2 ranging from 0.86 to 0.99 and the root mean square error (RMSE) from 0.2 to 1.2 g C x m(-2) x d(-1). The simulated values by BEPS could explain 78% of the changes in annual NPP, and the RMSE was 118 g C x m(-2) x a(-1). In 2000-2005, the averaged total GPP and total NPP of the terrestrial ecosystems in East Asia were 21.7 and 10.5 Pg C x a(-1), respectively, and the GPP and NPP exhibited similar spatial and temporal variation patterns. During the six years, the total NPP of the terrestrial ecosystems varied from 10.2 to 10.7 Pg C x a(-1), with a coefficient of variation being 2. 2%. High NPP (above 1000 g C x m(-2) x a(-1)) occurred in the southeast island countries, while low NPP (below 30 g C x m(-2) x a(-1)) occurred in the desert area of Northwest China. The spatial patterns of NPP were mainly attributed to the differences in the climatic variables across East Asia. The NPP per capita also varied greatly among different countries, which was the highest (70217 kg C x a(-1)) in Mongolia, far higher than that (1921 kg C x a(-1)) in China, and the lowest (757 kg C x a(-1)) in India. PMID:22586952

  15. EFFECTS OF NUTRIENT ENRICHMENT ON PRIMARY PRODUCTION AND BIOMASS OF SEDIMENT MICROALGAE IN A SUBTROPICAL SEAGRASS BED(1).

    PubMed

    Bucolo, Philip; Sullivan, Michael J; Zimba, Paul V

    2008-08-01

    Eutrophication of coastal waters often leads to excessive growth of microalgal epiphytes attached to seagrass leaves; however, the effect of increased nutrient levels on sediment microalgae has not been studied within seagrass communities. A slow-release NPK Osmocote fertilizer was added to sediments within and outside beds of the shoal grass Halodule wrightii, in Big Lagoon, Perdido Key, Florida. Gross primary production (GPP) and biomass (HPLC photopigments) of sediment microalgae within and adjacent to fertilized and control H. wrightii beds were measured following two 4-week enrichment periods during June and July 2004. There was no effect of position on sediment microalgal GPP or biomass in control and enriched plots. However, nutrient enrichment significantly increased GPP in both June and July. These results suggest that sediment microalgae could fill some of the void in primary production where seagrass beds disappear due to excessive nutrient enrichment. Sedimentary chl a (proxy of total microalgal biomass) significantly increased only during the June enrichment period, whereas fucoxanthin (proxy of total diatom biomass) was not increased by nutrient enrichment even though its concentration doubled in the enriched plots in June. PMID:27041604

  16. Sun-induced chlorophyll fluorescence and photochemical reflectance index improve remote-sensing gross primary production estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

    NASA Astrophysics Data System (ADS)

    Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

    2015-11-01

    This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different nitrogen (N) and phosphorous (P) availability. Sun-induced chlorophyll fluorescence yield computed at 760 nm (Fy760), scaled photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy chambers on the same locations sampled by the spectrometers. We tested whether light-use efficiency (LUE) models driven by remote-sensing quantities (RSMs) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed higher GPP in the N-fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was closely related to the mean of plant N content across treatments (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments, but it is affected by N availability. Results from a cross-validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv =140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However

  17. An Essential Role for (p)ppGpp in the Integration of Stress Tolerance, Peptide Signaling, and Competence Development in Streptococcus mutans.

    PubMed

    Kaspar, Justin; Kim, Jeong N; Ahn, Sang-Joon; Burne, Robert A

    2016-01-01

    The microbes that inhabit the human oral cavity are subjected to constant fluctuations in their environment. To overcome these challenges and gain a competitive advantage, oral streptococci employ numerous adaptive strategies, many of which appear to be intertwined with the development of genetic competence. Here, we demonstrate that the regulatory circuits that control development of competence in Streptococcus mutans, a primary etiological agent of human dental caries, are integrated with key stress tolerance pathways by the molecular alarmone (p)ppGpp. We first observed that the growth of a strain that does not produce (p)ppGpp (ΔrelAPQ, (p)ppGpp(0)) is not sensitive to growth inhibition by comX inducing peptide (XIP), unlike the wild-type strain UA159, even though XIP-dependent activation of the alternative sigma factor comX by the ComRS pathway is not impaired in the (p)ppGpp(0) strain. Overexpression of a (p)ppGpp synthase gene (relP) in the (p)ppGpp(0) mutant restored growth inhibition by XIP. We also demonstrate that exposure to micromolar concentrations of XIP elicited changes in (p)ppGpp accumulation in UA159. Loss of the RelA/SpoT homolog (RSH) enzyme, RelA, lead to higher basal levels of (p)ppGpp accumulation, but to decreased sensitivity to XIP and to decreases in comR promoter activity and ComX protein levels. By introducing single amino acid substitutions into the RelA enzyme, the hydrolase activity of the enzyme was shown to be crucial for full com gene induction and transformation by XIP. Finally, loss of relA resulted in phenotypic changes to ΔrcrR mutants, highlighted by restoration of transformation and ComX protein production in the otherwise non-transformable ΔrcrR-NP mutant. Thus, RelA activity and its influence on (p)ppGpp pools appears to modulate competence signaling and development through RcrRPQ and the peptide effectors encoded within rcrQ. Collectively, this study provides new insights into the molecular mechanisms that integrate

  18. An Essential Role for (p)ppGpp in the Integration of Stress Tolerance, Peptide Signaling, and Competence Development in Streptococcus mutans

    PubMed Central

    Kaspar, Justin; Kim, Jeong N.; Ahn, Sang-Joon; Burne, Robert A.

    2016-01-01

    The microbes that inhabit the human oral cavity are subjected to constant fluctuations in their environment. To overcome these challenges and gain a competitive advantage, oral streptococci employ numerous adaptive strategies, many of which appear to be intertwined with the development of genetic competence. Here, we demonstrate that the regulatory circuits that control development of competence in Streptococcus mutans, a primary etiological agent of human dental caries, are integrated with key stress tolerance pathways by the molecular alarmone (p)ppGpp. We first observed that the growth of a strain that does not produce (p)ppGpp (ΔrelAPQ, (p)ppGpp0) is not sensitive to growth inhibition by comX inducing peptide (XIP), unlike the wild-type strain UA159, even though XIP-dependent activation of the alternative sigma factor comX by the ComRS pathway is not impaired in the (p)ppGpp0 strain. Overexpression of a (p)ppGpp synthase gene (relP) in the (p)ppGpp0 mutant restored growth inhibition by XIP. We also demonstrate that exposure to micromolar concentrations of XIP elicited changes in (p)ppGpp accumulation in UA159. Loss of the RelA/SpoT homolog (RSH) enzyme, RelA, lead to higher basal levels of (p)ppGpp accumulation, but to decreased sensitivity to XIP and to decreases in comR promoter activity and ComX protein levels. By introducing single amino acid substitutions into the RelA enzyme, the hydrolase activity of the enzyme was shown to be crucial for full com gene induction and transformation by XIP. Finally, loss of relA resulted in phenotypic changes to ΔrcrR mutants, highlighted by restoration of transformation and ComX protein production in the otherwise non-transformable ΔrcrR-NP mutant. Thus, RelA activity and its influence on (p)ppGpp pools appears to modulate competence signaling and development through RcrRPQ and the peptide effectors encoded within rcrQ. Collectively, this study provides new insights into the molecular mechanisms that integrate

  19. GPP: A General-Purpose Post Processor for wind turbine data analysis

    NASA Astrophysics Data System (ADS)

    Buhl, M. L., Jr.; Kelley, N. D.; Simms, D. A.

    1994-10-01

    GPP (pronounced 'jeep') is a General-Purpose Post Processor for wind turbine data analysis. Engineers in the Wind Technology Division (WTD) of the National Renewable Energy Laboratory (NREL) developed it to postprocess test data and simulation predictions. GPP reads data into large arrays and allows you to run many types of analyses on the data in memory. GPP runs on inexpensive computers commonly used in the wind industry. You can even use it on a laptop computer in the field. We wrote the program in such a way as to make it easy to add new types of analyses and to port it to many types of computers. Although GPP is very powerful and feature-rich, it is still very easy to learn and use. Exhaustive error trapping prevents you from losing valuable work due to input errors. GPP should make a significant impact on engineering productivity in the wind industry.

  20. GPP user's guide: A general-purpose postprocessor for wind turbine data analysis

    NASA Astrophysics Data System (ADS)

    Buhl, M. L., Jr.

    1995-01-01

    GPP is a General-Purpose Postprocessor for wind turbine data analysis. The author, a member of the Wind Technology Division (WTD) of the National Renewable Energy Laboratory (NREL), developed GPP to postprocess test data and simulation predictions. GPP reads data into large arrays and allows the user to run many types of analyses on the data stored in memory. It runs on inexpensive computers common in the wind industry. One can even use it on a laptop in the field. The author wrote the program in such a way as to make it easy to add new types of analyses and to port it to many types of computers. Although GPP is very powerful and feature-rich, it is still very easy to learn and to use. Exhaustive error trapping prevents one from losing valuable work due to input errors. GPP will, hopefully, make a significant impact on engineering productivity in the wind industry.

  1. GPP user`s guide - a general-purpose postprocessor for wind turbine data analysis

    SciTech Connect

    Buhl, Jr, M L

    1995-01-01

    GPP (pronounced {open_quotes}jeep{close_quotes}) is a General-Purpose Postprocessor for wind turbine data analysis. The author, a member of the Wind Technology Division (WTD) of the National Renewable Energy Laboratory (NREL), developed GPP to postprocess test data and simulation predictions. GPP reads data into large arrays and allows the user to run many types of analyses on the data stored in memory. It runs on inexpensive computers common in the wind industry. One can even use it on a laptop in the field. The author wrote the program in such a way as to make it easy to add new types of analyses and to port it to many types of computers. Although GPP is very powerful and feature-rich, it is still very easy to learn and to use. Exhaustive error trapping prevents one from losing valuable work due to input errors. GPP will, hopefully, make a significant impact on engineering productivity in the wind industry.

  2. 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.

  3. Constraining Ecosystem Gross Primary Production and Transpiration with Measurements of Photosynthetic 13CO2 Discrimination

    NASA Astrophysics Data System (ADS)

    Blonquist, J. M.; Wingate, L.; Ogeé, J.; Bowling, D. R.

    2011-12-01

    The stable carbon isotope composition of atmospheric CO2 (δ13Ca) can provide useful information on water use efficiency (WUE) dynamics of terrestrial ecosystems and potentially constrain models of CO2 and water fluxes at the land surface. This is due to the leaf-level relationship between photosynthetic 13CO2 discrimination (Δ), which influences δ13Ca, and the ratio of leaf intercellular to atmospheric CO2 mole fractions (Ci / Ca), which is related to WUE and is determined by the balance between C assimilation (CO2 demand) and stomatal conductance (CO2 supply). We used branch-scale Δ derived from tunable diode laser absorption spectroscopy measurements collected in a Maritime pine forest to estimate Ci / Ca variations over an entire growing season. We combined Ci / Ca estimates with rates of gross primary production (GPP) derived from eddy covariance (EC) to estimate canopy-scale stomatal conductance (Gs) and transpiration (T). Estimates of T were highly correlated to T estimates derived from sapflow data (y = 1.22x + 0.08; r2 = 0.61; slope P < 0.001) and T predictions from an ecosystem model (MuSICA) (y = 0.88x - 0.05; r2 = 0.64; slope P < 0.001). As an alternative to estimating T, Δ measurements can be used to estimate GPP by combining Ci / Ca estimates with Gs estimates from sapflow data. Estimates of GPP were determined in this fashion and were highly correlated to GPP values derived from EC (y = 0.82 + 0.07; r2 = 0.61; slope P < 0.001) and GPP predictions from MuSICA (y = 1.10 + 0.42; r2 = 0.50; slope P < 0.001). Results demonstrate that the leaf-level relationship between Δ and Ci / Ca can be extended to the canopy-scale and that Δ measurements have utility for partitioning ecosystem-scale CO2 and water fluxes.

  4. Impacts of Climate Extremes on Gross Primary Productivity at Multiple Spatial Scales

    NASA Astrophysics Data System (ADS)

    Kim, Soyoun; Ryu, Youngryel; Jiang, Chongya

    2016-04-01

    Climate extreme events have made significant impacts on terrestrial carbon cycles. Recent studies on detection and attribution of climate extreme events and their impact on carbon cycles used coarse spatial resolution data such as 0.5 degree. The coarse resolution data might miss important climate extremes and their impacts on GPP. To fill this research gap, we use a new global GPP product derived from a process-based model, the Breathing Earth System Simulator (BESS). The BESS takes full advantages of MODIS/AVHRR land and atmosphere products, providing global GPP product in 1 km resolution from 2000 to 2015 and 1/12 degree resolution from 1982 to 1999. We first integrate the BESS GPP products to 0.5 degree (1982-2015) and apply the method of Zscheischler et al. (2013). To test the impacts of spatial resolutions on detecting extreme events, we enhance spatial resolutions of the BESS GPP from 0.5 degree to 0.25, 0.125, and 1/12 degrees and quantify the variations of areas which experienced climate extremes. We subsequently investigate hotspot regions where the extremes occur using fine resolution GPP data at 1/12 degree (1982-2015), then analyze the causes of the extreme events that substantially decreased GPP by using precipitation, air temperature, and frost. This study could improve the understanding of the relationship between climate extremes and the carbon cycle at multiple spatial scales.

  5. Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites

    NASA Astrophysics Data System (ADS)

    Zhou, Yanlian; Wu, Xiaocui; Ju, Weimin; Chen, Jing M.; Wang, Shaoqiang; Wang, Huimin; Yuan, Wenping; Andrew Black, T.; Jassal, Rachhpal; Ibrom, Andreas; Han, Shijie; Yan, Junhua; Margolis, Hank; Roupsard, Olivier; Li, Yingnian; Zhao, Fenghua; Kiely, Gerard; Starr, Gregory; Pavelka, Marian; Montagnani, Leonardo; Wohlfahrt, Georg; D'Odorico, Petra; Cook, David; Arain, M. Altaf; Bonal, Damien; Beringer, Jason; Blanken, Peter D.; Loubet, Benjamin; Leclerc, Monique Y.; Matteucci, Giorgio; Nagy, Zoltan; Olejnik, Janusz; Paw U, Kyaw Tha; Varlagin, Andrej

    2016-04-01

    Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (ɛmsh) was 2.63 to 4.59 times that of sunlit leaves (ɛmsu). Generally, the relationships of ɛmsh and ɛmsu with ɛmax were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.

  6. Golgi Phosphoprotein 4 (GPP130) is a Sensitive and Selective Cellular Target of Manganese Exposure

    PubMed Central

    Masuda, Melisa; Braun-sommargren, Michelle; Crooks, Dan; Smith, Donald R.

    2014-01-01

    Chronic elevated exposure to manganese (Mn) is associated with neurocognitive and fine motor deficits in children. However, relatively little is understood about cellular responses to Mn spanning the transition between physiologic to toxic levels of exposure. Here, we investigated the specificity, sensitivity, and time course of the Golgi Phosphoprotein 4 (GPP130) response to Mn exposure in AF5 GABAergic neuronal cells, and we determined the extent to which GPP130 degradation occurs in brain cells in vivo in rats subchronically exposed to Mn. Our results show that GPP130 degradation in AF5 cells was specific to Mn, and did not occur following exposure to cobalt, copper, iron, nickel, or zinc. GPP130 degradation occurred without measurable increases in intracellular Mn levels and at Mn exposures as low as 0.54 µM. GPP130 protein was detectable by immunofluorescence in only ~15–30% of cells in striatal and cortical rat brain slices, and Mn-exposed animals exhibited a significant reduction in both the number of GPP130-positive cells, and the overall levels of GPP130 protein, demonstrating the in vivo relevance of this Mn-specific response within the primary target organ of Mn toxicity. These results provide insight into specific mechanism(s) of cellular Mn regulation and toxicity within the brain, including the selective susceptibility of cells to Mn cytotoxicity. PMID:23280773

  7. Catastrophic shifts in the aquatic primary production revealed by a small low-flow section of tropical downstream after dredging.

    PubMed

    Marotta, H; Enrich-Prast, A

    2015-11-01

    Dredging is a catastrophic disturbance that directly affects key biological processes in aquatic ecosystems, especially in those small and shallow. In the tropics, metabolic responses could still be enhanced by the high temperatures and solar incidence. Here, we assessed changes in the aquatic primary production along a small section of low-flow tropical downstream (Imboassica Stream, Brazil) after dredging. Our results suggested that these ecosystems may show catastrophic shifts between net heterotrophy and autotrophy in waters based on three short-term stages following the dredging: (I) a strongly heterotrophic net primary production -NPP- coupled to an intense respiration -R- likely supported by high resuspended organic sediments and nutrients from the bottom; (II) a strongly autotrophic NPP coupled to an intense gross primary production -GPP- favored by the high nutrient levels and low solar light attenuation from suspended solids or aquatic macrophytes; and (III) a NPP near to the equilibrium coupled to low GPP and R rates following, respectively, the shading by aquatic macrophytes and high particulate sedimentation. In conclusion, changes in aquatic primary production could be an important threshold for controlling drastic shifts in the organic matter cycling and the subsequent silting up of small tropical streams after dredging events. PMID:26602334

  8. Predicting tree diversity across the United States as a function of modeled gross primary production.

    PubMed

    Nightingale, Joanne M; Fan, Weihong; Coops, Nicholas C; Waring, Richard H

    2008-01-01

    At the regional and continental scale, ecologists have theorized that spatial variation in biodiversity can be interpreted as a response to differences in climate. To test this theory we assumed that ecological constraints associated with current climatic conditions (2000-2004) might best be correlated with tree richness if expressed through satellite-derived measures of gross primary production (GPP), rather than the more commonly used, but less consistently derived, net primary production. To evaluate current patterns in tree diversity across the contiguous United States we acquired information on tree composition from the USDA Forest Service's Forest Inventory and Analysis program that represented more than 17,4000 survey plots. We selected 2693 cells of 1000 km2 within which a sufficient number of plots were available to estimate tree richness per hectare. Our estimates of forest productivity varied from simple vegetation indices indicative of the fraction of light intercepted by canopies at 16-d intervals, a product from the MODIS (Moderate Resolution Imaging Spectro-radiometer), to 8- and 10-d GPP products derived with minimal climatic data (MODIS) and SPOT-Vegetation (Systeme Pour l'Observation de la Terre), to 3-PGS (Physiological Principles Predicting Growth with Satellites), which requires both climate and soil data. Across the contiguous United States, modeled predictions of gross productivity accounted for between 51% and 77% of the recorded spatial variation in tree diversity, which ranged from 2 to 67 species per hectare. When the analyses were concentrated within nine broadly defined ecoregions, predictive relations largely disappeared. Only 3-PGS predictions fit a theorized unimodal function by being able to distinguish highly productive forests in the Pacific Northwest that support lower than expected tree diversity. Other models predicted a continuous steep rise in tree diversity with increasing productivity, and did so with generally better or

  9. Gross primary production and light response parameters of four Southern Plains ecosystems estimated using long-term CO2-flux tower measurements

    NASA Astrophysics Data System (ADS)

    Gilmanov, Tagir G.; Verma, Shashi B.; Sims, Phillip L.; Meyers, Tilden P.; Bradford, James A.; Burba, George G.; Suyker, Andrew E.

    2003-06-01

    Gross primary production (GPP) is one of the most important characteristics of an ecosystem. At present, no empirically based method to estimate GPP is available, other than measurements of net CO2 exchange and calculations of respiration. Data sets from continuous CO2 flux measurements in a number of ecosystems (Ameriflux, AgriFlux, etc.) for the first time provide an opportunity to obtain empirically based estimates of GPP. In this paper, using the results of CO2 flux tower measurements during the 1997 season at four sites in Oklahoma (tallgrass prairie, mixed prairie, pasture, and winter wheat crop), we describe a method to evaluate the average daytime rate of ecosystem respiration, Rd, by estimation of the respiration term of the nonrectangular hyperbolic model of the ecosystem-scale light-response curve. Comparison of these predicted daytime respiration rates with directly measured corresponding nighttime values, Rn, after appropriate length of the night and temperature correction, demonstrated close linear relationship, with 0.82 ≤ R2 ≤ 0.98 for weekly averaged fluxes. Daily gross primary productivity, Pg, can be calculated as Pg = Pd + Rd, where Pd is the daytime integral of the net ecosystem CO2 exchange, obtained directly from measurements. Annual GPP for the sites, obtained as the sum of Pg over the whole period with Pg > 0 were: tallgrass prairie, 5223 g CO2 m-2; winter wheat, 2853 g CO2 m-2; mixed prairie, 3037 g CO2 m-2; and pasture, 2333 g CO2 m-2. These values are in agreement with published GPP estimates for nonforest terrestrial ecosystems.

  10. Marginal Lands Gross Primary Production Dominate Atmospheric CO2 Interannual Variations

    NASA Astrophysics Data System (ADS)

    Ahlström, A.; Raupach, M. R.; Schurgers, G.; Arneth, A.; Jung, M.; Reichstein, M.; Smith, B.

    2014-12-01

    Since the 1960s terrestrial ecosystems have acted as a substantial sink for atmospheric CO2, sequestering about one quarter of anthropogenic emissions in an average year. Variations in this land carbon sink are also responsible for most of the large interannual variability in atmospheric CO2 concentrations. While most evidence places the majority of the sink in highly productive forests and at high latitudes experiencing warmer and longer growing seasons, the location and the processes governing the interannual variations are still not well characterised. Here we evaluate the hypothesis that the long-term trend and the variability in the land CO2 sink are respectively dominated by geographically distinct regions: the sink by highly productive lands, mainly forests, and the variability by semi-arid or "marginal" lands where vegetation activity is strongly limited by water and therefore responds strongly to climate variability. Using novel analysis methods and data from both upscaled flux-tower measurements and a dynamic global vegetation model, we show that (1) the interannual variability in the terrestrial CO2 sink arises mainly from variability in terrestrial gross primary production (GPP); (2) most of the interannual variability in GPP arises in tropical and subtropical marginal lands, where negative anomalies are driven mainly by warm, dry conditions and positive anomalies by cool, wet conditions; (3) the variability in the GPP of high-latitude marginal lands (tundra and shrublands) is instead controlled by temperature and light, with warm bright conditions resulting in positive anomalies. The influence of ENSO (El Niño-Southern Oscillation) on the growth rate of atmospheric CO2 concentrations is mediated primarily through climatic effects on GPP in marginal lands, with opposite signs in subtropical and higher-latitude regions. Our results show that the land sink of CO2 (dominated by forests) and its interannual variability (dominated by marginal lands) are

  11. 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. PMID:26179484

  12. Alarmone (p)ppGpp regulates the transition from pathogenicity to mutualism in Photorhabdus luminescens.

    PubMed

    Bager, Ragnhild; Roghanian, Mohammad; Gerdes, Kenn; Clarke, David J

    2016-05-01

    The enteric gamma-proteobacterium Photorhabdus luminescens kills a wide range of insects, whilst also maintaining a mutualistic relationship with soil nematodes from the family Heterorhabditis. Pathogenicity is associated with bacterial exponential growth, whilst mutualism is associated with post-exponential (stationary) phase. During post-exponential growth, P. luminescens also elaborates an extensive secondary metabolism, including production of bioluminescence, antibiotics and pigment. However, the regulatory network that controls the expression of this secondary metabolism is not well understood. The stringent response is a well-described global regulatory system in bacteria and mediated by the alarmone (p)ppGpp. In this study, we disrupted the genes relA and spoT, encoding the two predicted (p)ppGpp synthases of P. luminescens TTO1, and we showed that (p)ppGpp is required for secondary metabolism. Moreover, we found the (p)ppGpp is not required for pathogenicity of P. luminescens, but is required for bacterial survival within the insect cadaver. Finally, we showed that (p)ppGpp is required for P. luminescens to support normal nematode growth and development. Therefore, the regulatory network that controls the transition from pathogenicity to mutualism in P. luminescens requires (p)ppGpp. This is the first report outlining a role for (p)ppGpp in controlling the outcome of an interaction between a bacteria and its host. PMID:26845750

  13. Sun-induced Chlorophyll fluorescence and PRI improve remote sensing GPP estimates under varying nutrient availability in a typical Mediterranean savanna ecosystem

    NASA Astrophysics Data System (ADS)

    Perez-Priego, O.; Guan, J.; Rossini, M.; Fava, F.; Wutzler, T.; Moreno, G.; Carvalhais, N.; Carrara, A.; Kolle, O.; Julitta, T.; Schrumpf, M.; Reichstein, M.; Migliavacca, M.

    2015-07-01

    This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna with different Nitrogen (N) and Phosphorous (P) availability. Sun-induced chlorophyll Fluorescence yield computed at 760 nm (Fy760), scaled-photochemical reflectance index (sPRI), MERIS terrestrial-chlorophyll index (MTCI) and Normalized difference vegetation index (NDVI) were computed from near-surface field spectroscopy measurements collected using high spectral resolution spectrometers covering the visible near-infrared regions. GPP was measured using canopy-chambers on the same locations sampled by the spectrometers. We hypothesized that light-use efficiency (LUE) models driven by remote sensing quantities (RSM) can better track changes in GPP caused by nutrient supplies compared to those driven exclusively by meteorological data (MM). Particularly, we compared the performances of different RSM formulations - relying on the use of Fy760 or sPRI as proxy for LUE and NDVI or MTCI as fraction of absorbed photosynthetically active radiation (fAPAR) - with those of classical MM. Results showed significantly higher GPP in the N fertilized experimental plots during the growing period. These differences in GPP disappeared in the drying period when senescence effects masked out potential differences due to plant N content. Consequently, although MTCI was tightly related to plant N content (r2 = 0.86, p < 0.01), it was poorly related to GPP (r2 = 0.45, p < 0.05). On the contrary sPRI and Fy760 correlated well with GPP during the whole measurement period. Results revealed that the relationship between GPP and Fy760 is not unique across treatments but it is affected by N availability. Results from a cross validation analysis showed that MM (AICcv = 127, MEcv = 0.879) outperformed RSM (AICcv = 140, MEcv = 0.8737) when soil moisture was used to constrain the seasonal dynamic of LUE. However, residual analyses

  14. Understanding COS Fluxes in a Boreal Forest: Towards COS-Based GPP Estimates.

    NASA Astrophysics Data System (ADS)

    Chen, H.; Kooijmans, L.; Franchin, A.; Keskinen, H.; Levula, J.; Mammarella, I.; Maseyk, K. S.; Pihlatie, M.; Praplan, A. P.; Seibt, U.; Sun, W.; Vesala, T.

    2015-12-01

    Carbonyl Sulfide (COS) is a promising new tracer that can be used to partition the Net Ecosystem Exchange into gross primary production (GPP) and respiration. COS and CO2 vegetation fluxes are closely related as these gases share the same diffusion pathway into stomata, which makes COS a potentially powerful tracer for GPP. While vegetative uptake is the largest sink of COS, the environmental drivers are poorly understood, and soil fluxes represent an important but relatively unconstrained component. Therefore, the realization of the COS tracer method requires proper characterization of both soil and ecosystem fluxes. A campaign to provide better constrained soil and ecosystem COS flux data for boreal forests took place in the summer of 2015 at the SMEAR II site in Hyytiälä, Finland. Eddy covariance flux measurements were made above the forest canopy on an Aerodyne continuous-wave quantum cascade laser (QCL) system that is capable of measuring COS, CO2, CO and H2O. Soil COS fluxes were obtained using modified LI-COR LI-8100 chambers together with high accuracy concentration measurements from another Aerodyne QCL instrument. The same instrument alternately measured concentrations in and above the canopy on a cycle through 4 heights, which will be used to calculate ecosystem fluxes using the Radon-tracer method, providing ecosystem fluxes under low-turbulent conditions. We will compare ecosystem fluxes from both eddy covariance and profile measurements and show estimates of the fraction of ecosystem fluxes attributed to the soil component. With the better understanding of ecosystem and soil COS fluxes, as obtained with this dataset, we will be able to derive COS-based GPP estimates for the Hyytiälä site.

  15. Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data

    NASA Astrophysics Data System (ADS)

    Gilabert, M. A.; Moreno, A.; Maselli, F.; Martínez, B.; Chiesi, M.; Sánchez-Ruiz, S.; García-Haro, F. J.; Pérez-Hoyos, A.; Campos-Taberner, M.; Pérez-Priego, O.; Serrano-Ortiz, P.; Carrara, A.

    2015-04-01

    The accurate representation of terrestrial CO2 uptake (GPP) using Monteith's approach requires a frequent and site-specific parameterization of the model inputs. In this work, an optimization of this approach has been carried out by adjusting the inputs (fAPAR, PAR and ε) for the study area, peninsular Spain, a typical Mediterranean region. The daily GPP images have been calculated for 2008 and 2011 with a 1-km spatial resolution and validated by comparison with in situ GPP estimates from the eddy covariance data (direct validation) and by inter-comparison with the MODIS GPP product. The direct validation has evidenced an excellent agreement with correlations up to 0.98 in 2008 and 0.92 in 2011 in some sites. The inter-comparison has shown that the two GPP products are consistent temporally. However, a slightly decrease of the correlation has been observed in some areas. The validation has also shown that our optimized GPP product accounts better for the water stress than the MODIS product. The analysis of the explanatory power of the model in terms of its inputs shows, as expected, that PAR and fAPAR are the most relevant inputs. The fAPAR plays a major role on GPP estimation when the vegetation phenology maximum is not reached during solar solstice. Finally, it has been shown that the influence of the water stress, associated with the water shortage typical of Mediterranean landscapes, has to be evaluated accurately in order to explain the GPP inter-annual variability.

  16. Plant invasion impacts on the gross and net primary production of the salt marsh on eastern coast of China: Insights from leaf to ecosystem

    NASA Astrophysics Data System (ADS)

    Ge, Zhen-Ming; Guo, Hai-Qiang; Zhao, Bin; Zhang, Li-Quan

    2015-01-01

    exotic Spartina alterniflora from North America has been rapidly invading the entire Chinese coast, while the impacts of plant invasion on the gross (GPP) and net primary production (NPP) of the coastal salt marshes were less known. In this study, we investigated the photosynthetic performance, leaf characteristics, and primary production of the exotic C4 grass and the dominant native C3 grass (Phragmites australis) in two marsh mixtures (equipped with eddy covariance systems) in the Yangtze Estuary. The light-saturated photosynthetic rate and annual peak leaf area index (LAI) of S. alterniflora was higher than that of P. australis throughout the growing season. The leaf nitrogen content of P. australis declined sharper during the latter growing season than that of S. alterniflora. The leaf-to-canopy production model with species-specific (C3 and C4 types) parameterizations could reasonably simulate the daily trends and annual GPP amount against the 3 year flux measurements from 2005 to 2007, and the modeled NPP agreed with biomass measurements from the two species during 2012. The percentage contributions of GPP between S. alterniflora and P. australis were on average 5.82:1 and 2.91:1 in the two mixtures, respectively. The annual NPP amounts from S. alterniflora were higher by approximately 1.6 times than that from P. australis. Our results suggested that higher photosynthesis efficiency, higher LAI, and longer growing season resulted in greater GPP and NPP in the exotic species relative to the native species. The rapid expansion rate of S. alterniflora further made it the leading contributor of primary production in the salt marsh.

  17. Evaluation of the impact of storm event inputs on levels of gross primary production and respiration in a drinking water reservoir

    NASA Astrophysics Data System (ADS)

    Samal, N. R.; Pierson, D. C.; Staehr, P. A.; Pradhanang, S. M.; Smith, D. G.

    2013-12-01

    Episodic inputs of dissolved and particulate material during storm events can have important effects on lake and reservoir ecosystem function and also impact reservoir drinking water quality. We evaluate the impacts of storm events using vertical profiles of temperature, dissolved oxygen, turbidity, conductivity and chlorophyll automatically collected at 6 hour intervals in Ashokan Reservoir, which is a part of the New York City drinking water supply. Storm driven inputs to the reservoir periodically result in large input of suspended sediments that result in reservoir turbidity levels exceeding 25 NTU, and substantial reductions in the euphotic depth. Dissolved materials associated with these same storms would be expected to stimulate bacterial production. This study involves the use of a conceptual model to calculate depth specific estimates of gross primary production (GPP) and ecosystem respiration (R) using three years of data that included 777 events that increased reservoir turbidity levels to over 25 NTU. Using data from before, during and after storm events, we examine how the balance between GPP and R is influenced by storm related increases in turbidity and dissolved organic matter, which would in turn influence light attenuation and bacterial production. Key words: metabolism, primary production, GPP, respiration, euphotic depth, storm event, reservoir

  18. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession

    USGS Publications Warehouse

    Goulden, M.L.; Mcmillan, A.M.S.; Winston, G.C.; Rocha, A.V.; Manies, K.L.; Harden, J.W.; Bond-Lamberty, B. P.

    2011-01-01

    We combined year-round eddy covariance with biometry and biomass harvests along a chronosequence of boreal forest stands that were 1, 6, 15, 23, 40, 74, and 154 years old to understand how ecosystem production and carbon stocks change during recovery from stand-replacing crown fire. Live biomass (Clive) was low in the 1 and 6 year old stands, and increased following a logistic pattern to high levels in the 74 and 154year old stands. Carbon stocks in the forest floor (Cforest floor) and coarse woody debris (CCWD) were comparatively high in the 1year old stand, reduced in the 6 through 40year old stands, and highest in the 74 and 154year old stands. Total net primary production (TNPP) was reduced in the 1 and 6year old stands, highest in the 23 through 74year old stands and somewhat reduced in the 154year old stand. The NPP decline at the 154year old stand was related to increased autotrophic respiration rather than decreased gross primary production (GPP). Net ecosystem production (NEP), calculated by integrated eddy covariance, indicated the 1 and 6 year old stands were losing carbon, the 15year old stand was gaining a small amount of carbon, the 23 and 74year old stands were gaining considerable carbon, and the 40 and 154year old stands were gaining modest amounts of carbon. The recovery from fire was rapid; a linear fit through the NEP observations at the 6 and 15year old stands indicated the transition from carbon source to sink occurred within 11-12 years. The NEP decline at the 154year old stand appears related to increased losses from Clive by tree mortality and possibly from Cforest floor by decomposition. Our findings support the idea that NPP, carbon production efficiency (NPP/GPP), NEP, and carbon storage efficiency (NEP/TNPP) all decrease in old boreal stands. ?? 2010 Blackwell Publishing Ltd.

  19. Sensitivity of Vegetation Index and Gross Primary Productivity to Drought and Heat Waves in Europe

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Xiao, X.

    2014-12-01

    Drought and heat waves greatly influenced vegetation growth and photosynthesis. With an increasing frequency, these extreme climate events could alter the carbon cycle at regional and continental scales. To better understand the impacts of drought and heat wave on vegetation and carbon fluxes in temperate terrestrial ecosystems, we first evaluated three vegetation indices (Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI)) during 2000-2013 to determine the sensitivity of these vegetation indices to drought and heat waves in 2003 at 14 CO2 eddy covariance flux tower sites in Europe. We then ran the satellite-based Vegetation Photosynthesis Model (VPM) at these sites and compared gross primary production (GPP) estimates from the VPM model (GPPVPM) with estimates from the eddy covariance measurements (GPPEC). The VPM model is driven by climate data (air temperature and photosynthetically active radiation) and two vegetation indices (EVI and LSWI). The comparison shows that the VPM model has a good capability in predicting vegetation photosynthesis in both normal and drought periods. The results from this research work not only reveals the various sensitivity of NDVI, EVI and LSWI to drought and heat wave in 2003, in Europe, but also shows that the VPM model is a robust tool for modeling GPP in terrestrial ecosystems in Europe.

  20. Impact of Chromophoric Dissolved Organic Matter on UV Inhibition of Primary Productivity in the Sea

    NASA Technical Reports Server (NTRS)

    Arrigo, Kevin R.; Brown, Christopher W.

    1996-01-01

    A model was developed to assess the impact of chromophoric dissolved organic matter (CDOM) on phytoplankton production within the euphotic zone. The rate of depth-integrated daily gross primary productivity within the euphotic zone was evaluated as a function of date, latitude, CDONI absorption characteristics, chlorophyll a (chl a) concentration, vertical stratification, and phytoplankton sensitivity to UV radiation (UVR). Results demonstrated that primary production was enhanced in the upper 30 m of the water column by the presence of CDOM, where predicted increases in production due to the removal of damaging UVR more than offset its reduction resulting from the absorption of photosynthetically usable radiation. At greater depths, where little UVR remained, primary production was always reduced due to removal by CDOM of photosynthetically usable radiation. When CDOM was distributed homogeneously within the euphotic zone, the integral over z [(GPP)(sub ez)], was reduced under most bio-optical (i.e. solar zenith angle, and CDOM absorption, and ozone concentration) and photophysiological production at depth was greater than the enhancement of production at the surface.

  1. Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

    NASA Astrophysics Data System (ADS)

    Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

    2014-05-01

    Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross

  2. Primary production in Southern Ocean waters

    NASA Astrophysics Data System (ADS)

    Arrigo, Kevin R.; Worthen, Denise; Schnell, Anthony; Lizotte, Michael P.

    1998-07-01

    The Southern Ocean forms a link between major ocean basins, is the site of deep and intermediate water ventilation, and is one of the few areas where macronutrients are underutilized by phytoplankton. Paradoxically, prior estimates of annual primary production are insufficient to support the Antarctic food web. Here we present results from a primary production algorithm based upon monthly climatological phytoplankton pigment concentrations from the coastal zone color scanner (CZCS). Phytoplankton production was forced using monthly temperature profiles and a radiative transfer model that computed changes in photosynthetically usable radiation at each CZCS pixel location. Average daily productivity (g C m-2 d-1) and total monthly production (Tg C month-1) were calculated for each of five geographic sectors (defined by longitude) and three ecological provinces (defined by sea ice coverage and bathymetry as the pelagic province, the marginal ice zone, and the shelf). Annual primary production in the Southern Ocean (south of 50°S) was calculated to be 4414 Tg C yr-1, 4-5 times higher than previous estimates made from in situ data. Primary production was greatest in the month of December (816 Tg C month-1) and in the pelagic province (contributing 88.6% of the annual primary production). Because of their small size the marginal ice zone (MIZ) and the shelf contributed only 9.5% and 1.8%, respectively, despite exhibiting higher daily production rates. The Ross Sea was the most productive region, accounting for 28% of annual production. The fourfold increase in the estimate of primary production for the Southern Ocean likely makes the notion of an "Antarctic paradox" (primary production insufficient to support the populations of Southern Ocean grazers, including krill, copepods, microzooplankton, etc.) obsolete.

  3. A new model of the global biogeochemical cycle of carbonyl sulfide - Part 2: Use of carbonyl sulfide to constrain gross primary productivity in current vegetation models

    NASA Astrophysics Data System (ADS)

    Launois, T.; Peylin, P.; Belviso, S.; Poulter, B.

    2015-08-01

    Clear analogies between carbonyl sulfide (OCS) and carbon dioxide (CO2) diffusion pathways through leaves have been revealed by experimental studies, with plant uptake playing an important role for the atmospheric budget of both species. Here we use atmospheric OCS to evaluate the gross primary production (GPP) of three dynamic global vegetation models (Lund-Potsdam-Jena, LPJ; National Center for Atmospheric Research - Community Land Model 4, NCAR-CLM4; and Organising Carbon and Hydrology In Dynamic Ecosystems, ORCHIDEE). Vegetation uptake of OCS is modeled as a linear function of GPP and leaf relative uptake (LRU), the ratio of OCS to CO2 deposition velocities of plants. New parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of OCS are also provided. Despite new large oceanic emissions, global OCS budgets created with each vegetation model show exceeding sinks by several hundred Gg S yr-1. An inversion of the surface fluxes (optimization of a global scalar which accounts for flux uncertainties) led to balanced OCS global budgets, as atmospheric measurements suggest, mainly by drastic reduction (up to -50 %) in soil and vegetation uptakes. The amplitude of variations in atmospheric OCS mixing ratios is mainly dictated by the vegetation sink over the Northern Hemisphere. This allows for bias recognition in the GPP representations of the three selected models. The main bias patterns are (i) the terrestrial GPP of ORCHIDEE at high northern latitudes is currently overestimated, (ii) the seasonal variations of the GPP are out of phase in the NCAR-CLM4 model, showing a maximum carbon uptake too early in spring in the northernmost ecosystems, (iii) the overall amplitude of the seasonal variations of GPP in NCAR-CLM4 is too small, and (iv) for the LPJ model, the GPP is slightly out of phase for the northernmost ecosystems and the respiration fluxes might be too large in summer in the

  4. Effects of in-situ and reanalysis climate data on estimation of cropland gross primary production using the Vegetation Photosynthesis Model

    SciTech Connect

    Jin, Cui; Xiao, Xiangming; Wagle, Pradeep; Griffis, Timothy; Dong, Jinwei; Wu, Chaoyang; Qin, Yuanwei; Cook, David R.

    2015-11-01

    Satellite-based Production Efficiency Models (PEMs) often require meteorological reanalysis data such as the North America Regional Reanalysis (NARR) by the National Centers for Environmental Prediction (NCEP) as model inputs to simulate Gross Primary Production (GPP) at regional and global scales. This study first evaluated the accuracies of air temperature (TNARR) and downward shortwave radiation (RNARR) of the NARR by comparing with in-situ meteorological measurements at 37 AmeriFlux non-crop eddy flux sites, then used one PEM – the Vegetation Photosynthesis Model (VPM) to simulate 8-day mean GPP (GPPVPM) at seven AmeriFlux crop sites, and investigated the uncertainties in GPPVPM from climate inputs as compared with eddy covariance-based GPP (GPPEC). Results showed that TNARR agreed well with in-situ measurements; RNARR, however, was positively biased. An empirical linear correction was applied to RNARR, and significantly reduced the relative error of RNARR by ~25% for crop site-years. Overall, GPPVPM calculated from the in-situ (GPPVPM(EC)), original (GPPVPM(NARR)) and adjusted NARR (GPPVPM(adjNARR)) climate data tracked the seasonality of GPPEC well, albeit with different degrees of biases. GPPVPM(EC) showed a good match with GPPEC for maize (Zea mays L.), but was slightly underestimated for soybean (Glycine max L.). Replacing the in-situ climate data with the NARR resulted in a significant overestimation of GPPVPM(NARR) (18.4/29.6% for irrigated/rainfed maize and 12.7/12.5% for irrigated/rainfed soybean). GPPVPM(adjNARR) showed a good agreement with GPPVPM(EC) for both crops due to the reduction in the bias of RNARR. The results imply that the bias of RNARR introduced significant uncertainties into the PEM-based GPP estimates, suggesting that more accurate surface radiation datasets are needed to estimate primary production of terrestrial ecosystems at regional and global scales.

  5. Variability in primary productivity determines metapopulation dynamics.

    PubMed

    Fernández, Néstor; Román, Jacinto; Delibes, Miguel

    2016-04-13

    Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity-a major outcome of ecosystem functions-on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. PMID:27053739

  6. Interpretation of tree-ring data with a model for primary production, carbon allocation and growth

    NASA Astrophysics Data System (ADS)

    Li, G.; Wang, H.; Harrison, S. P.; Prentice, I. C.

    2013-12-01

    We present a simple, generic model of annual tree growth, called ';T'. This model accepts input from a generic light-use efficiency model which is known to provide good simulations of terrestrial carbon exchange. The light-use efficiency model provides values for Gross Primary Production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport-tissue, and fine-root production and respiration, in such a way as to satisfy well-understood dimensional relationships. The result is a model that can represent both ontogenetic effects and the effects of environmental variations and trends on growth. The model has been applied to simulate ring-width series from multiple individual trees in temperature- and drought-limited contexts. Each tree is initialized at its actual diameter at the time when local climate records started. These records are used to drive the trees' subsequent growth. Realistic simulations of the pattern of interannual variability of ring-width are generated, and shown to relate statistically to climate. An upward trend in ring-width during 1958-2007 is shown to be present in the primary observations, and in the simulations; but not in the standard, detrended ring-width series. This approach combines two modelling approaches previously developed in the global carbon cycle and forest science literature respectively. Neither has been widely applied in the context of tree-ring based climate reconstruction. This combination of methods offers promise, however, because it could provide a way to sidestep several known problems. These include: reliance on correlations for the interpretation of ring-width variations in terms of climate; the necessity of detrending using empirical functions (which can remove trends caused by variations in the environment as well as those that are ontogenetic); and the difficulty of assessing effects of extrinsic, non

  7. (p)ppGpp, a Small Nucleotide Regulator, Directs the Metabolic Fate of Glucose in Vibrio cholerae*

    PubMed Central

    Oh, Young Taek; Lee, Kang-Mu; Bari, Wasimul; Raskin, David M.; Yoon, Sang Sun

    2015-01-01

    When V. cholerae encounters nutritional stress, it activates (p)ppGpp-mediated stringent response. The genes relA and relV are involved in the production of (p)ppGpp, whereas the spoT gene encodes an enzyme that hydrolyzes it. Herein, we show that the bacterial capability to produce (p)ppGpp plays an essential role in glucose metabolism. The V. cholerae mutants defective in (p)ppGpp production (i.e. ΔrelAΔrelV and ΔrelAΔrelVΔspoT mutants) lost their viability because of uncontrolled production of organic acids, when grown with extra glucose. In contrast, the ΔrelAΔspoT mutant, a (p)ppGpp overproducer strain, exhibited better growth in the presence of the same glucose concentration. An RNA sequencing analysis demonstrated that transcriptions of genes consisting of an operon for acetoin biosynthesis were markedly elevated in N16961, a seventh pandemic O1 strain, but not in its (p)ppGpp0 mutant during glucose-stimulated growth. Transposon insertion in acetoin biosynthesis gene cluster resulted in glucose-induced loss of viability of the ΔrelAΔspoT mutant, further suggesting the crucial role of acetoin production in balanced growth under glucose-rich environments. Additional deletion of the aphA gene, encoding a negative regulator for acetoin production, failed to rescue the (p)ppGpp0 mutant from the defective glucose-mediated growth, suggesting that (p)ppGpp-mediated acetoin production occurs independent of the presence of AphA. Overall, our results reveal that (p)ppGpp, in addition to its well known role as a stringent response mediator, positively regulates acetoin production that contributes to the successful glucose metabolism and consequently the proliferation of V. cholerae cells under a glucose-rich environment, a condition that may mimic the human intestine. PMID:25882848

  8. Variability in primary productivity determines metapopulation dynamics

    PubMed Central

    2016-01-01

    Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity—a major outcome of ecosystem functions—on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. PMID:27053739

  9. Patterns of net primary production across sites

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Net primary production (NPP) is a fundamentally important and commonly measured ecosystem process that provides an integrative estimate of energy capture and flow into systems, and consequently the energy available for use by other trophic levels. A wide range of productivity levels occurs globally ...

  10. Primary Production in Antarctic Sea Ice

    NASA Technical Reports Server (NTRS)

    Arrigo, Kevin R.; Worthen, Denise L.; Lizotte, Michael P.; Dixon, Paul; Dieckmann, Gerhard

    1997-01-01

    A numerical model shows that in Antarctic sea ice, increased flooding in regions with thick snow cover enhances primary production in the infiltration (surface) layer. Productivity in the freeboard (sea level) layer is also determined by sea ice porosity, which varies with temperature. Spatial and temporal variation in snow thickness and the proportion of first-year ice thus determine regional differences in sea ice primary production. Model results show that of the 40 tera-grams of carbon produced annually in the Antarctic ice pack, 75 percent was associated with first-year ice and nearly 50 percent was produced in the Weddell Sea.

  11. How tropical cyclone inter-annual timing and trajectory control gross primary productivity in the SE US at seasonal and annual timescales and impacts on mountain forest eco-hydrology

    NASA Astrophysics Data System (ADS)

    Lowman, L.; Barros, A.

    2015-12-01

    Tropical cyclones (TCs) are an important source of freshwater input to the SE US eco-hydrologic function. Soil moisture, a temporal integral of precipitation, is critical to plant photosynthesis and carbon assimilation. In this study, we investigate the impact TCs have on gross primary productivity (GPP) in the SE US using the physically-based Duke Coupled Hydrology Model with Vegetation (DCHM-V) which includes coupled water and energy cycles and a biochemical representation of photosynthesis. A parsimonious evaluation of model-estimated GPP against all available AmeriFlux data in the SE US is presented. We characterize the seasonality of vegetation activity in the SE US by simulating water, energy, and carbon fluxes using the DCHM-V at high spatial (4 km) and temporal (30-min) resolution over the period 2002 - 2012. The model is run offline using atmospheric forcing data from NLDAS-2, precipitation from StageIV, and phenology indices from MODIS FPAR/LAI. Analysis of model results show the tendency for low GPP to occur in the Appalachian Mountains during peak summer months when water stress limits stomatal function. We contrast these simulations with model runs where periods of TC activity are replaced with the monthly climatological diurnal cycle from NARR. Results show that the timing and trajectory of TCs are key to understanding their impact on GPP across the SE US. Specifically: 1) Timing of moisture input from TCs greatly influences the vegetation response. TCs during peak summer months increase GPP and years with TCs falling in peak summer months see much higher annual GPP averages; 2) Years of drought and low plant productivity (2006-2007, 2011-2012) in the SE US tend to have TCs that fall later in the year when the additional moisture input does not have a significant impact on vegetation activity; and 3) TC path impacts regional GPP averages. The mountain region shows large inter- and intra-annual variability in plant productivity and high sensitivity to

  12. Green light: gross primary production influences seasonal stream N export by controlling fine-scale N dynamics.

    PubMed

    Lupon, Anna; Martí, Eugènia; Sabater, Francesc; Bernal, Susana

    2016-01-01

    Monitoring nutrient concentrations at fine-scale temporal resolution contributes to a better understanding of nutrient cycling in stream ecosystems. However, the mechanisms underlying fine-scale nutrient dynamics and its implications for budget catchent fluxes are still poorly understood. To gain understanding of patterns and controls of fine-scale stream nitrogen (N) dynamics and to assess how they affect hydrological N fluxes, we explored diel variation in stream nitrate (NO3-) concentration along a headwater stream with increasing riparian area and channel width. At the downstream site, the highest day-night variations occurred in early spring, when stream NO3- concentrations were 13% higher at night than at daytime. Such day-night variations were strongly related to daily light inputs (R2 = 0.74) and gross primary production (GPP; R2 = 0.74), and they showed an excellent fit with day-night NO- variations predicted from GPP (R2 = 0.85). These results suggest that diel fluctuations in stream NO3- concentration were mainly driven by photoautotrophic N uptake. Terrestrial influences were discarded because no simultaneous diel variations in stream discharge, riparian groundwater level, or riparian solute concentration were observed. In contrast to the downstream site, no diel variations in NO3- concentration occurred at the upstream site, likely because water temperature was colder (10 degrees C vs. 12 degrees C) and light availability was lower (4 vs. 9 mol x m(-2) x d(-1)). Although daily GPP was between 10- and 100-fold lower than daily respiration, photoautotrophic N uptake contributed to a 10% reduction in spring NO3- loads at the downstream site. Our study clearly shows that the activity of photoautotrophs can substantially change over time and along the stream continuum in response to key environmental drivers such as light and temperature, and further, that its capacity to regulate diel and seasonal N fluxes can be important even in low-productivity streams

  13. Simulation of tree ring-widths with a model for primary production, carbon allocation and growth

    NASA Astrophysics Data System (ADS)

    Li, G.; Harrison, S. P.; Prentice, I. C.; Falster, D.

    2014-07-01

    We present a simple, generic model of annual tree growth, called "T". This model accepts input from a first-principles light-use efficiency model (the P model). The P model provides values for Gross Primary Production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport-tissue, and fine root production and respiration, in such a way as to satisfy well-understood dimensional and functional relationships. Our approach thereby integrates two modelling approaches separately developed in the global carbon-cycle and forest-science literature. The T model can represent both ontogenetic effects (impact of ageing) and the effects of environmental variations and trends (climate and CO2) on growth. Driven by local climate records, the model was applied to simulate ring widths during 1958-2006 for multiple trees of Pinus koraiensis from the Changbai Mountain, northeastern China. Each tree was initialised at its actual diameter at the time when local climate records started. The model produces realistic simulations of the interannual variability in ring width for different age cohorts (young, mature, old). Both the simulations and observations show a significant positive response of tree-ring width to growing-season total photosynthetically active radiation (PAR0) and the ratio of actual to potential evapotranspiration (α), and a significant negative response to mean annual temperature (MAT). The slopes of the simulated and observed relationships with PAR0 and α are similar; the negative response to MAT is underestimated by the model. Comparison of simulations with fixed and changing atmospheric CO2 concentration shows that CO2 fertilization over the past 50 years is too small to be distinguished in the ring-width data given ontogenetic trends and interannual variability in climate.

  14. Simulation of tree-ring widths with a model for primary production, carbon allocation, and growth

    NASA Astrophysics Data System (ADS)

    Li, G.; Harrison, S. P.; Prentice, I. C.; Falster, D.

    2014-12-01

    We present a simple, generic model of annual tree growth, called "T". This model accepts input from a first-principles light-use efficiency model (the "P" model). The P model provides values for gross primary production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport tissue, and fine-root production and respiration in such a way as to satisfy well-understood dimensional and functional relationships. Our approach thereby integrates two modelling approaches separately developed in the global carbon-cycle and forest-science literature. The T model can represent both ontogenetic effects (the impact of ageing) and the effects of environmental variations and trends (climate and CO2) on growth. Driven by local climate records, the model was applied to simulate ring widths during the period 1958-2006 for multiple trees of Pinus koraiensis from the Changbai Mountains in northeastern China. Each tree was initialised at its actual diameter at the time when local climate records started. The model produces realistic simulations of the interannual variability in ring width for different age cohorts (young, mature, and old). Both the simulations and observations show a significant positive response of tree-ring width to growing-season total photosynthetically active radiation (PAR0) and the ratio of actual to potential evapotranspiration (α), and a significant negative response to mean annual temperature (MAT). The slopes of the simulated and observed relationships with PAR0 and α are similar; the negative response to MAT is underestimated by the model. Comparison of simulations with fixed and changing atmospheric CO2 concentration shows that CO2 fertilisation over the past 50 years is too small to be distinguished in the ring-width data, given ontogenetic trends and interannual variability in climate.

  15. Assessing boreal forest photosynthetic dynamics through space-borne measurements of greenness, chlorophyll fluorescence and model GPP

    NASA Astrophysics Data System (ADS)

    Walther, Sophia; Guanter, Luis; Voigt, Maximilian; Köhler, Philipp; Jung, Martin; Joiner, Joanna

    2015-04-01

    sophia.walther@gfz-potsdam.de The seasonality of photosynthesis of boreal forests is an essential driver of the terrestrial carbon, water and energy cycles. However, current carbon cycle model results only poorly represent interannual variability and predict very different magnitudes and timings of carbon fluxes between the atmosphere and the land surface (e.g. Jung et al. 2011, Richardson et al. 2012). Reflectance-based satellite measurements, which give an indication of the amount of green biomass on the Earth's surface, have so far been used as input to global carbon cycle simulations, but they have limitations as they are not directly linked to instantaneous photosynthesis. As an alternative, space-borne retrievals of sun-induced chlorophyll fluorescence (SIF) boast the potential to provide a direct indication of the seasonality of boreal forest photosynthetic activity and thus to improve carbon model performances. SIF is a small electromagnetic signal that is re-emitted from the photosystems in the chloroplasts, which results in a direct relationship to photosynthetic efficiency. In this contribution we examine the seasonality of the boreal forests with three different vegetation parameters, namely greenness, SIF and model simulations of gross primary production (gross carbon flux into the plants by photosynthesis, GPP). We use the enhanced vegetation index (EVI) to represent green biomass. EVI is calculated from NBAR MODIS reflectance measurements (0.05deg, 16 days temporal resolution) for the time from January 2007-May 2013. SIF data originate from GOME-2 measurements on board the MetOp-A satellite in a spatial resolution of 0.5deg for the time from 2007-2011 (Joiner et al. (2013), Köhler et al. (2014)). As a third data source, data-driven GPP model results are used for the time from 2006-2012 with 0.5deg spatial resolution. The method to quantify phenology developed by Gonsamo et al. (2013) is applied to infer the main phenological phases (greenup/onset of

  16. QUANTIFYING UNCERTAINTY IN NET PRIMARY PRODUCTION MEASUREMENTS

    EPA Science Inventory

    Net primary production (NPP, e.g., g m-2 yr-1), a key ecosystem attribute, is estimated from a combination of other variables, e.g. standing crop biomass at several points in time, each of which is subject to errors in their measurement. These errors propagate as the variables a...

  17. Grazer Effects on Stream Primary Production and Nitrate Utilization: Estimating Feedbacks Under Reduced Nitrate Levels at High-Temporal Resolutions from the Patch to Reach-Scale

    NASA Astrophysics Data System (ADS)

    Reijo, C. J.; Cohen, M. J.

    2015-12-01

    While nutrient enrichment is often identified as the leading cause for changes in stream gross primary production (GPP) and shifts in vegetative communities, other factors such as grazers influence overall stream structure and function. Evidence shows that grazers are a top-down control on algae in streams; however, the specific feedbacks between overall stream metabolism, grazer effects, and nutrient cycling have been variable and little is known about these interactions at nutrient levels below ambient. To further our understanding of these linkages, a nutrient depletion chamber was created and paired with high-resolution in situ sensors to estimate stream metabolism and characterize nitrate uptake (UNO3) pathways (i.e. plant uptake and denitrification). The Plexiglas chamber blocks flow and nutrient supply, inserts into upper sediments, allows light in and sediment-water-air interactions to occur. At Gum Slough Springs, FL, nitrate was reduced from ambient levels (1.40 mg N/L) to below regulatory thresholds (ca. 0.20 mg N/L) within one week. Paired chambers with and without the presence of snails (Elimia floridensis) were deployed across submerged aquatic vegetation (SAV; Vallisneria americana) and algae (Lyngbya) substrates. Results show that GPP and UNO3 were higher under SAV (70 g O2/m2/d and 300 mg NO3/m2/d, respectively) and a general lack of nutrient limitation even at low [NO3]. Grazer effects differed by vegetation type as it alleviated the reduction of NO3 levels and GPP under SAV but enhanced the decrease of algal GPP and NO3 levels over time. Continued work includes estimating grazer effects on denitrification, quantifying snail nutrient excretion contributions, and scaling up all estimates from the patch to reach level. Overall, this study will further our understanding of grazer-production-nutrient interactions within stream systems, making it possible to predict changes in feedbacks when one part of the biotic or abiotic ecosystem is altered.

  18. Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems

    NASA Astrophysics Data System (ADS)

    Houborg, Rasmus; F. McCabe, Matthew; Cescatti, Alessandro; A. Gitelson, Anatoly

    2015-12-01

    Leaf chlorophyll content (Chll) may serve as an observational proxy for the maximum rate of carboxylation (Vmax), which describes leaf photosynthetic capacity and represents the single most important control on modeled leaf photosynthesis within most Terrestrial Biosphere Models (TBMs). The parameterization of Vmax is associated with great uncertainty as it can vary significantly between plants and in response to changes in leaf nitrogen (N) availability, plant phenology and environmental conditions. Houborg et al. (2013) outlined a semi-mechanistic relationship between Vmax25 (Vmax normalized to 25 °C) and Chll based on inter-linkages between Vmax25, Rubisco enzyme kinetics, N and Chll. Here, these relationships are parameterized for a wider range of important agricultural crops and embedded within the leaf photosynthesis-conductance scheme of the Community Land Model (CLM), bypassing the questionable use of temporally invariant and broadly defined plant functional type (PFT) specific Vmax25 values. In this study, the new Chll constrained version of CLM is refined with an updated parameterization scheme for specific application to soybean and maize. The benefit of using in-situ measured and satellite retrieved Chll for constraining model simulations of Gross Primary Productivity (GPP) is evaluated over fields in central Nebraska, U.S.A between 2001 and 2005. Landsat-based Chll time-series records derived from the Regularized Canopy Reflectance model (REGFLEC) are used as forcing to the CLM. Validation of simulated GPP against 15 site-years of flux tower observations demonstrate the utility of Chll as a model constraint, with the coefficient of efficiency increasing from 0.91 to 0.94 and from 0.87 to 0.91 for maize and soybean, respectively. Model performances particularly improve during the late reproductive and senescence stage, where the largest temporal variations in Chll (averaging 35-55 μg cm-2 for maize and 20-35 μg cm-2 for soybean) are observed. While

  19. DksA and ppGpp Directly Regulate Transcription of the Escherichia coli Flagellar Cascade

    PubMed Central

    Lemke, Justin J.; Durfee, Tim; Gourse, Richard L.

    2009-01-01

    The components of the Escherichia coli flagella apparatus are synthesized in a three-level transcriptional cascade activated by the master regulator FlhDC. The cascade coordinates the synthesis rates of a large number of gene products with each other and with nutritional conditions. Recent genome-wide studies have reported that flagellar transcription is altered in cells lacking the transcription regulators DksA or ppGpp, but some or all reported effects could be indirect, and some are contradictory. We report here that the activities of promoters at all three levels of the cascade are much higher in strains lacking dksA, resulting in overproduction of flagellin and hyperflagellated cells. In vitro, DksA/ppGpp inhibits the flhDC promoter and the σ70-dependent fliA promoter transcribing the gene for σ28. However, DksA and ppGpp do not affect the σ28-dependent fliA promoter or the σ28-dependent fliC promoter in vitro, suggesting that the dramatic effects on expression of those genes in vivo are mediated indirectly through direct effects of DksA/ppGpp on FlhDC and σ28 expression. We conclude that DksA/ppGpp inhibits expression of the flagellar cascade during stationary phase and following starvation, thereby coordinating flagella and ribosome assembly and preventing expenditure of scarce energy resources on synthesis of two of the cell’s largest macromolecular complexes. PMID:19889089

  20. Relationships between primary production and crop yields in semi-arid and arid irrigated agro-ecosystems

    NASA Astrophysics Data System (ADS)

    Jaafar, H. H.; Ahmad, F. A.

    2015-04-01

    In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.

  1. Stomata-controlled nighttime COS fluxes in a boreal forest: implications for the use of COS as a GPP tracer

    NASA Astrophysics Data System (ADS)

    Kooijmans, Linda M. J.; Maseyk, Kadmiel; Seibt, Ulli; Vesala, Timo; Mammarella, Ivan; Baker, Ian T.; Franchin, Alessandro; Kolari, Pasi; Sun, Wu; Keskinen, Helmi; Levula, Janne; Chen, Huilin

    2016-04-01

    Carbonyl Sulfide (COS) is a promising new tracer that can be used to partition the Net Ecosystem Exchange into gross primary production (GPP) and respiration. COS and CO2 vegetation fluxes are closely related as these gases share the same diffusion pathway into stomata. This close coupling is the fundamental principle for the use of COS as tracer for GPP. Nonetheless, in contrast to CO2 , the uptake of COS by vegetation is not light-dependent, and therefore the vegetative uptake of COS can continue during the night as long as stomata are open. Nighttime stomatal conductance is observed in a variety of studies, and also nighttime depletion of COS concentrations is reported several times but it is not confirmed with field measurements that the depletion of COS in the night is indeed driven by stomatal opening. In the summer of 2015 a campaign took place at the SMEAR II site in Hyytiälä, Finland to provide better constrained COS flux data for boreal forests using a combination of COS measurements, i.e. atmospheric profile concentrations up to 125 m, eddy-covariance fluxes and soil chamber fluxes, and collocated measurements of stomatal conductance and 222Radon. A high correlation between concentrations of 222Radon and COS implies that the radon-tracer method is a valuable tool to derive nighttime ecosystem COS fluxes. We find that soils contribute to 17% of the total ecosystem COS flux during nighttime in the peak growing season. Nighttime ecosystem COS fluxes show a correlation with stomatal conductance (R2 = 0.3), indicating that nighttime COS fluxes are primarily driven by vegetation. The COS vegetation fluxes will be compared with calculated fluxes from the Simple Biosphere model. Furthermore, the nighttime vegetative COS uptake covers a substantial fraction (25%) of the daily maximum COS uptake by vegetation. Accurate quantification of nighttime COS uptake is required to be able to use COS as a useful tracer for GPP.

  2. Net ecosystem exchange, gross primary production, and ecosystem respiration of carbon dioxide during barley growing season in rice-barley paddy field of Korea

    NASA Astrophysics Data System (ADS)

    Jung, M.; Shim, K.; Min, S.; Kim, Y.; Kim, S.; So, K.

    2013-12-01

    This study was conducted to measure carbon dioxide exchange between customarily cultivated rice-barley double cropping paddy field and the atmosphere during barley growing season (October 2012 and June 2013) and to estimate carbon dioxide fluxes using agro-meteorological factors (temperature, net radiation etc. ) and barley biomass. The carbon dioxide fluxes were quantified by eddy covariance technique in paddy fields with rice-barley double cropping system, located at the Gimje flux site in the southwestern coast of Korea. The total values of net ecosystem carbon dioxide exchange (NEE), gross primary production (GPP), and ecosystem respiration (Re) were -100.6, 782.7, and 682.5 g C m-2 during barley growing season, respectively. The NEE was tended to keep between 0 and 5 g C m-2 d-1 from sowing date (Oct. 21, 2012) to winter rest stage (Dec. 3, 2012 to Feb. 22, 2013), and gradually decreased in tillering stage (Feb. 23, 2013 to May 5, 2013) with its maximum around heading date, and then started to increase in ripening stage (May 6, 2013 to Jun. 8, 2013). The soil temperature was strongly correlated with the Re (r2=0.86), while the net radiation showed the weak relationship with the GPP during the emergence, seedling, and winter rest stage. The aboveground biomass of barley was significantly correlated with the values of NEE (r2=0.79), GPP (r2=0.83), and Re (r2=0.77), respectively.

  3. 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

  4. Chemolithotrophic Primary Production in a Subglacial Ecosystem

    PubMed Central

    Hamilton, Trinity L.; Havig, Jeff R.; Skidmore, Mark L.; Shock, Everett L.

    2014-01-01

    Glacial comminution of bedrock generates fresh mineral surfaces capable of sustaining chemotrophic microbial communities under the dark conditions that pervade subglacial habitats. Geochemical and isotopic evidence suggests that pyrite oxidation is a dominant weathering process generating protons that drive mineral dissolution in many subglacial systems. Here, we provide evidence correlating pyrite oxidation with chemosynthetic primary productivity and carbonate dissolution in subglacial sediments sampled from Robertson Glacier (RG), Alberta, Canada. Quantification and sequencing of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) transcripts suggest that populations closely affiliated with Sideroxydans lithotrophicus, an iron sulfide-oxidizing autotrophic bacterium, are abundant constituents of microbial communities at RG. Microcosm experiments indicate sulfate production during biological assimilation of radiolabeled bicarbonate. Geochemical analyses of subglacial meltwater indicate that increases in sulfate levels are associated with increased calcite and dolomite dissolution. Collectively, these data suggest a role for biological pyrite oxidation in driving primary productivity and mineral dissolution in a subglacial environment and provide the first rate estimate for bicarbonate assimilation in these ecosystems. Evidence for lithotrophic primary production in this contemporary subglacial environment provides a plausible mechanism to explain how subglacial communities could be sustained in near-isolation from the atmosphere during glacial-interglacial cycles. PMID:25085483

  5. Chemolithotrophic primary production in a subglacial ecosystem.

    PubMed

    Boyd, Eric S; Hamilton, Trinity L; Havig, Jeff R; Skidmore, Mark L; Shock, Everett L

    2014-10-01

    Glacial comminution of bedrock generates fresh mineral surfaces capable of sustaining chemotrophic microbial communities under the dark conditions that pervade subglacial habitats. Geochemical and isotopic evidence suggests that pyrite oxidation is a dominant weathering process generating protons that drive mineral dissolution in many subglacial systems. Here, we provide evidence correlating pyrite oxidation with chemosynthetic primary productivity and carbonate dissolution in subglacial sediments sampled from Robertson Glacier (RG), Alberta, Canada. Quantification and sequencing of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) transcripts suggest that populations closely affiliated with Sideroxydans lithotrophicus, an iron sulfide-oxidizing autotrophic bacterium, are abundant constituents of microbial communities at RG. Microcosm experiments indicate sulfate production during biological assimilation of radiolabeled bicarbonate. Geochemical analyses of subglacial meltwater indicate that increases in sulfate levels are associated with increased calcite and dolomite dissolution. Collectively, these data suggest a role for biological pyrite oxidation in driving primary productivity and mineral dissolution in a subglacial environment and provide the first rate estimate for bicarbonate assimilation in these ecosystems. Evidence for lithotrophic primary production in this contemporary subglacial environment provides a plausible mechanism to explain how subglacial communities could be sustained in near-isolation from the atmosphere during glacial-interglacial cycles. PMID:25085483

  6. The Stringent Response Mediated by (p)ppGpp Is Required for Virulence of Pseudomonas syringae pv. tomato and Its Survival on Tomato.

    PubMed

    Chatnaparat, Tiyakhon; Li, Zhong; Korban, Schuyler S; Zhao, Youfu

    2015-07-01

    The hypersensitive response and pathogenicity (hrp) type III secretion system (T3SS) is a key pathogenicity factor in Pseudomonas syringae pv. tomato DC3000 (DC3000). In this study, the role of the second messenger (p)ppGpp on virulence and survival of DC3000 was investigated. Results have demonstrated that (p)ppGpp-deficient mutant (ppGpp(0)) of DC3000 exhibited lower levels of expression of the T3SS and genes of other virulence traits, such as coronatine toxin. The ppGpp(0) mutant of DC3000 was greatly impaired in causing disease and in growth in planta. Furthermore, (p)ppGpp was required for swarming motility, pyoverdine production, the oxidative stress response, as well as γ-amino butyric acid utilization. Screening of amino acids, major signals in activation of ppGpp biosynthesis, revealed that promoter activities of the avrPto gene could be either activated or suppressed by various amino acids in a ppGpp-dependent or -independent manner. Moreover, the ppGpp(0) mutant exhibited increased cell size and decreased survival on plant surfaces. Altogether, these findings indicate that ppGpp acts as an internal signal that regulates the T3SS as well as other virulence factors in pseudomonads and suggest that bacterial pathogens utilize intracellular messengers to sense environmental and nutritional signals for rapid, precise, and reversible control of their pathogenesis and survival. PMID:25675257

  7. Ecosystem carbon partitioning: aboveground net primary productivity correlates with the root carbon input in different land use types of Southern Alps

    NASA Astrophysics Data System (ADS)

    Rodeghiero, Mirco; Martinez, Cristina; Gianelle, Damiano; Camin, Federica; Zanotelli, Damiano; Magnani, Federico

    2013-04-01

    Terrestrial plant carbon partitioning to above- and below-ground compartments can be better understood by integrating studies on biomass allocation and estimates of root carbon input based on the use of stable isotopes. These experiments are essential to model ecosystem's metabolism and predict the effects of global change on carbon cycling. Using in-growth soil cores in conjunction with the 13C natural abundance method we quantified net plant-derived root carbon input into the soil, which has been pointed out as the main unaccounted NPP (net primary productivity) component. Four land use types located in the Trentino Region (northern Italy) and representing a range of aboveground net primary productivity (ANPP) values (155-868 gC m-2 y-1) were investigated: conifer forest, apple orchard, vineyard and grassland. Cores, filled with soil of a known C4 isotopic signature were inserted at 18 sampling points for each site and left in place for twelve months. After extraction, cores were analysed for %C and d13C, which were used to calculate the proportion of new plant-derived root C input by applying a mass balance equation. The GPP (gross primary productivity) of each ecosystem was determined by the eddy covariance technique whereas ANPP was quantified with a repeated inventory approach. We found a strong and significant relationship (R2 = 0.93; p=0.03) between ANPP and the fraction of GPP transferred to the soil as root C input across the investigated sites. This percentage varied between 10 and 25% of GPP with the grassland having the lowest value and the apple orchard the highest. Mechanistic ecosystem carbon balance models could benefit from this general relationship since ANPP is routinely and easily measured at many sites. This result also suggests that by quantifying site-specific ANPP, root carbon input can be reliably estimated, as opposed to using arbitrary root/shoot ratios which may under- or over-estimate C partitioning.

  8. Ecosystem Disturbance Effects on Land Surface Temperature, Forest Carbon Stocks, and Primary Productivity in the Western United States

    NASA Astrophysics Data System (ADS)

    Cooper, L. A.; Ballantyne, A.; Holden, Z. A.; Landguth, E.

    2015-12-01

    Disturbance plays an important role in the structure, composition, and nutrient cycling of forest ecosystems. Climate change is resulting in an increase in disturbance frequency and intensity, making it critical that we quantify the physical and chemical impacts of disturbances on forests. The impacts of disturbance are thought to vary widely depending on disturbance type, location, and climate. More specifically, fires, insect infestations, and other types of disturbances differ in their timing, extent, and intensity making it difficult to assess the true impact of disturbances on local energy budgets and carbon cycling. Here, we provide a regional analysis of the impacts of fire, insect attack, and other disturbances on land surface temperature (LST), carbon stocks, and gross primary productivity (GPP). Using disturbances detected with MODIS Enhanced Vegetation Index (EVI) time series between 2002 and 2012, we find that the impacts of disturbance on LST, carbon stocks, and GPP vary widely according to local climate, vegetation, and disturbance type and intensity. Fires resulted in the most distinct impacts on all response variables. Forest responses to insect epidemics were more varied in their magnitude and timing. The results of this study provide an important estimation of the variability of climate and ecosystem responses to disturbance across a large and heterogeneous landscape. With disturbance projected to increase in both frequency and intensity around the globe in the coming years, this information is vitally important to effectively manage forests into the future.

  9. Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations

    SciTech Connect

    Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.; Yang, Dawen; Shi, Xiaoying; Mao, Jiafu; Hayes, Daniel J.; Schwalm, C.; Wei, Yaxing; Liu, Shishi

    2014-09-01

    The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically, differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.

  10. PRIMARY PRODUCTION ESTIMATES IN CHESAPEAKE BAY USING SEAWIFS

    EPA Science Inventory

    The temporal and spatial variability in primary production along the main stem of Chesapeake Bay was examined from 1997 through 2000. Primary production estimates were determined from the Vertically Generalized Production Model (VGPM) (Behrenfeld and Falkowski, 1997) using chloro...

  11. A Model-Data Fusion Approach for Constraining Modeled GPP at Global Scales Using GOME2 SIF Data

    NASA Astrophysics Data System (ADS)

    MacBean, N.; Maignan, F.; Lewis, P.; Guanter, L.; Koehler, P.; Bacour, C.; Peylin, P.; Gomez-Dans, J.; Disney, M.; Chevallier, F.

    2015-12-01

    Predicting the fate of the ecosystem carbon, C, stocks and their sensitivity to climate change relies heavily on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. However, there are large differences in the Gross Primary Productivity (GPP) simulated by different land surface models (LSMs), not only in terms of mean value, but also in terms of phase and amplitude when compared to independent data-based estimates. This strongly limits our ability to provide accurate predictions of carbon-climate feedbacks. One possible source of this uncertainty is from inaccurate parameter values resulting from incomplete model calibration. Solar Induced Fluorescence (SIF) has been shown to have a linear relationship with GPP at the typical spatio-temporal scales used in LSMs (Guanter et al., 2011). New satellite-derived SIF datasets have the potential to constrain LSM parameters related to C uptake at global scales due to their coverage. Here we use SIF data derived from the GOME2 instrument (Köhler et al., 2014) to optimize parameters related to photosynthesis and leaf phenology of the ORCHIDEE LSM, as well as the linear relationship between SIF and GPP. We use a multi-site approach that combines many model grid cells covering a wide spatial distribution within the same optimization (e.g. Kuppel et al., 2014). The parameters are constrained per Plant Functional type as the linear relationship described above varies depending on vegetation structural properties. The relative skill of the optimization is compared to a case where only satellite-derived vegetation index data are used to constrain the model, and to a case where both data streams are used. We evaluate the results using an independent data-driven estimate derived from FLUXNET data (Jung et al., 2011) and with a new atmospheric tracer, Carbonyl sulphide (OCS) following the approach of Launois et al. (ACPD, in review). We show that the optimization reduces the strong positive

  12. Observations of Ocean Primary Productivity Using MODIS

    NASA Technical Reports Server (NTRS)

    Esaias, Wayne E.; Abbott, Mark R.; Koblinsky, Chester J. (Technical Monitor)

    2001-01-01

    Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP

  13. Modelling the Gross Primary Productivity of West Africa with the Regional Biomass Model RBM+, using optimized 250 m MODIS FPAR and fractional vegetation cover information

    NASA Astrophysics Data System (ADS)

    Machwitz, Miriam; Gessner, Ursula; Conrad, Christopher; Falk, Ulrike; Richters, Jochen; Dech, Stefan

    2015-12-01

    Global warming associated with climate change is one of the greatest challenges of today's world. Increasing emissions of the greenhouse gas CO2 are considered as a major contributing factor to global warming. One regulating factor of CO2 exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO2. The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250 m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000-250 m spatial resolution (RBM+). The adaptation to the 250 m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000 m MODIS MOD15A2 FPAR product which was downscaled to 250 m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated. The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP

  14. Reconciling estimates of regional gross primary productivity among top-down and bottom-up approaches for a tall-tower CO2 concentration footprint area in central Saskatchewan, Canada

    NASA Astrophysics Data System (ADS)

    Chen, Baozhang

    2013-04-01

    Quantifying regional (~103 - 105 km^2) CO2 fluxes is a key to improve our understanding of the terrestrial carbon cycle. Four independent techniques were used to estimate daily regional gross primary productivity (GPP) for a tall-tower CO2 concentration footprint area (~103 - 105 km^2) in central Saskatchewan, Canada, which is characterized as a spatially heterogeneous boreal forest-agriculture transition region. These techniques include three bottom-up methods (a processed based ecosystem modeling approach using Dynamic Land Model (DLM), a flux-tower based upscaling approach, a "two-leaf" light use efficiency modeling approach based on remote sensing, and MODIS GPP products (MOD17A3)) and one simply top-down approach based on tall tower equilibrium boundary layer (EBL) budget analysis that allows the estimation of regional GPP at daily time steps from hourly CO2 concentration measurements. The top-down EBL method was applied to two CO2 concentration towers (the East Trout Lake 106-m tall tower (54°21'N, 104°59'W) with 4-height measurements (95, 55, 33, 22 m) and the Candle Lake 28-m high tower (53°59'N, 105°07'W).The daily concentration footprints were estimated using the authors previously developed footprint model (SAFE-C) based on Eulerian similarity theory. The estimated monthly and annual footprints for each height were similar in orientation and shapes but apparently different in size. The areas of footprints were significantly increased with heights. The 90% accumulative footprint areas for the heights of 22 m to 95 m varied from ~150 - 500 km2 and ~104 - 105 km2 at daily and annual time scales, respectively. The spatial representativeness of the GPP values extracted from CO2 mixing ratio data using the EBL method for each measured heights is theoretically associated with each-level's footprints. These bottom-up estimated GPP values weighted with concentration footprints were highly correlated with tower-based atmospheric top-down estimates for the

  15. The productivity of primary care research networks.

    PubMed

    Griffiths, F; Wild, A; Harvey, J; Fenton, E

    2000-11-01

    Primary care research networks are being publicly funded in the United Kingdom to promote a culture of research and development in primary care. This paper discusses the organisational form of these networks and how their productivity can be evaluated, drawing on evidence from management science. An evaluation of a research network has to take account of the complexity of the organisation, the influence of its local context, and its stage of development. Output measures, such as number of research papers, and process measures, such as number of research meetings, may contribute to an evaluation. However, as networking relies on the development of informal, trust-based relationships, the quality of interactions within a network is of paramount importance for its success. Networks can audit and reflect on their success in promoting such relationships and a more formal qualitative evaluation by an independent observer can document their success to those responsible for funding. PMID:11141879

  16. (p)ppGpp and the bacterial cell cycle.

    PubMed

    Nazir, Aanisa; Harinarayanan, Rajendran

    2016-06-01

    Genes of the Rel/Spo homolog (RSH) superfamily synthesize and/or hydrolyse the modified nucleotides pppGpp/ ppGpp (collectively referred to as (p)ppGpp) and are prevalent across diverse bacteria and in plant chloroplasts. Bacteria accumulate (p)ppGpp in response to nutrient deprivation (generically called the stringent response) and elicit appropriate adaptive responses mainly through the regulation of transcription. Although at different concentrations (p)ppGpp affect the expression of distinct set of genes, the two well-characterized responses are reduction in expression of the protein synthesis machinery and increase in the expression of genes coding for amino acid biosynthesis. In Escherichia coli, the cellular (p)ppGpp level inversely correlates with the growth rate and increasing its concentration decreases the steady state growth rate in a defined growth medium. Since change in growth rate must be accompanied by changes in cell cycle parameters set through the activities of the DNA replication and cell division apparatus, (p)ppGpp could coordinate protein synthesis (cell mass increase) with these processes. Here we review the role of (p)ppGpp in bacterial cell cycle regulation. PMID:27240988

  17. Coupling gross primary production and transpiration for a consistent estimate of canopy water use efficiency

    NASA Astrophysics Data System (ADS)

    Yebra, Marta; van Dijk, Albert

    2015-04-01

    Water use efficiency (WUE, the amount of transpiration or evapotranspiration per unit gross (GPP) or net CO2 uptake) is key in all areas of plant production and forest management applications. Therefore, mutually consistent estimates of GPP and transpiration are needed to analysed WUE without introducing any artefacts that might arise by combining independently derived GPP and ET estimates. GPP and transpiration are physiologically linked at ecosystem level by the canopy conductance (Gc). Estimates of Gc can be obtained by scaling stomatal conductance (Kelliher et al. 1995) or inferred from ecosystem level measurements of gas exchange (Baldocchi et al., 2008). To derive large-scale or indeed global estimates of Gc, satellite remote sensing based methods are needed. In a previous study, we used water vapour flux estimates derived from eddy covariance flux tower measurements at 16 Fluxnet sites world-wide to develop a method to estimate Gc using MODIS reflectance observations (Yebra et al. 2013). We combined those estimates with the Penman-Monteith combination equation to derive transpiration (T). The resulting T estimates compared favourably with flux tower estimates (R2=0.82, RMSE=29.8 W m-2). Moreover, the method allowed a single parameterisation for all land cover types, which avoids artefacts resulting from land cover classification. In subsequent research (Yebra et al, in preparation) we used the same satellite-derived Gc values within a process-based but simple canopy GPP model to constrain GPP predictions. The developed model uses a 'big-leaf' description of the plant canopy to estimate the mean GPP flux as the lesser of a conductance-limited and radiation-limited GPP rate. The conductance-limited rate was derived assuming that transport of CO2 from the bulk air to the intercellular leaf space is limited by molecular diffusion through the stomata. The radiation-limited rate was estimated assuming that it is proportional to the absorbed photosynthetically

  18. Mass extinctions: Ecological selectivity and primary production

    NASA Astrophysics Data System (ADS)

    Rhodes, Melissa Clark; Thayer, Charles W.

    1991-09-01

    If mass extinctions were caused by reduced primary productivity, then extinctions should be concentrated among animals with starvation-susceptible feeding modes, active lifestyles, and high-energy budgets. The stratigraphic ranges (by stage) of 424 genera of bivalves and 309 genera of articulate brachiopods suggest that there was an unusual reduction of primary productivity at the Cretaceous/Tertiary (K/T) boundary extinction. For bivalves at the K/T, there were (1) selective extinction of suspension feeders and other susceptible trophic categories relative to deposit feeders and other resistant categories, and (2) among suspension feed-ers, selective extinction of bivalves with active locomotion. During the Permian-Triassic (P/Tr) extinction and Jurassic background time, extinction rates among suspension feeders were greater for articulate brachiopods than for bivalves. But during the K/T event, extinction rates of articulates and suspension-feeding bivalves equalized, possibly because the low-energy budgets of articulates gave them an advantage when food was scarce.

  19. Estimating crop net primary production using inventory data and MODIS-derived parameters

    SciTech Connect

    Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

    2013-06-03

    National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

  20. The magic dance of the alarmones (p)ppGpp.

    PubMed

    Steinchen, Wieland; Bange, Gert

    2016-08-01

    The alarmones (p)ppGpp are important second messengers that orchestrate pleiotropic adaptations of bacteria and plant chloroplasts in response to starvation and stress. Here, we review our structural and mechanistic knowledge on (p)ppGpp metabolism including their synthesis, degradation and interconversion by a highly diverse set of enzymes. Increasing structural information shows how (p)ppGpp interacts with an incredibly diverse set of different targets that are essential for replication, transcription, translation, ribosome assembly and metabolism. This raises the question how the chemically rather simple (p)ppGpp is able to interact with these different targets? Structural analysis shows that the diversity of (p)ppGpp interaction with cellular targets critically relies on the conformational flexibility of the 3' and 5' phosphate moieties allowing alarmones to efficiently modulate the activity of target structures in a broad concentration range. Current approaches in the design of (p)ppGpp-analogs as future antibiotics might be aided by the comprehension of conformational flexibility exhibited by the magic dancers (p)ppGpp. PMID:27149325

  1. Leaf demography and physiology of the Tapajós National Forest: could phenology cause a forest-level increase in gross primary productivity during the dry season?

    NASA Astrophysics Data System (ADS)

    Albert, L.; Wu, J.; Prohaska, N.; Camargo, P. B. D.; Cosme, R., Jr.; Huxman, T. E.; Saleska, S. R.

    2014-12-01

    Tropical forests such as the forests of the Amazon basin are a significant component of the earth's carbon budget, yet how these forests respond to seasonal changes in weather, along with the extent to which tree biology synchronizes with seasonal cycles, are poorly understood. For evergreen forests in equatorial Amazon that experience dry seasons, most global vegetation models project a dry-season decrease in gross primary productivity (GPP). However, eddy covariance observations and remote sensing assessments suggest a late-dry season increase in GPP. Most global vegetation models assume that there is no seasonal variation in leaf phenology (cycles of leaf flush and senescence), or in leaf physiology. We conducted a case study in the Tapajos National Forest KM67 site, near Santarém, Brazil, to investigate whether leaf aging and seasonal shifts in leaf demography could cause an increase in GPP during the dry season. In a series of fieldwork campaigns beginning in August 2012, we monitored leaf demographic composition (leaf age categories) from 1-m branches collected from 20 trees representing abundant species, and we assessed how photosynthesis varies with leaf age for a subset of these trees. Our results show that photosynthetic capacity (e.g. Vcmax) is higher for leaves that matured during the most recent dry season than for older leaves from previous periods of growth. For many trees, leaf demography shifted during the dry season such that recently matured leaves replaced old leaves. For instance, leaf demography of an Erisma uncinatum, the most abundant canopy tree species at our site, had significantly more recently matured leaves, and significantly fewer old leaves, during surveys late in the dry season (after mid-October) than early in the dry season (prior to mid-September). These results suggest that shifts in leaf demography together with the effects of leaf age on leaf physiology can increase GPP during the dry season at the KM67 site. Thus, leaf

  2. Biospheric primary production during an ENSO transition.

    PubMed

    Behrenfeld, M J; Randerson, J T; McClain, C R; Feldman, G C; Los, S O; Tucker, C J; Falkowski, P G; Field, C B; Frouin, R; Esaias, W E; Kolber, D D; Pollack, N H

    2001-03-30

    The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides global monthly measurements of both oceanic phytoplankton chlorophyll biomass and light harvesting by land plants. These measurements allowed the comparison of simultaneous ocean and land net primary production (NPP) responses to a major El Niño to La Niña transition. Between September 1997 and August 2000, biospheric NPP varied by 6 petagrams of carbon per year (from 111 to 117 petagrams of carbon per year). Increases in ocean NPP were pronounced in tropical regions where El Niño-Southern Oscillation (ENSO) impacts on upwelling and nutrient availability were greatest. Globally, land NPP did not exhibit a clear ENSO response, although regional changes were substantial. PMID:11283369

  3. Vegetation Responses to Future Climates: Global Variability in Water Use Efficiency and Primary Productivity in a CMIP5 Multimodel Ensemble

    NASA Astrophysics Data System (ADS)

    Bernardes, S.; Campbell, P. K. E.; Zhang, Q.; Middleton, E.

    2015-12-01

    Climate projections for the 21st century predict substantial changes in temperature and in the quantity and spatiotemporal distribution of precipitation for large regions on the planet. Reductions in water availability resulting from decreased precipitation and increased water demand by the atmosphere can negatively affect plant metabolism, reduce carbon uptake, and limit services of entire ecosystems. Future increases in temperature and in atmospheric carbon dioxide concentrations may help offset some of these impacts on vegetation. In particular, plants may adjust their water use efficiency (WUE, plant production per water loss by evapotranspiration) in response to changing environmental conditions. We assessed an ensemble of thirteen models from the Coupled Model Intercomparison Project 5 (CMIP5) and analyzed future changes in climate variables, carbon mass in vegetation, vegetation primary productivity and WUE. The analysis considered two representative concentration pathways (RCP4.5 and RCP8.5) for the period 2006-2099 and compared projections to historical values (1850-2005). Results include differences between historical and projected conditions for global, regional and latitudinal distributions of model outputs, for both RCPs. We observed significant intermodel variability when representing changes in WUE over the century, including high model sensitivity to different greenhouse concentration scenarios. Model agreement varied with RCP (higher agreement for RCP4.5), as well as regionally (higher agreement in Southeast Asia, lower agreement in arid areas, including the Sahara and Western Australia). The majority of models point to an increase in GPP and WUE for most of the planet under both concentration pathways, with changes ranging from zero to 100% of their historical values. These increases were observed to be consistently higher for RCP8.5. In addition, higher increases in GPP and WUE are predicted to occur over higher latitudes in the northern

  4. Herbivory and Stoichiometric Feedbacks to Primary Production.

    PubMed

    Krumins, Jennifer Adams; Krumins, Valdis; Forgoston, Eric; Billings, Lora; van der Putten, Wim H

    2015-01-01

    Established theory addresses the idea that herbivory can have positive feedbacks on nutrient flow to plants. Positive feedbacks likely emerge from a greater availability of organic carbon that primes the soil by supporting nutrient turnover through consumer and especially microbially-mediated metabolism in the detrital pool. We developed an entirely novel stoichiometric model that demonstrates the mechanism of a positive feedback. In particular, we show that sloppy or partial feeding by herbivores increases detrital carbon and nitrogen allowing for greater nitrogen mineralization and nutritive feedback to plants. The model consists of differential equations coupling flows among pools of: plants, herbivores, detrital carbon and nitrogen, and inorganic nitrogen. We test the effects of different levels of herbivore grazing completion and of the stoichiometric quality (carbon to nitrogen ratio, C:N) of the host plant. Our model analyses show that partial feeding and plant C:N interact because when herbivores are sloppy and plant biomass is diverted to the detrital pool, more mineral nitrogen is available to plants because of the stoichiometric difference between the organisms in the detrital pool and the herbivore. This model helps to identify how herbivory may feedback positively on primary production, and it mechanistically connects direct and indirect feedbacks from soil to plant production. PMID:26098841

  5. Herbivory and Stoichiometric Feedbacks to Primary Production

    PubMed Central

    Krumins, Jennifer Adams; Krumins, Valdis; Forgoston, Eric; Billings, Lora; van der Putten, Wim H.

    2015-01-01

    Established theory addresses the idea that herbivory can have positive feedbacks on nutrient flow to plants. Positive feedbacks likely emerge from a greater availability of organic carbon that primes the soil by supporting nutrient turnover through consumer and especially microbially-mediated metabolism in the detrital pool. We developed an entirely novel stoichiometric model that demonstrates the mechanism of a positive feedback. In particular, we show that sloppy or partial feeding by herbivores increases detrital carbon and nitrogen allowing for greater nitrogen mineralization and nutritive feedback to plants. The model consists of differential equations coupling flows among pools of: plants, herbivores, detrital carbon and nitrogen, and inorganic nitrogen. We test the effects of different levels of herbivore grazing completion and of the stoichiometric quality (carbon to nitrogen ratio, C:N) of the host plant. Our model analyses show that partial feeding and plant C:N interact because when herbivores are sloppy and plant biomass is diverted to the detrital pool, more mineral nitrogen is available to plants because of the stoichiometric difference between the organisms in the detrital pool and the herbivore. This model helps to identify how herbivory may feedback positively on primary production, and it mechanistically connects direct and indirect feedbacks from soil to plant production. PMID:26098841

  6. Primary production in the northern Red Sea

    NASA Astrophysics Data System (ADS)

    Qurban, Mohammed Ali; Balala, Arvin C.; Kumar, Sanjeev; Bhavya, P. S.; Wafar, Mohideen

    2014-04-01

    Rates of uptake of carbon and nitrogen (ammonium, nitrate and urea) by phytoplankton, along with concentrations of nutrients and chlorophyll a, in the Saudi Arabian waters of the northern Red Sea (23 °N-28 °N) were measured in autumn, 2012. Concentrations of nitrate, nitrite and phosphate within the euphotic zone were in trace amounts while those of silicon were in excess of 0.5 μmol L- 1. Concentrations of chlorophyll (Chl a) were very low within the euphotic zone (0.01-0.6 μg L- 1 at discrete depths and 1.53-21.5 mg m- 2 as column-integrated values). A deep chlorophyll maximum and a nitrite maximum were present between 60 and 80 m at almost all of the stations occupied. Rates of carbon uptake at discrete depths ranged from 0.02 to 3 μg C L- 1 h- 1. Chl-normalized carbon uptake rates related with ambient light in a Michaelis-Menten kinetic pattern. About 80% of the carbon uptake was attributable to the < 20 μm fraction. Ammonium and urea were the nitrogen compounds taken up in preference by phytoplankton and accounted for close to 90% of the total N uptake. Considered together, these results indicate that the waters of the northern Red Sea are oligotrophic and that the primary production is strongly N-controlled. Analyses of the data and interpretation of the results led to the following speculations: (1) the perceived north-south gradient in Chl a (and possibly in primary production) in the Red Sea is maintained by circulation of Chl- and nutrient-rich waters through a series of gyres, (2) there is a greater role for heterotrophy and microbial loop in the trophic dynamics, and (3) in situ nitrification in the euphotic zone is an important source of N for phytoplankton and consequently export of carbon to deep sea could be lesser than that indicated by f-ratios.

  7. Responses of primary productivity to increased temperature and phytoplankton diversity

    NASA Astrophysics Data System (ADS)

    Lewandowska, Aleksandra M.; Breithaupt, Petra; Hillebrand, Helmut; Hoppe, Hans-Georg; Jürgens, Klaus; Sommer, Ulrich

    2012-08-01

    In order to examine the effects of warming and diversity changes on primary productivity, we conducted a meta-analysis on six independent indoor mesocosm experiments with a natural plankton community from the Baltic Sea. Temperature effects on primary productivity changed with light intensity and zooplankton density and analysed pathways between temperature, diversity and productivity, elucidating direct and indirect effects of warming on primary productivity during the spring phytoplankton bloom. Our findings indicate that warming directly increased carbon specific primary productivity, which was more pronounced under low grazing pressure. On the other hand, primary productivity per unit water volume did not respond to increased temperature, because of a negative temperature effect on phytoplankton biomass. Moreover, primary productivity response to temperature changes depended on light limitation. Using path analysis, we tested whether temperature effects were direct or mediated by warming effects on phytoplankton diversity. Although phytoplankton species richness had a positive impact on both net primary productivity and carbon specific primary productivity - and evenness had a negative effect on net primary productivity - both richness and evenness were not affected by temperature. Thus, we suggest that diversity effects on primary productivity depended mainly on other factors than temperature like grazing, sinking or nutrient limitation, which themselves are temperature dependent.

  8. The 'overflow tap' theory: linking GPP to forest soil carbon dynamics and the mycorrhizal component

    NASA Astrophysics Data System (ADS)

    Heinemeyer, Andreas; Willkinson, Matthew; Subke, Jens-Arne; Casella, Eric; Vargas, Rodrigo; Morison, James; Ineson, Phil

    2010-05-01

    productivity. The work presented here focuses on three critical areas: (1) We present annual fluxes at hourly intervals for the three soil CO2 efflux components (R, F and H) from a 75 year-old deciduous oak forest in SE England. We investigate the individual environmental responses of the three flux components, and compare them to soil decomposition modelled by CENTURY and its latest version (i.e. DAYCENT), which separately models root-derived respiration in addition to the soil decomposition output. (2) Using estimates of gross primary productivity (GPP) based on eddy covariance measurements from the same site, we explore linkages between GPP and soil respiration component fluxes using basic regression and wavelet analyses. We show a distinctly different time lag signal between GPP and root vs. mycorrhizal fungal respiration. We then discuss how models might need to be improved to accurately predict total soil CO2 efflux, including root-derived respiration. (3) We finally discuss the ‘overflow tap' theory, that during periods of high assimilation (e.g. optimum environmental conditions or elevated CO2) surplus non-structural C is allocated belowground to the mycorrhizal network; this additional C could then be used and released by the associated fungal partners, causing soil priming through stimulating decomposition.

  9. Combining remote sensing and eddy covariance data to monitor the gross primary production of an estuarine wetland ecosystem in East China.

    PubMed

    Wu, Mingquan; Muhammad, Shakir; Chen, Fang; Niu, Zheng; Wang, Changyao

    2015-04-01

    Wetland ecosystems are very important for ecological diversity and have a strong ability to sequester carbon. Through comparisons with field measured eddy covariance data, we evaluated the relationships between the light use efficiency (LUE) index and the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface temperature (LST). Consequently, we have proposed a new model for the estimation of gross primary production (GPP) for wetland ecosystems using Moderate Resolution Imaging Spectroradiometer (MODIS) products, including these vegetation indices, LST and the fraction of photosynthetically active radiation (FAPAR) absorbed by the active vegetation. This model was developed and validated for a study site on Chongming Island, Shanghai, China. Our results show that photosynthetically active radiation (PAR) was highly correlated with the LST, with a coefficient of determination (R(2)) of 0.59 (p < 0.001). Vegetation indices, such as EVI, NDVI and LST, were highly correlated with LUE. We found that the product of vegetation indices (VIs) and a modified form of LST (Te) can be used to estimate LUE, with an R(2) of 0.82 (P < 0.0001) and an RMSE of 0.054 kg C per mol PAR. This new model can provide reliable estimates of GPP (R(2) of 0.87 and RMSE of 0.009 kg C m(-2) 8 d(-1) (P < 0.0001)). PMID:25797359

  10. Enhanced Primary Productivity at the Subtropical Convergence

    NASA Astrophysics Data System (ADS)

    Llido, J.; Garcon, V.; Lutjeharms, J.; Sudre, J.

    2004-12-01

    The Subtropical Convergence is one of the major frontal systems in the world ocean. It is not just simply a biogeographical boundary, but forms a unique biological habitat of its own. Ocean colour satellite data indicate that it is a region of enhanced chlorophyll a and thus a potential key region of carbon drawdown from the atmosphere. Ship crossings sometimes show peaks in chlorophyll a at the front, but at other times these peaks are absent. If the normal mode of primary productivity at the front consists of intermittent bloom events, as these observations suggest, organisms endemic to this habitat may have to be adapted to a boom-or-bust situation. We have studied the presence of chlorophyll a using daily SeaWiFS images and showed that bloom events with limited spatial and temporal scales are indeed the norm. A coupled physical-biological model simulates this process with a fair degree of verisimilitude. We use this model to investigate the physico-biogeochemical requirements for bloom events and demonstrate that in most cases the limiting factor is intensity of vertical stratification combined with light availability.

  11. Global Patterns in Human Consumption of Net Primary Production

    NASA Technical Reports Server (NTRS)

    Imhoff, Marc L.; Bounoua, Lahouari; Ricketts, Taylor; Loucks, Colby; Harriss, Robert; Lawrence William T.

    2004-01-01

    The human population and its consumption profoundly affect the Earth's ecosystems. A particularly compelling measure of humanity's cumulative impact is the fraction of the planet's net primary production that we appropriate for our Net primary production-the net amount of solar energy converted to plant organic matter through photosynthesis-can be measured in units of elemental carbon and represents the primary food energy source for the world's ecosystems. Human appropriation of net primary production, apart from leaving less for other species to use, alters the composition of the atmosphere, levels of biodiversity, flows within food webs and the provision of important primary production required by humans and compare it to the total amount generated on the landscape. We then derive a spatial ba!mce sheet of net primary production supply and demand for the world. We show that human appropriation of net primary production varies spatially from almost zero to many times the local primary production. These analyses reveal the uneven footprint of human consumption and related environmental impacts, indicate the degree to which human populations depend on net primary production "imports" and suggest policy options for slowing future growth of human appropriation of net primary production.

  12. How drought severity constrains GPP and its partitioning among carbon pools in a Quercus ilex coppice?

    NASA Astrophysics Data System (ADS)

    Rambal, S.; Lempereur, M.; Limousin, J. M.; Martin-StPaul, N. K.; Ourcival, J. M.; Rodríguez-Calcerrada, J.

    2014-06-01

    The partitioning of photosynthates toward biomass compartments has a crucial role in the carbon sink function of forests. Few studies have examined how carbon is allocated toward plant compartments in drought prone forests. We analyzed the fate of GPP in relation to yearly water deficit in an old evergreen Mediterranean Quercus ilex coppice severely affected by water limitations. Gross and net carbon fluxes between the ecosystem and the atmosphere were measured with an eddy-covariance flux tower running continuously since 2001. Discrete measurements of litterfall, stem growth and fAPAR allowed us to derive annual productions of leaves, wood, flowers and acorns and an isometric relationship between stem and belowground biomass has been used to estimate perennial belowground growth. By combining eddy-covariance fluxes with annual productions we managed to close a C budget and derive values of autotrophic and heterotrophic respirations, NPP and carbon use efficiency (CUE, the ratio between NPP and GPP). Average values of yearly NEP, GPP and Reco were 282, 1259 and 977 g C m-2. The corresponding ANPP components were 142.5, 26.4 and 69.6 g C m-2 for leaves, reproductive effort (flowers and fruits) and stems. Gross and net carbon exchange between the ecosystem and the atmosphere were affected by annual water deficit. Partitioning to the different plant compartments was also impacted by drought, with a hierarchy of responses going from the most affected, the stem growth, to the least affected, the leaf production. The average CUE was 0.40, which is well in the range for Mediterranean-type forest ecosystems. CUE tended to decrease more slightly in response to drought than GPP and NPP, probably due to drought-acclimation of autotrophic respiration. Overall, our results provide a baseline for modeling the inter-annual variations of carbon fluxes and allocation in this widespread Mediterranean ecosystem and highlight the value of maintaining continuous experimental

  13. Stand-level patterns of carbon fluxes and partitioning in a Eucalyptus grandis plantation across a gradient of productivity, in Sao Paulo State, Brazil.

    PubMed

    Campoe, Otávio C; Stape, José Luiz; Laclau, Jean-Paul; Marsden, Claire; Nouvellon, Yann

    2012-06-01

    Wood production represents a large but variable fraction of gross primary production (GPP) in highly productive Eucalyptus plantations. Assessing patterns of carbon (C) partitioning (C flux as a fraction of GPP) between above- and belowground components is essential to understand mechanisms driving the C budget of these plantations. Better knowledge of fluxes and partitioning to woody and non-woody tissues in response to site characteristics and resource availability could provide opportunities to increase forest productivity. Our study aimed at investigating how C allocation varied within one apparently homogeneous 90 ha stand of Eucalyptus grandis (W. Hill ex Maiden) in Southeastern Brazil. We assessed annual above-ground net primary production (ANPP: stem, leaf, and branch production) and total belowground C flux (TBCF: the sum of root production and respiration and mycorrhizal production and respiration), GPP (computed as the sum of ANPP, TBCF and estimated aboveground respiration) on 12 plots representing the gradient of productivity found within the stand. The spatial heterogeneity of topography and associated soil attributes across the stand likely explained this fertility gradient. Component fluxes of GPP and C partitioning were found to vary among plots. Stem NPP ranged from 554 g C m(-2) year(-1) on the plot with lowest GPP to 923 g C m(-2) year(-1) on the plot with highest GPP. Total belowground carbon flux ranged from 497 to 1235 g C m(-2) year(-1) and showed no relationship with ANPP or GPP. Carbon partitioning to stem NPP increased from 0.19 to 0.23, showing a positive trend of increase with GPP (R(2) = 0.29, P = 0.07). Variations in stem wood production across the gradient of productivity observed at our experimental site were a result of the variability in C partitioning to different forest system components. PMID:22543478

  14. A multi-scale assessment of forest primary production across the eastern USA using Forest Inventory and Analysis (FIA) and MODIS data

    NASA Astrophysics Data System (ADS)

    Kwon, Youngsang

    As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale

  15. A simplified gross primary production and evapotranspiration model for boreal coniferous forests - is a generic calibration sufficient?

    NASA Astrophysics Data System (ADS)

    Minunno, F.; Peltoniemi, M.; Launiainen, S.; Aurela, M.; Lindroth, A.; Lohila, A.; Mammarella, I.; Minkkinen, K.; Mäkelä, A.

    2015-07-01

    The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions.

  16. Towards a universal trait-based model of terrestrial primary production

    NASA Astrophysics Data System (ADS)

    Wang, H.; Prentice, I. C.; Cornwell, W.; Keenan, T. F.; Davis, T.; Wright, I. J.; Evans, B. J.; Peng, C.

    2015-12-01

    Systematic variations of plant traits along environmental gradients have been observed for decades. For example, the tendencies of leaf nitrogen per unit area to increase, and of the leaf-internal to ambient CO2 concentration ratio (ci:ca) to decrease, with aridity are well established. But ecosystem models typically represent trait variation based purely on empirical relationships, or on untested conjectures, or not at all. Neglect of quantitative trait variation and its adapative significance probably contributes to the persistent large uncertainties among models in predicting the response of the carbon cycle to environmental change. However, advances in ecological theory and the accumulation of extensive data sets during recent decades suggest that theoretically based and testable predictions of trait variation could be achieved. Based on well-established ecophysiological principles and consideration of the adaptive significance of traits, we propose universal relationships between photosynthetic traits (ci:ca, carbon fixation capacity, and the ratio of electron transport capacity to carbon fixation capacity) and primary environmental variables, which capture observed trait variations both within and between plant functional types. Moreover, incorporating these traits into the standard model of C3photosynthesis allows gross primary production (GPP) of natural vegetation to be predicted by a single equation with just two free parameters, which can be estimated from independent observations. The resulting model performs as well as much more complex models. Our results provide a fresh perspective with potentially high reward: the possibility of a deeper understanding of the relationships between plant traits and environment, simpler and more robust and reliable representation of land processes in Earth system models, and thus improved predictability for biosphere-atmosphere interactions and climate feedbacks.

  17. Carbon accumulation and allocation in a primary Bornean tropical rainforest

    NASA Astrophysics Data System (ADS)

    Katayama, A.; Komatsu, H.; Kume, T.; Ohashi, M.; Nakagawa, M.; Otsuki, K.; Kumagai, T.

    2010-12-01

    To develop our knowledge of global carbon cycling, it is important to know all components of allocated carbon in tropical rainforests because of their enormous accumulation and elimination. Our goals in this study are to estimate carbon allocation (i.e. carbon flux to aboveground biomass increment, litterfall, aboveground plant respiration and belowground) and compare GPP based on biometric and flux measurement in a primary Bornean tropical rainforest. GPP estimated by biometric method (35.39 tCha-2yr-1) was similar to that measured by flux measurement (31.56 tCha-2yr-1). Mean annual aboveground biomass increment (2.77 tCha-2yr-1) was reasonable compared to former literatures in spite of larger aboveground biomass (272 tCha-2yr-1). Ratio of TBCF to GPP (0.55) was extremely high. These results suggested that considerable carbon is allocated to belowground, causing low productivity of aboveground biomass.

  18. Diversity in (p)ppGpp metabolism and effectors.

    PubMed

    Liu, Kuanqing; Bittner, Alycia N; Wang, Jue D

    2015-04-01

    Bacteria produce guanosine tetraphosphate and pentaphosphate, collectively named (p)ppGpp, in response to a variety of environmental stimuli. These two remarkable molecules regulate many cellular processes, including the central dogma processes and metabolism, to ensure survival and adaptation. Work in Escherichia coli laid the foundation for understanding the molecular details of (p)ppGpp and its cellular functions. As recent studies expand to other species, it is apparent that there exists considerable variation, with respect to not only (p)ppGpp metabolism, but also to its mechanism of action. From an evolutionary standpoint, this diversification is an elegant example of how different species adapt a particular regulatory network to their diverse lifestyles. PMID:25636134

  19. Primary production and respiration of hypersaline microbial mats as a response for high and low CO2 availability

    NASA Astrophysics Data System (ADS)

    Bento, L.; Enrich-Prast, A.; Nielsen, L. P.

    2012-09-01

    Here we report a time series of experiments performed in a microcosm to test the response of hypersaline microbial mats to diverse atmospheric CO2 conditions. Different from most part of the literature, our study used a sample chamber were carbon dioxide concentration was controlled. Our aim was to test the effect of different atmospheric CO2 conditions in benthic gross and net primary production, and respiration. This study showed for the first time to our knowledge absolute carbon limitation in a microbial mat. Oxygen concentration profile varied from a flattened shape to almost linear when atmospheric CO2 at the chamber reached 0 ppm, with NPP reaching 0 nmol cm-3 s-1 throughout most part of the profile. In this conditions sediment community respiration represented 100% of GPP. Extreme close coupling between primary production and respiration in microbial mats can be even self-sustainable in environments with temporally no atmospheric CO2 available. When submitted to even high CO2 concentrations (550 ppm), our sample showed a characteristic shape that indicate limitation composed by a more rectilinear oxygen profile, and NPP peaks mainly restricted to deeper layers. Therefore, we suggest that phototrophic communities in aquatic shallow ecosystems can be carbon limited. This limitation could be common especially in ecosystems submitted to variable water depth conditions, like coastal lagoons and intertidal sediments.

  20. A review of ocean chlorophyll algorithms and primary production models

    NASA Astrophysics Data System (ADS)

    Li, Jingwen; Zhou, Song; Lv, Nan

    2015-12-01

    This paper mainly introduces the five ocean chlorophyll concentration inversion algorithm and 3 main models for computing ocean primary production based on ocean chlorophyll concentration. Through the comparison of five ocean chlorophyll inversion algorithm, sums up the advantages and disadvantages of these algorithm,and briefly analyzes the trend of ocean primary production model.

  1. (p)ppGpp-dependent and -independent pathways for salt tolerance in Escherichia coli.

    PubMed

    Tarusawa, Takefusa; Ito, Shion; Goto, Simon; Ushida, Chisato; Muto, Akira; Himeno, Hyouta

    2016-07-01

    Addition of some kinds of translation inhibitors targeting the ribosome such as kasugamycin to the culture medium as well as removal of a ribosome maturation factor or a ribosomal protein provides Escherichia coli cells with tolerance to high salt stress. Here, we found that another kind of translation inhibitor, serine hydroxamate (SHX), which induces amino acid starvation leading to (p)ppGpp production, also has a similar effect, but via a different pathway. Unlike kasugamycin, SHX was not effective in (p)ppGpp-null mutant cells. SHX and depletion of RsgA, a ribosome maturation factor, had an additive effect on salt tolerance, while kasugamycin or depletion of RsgA did not. These results indicate the presence of two distinct pathways, (p)ppGpp-dependent and -independent pathways, for salt tolerance of E. coli cell. Both pathways operate even in the absence of σ(S), an alternative sigma factor involved in the stationary phase or stress response. Hastened activation of the exocytoplasmic stress-specific sigma factor, σ(E), after salt shock was observed in the cells treated with SHX, as has been observed in the cells treated with a translation inhibitor or depleted of a ribosome maturation factor. PMID:26823481

  2. Catchment disturbance and stream metabolism: Patterns in ecosystem respiration and gross primary production along a gradient of upland soil and vegetation disturbance

    USGS Publications Warehouse

    Houser, J.N.; Mulholland, P.J.; Maloney, K.O.

    2005-01-01

    Catchment characteristics determine the inputs of sediments and nutrients to streams. As a result, natural or anthropogenic disturbance of upland soil and vegetation can affect instream processes. The Fort Benning Military Installation (near Columbus, Georgia) exhibits a wide range of upland disturbance levels because of spatial variability in the intensity of military training. This gradient of disturbance was used to investigate the effect of upland soil and vegetation disturbance on rates of stream metabolism (ecosystem respiration rate [ER] and gross primary production rate [GPP]). Stream metabolism was measured using an open-system, single-station approach. All streams were net heterotrophic during all seasons. ER was highest in winter and spring and lowest in summer and autumn. ER was negatively correlated with catchment disturbance level in winter, spring, and summer, but not in autumn. ER was positively correlated with abundance of coarse woody debris, but not significantly related to % benthic organic matter. GPP was low in all streams and generally not significantly correlated with disturbance level. Our results suggest that the generally intact riparian zones of these streams were not sufficient to protect them from the effect of upland disturbance, and they emphasize the role of the entire catchment in determining stream structure and function. ?? 2005 by The North American Benthological Society.

  3. Interannual Variation in Phytoplankton Primary Production at a Global Scale

    NASA Technical Reports Server (NTRS)

    Rousseaux, Cecile Severine; Gregg, Watson W.

    2013-01-01

    We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect

  4. Mean Angular Momenta of Primary Photofission Products

    SciTech Connect

    Bezshyyko, O.A.; Kadenko, I.M.; Plujko, V.A.; Yermolenko, R.V.; Mazur, V.M.; Strilchuk, N.V.; Vishnevsky, I.M.; Zheltonozhsky, V.A.

    2005-05-24

    Isomer ratios and mean angular momenta for photofission products of 237Np and 238U are obtained. The technique of gamma-ray spectrometry for isomeric ratio determination was used. Fissionable nuclei were irradiated by bremsstrahlung spectrum of microtron M-30 with electron energy 16 MeV. Calculations of mean angular momenta were performed by modified version of the EMPIRE II code.

  5. Primary and Bacterial Secondary Production in a Southwestern Reservoir

    PubMed Central

    Chrzanowski, Thomas H.; Hubbard, James G.

    1988-01-01

    Rates of primary and bacterial secondary production in Lake Arlington, Texas, were determined. The lake is a warm (annual temperature range, 7 to 32°C), shallow, monomictic reservoir with limited macrophyte development in the littoral zone. Samples were collected from six depths within the photic zone from a site located over the deepest portion of the lake. Primary production and bacterial production were calculated from NaH14CO3 and [methyl-3H]thymidine incorporation, respectively. Peak instantaneous production ranged between 14.8 and 220.5 μg of C liter−1 h−1. There were two distinct periods of high rates of production. From May through July, production near the metalimnion exceeded 100 μg of C liter−1 h−1. During holomixis, production throughout the water column was in excess of 100 μg of C liter−1 h−1 and above 150 μg of C liter−1 h−1 near the surface. Annual areal primary production was 588 g of C m−2. Bacterial production was markedly seasonal. Growth rates during late fall through spring were typically around 0.002 h−1, and production rates were typically 5 μg of C liter−1 h−1. Growth rates were higher during warmer parts of the year and reached 0.03 h−1 by August. The maximum instantaneous rate of bacterial production was approximately 45 μg of C liter−1 h−1. Annual areal bacterial production was 125 g of C m−2. Temporal and spatial distributions of bacterial numbers and activities coincided with temporal and spatial distributions of primary production. Areal primary and bacterial secondary production were highly correlated (r = 0.77, n = 15, P < 0.002). PMID:16347577

  6. Solar Induced Vegetation Fluorescence Retrieval Using SCIAMACHY and GOME-2 Measurements And Its Correlation To GPP And FAPAR

    NASA Astrophysics Data System (ADS)

    Vountas, M.; Khosravi, N.; Rozanov, V. V.; Burrows, J. P.

    2015-12-01

    Global carbon cycle is connected to terrestrial vegetation as an important sink of CO2. Plants contribute to the global carbon cycle both through photosynthesis and respiration processes. Fluorescence is a fraction of surplus energy, emitted to the environment by Chlorophyll molecules as a side-product of photosynthesis. As a result, Sun-Induced plant Fluorescence (SIF) is a reliable indicator of photosynthesis efficiency and therefore, important for vegetation observation, forest monitoring, global carbon uptake formulation and even agriculture.In our study, a newly developed retrieval scheme is used to quantify SIF from non-invasive satellite measurements of Top of Atmosphere (TOA) Earthshine radiances. Our method has been developed and tested on simulated data, created by the comprehensive radiative transfer model, SCIATRAN. Sensitivity studies showed that the method is capable of assessing SIF. The method is then applied on long-term data of 10 years from SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) and GOME-2 (Global Ozone Monitoring Experiment-2) instruments and produced promising results.Furthermore, the relationship between the retrieved SIF values and vegetation's contribution to the global CO2 uptake is investigated by comparing monthly variation of SIF against GPP (Gross Primary Production) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) for selected regions.

  7. Global climate change and terrestrial net primary production

    NASA Technical Reports Server (NTRS)

    Melillo, Jerry M.; Mcguire, A. D.; Kicklighter, David W.; Moore, Berrien, III; Vorosmarty, Charles J.; Schloss, Annette L.

    1993-01-01

    A process-based model was used to estimate global patterns of net primary production and soil nitrogen cycling for contemporary climate conditions and current atmospheric CO2 concentration. Over half of the global annual net primary production was estimated to occur in the tropics, with most of the production attributable to tropical evergreen forest. The effects of CO2 doubling and associated climate changes were also explored. The responses in tropical and dry temperate ecosystems were dominated by CO2, but those in northern and moist temperate ecosystems reflected the effects of temperature on nitrogen availability.

  8. Primary production of the cryptoendolithic microbiota from the Antarctic Desert

    NASA Technical Reports Server (NTRS)

    Vestal, J. R.; Friedmann, E. I. (Principal Investigator)

    1988-01-01

    Primary production in the Antarctic cryptoendolithic microbiota can be determined from biomass and photosynthetic 14CO2 incorporation measurements. Even though good nanoclimate data are available, it is difficult to determine the amount of time when abiotic conditions permit metabolism. Making appropriate assumptions concerning the metabolism of the cryptoendolithic microbiota during periods of warmth, light and moisture, the primary production of the biota was calculated to be on the order of 0.108 to 4.41 mgC/m2/yr, with a carbon turnover time from 576 to 23,520 years. These production values are the lowest found on planet Earth.

  9. The role of acclimation in scaling GPP from the leaf to the canopy for crops in a changing climate

    NASA Astrophysics Data System (ADS)

    Bernacchi, C.; Bagley, J. E.; Ort, D. R.; Kumar, P.; Ruiz Vera, U. M.

    2013-12-01

    Multi-faceted challenges from global climate change and increased demands on agriculture for food, fiber and, increasingly fuel is driving a need to understand how major climate change factors, particularly increasing atmospheric concentrations of CO2 and rising temperature, will influence leaf photosynthesis (A) and ecosystem gross primary productivity (GPP). Eight of the ten major crops grown globally utilize the C3 photosynthetic pathway and based on mechanistic understanding of C3 photosynthesis, a synergism exists with rising CO2 and increasing temperature that is predicted to increase A beyond that of an increase in [CO2] alone. However, considerable uncertainty surrounds the acclimation response of photosynthesis to global change and, as a result, the influence of physiological adjustments of photosynthesis is currently not represented in leaf, canopy, ecosystem or general circulation models that are used to predict ecosystem-scale responses to global change scenarios. Here, we incorporate into mechanistic leaf and canopy photosynthesis models the acclimation responses of the two key parameters required for modeling A and GPP, the maximum velocity for carboxylation (Vc,max) and maximum rate of electron transport (Jmax), determined from in-field experimentation for soybean and poplar, which vary in regards to what limits A in elevated CO2. Measurements of Vc,max and Jmax from the Soybean Temperature by Free Air CO2 Enrichment (Soy-T-FACE) experiment and of poplar at the Poplar FACE experiment were used to model the response of net carbon uptake to [CO2] and/or temperature. The modeling was conducted using the mechanistic leaf photosynthesis model (Farquhar, von Caemmerer, & Berry Model) and the latest generation canopy photosynthesis model with an integrated mechanistic representation of physiology and biophysical components, the Multi-Layer Canopy (MLCan) model. While the theory behind the interactions of [CO2] and temperature on photosynthesis are well

  10. Benthic primary production in the Columbia River Estuary. Final report

    SciTech Connect

    McIntire, C.D.; Amspoker, M.C.

    1984-02-01

    The general objective of the research associated with the Benthic Primary Production Work Unit of Columbia River Estuary Development Program was to determine mechanisms that control the production dynamics and species composition of benthic plant assemblages in the Columbia River Estuary. In particular, the work was concerned with effects of selected physical variables on structural and functional attributes of micro- and macro- vegetation, and on the productivity and biomass of benthic autotrophs on the tidal flats of the estuary.

  11. Human Appropriation of Net Primary Production - Can Earth Keep Up?

    NASA Technical Reports Server (NTRS)

    Imhoff, Marc L.

    2006-01-01

    The amount of Earth's vegetation or net primary production required to support human activities is powerful measure of aggregate human impacts on the biosphere. Biophysical models applied to consumption statistics were used to estimate the annual amount of net primary production in the form of elemental carbon required for food, fibre, and fuel-wood by the global population. The calculations were then compared to satellite-based estimates of Earth's average net primary production to produce a geographically explicit balance sheet of net primary production "supply" and "demand". Humans consume 20% of Earth's net primary production (11.5 petagrams carbon) annually and this percentage varies regionally from 6% (South America) to over 70% (Europe and Asia), and locally from near 0% (central Australia) to over 30,000% (New York City, USA). The uneven footprint of human consumption and related environmental impacts, indicate the degree to which human populations are vulnerable to climate change and suggest policy options for slowing future growth of NPP demand.

  12. Nuclide production by primary cosmic-ray protons

    SciTech Connect

    Reedy, R.C.

    1986-01-01

    The production rates of cosmogenic nuclides in the solar system and in interstellar space were calculated for the primary protons in the galactic and solar cosmic rays. At 1 AU, the long-term average fluxes of solar protons usually produce many more atoms of a cosmogenic nuclide than the primary protons in the galactic cosmic rays (GCR), the exceptions being nuclides made only by high-energy reactions (like /sup 10/Be). Because the particle fluxes inside meteorites and other large objects in space include many secondary neutrons, the production rates are much higher and ratios inside large objects are often very different from those by just the primary GCR protons in small objects. The production rates of cosmogenic nuclides are calculated to vary by about factors of 2.5 during at typical 11-year solar cycle, in agreement with measurements of short-lived radionuclides in recently fallen meteorites. The production of cosmogenic nuclides by the GCR particles outside the heliosphere is higher than that by the modulated GCR primaries normally in the solar system. However, there is considerable uncertainty in the fluxes of interstellar protons and, therefore, in the production rates of cosmogenic nuclides in interstellar space. Production rates and ratios for cosmogenic nuclides would be able to identify particles that were small in space or that were exposed to an unmodulated spectrum of GCR particles. 25 refs., 2 figs., 2 tabs.

  13. A vegetation sensitivity approximation for gross primary production in water limited conditions.

    NASA Astrophysics Data System (ADS)

    Claesson, Jonas; Nycander, Jonas

    2013-04-01

    The most severe impact of climate change on vegetation growth and agriculture is likely to occur under water-limited conditions. Under such conditions the plants optimize the inward flux of CO2 and the outward flux of water vapor (the transpiration) by regulating the size of the stomata openings. Higher temperature increases water loss through transpiration, forcing the plants to diminish the stomata openings, which decreases photosynthesis. This is counteracted by higher CO2 concentration, which allows plants to maintain the inward flux of CO2 through the smaller openings. These two counteracting effects, combined with the change in precipitation, determine the net change of biological productivity in a changed climate. Here, a vegetation sensitivity approximation (VSA) is introduced, in order to understand and estimate the combined effect of changed temperature, CO2-concentration and precipitation on gross primary production (GPP) to first order. According to the VSA, we have: ( ) ?CO2atm ν GP P = ?0 P Here ?CO2atm is the atmospheric CO2 concentration, ?0 is the baseline for atmospheric CO2 concentration, P is precipitation and ν is defined by: -s- ν = 1 - 11°C where s is the climate sensitivity i.e. the increase in temperature when atmospheric CO2 is doubled. The VSA is based on the physical laws of gas flux through the stomata openings, and is only valid under water-limited conditions. It assumes that the temperature depends logarithmically on the CO2 concentration with a given climate sensitivity. Transpiration is assumed to be a constant fraction of precipitation, which is reasonable under water-limited conditions. The VSA is compared to simulations with the dynamic vegetation model LPJ. The agreement is reasonable, and the deviations can be understood by comparison with Köppen's definition of arid climate: in an arid climate growth increases more according to LPJ than according to the VSA, and in non-arid conditions the reverse is true. Both the VSA and

  14. Net primary productivity, allocation pattern and carbon use efficiency in an apple orchard assessed by integrating eddy covariance, biometric and continuous soil chamber measurements

    NASA Astrophysics Data System (ADS)

    Zanotelli, D.; Montagnani, L.; Manca, G.; Tagliavini, M.

    2013-05-01

    Carbon use efficiency (CUE), the ratio of net primary production (NPP) over gross primary production (GPP), is a functional parameter that could possibly link the current increasingly accurate global GPP estimates with those of net ecosystem exchange, for which global predictors are still unavailable. Nevertheless, CUE estimates are actually available for only a few ecosystem types, while information regarding agro-ecosystems is scarce, in spite of the simplified spatial structure of these ecosystems that facilitates studies on allocation patterns and temporal growth dynamics. We combined three largely deployed methods, eddy covariance, soil respiration and biometric measurements, to assess monthly values of CUE, NPP and allocation patterns in different plant organs in an apple orchard during a complete year (2010). We applied a measurement protocol optimized for quantifying monthly values of carbon fluxes in this ecosystem type, which allows for a cross check between estimates obtained from different methods. We also attributed NPP components to standing biomass increments, detritus cycle feeding and lateral exports. We found that in the apple orchard, both net ecosystem production and gross primary production on a yearly basis, 380 ± 30 g C m-2 and 1263 ± 189 g C m-2 respectively, were of a magnitude comparable to those of natural forests growing in similar climate conditions. The largest differences with respect to forests are in the allocation pattern and in the fate of produced biomass. The carbon sequestered from the atmosphere was largely allocated to production of fruit: 49% of annual NPP was taken away from the ecosystem through apple production. Organic material (leaves, fine root litter, pruned wood and early fruit falls) contributing to the detritus cycle was 46% of the NPP. Only 5% was attributable to standing biomass increment, while this NPP component is generally the largest in forests. The CUE, with an annual average of 0.71 ± 0.12, was higher

  15. Climate extremes and ecosystem productivity in global warming simulations

    NASA Astrophysics Data System (ADS)

    Williams, I. N.; Torn, M. S.; Riley, W. J.; Wehner, M. F.; Collins, W.

    2013-12-01

    Ecosystem responses to present-day droughts and heat-waves are often considered indicative of future global warming impacts on ecosystems, under the assumption that the temperature above which vegetation experiences heat and drought stress is invariant with changes in climate and carbon dioxide concentration. Understanding how the impacts of temperature extremes on ecosystems can change with climate change is essential for correctly evaluating and developing Earth System Models (ESMs). The Coupled Model Inter-comparison Project (CMIP5) historical and future (RCP8.5) climate predictions were analyzed in this study to illustrate non-stationarity of climate impacts on ecosystems, as evident by changes in the distribution of Gross Primary Production (GPP) as a function of temperature between future and historical climates. These changes consist of (1) a uniform shift in the GPP distribution toward warmer temperatures between future and historical climates, and (2) a proportional increase in GPP at all temperatures, consistent with CO2 fertilization. The temperature at which GPP has a local maximum within a given climate increases with global warming and closely tracks the change in mean temperature for each ecosystem. This maximum GPP temperature can be conceptualized as a stable equilibrium determined by the temperature at which an increase in plant water stress is compensated by a decrease in light stress (decreasing cloud cover) with increasing temperature. Temperature relative to the temperature of maximum GPP is proposed as an improved measure of climate extremes more relevant to ecosystem productivity than absolute temperature. The percentage change in GPP attributed to changes in relative temperature extremes is up to 3% per K (decrease in GPP), and reflects both an increase in the frequency of climate extremes in global warming scenarios and the change in temperature criteria for negative climate impacts on ecosystem productivity. Temperature at GPP maximum as

  16. NEE and GPP dynamic evolution at two biomes in the upper Spanish plateau

    NASA Astrophysics Data System (ADS)

    Sánchez, María Luisa; Pardo, Nuria; Pérez, Isidro Alberto; García, Maria de los Angeles

    2014-05-01

    In order to assess the ability of dominant biomes to act as a CO2 sink, two eddy correlation stations close to each other in central Spain have been concurrently operational since March 2008 until the present. The land use of the first station, AC, is a rapeseed rotating crop consisting of annual rotation of non-irrigated rapeseed, barley, peas, rye, and sunflower, respectively. The land use of the second, CIBA, is a mixture of open shrubs/crops, with open shrubs being markedly dominant. The period of measurements covered variable general meteorological conditions. 2009 and 2012 were dominated by drought, whereas 2010 was the rainiest year. Annual rainfall during 2008 and 2009 was close to the historical averaged annual means. This paper presents the dynamic evolution of NEE-8d and GPP-8d observed at the AC station over five years and compares the results with those concurrently observed at the CIBA station. GGP 8-d estimates at both stations were determined using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MODIS, PAR in situ measurements, and a scalar f, varying between 0 and 1, to take account of the reduction in maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. f values were assumed to be dependent on air temperature and evaporative fraction, EF, which was considered a proxy of soil moisture. ɛ0, a key parameter, which depends on land use types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites observed and the LUE concurrent 8-d model estimates. Over the five-year study period, both biomes behaved as CO2 sinks. However, the ratio of the NEE-8d total accumulated at AC and CIBA, respectively, was close to a factor two, revealing the effectiveness of the studied crops as CO2 sinks. On an annual basis, accumulated NEE-8d exhibited major variability in both biomes. At CIBA, the results were largely dominated by the

  17. Primary production control of methane emission from wetlands

    NASA Technical Reports Server (NTRS)

    Whiting, G. J.; Chanton, J. P.

    1993-01-01

    Based on simultaneous measurements of CO2 and CH4 exchange in wetlands extending from subarctic peatlands to subtropical marshes, a positive correlation between CH4 emission and net ecosystem production is reported. It is suggested that net ecosystem production is a master variable integrating many factors which control CH4 emission in vegetated wetlands. It is found that about 3 percent of the daily net ecosystem production is emitted back to the atmosphere as CH4. With projected stimulation of primary production and soil microbial activity in wetlands associated with elevated atmospheric CO2 concentration, the potential for increasing CH4 emission from inundated wetlands, further enhancing the greenhouse effect, is examined.

  18. Assessment of regional-scale primary production in terrestrial ecosystems to estimate the possible influence of future climate change on biodiversity

    NASA Astrophysics Data System (ADS)

    Noda, Hibiki; Nishina, Kazuya; Ito, Akihiko

    2015-04-01

    biodiversity. Photosynthetic carbon fixation, namely gross primary production (GPP), is a fundamental process of ecosystems and known to be highly sensitive to meteorological changes including radiation, temperature, precipitation and CO2 concentration. Thus analysis of the effect of future climate change on ecosystem GPP in a biogeographical region, which is important from the viewpoint of the biodiversity conservation, such as "biodiversity hotspot" and "Global 200 Ecoregion", might enable us to discuss the relevance between climate change and biodiversity. In ISI-MIP (Inter-Sectoral Impact Model Intercomparison Project) phase 1, we have estimated GPP by seven global biome models under future climate based on four RCPs (Representative Concentration Pathways for 2.6, 4.5, 6.0, and 8.5 W/m2 stabilization targets) and five global climate models. In present study, we analyzed these outputs to reveal the effect of future climate change on the ecosystem GPP in several biodiversity hotspots and will discuss the relevance between the climate change and biodiversity.

  19. Evaluation of primary production in Lake Erie by multiple proxies.

    PubMed

    Ostrom, Nathaniel E; Carrick, Hunter J; Twiss, Michael R; Piwinski, Leah

    2005-06-01

    Direct measurements of rates of primary production in Lake Erie are few and uncertainties surround rate measurements based on radiocarbon and the light-dark bottle incubation methods. For these reasons, we conducted a series of simultaneous primary productivity measurements in Lake Erie in July and August of 2003, based on incubation with [14C]-NaHCO3, the light-dark bottle method, and incubation with (18)O enriched water. Significant differences in the rates of primary production obtained by incubations with [(18)O]-H2O (0.19-34.60 mmol-O2 m(-3) h(-1)), [14C]-NaHCO3 (0.03-90.50 mmol-C m(-3) h(-1)), and light-dark bottles (0.06-60.78 mmol-O2 m(-3) h(-1)) were evident in six out of nine comparisons. Within the epilimnion, [(18)O]-H2O rates of primary production were significantly different from rates based on [14C]-NaHCO3 and light-dark bottles in all four comparisons and lower rates were obtained in three out of four comparisons. Eutrophic conditions in Sandusky Bay, Lake Erie were evident from the high primary production rates of 20.50-34.60 mmol-O2 m(-3) h(-1) ([(18)O]-H2O), 34.39-90.50 mmol-C m(-3) h(-1) ([14C]-NaHCO3), and 46.66-60.78 mmol-O2 m(-3) h(-1) (light-dark bottle). The photosynthetic quotient (PQ), or ratio of O2 production to CO2 consumption during photosynthesis, averaged 0.64+/-0.33 and 1.93+/-1.93, respectively, based on a comparison of [(18)O]-H2O to [14C]-NaHCO3 rates or light-dark bottle to [14C]-NaHCO3 production rates, respectively, demonstrating that photosynthesis in Lake Erie communities primarily follows expected stochiometric trends. The average of the ratio of production rates based on incubation with [(18)O]-H2O relative to those obtained by the light-dark incubation method was 0.66+/-0.33, indicating a tendency for the [(18)O]-H2O method to provide slightly lower estimates of production in Lake Erie. Lower estimates of primary production based on [(18)O]-H2O incubation relative to the other two approaches is most likely a consequence

  20. A scaling approach of net ecosystem productivity over Alaskan black spruce forests, using the eddy covariance, BIOME-BGC, and MODIS

    NASA Astrophysics Data System (ADS)

    Ueyama, M.; Harazono, Y.

    2006-12-01

    We evaluated gross primary production (GPP), net ecosystem productivity (NPP), and autotrophic respiration over Alaska black spruce forests by combining a field-observed dataset and a newly developed satellite-based model. A three-year continuous dataset derived from the eddy covariance technique at a black spruce forest was used to link the MODIS products of NDVI and land surface temperature (LST) to the tower-based GPP. In order to determine NPP and autotrophic respiration (RES), BIOME-BGC was tuned and validated for Alaska black spruce forests. Using simulation results from a sensitivity analysis, ratios, NPP/GPP and RES/GPP, were determined as functions of LST, and then applied to calculate NPP and RES. The model satisfactorily reproduced not only the tower-based GPP but also simulated NPP and autotrophic respiration by BIOME-BGC. The spatial distributions of the carbon fluxes showed weak longitudinal trends with relatively lower values in the eastern interior around the Brooks Range. The estimated GPP, NPP, and autotrophic respiration over Alaska black spruce forests were 1840, 590, and 1250 g CO2 my-2 y^{- 1}, respectively, between 2003 and 2005.

  1. Decadal Changes in Global Ocean Annual Primary Production

    NASA Technical Reports Server (NTRS)

    Gregg, Watson; Conkright, Margarita E.; Behrenfeld, Michael J.; Ginoux, Paul; Casey, Nancy W.; Koblinsky, Chester J. (Technical Monitor)

    2002-01-01

    The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence

  2. Regulon Controlled by the GppX Hybrid Two Component system in Porphyromonas gingivalis

    PubMed Central

    Hirano, Takanori; Beck, David A. C.; Wright, Chris J.; Demuth, Donald R.; Hackett, Murray; Lamont, Richard J.

    2012-01-01

    Summary The periodontal pathogen Porphyromonas gingivalis experiences a number of environmental conditions in the oral cavity and must monitor and respond to a variety of environmental cues. However the organism possesses only five full two-component systems, one of which is the hybrid system GppX. To investigate the regulon controlled by GppX we performed RNA-Seq on a ΔgppX mutant. Fifty three genes were up-regulated and 37 genes were down-regulated in the ΔgppX mutant. Pathway analyses revealed no systemic function for GppX under nutrient replete conditions; however, over 40% of the differentially abundant genes were annotated as encoding hypothetical proteins indicating a novel role for GppX. Abundance of small (s)RNA was, in general, not affected by the absence of GppX. To further define the role of GppX with respect to regulation of a hypothetical protein observed with the greatest significant relative abundance change relative to a wild-type control, PGN_0151, we constructed a series of strains in which a ΔgppX mutation was complemented with GppX protein containing specific domain and phosphotransfer mutations. The transmembrane domains, the DNA binding domain and the phosphotransfer residues were all required for regulation of PGN_0151. In addition, binding of GppX to the PGN_0151 promoter regions was confirmed by an electrophoretic mobility shift assay (EMSA). Both the ΔgppX mutant and a ΔPGN_0151 mutant were deficient in monospecies biofilm formation, suggesting a role for the GppX-PGN_0151 regulon in colonization and survival of the organism. PMID:23194602

  3. Deep-sea primary production at the Galapagos hydrothermal vents

    SciTech Connect

    Karl, D.M.; Wirsen, C.O.; Jannasch, H.W.

    1980-03-21

    Dense animal populations surrounding recently discovered hydrothermal vents at the Galapagos Rift sea-floor spreading center, 2550 meters deep, are probably sustained by microbial primary production. Energy in the form of geothermically reduced sulfur compounds emitted from the vents is liberated during oxidation and used for the reduction of carbon dioxide to organic matter by chemosynthetic bacteria.

  4. Forecasting annual aboveground net primary production in the intermountain west

    Technology Transfer Automated Retrieval System (TEKTRAN)

    For many land manager’s annual aboveground net primary production, or plant growth, is a key factor affecting business success, profitability and each land manager's ability to successfully meet land management objectives. The strategy often utilized for forecasting plant growth is to assume every y...

  5. Chapter 12. Net primary production in the shortgrass steppe

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Net primary production (NPP), the amount of carbon or energy fixed by green plants in excess of their respiratory needs, is the fundamental quantity upon which all heterotrophs and the ecosystem processes they are associated with depend. Understanding NPP is therefore a prerequisite to understanding...

  6. CLIMATE CHANGE IMPACTS OF NET PRIMARY PRODUCTION IN CHINA

    EPA Science Inventory

    Several studies have estimated the potential effects of greenhouse gas-induced climate change on various systems using outputs of general circulation models (GCMs). he purpose of this study was to generate comparable estimates of potential impacts on net primary production using ...

  7. STUDIES OF CIRCULATION AND PRIMARY PRODUCTION IN DEEP INLET ENVIRONMENTS

    EPA Science Inventory

    This report summarizes the results of a three-year grant from the U.S. Environmental Protection Agency to investigate various aspects of circulation dynamics and primary production in a deep inlet environment. Throughout the course of the research, special attention has been give...

  8. Quantifying Annual Aboveground Net Primary Production in the Intermountain West

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As part of a larger project, methods were developed to quantify current year growth on grasses, forbs, and shrubs. Annual aboveground net primary production (ANPP) data are needed for this project to calibrate results from computer simulation models and remote-sensing data. Measuring annual ANPP of ...

  9. Estimation of primary dendrite arm spacings in continuous casting products

    SciTech Connect

    Cicutti, C.; Bilmes, P.; Boeri, R.

    1997-09-01

    The proportion of steels produced by continuous casting has grown drastically during the last two decades, increasing to such an extent that in some countries, several grades of steel are exclusively made by this process. Many investigations recognized the significant influence of the solidification structure on the quality of cast products, and pointed out the importance of the development of appropriate tools to predict the microstructure as a function of thermal and physical parameters. The estimation of secondary dendrite arm spacings in continuously cast steel products has received some attention. However, very little effort has been focused on the prediction of primary dendrite arm spacings, to the best of the authors` knowledge. The main objective of this study is to develop simple expressions to estimate the variation of primary dendrite arm spacings through the section of continuous casting steel products.

  10. Investigating the usefulness of satellite-derived fluorescence data in inferring gross primary productivity within the carbon cycle data assimilation system

    NASA Astrophysics Data System (ADS)

    Koffi, E. N.; Rayner, P. J.; Norton, A. J.; Frankenberg, C.; Scholze, M.

    2015-07-01

    Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system.