988 resultados para biomass productivity


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Species composition, cell number and biomass of pico-, nanno- and microalgae were estimated for open waters of the northern subtropical zone of the Pacific Ocean and coastal waters off the North America. Total phytoplankton abundance was also evaluated. Productivity of these waters was newly estimated. Distribution of phytoplankton, its size, and taxonomic groups were compared with chlorophyll distribution estimated during the same cruise. Dissimilarities between distribution of small and large forms result from their adaptation to various peculiarities of the environment.

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Determining the manner in which food webs will respond to environmental changes is difficult because the relative importance of top-down vs. bottom-up forces in controlling ecosystems is still debated. This is especially true in the Arctic tundra where, despite relatively simple food webs, it is still unclear which forces dominate in this ecosystem. Our primary goal was to assess the extent to which a tundra food web was dominated by plant-herbivore or predator--rey interactions. Based on a 17-year (1993-2009) study of terrestrial wildlife on Bylot Island, Nunavut, Canada, we developed trophic mass balance models to address this question. Snow Geese were the dominant herbivores in this ecosystem, followed by two sympatric lemming species (brown and collared lemmings). Arctic foxes, weasels, and several species of birds of prey were the dominant predators. Results of our trophic models encompassing 19 functional groups showed that <10% of the annual primary production was consumed by herbivores in most years despite the presence of a large Snow Goose colony, but that 20-100% of the annual herbivore production was consumed by predators. The impact of herbivores on vegetation has also weakened over time, probably due to an increase in primary production. The impact of predators was highest on lemmings, intermediate on passerines, and lowest on geese and shorebirds, but it varied with lemming abundance. Predation of collared lemmings exceeded production in most years and may explain why this species remained at low density. In contrast, the predation rate on brown lemmings varied with prey density and may have contributed to the high-amplitude, periodic fluctuations in the abundance of this species. Our analysis provided little evidence that herbivores are limited by primary production on Bylot Island. In contrast, we measured strong predator-prey interactions, which supports the hypothesis that this food web is primarily controlled by top-down forces. The presence of allochthonous resources subsidizing top predators and the absence of large herbivores may partly explain the predominant role of predation in this low-productivity ecosystem.

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Subtropical estuaries have received comparatively little attention in the study of nutrient loading and subsequent nutrient processing relative to temperate estuaries. Australian estuaries are particularly susceptible to increased nutrient loading and eutrophication, as 75% of the population resides within 200 km of the coastline. We assessed the factors potentially limiting both biomass and production in one Australian estuary, Moreton Bay, through stoichiometric comparisons of nitrogen (N), phosphorus (P), silicon (Si), and carbon (C) concentrations, particulate compositions, and rates of uptake. Samples were collected over 3 seasons in 1997-1998 at stations located throughout the bay system, including one riverine endmember site. Concentrations of all dissolved nutrients, as well as particulate nutrients and chlorophyll, declined 10-fold to 100-fold from the impacted western embayments to the eastern, more oceanic-influenced regions of the bay during all seasons. For all seasons and all regions, both the dissolved nutrients and particulate biomass yielded N : P ratios < 6 and N : Si ratios < 1. Both relationships suggest strong limitation of biomass by N throughout the bay. Limitation of rates of nutrient uptake and productivity were more complex. Low C : N and C : P uptake ratios at the riverine site suggested light limitation at all seasons, low N : P ratios suggested some degree of N limitation and high N : Si uptake ratios in austral winter suggested Si limitation of uptake during that season only. No evidence of P limitation of biomass or productivity was evident.

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Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

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BACKGROUND: Recombinant protein production is universally employed as a solution to obtain the milligram to gram quantities of a given protein required for applications as diverse as structural genomics and biopharmaceutical manufacture. Yeast is a well-established recombinant host cell for these purposes. In this study we wanted to investigate whether our respiratory Saccharomyces cerevisiae strain, TM6*, could be used to enhance the productivity of recombinant proteins over that obtained from corresponding wild type, respiro-fermentative strains when cultured under the same laboratory conditions. RESULTS: Here we demonstrate at least a doubling in productivity over wild-type strains for three recombinant membrane proteins and one recombinant soluble protein produced in TM6* cells. In all cases, this was attributed to the improved biomass properties of the strain. The yield profile across the growth curve was also more stable than in a wild-type strain, and was not further improved by lowering culture temperatures. This has the added benefit that improved yields can be attained rapidly at the yeast's optimal growth conditions. Importantly, improved productivity could not be reproduced in wild-type strains by culturing them under glucose fed-batch conditions: despite having achieved very similar biomass yields to those achieved by TM6* cultures, the total volumetric yields were not concomitantly increased. Furthermore, the productivity of TM6* was unaffected by growing cultures in the presence of ethanol. These findings support the unique properties of TM6* as a microbial cell factory. CONCLUSIONS: The accumulation of biomass in yeast cell factories is not necessarily correlated with a proportional increase in the functional yield of the recombinant protein being produced. The respiratory S. cerevisiae strain reported here is therefore a useful addition to the matrix of production hosts currently available as its improved biomass properties do lead to increased volumetric yields without the need to resort to complex control or cultivation schemes. This is anticipated to be of particular value in the production of challenging targets such as membrane proteins.

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Antifoams are often added to bioprocesses with little knowledge of their impact on the cells or product. However, it is known that certain antifoams can affect the growth rates of both prokaryotic and eukaryotic organisms in addition to changing surface properties such as lipid content, resulting in changes to permeability. This in turn can be beneficial to a recombinant protein production system for soluble proteins, as has been demonstrated by increased secretion of a-amylase and GFP, or achievement of greater yields of protein due to increased biomass. However, in some cases, certain concentrations of antifoams appear to have a detrimental effect upon cells and protein production, and the effects vary depending upon the protein being expressed. These findings emphasise the importance of optimising and understanding antifoam addition to bioprocesses.

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Biomass, net primary productivity (NPP), foliar elemental content, and demography of Thalassia testudinum were monitored in populations from five sites across Florida Bay beginning in January 2001. Sites were selected to take advantage of the spatial variability in phosphorus (P) availability and salinity climates across the bay. Aboveground biomass and NPP of T. testudinum were determined five to six times annually. Short-shoot demography, belowground biomass, and belowground NPP were assessed from a single destructive harvest at each site and short-shoot cohorts were estimated from leaf scar counts multiplied by site-specific leaf production rates. Biomass, relative growth rate (RGR), and overall NPP were positively correlated with P availability. Additionally, a positive correlation between P availability and the ratio of photosynthetic to non-photosynthetic biomass suggests that T. testudinum increases allocation to aboveground biomass as P availability increases. Population turnover increased with P availability, evident in positive correlations of recruitment and mortality rates with P availability. Departures from seasonally modeled estimates of RGR were found to be influenced by salinity, which depressed RGR when below 20 psu or above 40 psu. Freshwater management in the headwaters of Florida Bay will alter salinity and nutrient climates. It is becoming clear that such changes will affect T. testudinum, with likely feedbacks on ecosystem structure, function, and habitat quality.

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Physiological processes and local-scale structural dynamics of mangroves are relatively well studied. Regional-scale processes, however, are not as well understood. Here we provide long-term data on trends in structure and forest turnover at a large scale, following hurricane damage in mangrove ecosystems of South Florida, U.S.A. Twelve mangrove vegetation plots were monitored at periodic intervals, between October 1992 and March 2005. Mangrove forests of this region are defined by a −1.5 scaling relationship between mean stem diameter and stem density, mirroring self-thinning theory for mono-specific stands. This relationship is reflected in tree size frequency scaling exponents which, through time, have exhibited trends toward a community average that is indicative of full spatial resource utilization. These trends, together with an asymptotic standing biomass accumulation, indicate that coastal mangrove ecosystems do adhere to size-structured organizing principles as described for upland tree communities. Regenerative dynamics are different between areas inside and outside of the primary wind-path of Hurricane Andrew which occurred in 1992. Forest dynamic turnover rates, however, are steady through time. This suggests that ecological, more-so than structural factors, control forest productivity. In agreement, the relative mean rate of biomass growth exhibits an inverse relationship with the seasonal range of porewater salinities. The ecosystem average in forest scaling relationships may provide a useful investigative tool of mangrove community biomass relationships, as well as offer a robust indicator of general ecosystem health for use in mangrove forest ecosystem management and restoration.

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.

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Macro- and meiobenthic abundance and biomass as well as metabolic activity (respiration, ETS activity) have been studied along a transect ranging from 130 to 3000 m water depth off northern Morocco (35° N) during "Meteor" cruise No. 53 (1980). The distribution of chloroplastic pigment concentration (chlorophyll a, pheophytins) in the sediment has been investigated as a measure of sedimented primary organic matter. High chloroplastic pigment concentrations were found on the shelf and around the shelf break, but values declined rapidly between 200 and 600 m depth. Below 1200 m pigment concentrations remained at a relatively uniform low level. Macrobenthic abundance and biomass (wet weight) decreased with increasing water depth and with distance from the shore. Significant changes occurred between the shelf and upper slope and below 2000 m depth. Meiobenthic abundance and biomass (ash free dry weight) followed the same general pattern, but changes were found below 400 and 800 m depth. In the depth range of 1200 to 3000 m values differ only slightly. Meiofauna abundance and biomass show a good correlation with the sedimentary chloroplastic pigment concentrations. Respiratory activity of sediment cores, measured by a shipboard technique at ambient temperatures, decreased with water depth and shows a good correlation with the pigment concentrations. ETS activity was highest on the shelf and decreased with water depth, with significant changes between 200 and 400 m, and below 1200 m depth, respectively. Activity was generally highest in the top 5 cm of the sediment and was measurable, at all stations, down to 15 cm sediment depth. Shelf and upper slope stations exhibited a vertical distribution pattern of ETS activity in the sediment column, different from that of deeper stations. The importance of biological activity measurements as an estimate of productivity is discussed. To prove the thesis that differences in benthic abundance, biomass and activity reflect differences in pelagic surface primary production, in the case of the NW-African coast caused by different upwelling intensities, the values from 35° N were compared with data from 21° N (permanent upwelling activity) and 17° N (ca. 9 months upwelling per year). On the shelf and upper slope (< 500 m) hydrographical conditions (currents, internal waves) influence the deposition of organic matter and cause a biomass minimum between 200 and 400 m depth in some regions. But, in general, macrobenthic abundance and biomass increases with enhanced upwelling activity and reaches a maximum in the area off Cape Blanc (21° N). On the shelf and in the shelf break region meiofauna densities are higher at 35° N in comparison to 21° N; but in contrast to the decreasing meiofauna abundance with increasing water depth at 35° N, an abundance maximum between 400 and 1200 m depth is formed in the Cape Blanc region; this maximum coincides with the maximum of sedimentary chloroplastic pigment equivalents. The comparison of ETS activities between 35° N and 21° N shows on the shelf activity at 21° N is up to 14 times higher and on the slope 4-9 times higher, which demonstrates that benthic activity responds to the surface productivity regime.

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This data set comprises time series of aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of several experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). Aboveground community biomass was normally harvested twice a year just prior to mowing (during peak standing biomass twice a year, generally in May and August; in 2002 only once in September) on all experimental plots in the Jena Experiment. This was done by clipping the vegetation at 3 cm above ground in up to four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned by random selection of new coordinates every year within the core area of the plots. The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship. The following series of datasets are contained in this collection: 1. Plant biomass form the Main Experiment: In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). 2. Plant biomass from the Dominance Experiment: In the Dominance Experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). 3. Plant biomass from the monoculture plots: In the monoculture plots the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species like the other experiments in May 2002. All plots were maintained by bi-annual weeding and mowing.

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths.

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This data set contains aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the dominance experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the dominance experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 plant species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in May and August 2008 on all experimental plots of the dominance experiment. This was done by clipping the vegetation at 3 cm above ground in two rectangles of 0.2 x 0.5 m per experimental plot. The location of these rectangles was assigned by random selection of coordinates within the central area of the plots (excluding an outer edge of 50cm). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material, and remaining plant material that could not be assigned to any category. All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The mean of both samples per plot and the individual measurements are provided in the data file. Overall, analyses of the community biomass data have identified species richness and the presence of particular species as an important driver of a positive biodiversity-productivity relationship.

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This data set contains aboveground community biomass in 2009 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2009 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in three rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for all biomass measures are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.