Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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 Gamma-A nifH genes abundance, computed from a collection of source data sets.

Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

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 nitrogen fixation rates, computed from a collection of source data sets.

Influence of Nitrogen and Sink Competition on Shoot Growth of Poplar

Terrestrial and oceanic biomass carbon sinks help reduce anthropogenic CO2 emissions and mitigate the long-term effect of increasing atmospheric CO2. Woody plants have large carbon pools because of their long residence time, however N availability can negatively impact tree responses to elevated CO2. Seasonal cycling of internal N in trees is a component that contributes to fitness especially in N limited environments. It involves resorption from senescing leaves of deciduous trees and storage as vegetative storage proteins (VSP) in perennial organs. Populus is a model organism for tree biology that efficiently recycles N. Bark storage proteins (BSP) are the most abundant VSP that serves as seasonal N reserves. Here I show how poplar growth is influenced by N availability and how growth is influenced by shoot competition for stored N reserves. I also provide data that indicates that auxin mediates BSP catabolism during renewed shoot growth. Understanding the components of N accumulation, remobilization and utilization can provide insights leading to increasing N use efficiency (NUE) of perennial plants.

Straw and early nitrogen fertilization affect soil properties and upland rice yield.

The presence of cover crop straw and early application of total N at sowing may provide significant changes in the microbial population, reflecting on the N dynamics in the soil and in upland rice plants. This study aimed at determining the effect of the early application of nitrogen doses as mineral N and microbial biomass carbon in the soil, as well as in the activity of nitrate reductase, and grain yield of upland rice plants cultivated under notillage system (NTS). A randomized blocks design, in a split-plot scheme, with four replications, was used. The treatments consisted of N doses (0 kg ha-1, 40 kg ha-1, 80 kg ha-1 and 120 kg ha-1) and the presence or absence of U. brizantha cover straw. Maintaining the straw on the soil surface reduces the ammonium levels and increases the microbial biomass carbon content of the soil. The application of increasing doses of N in the soil provides increases in the levels of nitrate and ammonium in the soil up to 28 days after emergence. The activity of the nitrate reductase enzyme in the plants increases and the contents of ammonium and nitrate in the soil decrease with the crop development. The number of panicles and grain yield of upland rice increase with the increase of the nitrogen fertilization, but decrease in the presence of U. brizantha straw. Thus, it is recommend the use of early N fertilization in upland rice crop.

Forest inventory-based large-scale forest biomass and carbon budget assessment: new enhanced methods and use of remote sensing for verification

In recent years, concern has arisen over the effects of increasing carbon dioxide (CO2) in the earth's atmosphere due to the burning of fossil fuels. One way to mitigate increase in atmospheric CO2 concentration and climate change is carbon sequestration to forest vegeta-tion through photosynthesis. Comparable regional scale estimates for the carbon balance of forests are therefore needed for scientific and political purposes. The aim of the present dissertation was to improve methods for quantifying and verifying inventory-based carbon pool estimates of the boreal forests in the mineral soils. Ongoing forest inventories provide a data based on statistically sounded sampling for estimating the level of carbon stocks and stock changes, but improved modelling tools and comparison of methods are still needed. In this dissertation, the entire inventory-based large-scale forest carbon stock assessment method was presented together with some separate methods for enhancing and comparing it. The enhancement methods presented here include ways to quantify the biomass of understorey vegetation as well as to estimate the litter production of needles and branches. In addition, the optical remote sensing method illustrated in this dis-sertation can be used to compare with independent data. The forest inventory-based large-scale carbon stock assessment method demonstrated here provided reliable carbon estimates when compared with independent data. Future ac-tivity to improve the accuracy of this method could consist of reducing the uncertainties regarding belowground biomass and litter production as well as the soil compartment. The methods developed will serve the needs for UNFCCC reporting and the reporting under the Kyoto Protocol. This method is principally intended for analysts or planners interested in quantifying carbon over extensive forest areas.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Phytoplankton carbon fixation chlorophyll-biomass and diagnostic pigments in the Atlantic Ocean

We have made daily measurements of phytoplankton pigments, size-fractionated (<2 and >2-μm) carbon fixation and chlorophyll-a concentration during four Atlantic Meridional Transect (AMT) cruises in 2003–04. Surface rates of carbon fixation ranged from <0.2-mmol C m−3 d−1 in the subtropical gyres to 0.2–0.5-mmol C m−3 d−1 in the tropical equatorial Atlantic. Significant intercruise variability was restricted to the subtropical gyres, with higher chlorophyll-a concentrations and carbon fixation in the subsurface chlorophyll maximum during spring in either hemisphere. In surface waters, although picoplankton (<2-μm) represented the dominant fraction in terms of both carbon fixation (50–70%) and chlorophyll-a (80–90%), nanoplankton (>2-μm) contributions to total carbon fixation (30–50%) were higher than to total chlorophyll-a (10–20%). However, in the subsurface chlorophyll maximum picoplankton dominated both carbon fixation (70–90%) and chlorophyll-a (70–90%). Thus, in surface waters chlorophyll-normalised carbon fixation was 2–3 times higher for nanoplankton and differences in picoplankton and nanoplankton carbon to chlorophyll-a ratios may lead to either higher or similar growth rates. These low chlorophyll-normalised carbon fixation rates for picoplankton may also reflect losses of fixed carbon (cell leakage or respiration), decreases in photosynthetic efficiency, grazing losses during the incubations, or some combination of all these. Comparison of nitrate concentrations in the subsurface chlorophyll maximum with estimates of those required to support the observed rates of carbon fixation (assuming Redfield stoichiometry) indicate that primary production in the chlorophyll maximum may be light rather than nutrient limited.

Flux and turnover of fixed carbon in soil microbial biomass of limed and unlimed plots of an upland grassland ecosystem

The influence of liming on rhizosphere microbial biomass C and incorporation of root exudates was studied in the field by in situ pulse labelling of temperate grassland vegetation with (13)CO(2) for a 3-day period. In plots that had been limed (CaCO(3) amended) annually for 3 years, incorporation into shoots and roots was, respectively, greater and lower than in unlimed plots. Analysis of chloroform-labile C demonstrated lower levels of (13)C incorporation into microbial biomass in limed soils compared to unlimed soils. The turnover of the recently assimilated (13)C compounds was faster in microbial biomass from limed than that from unlimed soils, suggesting that liming increases incorporation by microbial communities of root exudates. An exponential decay model of (13)C in total microbial biomass in limed soils indicated that the half-life of the tracer within this carbon pool was 4.7 days. Results are presented and discussed in relation to the absolute values of (13)C fixed and allocated within the plant-soil system.

Free atmospheric CO2 enrichment increased above ground biomass but did not affect symbiotic N2-fixation and soil carbon dynamics in a mixed deciduous stand in Wales

Through increases in net primary production (NPP), elevated CO2 is hypothesizes to increase the amount of plant litter entering the soil. The fate of this extra carbon on the forest floor or in mineral soil is currently not clear. Moreover, increased rates of NPP can be maintained only if forests can escape nitrogen limitation. In a Free atmospheric CO2 Enrichment (FACE) experiment near Bangor, Wales, 4 ambient CO2 and 4 FACE plots were planted with patches of Betula pendula, Alnus glutinosa and Fagus sylvatica on a former arable field. Four years after establishment, only a shallow L forest floor litter layer had formed due to intensive bioturbation. Total soil C and N contents increased irrespective of treatment and species as a result of afforestation. We could not detect an additional C sink in the soil, nor were soil C stabilization processes affected by FACE. We observed a decrease of leaf N content in Betula and Alnus under FACE, while the soil C/N ratio decreased regardless of CO2 treatment. The ratio of N taken up from the soil and by N2-fixation in Alnus was not affected by FACE. We infer that increased nitrogen use efficiency is the mechanism by which increased NPP is sustained under elevated CO2 at this site.

Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial–interglacial contrast

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial–interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies – that is, differences from the pre-industrial (PI) control climate – from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0–1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.