186 research outputs found

    Determination of uranium and zirconium by flow injection analysis

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    As an integral part of chemical quality control of nuclear materials a method for determination of uranium and zirconium, in a mixture is presented. A simple, cheap, selective and quantitative Flow Injection Analysis (FIA) system was developed. Zirconium and uranium were determinate in presence of each other and no prior separation was needed. Arsenazo III was used as a colorimetric reagent and parameters such as acidity and reagents concentration were studied and optimized. An analytical throughput of 30 sample determination per hour was obtained

    Direct evidence for phosphorus limitation on Amazon forest productivity

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    The productivity of rainforests growing on highly weathered tropical soils is expected to be limited by phosphorus availability1. Yet, controlled fertilization experiments have been unable to demonstrate a dominant role for phosphorus in controlling tropical forest net primary productivity. Recent syntheses have demonstrated that responses to nitrogen addition are as large as to phosphorus2, and adaptations to low phosphorus availability appear to enable net primary productivity to be maintained across major soil phosphorus gradients3. Thus, the extent to which phosphorus availability limits tropical forest productivity is highly uncertain. The majority of the Amazonia, however, is characterized by soils that are more depleted in phosphorus than those in which most tropical fertilization experiments have taken place2. Thus, we established a phosphorus, nitrogen and base cation addition experiment in an old growth Amazon rainforest, with a low soil phosphorus content that is representative of approximately 60% of the Amazon basin. Here we show that net primary productivity increased exclusively with phosphorus addition. After 2 years, strong responses were observed in fine root (+29%) and canopy productivity (+19%), but not stem growth. The direct evidence of phosphorus limitation of net primary productivity suggests that phosphorus availability may restrict Amazon forest responses to CO2 fertilization4, with major implications for future carbon sequestration and forest resilience to climate change.The authors acknowledge funding from the UK Natural Environment Research Council (NERC), grant number NE/L007223/1. This is publication 850 in the technical series of the BDFFP. C.A.Q. acknowledges the grants from Brazilian National Council for Scientific and Technological Development (CNPq) CNPq/LBA 68/2013, CNPq/MCTI/FNDCT no. 18/2021 and his productivity grant. C.A.Q., H.F.V.C., F.D.S., I.A., L.F.L., E.O.M. and S.G. acknowledge the AmazonFACE programme for financial support in cooperation with Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Institute of Amazonian Research as part of the grants CAPES-INPA/88887.154643/2017-00 and 88881.154644/2017-01. T.F.D. acknowledges funds from FundacAo de Amparo a Pesquisa do Estado de SAo Paulo (FAPESP), grant 2015/50488-5, and the Partnership for Enhanced Engagement in Research (PEER) programme grant AID-OAA-A-11-00012. L.E.O.C.A. thanks CNPq (314416/2020-0)

    Tree height integrated into pantropical forest biomass estimates

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    Copyright © 2012 European Geosciences Union. This is the published version available at http://www.biogeosciences.net/9/3381/2012/bg-9-3381-2012.htmlAboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation
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