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      Impacts of urea deep placement on nitrous oxide and nitric oxide emissions from rice fields in Bangladesh

      , , , , , , , ,
      Geoderma
      Elsevier BV

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          Small sample inference for fixed effects from restricted maximum likelihood.

          Restricted maximum likelihood (REML) is now well established as a method for estimating the parameters of the general Gaussian linear model with a structured covariance matrix, in particular for mixed linear models. Conventionally, estimates of precision and inference for fixed effects are based on their asymptotic distribution, which is known to be inadequate for some small-sample problems. In this paper, we present a scaled Wald statistic, together with an F approximation to its sampling distribution, that is shown to perform well in a range of small sample settings. The statistic uses an adjusted estimator of the covariance matrix that has reduced small sample bias. This approach has the advantage that it reproduces both the statistics and F distributions in those settings where the latter is exact, namely for Hotelling T2 type statistics and for analysis of variance F-ratios. The performance of the modified statistics is assessed through simulation studies of four different REML analyses and the methods are illustrated using three examples.
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            Global metaanalysis of the nonlinear response of soil nitrous oxide (N2O) emissions to fertilizer nitrogen.

            Nitrous oxide (N2O) is a potent greenhouse gas (GHG) that also depletes stratospheric ozone. Nitrogen (N) fertilizer rate is the best single predictor of N2O emissions from agricultural soils, which are responsible for ∼ 50% of the total global anthropogenic flux, but it is a relatively imprecise estimator. Accumulating evidence suggests that the emission response to increasing N input is exponential rather than linear, as assumed by Intergovernmental Panel on Climate Change methodologies. We performed a metaanalysis to test the generalizability of this pattern. From 78 published studies (233 site-years) with at least three N-input levels, we calculated N2O emission factors (EFs) for each nonzero input level as a percentage of N input converted to N2O emissions. We found that the N2O response to N inputs grew significantly faster than linear for synthetic fertilizers and for most crop types. N-fixing crops had a higher rate of change in EF (ΔEF) than others. A higher ΔEF was also evident in soils with carbon >1.5% and soils with pH <7, and where fertilizer was applied only once annually. Our results suggest a general trend of exponentially increasing N2O emissions as N inputs increase to exceed crop needs. Use of this knowledge in GHG inventories should improve assessments of fertilizer-derived N2O emissions, help address disparities in the global N2O budget, and refine the accuracy of N2O mitigation protocols. In low-input systems typical of sub-Saharan Africa, for example, modest N additions will have little impact on estimated N2O emissions, whereas equivalent additions (or reductions) in excessively fertilized systems will have a disproportionately major impact.
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              Soils, a sink for N2O? A review

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                Author and article information

                Journal
                Geoderma
                Geoderma
                Elsevier BV
                00167061
                December 2015
                December 2015
                : 259-260
                :
                : 370-379
                Article
                10.1016/j.geoderma.2015.06.001
                587a2b7d-3213-47a6-a909-934a17e62f85
                © 2015
                History

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