Nitrogen mineralisation in sugarcane soils in Queensland, Australia: I. evaluation of soil tests for predicting nitrogen mineralisation

Soil Research ◽  
2019 ◽  
Vol 57 (7) ◽  
pp. 738 ◽  
Author(s):  
D. E. Allen ◽  
P. M. Bloesch ◽  
T. G. Orton ◽  
B. L. Schroeder ◽  
D. M. Skocaj ◽  
...  
Keyword(s):  
Soil Properties ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Co2 Production ◽  
Organic N ◽  
Model Parameters ◽  
Nitrogen Mineralisation ◽  
Short Term ◽  
Available N

We explored soil properties as indices of mineralisable nitrogen (N) in sugarcane soils and whether we could increase the accuracy of predicting N mineralisation during laboratory incubations. Utilising historical data in combination with samples collected during 2016, we: (i) measured mineralised N over the course of short-term (14 days) and long-term (301 days) laboratory incubations; (ii) compared models representing mineralisation; then (iii) related model parameters to measured soil properties. We found measures representing the labile organic N pool (Hydrolysable NaOH organic N; amino sugar Illinois soil N test) best related to short-term mineralised N (R2 of 0.50–0.57, P < 0.001), while measures of CO2 production (3, 7, 10 and 14 days) best related to longer-term mineralised N (R2 of 0.75–0.84, P < 0.001). Indices were brought together to model the active and slow pools of a two-pool mineralisation model in the statistical framework of a mixed-effects model. Of the models that relied on measurement of one soil property, cumulative CO2 production (7 days) performed the best when considering all soil types; in a cross-validation test, this model gave an external R2 of 0.77 for prediction of the 301-day mineralised N. Since the mixed-effects model accounts for the various sources of uncertainty, we suggest this approach as a framework for prediction of in-field available N, with further measurement of long-term mineralised N in other soils to strengthen predictive certainty of these soil indices.

Assessing the Effect of Mansionization on Suburban Single-Family House Sales Prices

2019 ◽  
pp. 0739456X1983315
Author(s):  
Suzanne Lanyi Charles
Keyword(s):  
Random Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Single Family ◽  
Socioeconomic Characteristics ◽  
House Values ◽  
Crossed Random Effects ◽  
Family House

Using observed single-family house sales in the inner-ring suburbs of Chicago from 2010 through 2017, this paper uses a multilevel mixed-effects model with crossed random effects to estimate the effect that millennium mansions—new, large single-family houses—have on the sales prices of nearby single-family houses. Controlling for property, sale timing, and surrounding neighborhood socioeconomic characteristics, the study finds that mansionization is associated with an increase in the sales prices of neighboring houses. Long-term residents of a neighborhood undergoing mansionization should not fear a decrease in their house values; however, decreases in neighborhood affordability may result in exclusionary displacement.

Basic Study on Creep Properties of Eucalyptus Wood

2014 ◽  
Vol 911 ◽  
pp. 232-237
Author(s):  
Yuan Rong Ma ◽  
Xian Jun Li ◽  
Biao Deng ◽  
Ying She Luo
Keyword(s):  
Model Parameters ◽  
Short Term ◽  
Basic Study ◽  
Burger Model ◽  
Creep Properties ◽  
Eucalyptus Plantation ◽  
Moisture Contents ◽  
Creep Curves ◽  
Term Creep

The study tested the short-term bending creep curves of Eucalyptus Plantation Wood under different loads, moisture contents and temperatures, analyzed the influence of load, moisture content and temperature on creep of Eucalyptus. Guided by the rheological theory, the study adopted the Burger rheological model to do the curve fitting and solved the model parameters. A defect found from Burger model in simulating long-term creep properties of wood was preliminary discussed and remedied. The equivalence of creep test and relaxation one was discussed.

Soil responses to topsoil replacement depth and organic amendments in wellsite reclamation

2005 ◽  
Vol 85 (2) ◽  
pp. 307-317 ◽  
Author(s):  
Francis J. Larney ◽  
Olalekan O. Akinremi ◽  
Reynald L. Lemke ◽  
Vasile E. Klaassen ◽  
H. Henry Janzen
Keyword(s):  
Soil Properties ◽  
Nitrate Nitrogen ◽  
Organic Amendments ◽  
Soil Surface ◽  
Triticum Aestivum L ◽  
Organic N ◽  
Medicago Sativa L ◽  
Soil Responses ◽  
Changes In Soil Properties

Changes in soil properties reflect the success or failure of reclamation practices on abandoned wellsites. We examined the effect on soil properties of four (0, 50, 100 and 150%) topsoil replacement depths (TRD) and five amendment treatments [compost, manure, wheat (Triticum aestivum L.) straw, alfalfa (Medicago sativa L.) hay, check] aimed at reclaiming three wellsites (Strathmore, Hesketh and Rosedale) in southcentral Alberta. TRD treatment differences were consistent across all wellsites, with 30 to 32% higher soil organic carbon (SOC) on the 150% TRD compared to the 0% TRD. Initially, the alfalfa treatment showed higher levels of nitrate-nitrogen (e.g., 26 mg kg-1 vs. 3 to 7 mg kg-1 for the other amendment treatments in the 15- to 30-cm depth at Strathmore in fall 1998), which was related to its rapid breakdown and mineralization of organic N. After 40 mo (June 1997-October 2000), the average amounts (n = 3 wellsites) of added C conserved near the soil surface were: compost (65 ±10% SE) > manure (45 ±16% SE) > alfalfa (28 ±11% SE) > straw (23 ± 6% SE). Our results show that organic amendments play an important role in improving soil properties related to long-term productivity of reclaimed wellsites, especially where topsoil is scarce or absent. Key words: Wellsite reclamation, topsoil depth, organic amendments, soil quality

The effects of long-term applications of inorganic nitrogen fertilizer on soil nitrogen in the Broadbalk Wheat Experiment

1996 ◽  
Vol 127 (3) ◽  
pp. 347-363 ◽  
Author(s):  
M. J. Glendining ◽  
D. S. Powlson ◽  
P. R. Poulton ◽  
N. J. Bradbury ◽  
D. Palazzo ◽  
...  
Keyword(s):  
N Mineralization ◽  
Inorganic Nitrogen ◽  
Organic N ◽  
Soil N ◽  
Fertilizer N ◽  
Short Term ◽  
N Content ◽  
Total Soil ◽  
Total Soil N

SUMMARYThe Broadbalk Wheat Experiment at Rothamsted (UK) includes plots given the same annual applications of inorganic nitrogen (N) fertilizer each year since 1852 (48, 96 and 144 kg N/ha, termed N1 N2 and N3 respectively). These very long-term N treatments have increased total soil N content, relative to the plot never receiving fertilizer N (N0), due to the greater return of organic N to the soil in roots, root exudates, stubble, etc (the straw is not incorporated). The application of 144 kg N/ha for 135 years has increased total soil N content by 21%, or 570 kg/ha (0–23 cm). Other plots given smaller applications of N for the same time show smaller increases; these differences were established within 30 years. Increases in total soil N content have been detected after 20 years in the plot given 192 kg N/ha since 1968 (N4).There was a proportionally greater increase in N mineralization. Crop uptake of mineralized N was typically 12–30 kg N/ha greater from the N3 and N4 treatments than the uptake of c. 30 kg N/ha from the N0 treatment. Results from laboratory incubations show the importance of recently added residues (roots, stubble, etc) on N mineralization. In short-term (2–3 week) incubations, with soil sampled at harvest, N mineralization was up to 60% greater from the N3 treatment than from N0. In long-term incubations, or in soil without recently added residues, differences between long-term fertilizer treatments were much less marked. Inputs of organic N to the soil from weeds (principally Equisetum arvense L.) to the N0–N2 plots over the last few years may have partially obscured any underlying differences in mineralization.The long-term fertilizer treatments appeared to have had no effect on soil microbial biomass N or carbon (C) content, but have increased the specific mineralization rate of the biomass (defined as N mineralized per unit of biomass).Greater N mineralization will also increase losses of N from the system, via leaching and gaseous emissions. In December 1988 the N3 and N4 plots contained respectively 14 and 23 kg/ha more inorganic N in the profile (0–100 cm) than the N0 plot, due to greater N mineralization. These small differences are important as it only requires 23 kg N/ha to be leached from Broadbalk to increase the nitrate concentration of percolating water above the 1980 EC Drinking Water Quality Directive limit of 11·3mgN/l.The use of fertilizer N has increased N mineralization due to the build-up of soil organic N. In addition, much of the organic N in Broadbalk topsoil is now derived from fertilizer N. A computer model of N mineralization on Broadbalk estimated that after applying 144 kg N/ha for 140 years, up to half of the N mineralized each year was originally derived from fertilizer N.In the short-term, the amount of fertilizer N applied usually has little direct effect on losses of N over winter. In most years little fertilizer-derived N remains in Broadbalk soil in inorganic form at harvest from applications of up to 192 kg N/ha. However, in two very dry years (1989 and 1990) large inorganic N residues remained at harvest where 144 and 192 kg N/ha had been applied, even though the crop continued to respond to fertilizer N, up to at least 240 kg N/ha.

scholarly journals Modelling the Tree Height, Crown Base Height, and Effective Crown Height of Pinus koraiensis Plantations Based on Knot Analysis

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1778
Author(s):  
Wancai Zhu ◽  
Zhaogang Liu ◽  
Weiwei Jia ◽  
Dandan Li
Keyword(s):  
Tree Height ◽  
Information Criterion ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Pinus Koraiensis ◽  
Tree Level ◽  
Model Parameters ◽  
Crown Height ◽  
Crown Base Height ◽  
Pruning Intensity

Taking 1735 Pinus koraiensis knots in Mengjiagang Forest Farm plantations in Jiamusi City, Heilongjiang Province as the research object, a dynamic tree height, effective crown height, and crown base height growth model was developed using 349 screened knots. The Richards equation was selected as the basic model to develop a crown base height and effective crown height nonlinear mixed-effects model considering random tree-level effects. Model parameters were estimated with the non-liner mixed effect model (NLMIXED) Statistical Analysis System (SAS) module. The akaike information criterion (AIC), bayesian information criterion (BIC), −2 Log likelihood (−2LL), adjusted coefficient (Ra2), root mean square error (RMSE), and residual squared sum (RSS) values were used for the optimal model selection and performance evaluation. When tested with independent sample data, the mixed-effects model tree effects-considering outperformed the traditional model regarding their goodness of fit and validation; the two-parameter mixed-effects model outperformed the one-parameter model. Pinus koraiensis pruning times and intensities were calculated using the developed model. The difference between the effective crown and crown base heights was 1.01 m at the 15th year; thus, artificial pruning could occur. Initial pruning was performed with a 1.01 m intensity in the 15th year. Five pruning were required throughout the young forest period; the average pruning intensity was 1.46 m. The pruning interval did not differ extensively in the half-mature forest period, while the intensity decreased significantly. The final pruning intensity was only 0.34 m.

scholarly journals Handling Geological and Economic Uncertainties in Balancing Short-Term and Long-Term Objectives in Waterflooding Optimization

SPE Journal ◽  
2017 ◽  
Vol 22 (04) ◽  
pp. 1313-1325 ◽  
Author(s):  
M.. Mohsin Siraj ◽  
Paul M. Van den Hof ◽  
Jan-Dirk Jansen
Keyword(s):  
Net Present Value ◽  
Optimal Solution ◽  
Cycle Performance ◽  
Hierarchical Optimization ◽  
Model Parameters ◽  
Economic Uncertainty ◽  
Economic Optimization ◽  
Short Term ◽  
The Mean

Summary Model-based economic optimization of oil production has a significant scope to increase financial life-cycle performance. The net-present-value (NPV) objective in this optimization, because of its nature, focuses on long-term gains, whereas short-term production is not explicitly addressed. At the same time, the achievable NPV is highly uncertain because of strongly varying economic conditions and limited knowledge of the reservoir-model parameters. The prime focus of this work is to develop optimization strategies that balance both long-term and short-term economic objectives and also offer robustness to the long-term NPV. An earlier robust hierarchical optimization method honoring geological uncertainty with robust long-term and short-term NPV objectives serves as a starting base of this work. We address the issue of extending this approach to include economic uncertainty and aim to analyze how the optimal solution reduces the uncertainty in the achieved average NPV. An ensemble of varying oil prices is used to model economic uncertainty with average NPVs as robust objectives in the hierarchical approach. A weighted-sum approach is used with the same objectives to quantify the effect of uncertainty. To reduce uncertainty, a mean-variance-optimization (MVO) objective is then considered to maximize the mean and also minimize the variance. A reduced effect of uncertainty on the long-term NPV is obtained compared with the uncertainty in the mean-optimization (MO) objectives. Last, it is investigated whether, because of the better handling of uncertainty in MVO, a balance between short-term and long-term gains can be naturally obtained by solving a single-objective MVO. Simulation examples show that a faster NPV buildup is naturally achieved by choosing appropriate weighting of the variance term in the MVO objective.

Soil warming leads to an up-regulation of genes involved in the decomposition of organic N in a subarctic grassland

2020 ◽  
Author(s):  
Joana Séneca ◽  
Andrea Söllinger ◽  
Alexander Tveit ◽  
Petra Pjevac ◽  
Craig Herbold ◽  
...  
Keyword(s):  
Gene Expression ◽  
Organic Matter ◽  
Soil Samples ◽  
Organic N ◽  
Organic Substrates ◽  
Turnover Rates ◽  
Short Term ◽  
N Losses ◽  
Microbial Turnover

<p>Soil microorganisms control the breakdown (depolymerization) of high molecular weight organic matter in soil and its mineralization and release as CO<sub>2</sub> to the atmosphere. The enzymatic reactions involved in these steps are known to be temperature sensitive. Therefore, increasing global temperatures are expected to accelerate microbial activity and ecosystem processes and stimulate further CO<sub>2</sub> emissions, potentially causing a positive feedback to climate change. On the other hand, higher turnover rates demand an increased amount of energy allocated for growth, enzyme production and maintenance, which can progressively deplete soils from substrate, forcing a reduction of microbial biomass and/or activity and a higher metabolic investment in resource acquisition.</p><p>The response of ecosystems to warming has been shown to be related with its duration and magnitude. In this study, we analyzed soils from long-term (>50 years) and short-term (8 years) warmed plots at the natural geothermal warming experiment ForHot (https://forhot.is), located in a sub-arctic grassland in Iceland. Previous studies at this warming experiment have shown an accelerated C cycle in response to warming, with decreased soil carbon stocks, and higher rates of decomposition of labile and recalcitrant organic matter, regardless of the warming duration. In addition to carbon losses, increased N losses from soils were found, but no change in the N content of the vegetation along the temperature gradient. Additionally, both ammonification and nitrification rates were shown to increase under warming, pointing to higher N losses from warmed soils.</p><p>In this study, we tested the hypothesis that under warming microorganisms become progressively limited in organic substrates, leading to a higher microbial investment in organic N decomposing enzymes to mine the existing organic N sources present in their surroundings. This hypothesis is based on previous data, that showed that microbial turnover was increased in the warmed plots. Under this assumption, we expected to observe higher expression levels of genes coding for organic N mining extracellular enzymes in warmed plots.</p><p>We analyzed the metatranscriptome from a total of 16 soil samples representative of ambient (n=4) and +6°C warmed (n=4) soils, for both grassland types. Additionally, we sequenced the metagenomes of 4 soil samples, representative of each condition, to allow for transcript mapping and differential gene expression analysis.</p><p>We used Hidden Markov models to screen the assembled metatranscriptomes for genes involved in the degradation of chitin, proteinaceous compounds, nucleic acids and microbial cell walls. The subcellular location and presence/absence of signal peptides was assessed with Psort and SignalP to discriminate transcripts involved in internal recycling from those targeted for secretion. First results show a general up-regulation of all transcripts involved in organic N degradation in the grassland subjected to long-term warming, whereas this trend is less clear in the short-term warmed grassland. Further work includes cross-referencing gene expression patterns with potential changes in active community composition.</p><p>We conclude that an acceleration in microbial turnover rates in response to warming is coupled to a higher investment in N acquisition enzymes, as indicated by an up-regulation of genes involved in upstream processes of organic N degradation.</p>

A note on estimating single-class piecewise mixed-effects models with unknown change points

2018 ◽  
Vol 42 (5) ◽  
pp. 518-524 ◽  
Author(s):  
Nidhi Kohli ◽  
Yadira Peralta ◽  
Cengiz Zopluoglu ◽  
Mark L. Davison
Keyword(s):  
Bayesian Estimation ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Mixed Effects Models ◽  
Change Points ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Residual Variance ◽  
Monte Carlo Simulation Study ◽  
Ml Estimation

Piecewise mixed-effects models are useful for analyzing longitudinal educational and psychological data sets to model segmented change over time. These models offer an attractive alternative to commonly used quadratic and higher-order polynomial models because the coefficients obtained from fitting the model have meaningful substantive interpretation. The current study thus focuses on the estimation of piecewise mixed-effects model with unknown random change points using maximum likelihood (ML) as described in Du Toit and Cudeck (2009). Previous simulation work (Wang & McArdle, 2008) showed that Bayesian estimation produced reliable parameter estimates for the piecewise model in comparison to frequentist procedures (i.e., first-order Taylor expansion and the adaptive Gaussian quadrature) across all simulation conditions. In the current article a small Monte Carlo simulation study was conducted to assess the performance of the ML approach, a frequentist procedure, and the Bayesian approach for fitting linear–linear piecewise mixed-effects model. The obtained findings show that ML estimation approach produces reliable and accurate estimates under the conditions of small residual variance of the observed variables, and that the size of the residual variance had the most impact on the quality of model parameter estimates. Second, neither ML nor Bayesian estimation procedures performed well under all manipulated conditions with respect to the accuracy and precision of the estimated model parameters.

The Predicted Behavior of Griesgletscher, Wallis, Switzerland, and its Possible Threat to a Nearby Dam (Abstract only)

1983 ◽  
Vol 4 ◽  
pp. 295 ◽  
Author(s):  
Robert Bindschadler
Keyword(s):  
Climatic Changes ◽  
Model Parameters ◽  
Present Climate ◽  
Short Term ◽  
Additional Increase ◽  
Temperature Changes ◽  
Hydroelectric Dam ◽  
Glacier Flow ◽  
Mean Annual Air Temperature

The behavior of Griesgletscher, Switzerland, is studied by application of a numerical model of temperate glacier flow. The analysis addresses the possible danger posed to a hydroelectric dam which is 600 m from the calving terminus of the glacier. Model parameters are adjusted to fit data collected over eleven years. A calving law relating the calving flux to the water depth at the front provides a good fit of the data. Assuming a continuation of the present climate, the terminus is predicted to retreat 200 m over the next forty years, followed by an advance of 150 m lasting several centuries. Numerous experimental climate alterations show that the dam will not be threatened by short-term climatic changes. A long-term mass-balance increase of 0.12 m of ice per year (or a drop of 0.2°C in mean annual air temperature) would be sufficient to fill the reservoir with ice. With an additional increase of 0.07 m of ice per year the terminus would reach the dam. Data from the 1923 and 1850 moraines are used to suggest lower-bound estimates of temperature changes (-0.4 and -0.6°C respectively) during these periods of glacial maxima.

A Structural Approach to Estimate Short-Term and Long-Term Country Default Risk from Market Data: The Case of Argentina 2000/2001

2013 ◽  
Vol 64 (1) ◽  
pp. 29-50
Author(s):  
Dominik Maltritz
Keyword(s):  
Term Structure ◽  
Default Risk ◽  
Model Parameters ◽  
Special Importance ◽  
Short Term ◽  
Market Data ◽  
Likelihood Approach ◽  
Option Theory ◽  
Bond Spreads

Abstract We apply a structural pricing model to bond market data in order to estimate the default risk for Argentina in 2000/2001. The model explicitly considers short-term and long-term debt service payments and their dependencies by employing compound option theory. In this way, it is possible to take into account both the empirically observed dependency between the term structure of bond spreads and the default risk as well as the finding that the ratio of short-term to long-term debt is of special importance for default risk. The model parameters are estimated using Duan’s (1994) time series-based maximum likelihood approach.

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