INDUSTRIAL AND AGRICULTURAL WASTES DECREASED GREENHOUSE-GAS EMISSIONS AND INCREASED RICE GRAIN YIELD IN A SUBTROPICAL PADDY FIELD

SUMMARYReducing the emissions of greenhouse gases (GHG) from paddy fields is crucial both for the sustainability of rice production and mitigation of global climatic warming. The effects of applying industrial and agricultural wastes as fertilizer on the reduction of GHG emissions in cropland areas, however, remain poorly known. We studied the effects of the application of 8 Mg ha−1 of diverse wastes on GHG emission and rice yield in a subtropical paddy in southeastern China. Plots fertilized with steel slag, biochar, shell slag, gypsum slag and silicate and calcium fertilizer had lower total global-warming potentials (GWP, including CO2, CH4 and N2O emissions) per unit area than control plots without waste application despite non-significant differences among these treatments. Structural equation models showed that the effects of these fertilization treatments on gas emissions were partially due to their effects on soil variables, such as soil water content or soil salinity. Steel slag, biochar and shell slag increased rice yield by 7.1%, 15.5% and 6.5%, respectively. The biochar amendment had a 40% lower GWP by Mg−1 yield production, relative to the control. These results thus encourage further studies of the suitability of the use waste materials as fertilizers in other different types of paddy field as a way to mitigate GHG emissions and increase crop yield.

Download Full-text

Temporal and spatial dynamics of peat microbiomes in drained and rewetted soils of three temperate peatlands

10.1101/2020.02.16.951285 ◽

2020 ◽

Author(s):

Haitao Wang ◽

Micha Weil ◽

Dominik Zak ◽

Diana Münch ◽

Anke Günther ◽

...

Keyword(s):

Microbial Communities ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Community Composition ◽

Structural Equation ◽

Structural Equation Models ◽

Temporal Dynamics ◽

Salt Water ◽

Microbial Community Composition ◽

Gas Emissions

AbstractBackgroundDrainage of high-organic peatlands for agricultural purposes has led to increased greenhouse gas emissions and loss of biodiversity. In the last decades, rewetting of peatlands is on the rise worldwide, to mitigate these negative impacts. However, it remains still questionable how rewetting would influence peat microbiota as important drivers of nutrient cycles and ecosystem restoration. Here, we investigate the spatial and temporal dynamics of the diversity, community composition and network interactions of prokaryotes and eukaryotes, and the influence of rewetting on these microbial features in formerly long-term drained and agriculturally used fens. Peat-soils were sampled seasonally from three drained and three rewetted sites representing the dominating fen peatland types of glacial landscapes in Northern Germany, namely alder forest, costal fen and percolation fen.ResultsCostal fens as salt-water impacted systems showed a lower microbial diversity and their microbial community composition showed the strongest distinction from the other two peatland types. Prokaryotic and eukaryotic community compositions showed a congruent pattern which was mostly driven by peatland type and rewetting. Rewetting decreased the abundances of fungi and prokaryotic decomposers, while the abundance of potential methanogens was significantly higher in the rewetted sites. Rewetting also influenced the abundance of ecological clusters in the microbial communities identified from the co-occurrence network. The microbial communities changed only slightly with depth and over time. According to structural equation models rewetted conditions affected the microbial communities through different mechanisms across the three studied peatland types.ConclusionsOur results suggest that rewetting strongly impacts the structure of microbial communities and, thus, important biogeochemical processes, which may explain the high variation in greenhouse gas emissions upon rewetting of peatlands. The improved understanding of functional mechanisms of rewetting in different peatland types lays the foundation for securing best practices to fulfil multiple restoration goals including those targeting on climate, water, and species protection.

Download Full-text

Effects of steel slag application on greenhouse gas emissions and crop yield over multiple growing seasons in a subtropical paddy field in China

Field Crops Research ◽

10.1016/j.fcr.2014.10.014 ◽

2015 ◽

Vol 171 ◽

pp. 146-156 ◽

Cited By ~ 39

Author(s):

W. Wang ◽

J. Sardans ◽

D.Y.F. Lai ◽

C. Wang ◽

C. Zeng ◽

...

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Crop Yield ◽

Paddy Field ◽

Steel Slag ◽

Gas Emissions ◽

Growing Seasons

Download Full-text

Greenhouse gas emissions in a subtropical jasmine plantation managed with straw combined with industrial and agricultural wastes

Experimental Agriculture ◽

10.1017/s001447971900036x ◽

2019 ◽

Vol 56 (2) ◽

pp. 280-292

Author(s):

Qiang Jin ◽

Haitao Liu ◽

Chun Wang ◽

Xiaotong Wang ◽

Qingwen Min ◽

...

Keyword(s):

Greenhouse Gas ◽

Block Design ◽

Steel Slag ◽

Ghg Emissions ◽

Agricultural Wastes ◽

Emission Rates ◽

Soil C ◽

Randomized Block Design ◽

Global Warming Potentials ◽

Jasminum Sambac

AbstractThe effects of straw alone or combined with industrial and agricultural wastes as fertilizers on greenhouse gas (GHG) emissions are still poorly known in cropland areas. Here, we studied the effects of 3.5 Mg ha−1 straw and 3.5 Mg ha−1 straw combined with 8 Mg ha−1 of diverse wastes on GHG emission in a subtropical Jasminum sambac plantation in southeastern China. There were five treatments in a completely randomized block design: control, straw only, straw + biochar, straw + steel slag, and straw + gypsum slag. Emissions of carbon dioxide were generally higher in the treatments with waste than in the control or straw-only treatments, whereas the contrary pattern was observed in CH4 and N2O emission rates. Moreover, the total global warming potentials (GWPs) were no significantly higher in most of the amended treatments as compared to the control and straw-only treatments. In relation to the treatment with only straw, GWPs were 9.4% lower when steel slag was used. This finding could be a consequence of Fe amount added by steel slag, which would limit and inhibit the emissions of GHGs and their transport from soil to atmosphere. Our results showed that the application of slags did not increase the emission of GHGs and that the combination of straw with steel slag or biochar could be more effective than straw alone for controlling GHGs emission and improve soil C and nutrient provision.

Download Full-text

STEEL SLAG AMENDMENT INCREASES NUTRIENT AVAILABILITY AND RICE YIELD IN A SUBTROPICAL PADDY FIELD IN CHINA

Experimental Agriculture ◽

10.1017/s0014479717000412 ◽

2017 ◽

Vol 54 (6) ◽

pp. 842-856 ◽

Cited By ~ 3

Author(s):

WEIQI WANG ◽

JORDI SARDANS ◽

CHUN WANG ◽

CONGSHENG ZENG ◽

CHUAN TONG ◽

...

Keyword(s):

Nutrient Availability ◽

Paddy Field ◽

Rice Yield ◽

Steel Slag ◽

Rice Production ◽

Paddy Fields ◽

Growth And Yield ◽

Nutrient Allocation ◽

P Availability ◽

High Yields

SUMMARYRice is the main food for most of the human population, so sustainable rice production is very important for food security. The fertility of the soil in paddy fields is the key factor controlling rice growth and production. Steel slag amendment is becoming an effective method to increase the soil fertility, stabilize rice production and reduce greenhouse-gas emissions in Asiatic paddy fields (i.e. Korea, Japan, Bangladesh and China). We studied the relationships of steel slag amendment with plant–soil nutrient allocation, stoichiometry and rice yield in a paddy field in subtropical China. Amendment was associated with higher soil N and P availability, lower available-N:available-P ratio and higher available Ca and Si concentrations. Increases in P, Ca and Mg availability were correlated with high yields. High yields under steel slag amendment were also associated with high foliar and stem N and P concentrations and lower N:P ratios and with high shoot/root N and P concentration ratios, traits that are typically associated with productive ecosystems able to support species with high growth rates. The positive correlation between steel slag application and yield was partially due to an indirect effect (35% of the total effect) of enhancement of soil Ca, Si and P availability, which were positively correlated with yield. Steel slag amendment in this paddy field increased plant growth and yield by enhancing nutrient availability, altering soil and plant stoichiometry and shifting stem:root nutrient allocation.

Download Full-text

Measuring the Big Five in Self-Report and Other Ratings

European Journal of Psychological Assessment ◽

10.1027//1015-5759.16.1.31 ◽

2000 ◽

Vol 16 (1) ◽

pp. 31-43 ◽

Cited By ~ 24

Author(s):

Claudio Barbaranelli ◽

Gian Vittorio Caprara

Keyword(s):

Big Five ◽

Structural Equation ◽

Structural Equation Models ◽

Error Variance ◽

The Self ◽

Self Report ◽

Sources Of Information ◽

Third Person ◽

Fit Indexes ◽

Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Download Full-text

Collective Efficacy and Organizational Commitment in an Italian City Hall

European Psychologist ◽

10.1027/1016-9040.14.4.363 ◽

2009 ◽

Vol 14 (4) ◽

pp. 363-371 ◽

Cited By ~ 14

Author(s):

Laura Borgogni ◽

Silvia Dello Russo ◽

Laura Petitta ◽

Gary P. Latham

Keyword(s):

Organizational Commitment ◽

Collective Efficacy ◽

Structural Equation ◽

Structural Equation Models ◽

Practical Significance ◽

City Hall ◽

Italian City ◽

Public Sector Managers ◽

The Individual ◽

Level Group

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.

Download Full-text

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽

10.1027/1614-1881.1.2.81 ◽

2005 ◽

Vol 1 (2) ◽

pp. 81-85 ◽

Cited By ~ 5

Author(s):

Stefan C. Schmukle ◽

Jochen Hardt

Keyword(s):

Factor Analysis ◽

Maximum Likelihood ◽

Structural Equation ◽

Structural Equation Models ◽

Null Model ◽

Likelihood Estimation ◽

Parameter Estimates ◽

Fit Indices ◽

Cautionary Note ◽

Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Download Full-text

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽

10.1027/1614-2241/a000084 ◽

2014 ◽

Vol 10 (4) ◽

pp. 138-152 ◽

Cited By ~ 5

Author(s):

Hsien-Yuan Hsu ◽

Susan Troncoso Skidmore ◽

Yan Li ◽

Bruce Thompson

Keyword(s):

Structural Equation ◽

Structural Model ◽

Structural Equation Models ◽

Equation Model ◽

Model Fit ◽

Model Specification ◽

Simulation Design ◽

Measurement Models ◽

Fit Statistics ◽

Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

Download Full-text