Responses of soil biota to non-inversion tillage and organic amendments: An analysis on European multiyear field experiments

D’Hose, Tommy; Molendijk, L.P.G.; Vooren, Laura Van; Berg, W. van den; Hoek, H.; Runia, W.T.; Evert, F.K. van; Berge, Hein ten; Spiegel, Heide; Sandén, Taru; Grignani, Carlo; Ruysschaert, Greet

doi:10.1016/j.pedobi.2017.12.003

Cited by 56 publications

(33 citation statements)

References 81 publications

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“…Soil texture, total N, available N, and pH, are key factors modulating the effect of N fertilizer on wheat yield. Soil texture is an important soil parameter that affects crop productivity, due to its significant influence on N mineralization [33], soil organic matter storage [34], crop N requirements [35], and microbial biomass [36]. Our results showed that there was a greater increase in yield under conditions of coarse soil texture versus fine and medium soil textures ( Figure 7A).…”

Section: Soil Factorsmentioning

confidence: 69%

Synthesis of Climate, Soil Factors, and Nitrogen Management Practices Affecting the Responses of Wheat Productivity and Nitrogen Use Efficiency to Nitrogen Fertilizer in China

et al. 2018

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The reported effects of nitrogen (N) fertilizer on wheat yield and nitrogen use efficiency (NUE) vary greatly, due to differences in climate, soil factors, and N management practices in different regions of China. We collected literature published during 1950-2017 that reported the yield and NUE for wheat in China, under N application and control treatments, and analyzed the data therein. A significant increase in yield was observed with N application, and varied with climate, soil factors, and N management practices in different regions. A larger increase in yield was observed under an average annual temperature of 13-15 • C, an average annual precipitation of >800 mm, respectively. Greater yield-increasing effects were observed in soil with a coarse soil texture, lower soil total N, available N, and a soil pH of ≤7 and >8, respectively. In Northwest China, the yield increase was greater under multiple coated urea applications after anthesis, while the higher NUE was observed under single coated urea application before anthesis. In North China, the yield and NUE were greater under multiple coated urea applications before anthesis. In South China, the yield and NUE were greater under multiple N applications. Consequently, to improve wheat yield and NUE, site-specific N management practices should be adopted.

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Section: Soil Factorsmentioning

confidence: 69%

Synthesis of Climate, Soil Factors, and Nitrogen Management Practices Affecting the Responses of Wheat Productivity and Nitrogen Use Efficiency to Nitrogen Fertilizer in China

et al. 2018

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“…Other studies also found positive effects of no-till practices on earthworm populations (Jordan et al 1997;Briones and Schmidt 2017) whereas, in contrast, combined effects of chemical herbicides and pesticides used in reduced till systems may negate some of the observed positive effects (Bai et al 2018). Positive effects of reduced tillage on bacterial, fungal, nematode, collembolan, and earthworm communities have however been widely reported (Fu et al 2000;Sánchez-Moreno et al 2006;Zheng et al 2008;van Capelle et al 2012;Kuntz et al 2013;D'Hose et al 2018). By contrast, enchytraeid worms have shown to have higher numbers under conventional tillage (House and Parmelee 1985;Hendrix et al 1986;Wardle 1995).…”

Section: Tillagementioning

confidence: 97%

“…The effects of tillage on soil biota are both direct (death, injury, and exposure to predation) and indirect (disruption of habitat) (Kladivko 2001;Roger-Estrade et al 2010), with different responses reported for different groups. A majority of studies demonstrate higher soil microbial biomass under notill versus conventional tillage systems (Wardle 1995;D'Hose et al 2018). Soils under reduced or no-till systems also exhibit altered microbial communities in comparison to conventional tillage (Helgason et al 2009;Kuntz et al 2013;Smith et al 2016).…”

Section: Tillagementioning

confidence: 99%

Soil biodiversity and biogeochemical function in managed ecosystems

et al. 2020

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A complex combination of environmental, biological, chemical, and physical properties and processes determine soil biodiversity and its relationship to biogeochemical functions and ecosystem services. Vegetation, land-use, and land management, in turn, influence diversity and function in the soil ecosystem. The objective of this review was to assess how different land-use systems (crop production, animal production, and planted forest) affect soil biodiversity, and how consequent changes in soil biodiversity influence energy (carbon) and nutrient dynamics. Deficiencies in understanding relationships between soil biodiversity and biogeochemical function in managed ecosystems are highlighted, along with the need to investigate how diversity influences specific processes across different functional groups and trophic levels. The continued development and application of molecular techniques and data informatics with descriptive approaches will contribute to advancing our understanding of soil biodiversity and function in managed agricultural and forest ecosystems.

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“…Unfavorable soil structure can also negatively affect crop yields, for example, due to greater leaching losses (Kavdir and Smucker, 2005). Whether or not increased soil organic matter concentrations improve crop yields is still a subject of debate (e.g., Hijbeek et al, 2017), but it has been shown to greatly improve the soil biota (e.g., D'Hose et al, 2018). The remaining 20% of our primary productivity model was affected by crop attributes (Figure 3).…”

Section: Primary Productivity Decision Support Modelmentioning

confidence: 99%

Development of an Agricultural Primary Productivity Decision Support Model: A Case Study in France

Sandén

Trajanov

Spiegel

et al. 2019

Front. Environ. Sci.

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Agricultural soils provide society with several functions, one of which is primary productivity. This function is defined as the capacity of a soil to supply nutrients and water and to produce plant biomass for human use, providing food, feed, fiber, and fuel. For farmers, the productivity function delivers an economic basis and is a prerequisite for agricultural sustainability. Our study was designed to develop an agricultural primary productivity decision support model. To obtain a highly accurate decision support model that helps farmers and advisors to assess and manage the provision of the primary productivity soil function on their agricultural fields, we addressed the following specific objectives: (i) to construct a qualitative decision support model to assess the primary productivity soil function at the agricultural field level; (ii) to carry out verification, calibration, and sensitivity analysis of this model; and (iii) to validate the model based on empirical data. The result is a hierarchical qualitative model consisting of 25 input attributes describing soil properties, environmental conditions, cropping specifications, and management practices on each respective field. An extensive dataset from France containing data from 399 sites was used to calibrate and validate the model. The large amount of data enabled data mining to support model calibration. The accuracy of the decision support model prior to calibration supported by data mining was ∼40%. The data mining approach improved the accuracy to 77%. The proposed methodology of combining decision modeling and data mining proved to be an important step forward. This iterative approach yielded an accurate, reliable, and useful decision support model for the assessment of the primary productivity soil function at the field level. This can assist farmers and advisors in selecting the most appropriate crop management practices. Embedding this decision support model in a set of complementary models for four adjacent soil functions, as endeavored in the H2020 LANDMARK project, will help take the integrated sustainability of arable cropping systems to a new level.

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Responses of soil biota to non-inversion tillage and organic amendments: An analysis on European multiyear field experiments

Cited by 56 publications

References 81 publications

Synthesis of Climate, Soil Factors, and Nitrogen Management Practices Affecting the Responses of Wheat Productivity and Nitrogen Use Efficiency to Nitrogen Fertilizer in China

Synthesis of Climate, Soil Factors, and Nitrogen Management Practices Affecting the Responses of Wheat Productivity and Nitrogen Use Efficiency to Nitrogen Fertilizer in China

Soil biodiversity and biogeochemical function in managed ecosystems

Development of an Agricultural Primary Productivity Decision Support Model: A Case Study in France

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