Exploring the relationship between soil mesofauna, soil structure and N2O emissions

Porre, Rima J.; Groenigen, J.W. van; Deyn, Gerlinde B. De; Goede, R.G.M. de; Lubbers, Ingrid M.

doi:10.1016/j.soilbio.2016.01.018

Cited by 46 publications

(32 citation statements)

References 43 publications

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“…Moreover, it enables detection of plant roots and large fragments of organic material, that is, particulate organic matter (POM) (Kravchenko, Negassa, Guber, & Schmidt, 2014;Mooney & Morris, 2008). X-ray µCT images of intact soil samples allow analysis of these properties in situ and quantification of their influence on N 2 O emissions (Mangalassery et al, 2014;Mangalassery, Sjogersten, Sparkes, Sturrock, & Mooney, 2013;Porre, Groenigen, Deyn, Goede, & Lubbers, 2016;Rabot, Lacoste, Henault, & Cousin, 2015).…”

Section: Introductionmentioning

confidence: 99%

X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems

et al. 2018

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While renewable biofuels can reduce negative effects of fossil fuel energy consumption, the magnitude of their benefits depends on the magnitude of N2O emissions. High variability of N2O emissions overpowers efforts to curb uncertainties in estimating N2O fluxes from biofuel systems. In this study, we explored (a) N2O production via bacterial denitrification and (b) N2O emissions from soils under several contrasting bioenergy cropping systems, with specific focus on explaining N2O variations by accounting for soil pore characteristics. Intact soil samples were collected after 9 years of implementing five biofuel systems: continuous corn with and without winter cover crop, monoculture switchgrass, poplars, and early‐successional vegetation. After incubation, N2O emissions were measured and bacterial denitrification was determined based on the site‐preference method. Soil pore characteristics were quantified using X‐ray computed microtomography. Three bioenergy systems with low plant diversity, that is, corn and switchgrass systems, had low porosities, low organic carbon contents, and large volumes of poorly aerated soil. In these systems, greater volumes of poorly aerated soil were associated with greater bacterial denitrification, which in turn was associated with greater N2O emissions (R2 = 0.52, p < 0.05). However, the two systems with high plant diversity, that is, poplars and early‐successional vegetation, over the 9 years of implementation had developed higher porosities and organic carbon contents. In these systems, volumes of poorly aerated soil were positively associated with N2O emissions without a concomitant increase in bacterial denitrification. Our results suggest that changes in soil pore architecture generated by long‐term implementation of contrasting bioenergy systems may affect the pathways of N2O production, thus, change associations between N2O emissions and other soil properties. Plant diversity appears as one of the factors determining which microscale soil characteristics will influence the amounts of N2O emitted into the atmosphere and, thus, which can be used as effective empirical predictors.

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Section: Introductionmentioning

confidence: 99%

X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems

et al. 2018

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“…, Porre et al. ). The pronounced spatial variability among peds causes complex soil pore structures which create microenvironments that can alter the distribution of organisms and outcome of species interactions which may be perceived to be difficult to include in mathematical models.…”

Section: Overcome Challenges To the Application Of Mathematical Modelmentioning

confidence: 98%

“…These factors interact to influence the transport of water, air, and heat in soils. The stability and structure of peds are also influenced by processes occurring in the rhizosphere including biotic processes such as decomposition and movement, and ecological interactions among soil biota, including soil fauna, bacteria, mycorrhizal fungi, and plant roots (reviewed in Hinsinger et al 2009, Philippot et al 2013, Platt et al 2016, Porre et al 2016. The pronounced spatial variability among peds causes complex soil pore structures which create microenvironments that can alter the distribution of organisms and outcome of species interactions which may be perceived to be difficult to include in mathematical models.…”

Section: Overcome Challenges To the Application Of Mathematical Modelmentioning

confidence: 99%

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

et al. 2019

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Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution.

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“…This technique allows us to see inside the soil, to study and quantify what effects fauna have on soil structure. Figure 9 shows two such scans, derived from the master thesis research of Rima Porre (Porre et al, 2016). Both are scans of soil cores of about 5 x 10 cm.…”

Section: (Iii) Effects Of Soil Fauna On Greenhouse Gas Emissionsmentioning

confidence: 99%

“…Core dimensions were 6.7 cm diameter and 5 cm height. Color-coded areas denote air-filled pores (Porre et al, 2016). droppings, the casts, of earthworms. In her MSc thesis research, Hannah Vos found that the concentration of plant-available phosphorus in those casts can be very high compared to the surrounding bulk soil -up to a factor 100 or 1000 higher (left side of Figure 10; Vos et al, 2014).…”

Section: X-ray Micro Tomography Scans From a Soil Core Without (Left)mentioning

confidence: 99%

Natural cycles in unnatural soils

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Exploring the relationship between soil mesofauna, soil structure and N2O emissions

Cited by 46 publications

References 43 publications

X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems

X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

Natural cycles in unnatural soils

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Exploring the relationship between soil mesofauna, soil structure and N2O emissions

Cited by 46 publications

References 43 publications

X‐ray computed tomography to predict soil N2O production via bacterial denitrification and N2O emission in contrasting bioenergy cropping systems

X‐ray computed tomography to predict soil N2O production via bacterial denitrification and N2O emission in contrasting bioenergy cropping systems

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

Natural cycles in unnatural soils

Contact Info

Product

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X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems

X‐ray computed tomography to predict soil N₂O production via bacterial denitrification and N₂O emission in contrasting bioenergy cropping systems