Making Waves: Modeling bioturbation in soils - are we burrowing in the right direction?

The burrowing, feeding and foraging activities of terrestrial and benthic organisms induce displacements of soil and sediment materials, leading to a profound mixing of these media. Such particle movements, called "sediment reworking" in aquatic environments and "bioturbation" in soils, have been thoroughly studied and modeled in sediments, where they affect organic matter mineralization and contaminant fluxes. In comparison, studies characterizing the translocation, by soil burrowers, of mineral particles, organic matter and adsorbed contaminants are paradoxically fewer. Nevertheless, models borrowed from aquatic ecology are used to predict the impact of bioturbation on organic matter turnover and contaminant transport in the soil. However, these models are based on hypotheses that have not been tested with adequate observations in soils, and may not necessarily reflect the actual impact of soil burrowers on particle translocation. This paper aims to (i) highlight the possible shortcomings linked to the current use of sediment reworking models for soils, (ii) identify how recent progresses in aquatic ecology could help to circumvent these limitations, and (iii) propose key steps to ensure that soil bioturbation models are built on solid foundations: more accurate models of organic matter turnover, soil evolution and contaminant transport in the soil are at stake.

Multiscale modeling of microbial degradation of outer tissues of fiber-crop stems during the dew retting process.

Dew retting of fiber crops, such as hemp or flax, in the field after harvest promotes the microbial biodegradation of the tissues surrounding cellulosic fibers, which helps preserve the quality of fibers during their extraction and valorization for industry. This bioprocess is currently the bottleneck for plant fiber valorization because it is empirically managed and its controlling factors have not been properly quantified. A novel multiscale model representing tissue and polymer biodegradation was developed to simulate microbial growth on the stem during retting. The model was evaluated against experimental hemp retting data. It consistently simulated the mass loss of eight plant polymers belonging to two tissues of the stem outer layer, i.e., parenchyma and fiber bundles. Microbial growth was modeled by Monod equations and modulated by the functions of temperature and moisture. This work provides a tool for gaining more insights into microorganism behavior during retting under local climate conditions.

Mulch of plant residues at the soil surface impact the leaching and persistence of pesticides: A modelling study from soil columns.

Crop residues left on the soil surface as mulch greatly influence the fate of pesticides in conservation agricultural practices because most of the applied pesticide is intercepted by mulch before passing to the soil. Modelling of pesticide losses from wash-off and leaching will greatly improve our understanding of the environmental consequences of pesticides in these systems. The PASTIS model, which simulates water transfer, mulch decomposition, and pesticide dynamics, was adapted in this new version to model the interactions between pesticides and mulch in order to simulate the impact of mulch on pesticide dynamic. Parameters of mulch dynamics and pesticide degradation and retention processes were estimated using independent incubation experiments. The PASTIS model was tested with experimental laboratory data that were obtained from two pesticides (Glyphosate and s-metolachlor) applied to soil columns where mulch composed of maize and dolichos was placed at the soil surface impacted by two rain intensities (a high and infrequent intensity and a light and frequent intensity). Simulations indicated good agreement between simulated and experimental values. After 1 day, 45-46% of the pesticides leached from the mulch and 54-55% remained in the mulch for both pesticides and both rain intensities. During the experiment, pesticide wash-off was greater for the high and infrequent rain (56-57%) compare to light and frequent rain (39-45%) for both pesticides. A smaller amount of S-metolachlor washed off with the light and frequent rain intensity (39%) than glyphosate (45%) because of its lower desorption rate from mulch residues. Glyphosate was more degraded (37-45%) than s-metolachlor (17-37%), which agrees with preliminary incubation experiments that were used for parameter estimation. A sensitivity analysis indicated that the saturation index of mulch at which pesticides started their diffusion in the rainwater and the time of the first rainfall were the two parameters that influenced the most output variables of our model. This study suggests that the PASTIS model developed for pesticide dissipation in mulch is a useful tool to evaluate the potential risk of pesticide leaching to the groundwater in conservation agriculture systems.

Modelling the fate of PAH added with composts in amended soil according to the origin of the exogenous organic matter.

A new model that was able to simulate the behaviours of polycyclic aromatic hydrocarbons (PAH) during composting and after the addition of the composts to agricultural soil is presented here. This model associates modules that describe the physical, biological and biochemical processes involved in PAH dynamics in soils, along with a module describing the compost degradation resulting in PAH release. The model was calibrated from laboratory incubations using three 14C-PAHs, phenanthrene, fluoranthene and benzo(a)pyrene, and three different composts consisting of two mature and one non-mature composts. First, the labelled PAHs were added to the compost over 28days, and spiked composts were then added to the soil over 55days. The model calculates the proportion of biogenic and physically bound residues in the non-extractable compartment of PAHs at the end of the compost incubation to feed the initial conditions of the model for soil amended with composts. For most of the treatments, a single parameter set enabled to simulate the observed dynamics of PAHs adequately for all the amended soil treatments using a Bayesian approach. However, for fluoranthene, different parameters that were able to simulate the growth of a specific microbial biomass had to be considered for mature compost. Processes that occurred before the compost application to the soil strongly influenced the fate of PAHs in the soil. Our results showed that the PAH dissipation during compost incubation was higher in mature composts because of the higher specific microbial activity, while the PAH dissipation in amended soil was higher in the non-mature compost because of the higher availability of PAHs and the higher co-metabolic microbial activity.

In situ long-term modeling of phenanthrene dynamics in an aged contaminated soil using the VSOIL platform.

Management and remediation actions of polycyclic aromatic hydrocarbons (PAH) contaminated sites require an accurate knowledge of the dynamics of these chemicals in situ under real conditions. Here we developed, under the Virtual Soil Platform, a global model for PAH that describes the principal physical and biological processes controlling the dynamics of PAH in soil under real climatic conditions. The model was applied first to simulate the observed dynamics of phenanthrene in situ field experimental plots of industrial contaminated soil. In a second step, different long-term scenarios of climate change or bioavailability increase were applied. Our results show that the model can adequately predict the fate of phenanthrene and can contribute to clarify some of unexplored aspects regarding the behavior of phenanthrene in soil like its degradation mechanism and stabilization. Tested prospective scenarios showed that bioavailability increase (through the addition of solvent or surfactants) resulted in significant increase in substrate transfer rate, hence reducing remediation time. Regarding climate change effect, the model indicated that phenanthrene concentration decreased by 54% during 40years with a natural attenuation and both scenarios chosen for climatic boundaries provided very similar results.

Combined time-lapse magnetic resonance imaging and modeling to investigate colloid deposition and transport in porous media.

Colloidal particles can act as vectors of adsorbed pollutants in the subsurface, or be themselves pollutants. They can reach the aquifer and impair groundwater quality. The mechanisms of colloid transport and deposition are often studied in columns filled with saturated porous media. Time-lapse profiles of colloid concentration inside the columns have occasionally been derived from magnetic resonance imaging (MRI) data recorded in transport experiments. These profiles are valuable, in addition to particle breakthrough curves (BTCs), for testing and improving colloid transport models. We show that concentrations could not be simply computed from MRI data when both deposited and suspended colloids contributed to the signal. We propose a generic method whereby these data can still be used to quantitatively appraise colloid transport models. It uses the modeled suspended and deposited particle concentrations to compute modeled MRI data that are compared to the experimental data. We tested this method by performing transport experiments with sorbing colloids in sand, and assessed for the first time the capacity of the model calibrated from BTCs to reproduce the MRI data. Interestingly, the dispersion coefficient and deposition rate calibrated from the BTC were respectively overestimated and underestimated compared with those calibrated from the MRI data, suggesting that these quantities, when determined from BTCs, need to be interpreted with care. In a broader perspective, we consider that combining MRI and modeling offers great potential for the quantitative analysis of complex MRI data recorded during transport experiments in complex environmentally relevant porous media, and can help improve our understanding of the fate of colloids and solutes, first in these media, and later in soils.

Novel Experimental-Modeling Approach for Characterizing Perfluorinated Surfactants in Soils.

Soil contamination is still poorly understood and modeled in part because of the difficulties of looking inside the "black box" constituted by soils. Here, we investigated the application of a recently developed 1H NMR technique to 19F NMR relaxometry experiments and utilized the results as inputs for an existing model. This novel approach yields 19F T2 NMR relaxation values of any fluorinated contaminant, which are among the most dangerous contaminants, allowing us to noninvasively and directly monitor their fate in soils. Using this protocol, we quantified the amount of a fluorinated xenobiotic (heptafluorobutyric acid, HFBA) in three different environments in soil aggregate packings and monitored contaminant exchange dynamics between these compartments. A model computing HFBA partition dynamics between different soil compartments showed that these three environments corresponded to HFBA in solution (i) between and (ii) inside the soil aggregates and (iii) to HFBA adsorbed to (or strongly interacting with) the soil constituents. In addition to providing a straightforward way of determining the sorption kinetics of any fluorinated contaminant, this work also highlights the strengths of a combined experimental-modeling approach to unambiguously understand experimental data and more generally to study contaminant fate in soils.

A coordinated set of ecosystem research platforms open to international research in ecotoxicology, AnaEE-France.

The infrastructure for Analysis and Experimentation on Ecosystems (AnaEE-France) is an integrated network of the major French experimental, analytical, and modeling platforms dedicated to the biological study of continental ecosystems (aquatic and terrestrial). This infrastructure aims at understanding and predicting ecosystem dynamics under global change. AnaEE-France comprises complementary nodes offering access to the best experimental facilities and associated biological resources and data: Ecotrons, seminatural experimental platforms to manipulate terrestrial and aquatic ecosystems, in natura sites equipped for large-scale and long-term experiments. AnaEE-France also provides shared instruments and analytical platforms dedicated to environmental (micro) biology. Finally, AnaEE-France provides users with data bases and modeling tools designed to represent ecosystem dynamics and to go further in coupling ecological, agronomical, and evolutionary approaches. In particular, AnaEE-France offers adequate services to tackle the new challenges of research in ecotoxicology, positioning its various types of platforms in an ecologically advanced ecotoxicology approach. AnaEE-France is a leading international infrastructure, and it is pioneering the construction of AnaEE (Europe) infrastructure in the field of ecosystem research. AnaEE-France infrastructure is already open to the international community of scientists in the field of continental ecotoxicology.

Soil water flow is a source of the plant pathogen Pseudomonas syringae in subalpine headwaters.

The airborne plant pathogenic bacterium Pseudomonas syringae is ubiquitous in headwaters, snowpack and precipitation where its populations are genetically and phenotypically diverse. Here, we assessed its population dynamics during snowmelt in headwaters of the French Alps. We revealed a continuous and significant transport of P.syringae by these waters in which the population density is correlated with water chemistry. Via in situ observations and laboratory experiments, we validated that P.syringae is effectively transported with the snow melt and rain water infiltrating through the soil of subalpine grasslands, leading to the same range of concentrations as measured in headwaters (10(2) -10(5) CFU l(-1) ). A population structure analysis confirmed the relatedness between populations in percolated water and those above the ground (i.e. rain, leaf litter and snowpack). However, the transport study in porous media suggested that water percolation could have different efficiencies for different strains of P.syringae. Finally, leaching of soil cores incubated for up to 4 months at 8°C showed that indigenous populations of P.syringae were able to survive in subalpine soil under cold temperature. This study brings to light the underestimated role of hydrological processes involved in the long distance dissemination of P.syringae.

Emigration of the plant pathogen Pseudomonas syringae from leaf litter contributes to its population dynamics in alpine snowpack.

The recently discovered ubiquity of the plant pathogen Pseudomonas syringae in headwaters and alpine ecosystems worldwide elicits new questions about the ecology of this bacterium and subsequent consequences for disease epidemiology. Because of the major contribution of snow to river run-off during crop growth, we evaluated the population dynamics of P.syringae in snowpack and the underlying leaf litter during two years in the Southern French Alps. High population densities of P.syringae were found on alpine grasses, and leaf litter was identified as the main source of populations of P.syringae in snowpack, contributing more than the populations arriving with the snowfall. The insulating properties of snow foster survival of P.syringae throughout the winter in the 10 cm layer of snow closest to the soil. Litter and snowpack harboured populations of P.syringae that were very diverse in terms of phenotypes and genotypes. Neither substrate nor sampling site had a marked effect on the structure of P.syringae populations, and snow and litter had genotypes in common with other non-agricultural habitats and with crops. These results contribute to the mounting evidence that a highly diverse P.syringae metapopulation is disseminated throughout drainage basins between cultivated and non-cultivated zones.