Effect of Miscanthus × giganteus ash on survival, biomass, reproduction and avoidance behaviour of the endogeic earthworm Aporrectodea caliginosa.

To achieve the EU's targets for reducing energy production from fossil fuels, the use of energy crops, such as Miscanthus × giganteus, is increasing resulting in a corresponding increase in waste ash from incineration. The chemical properties of Miscanthus ash (e.g. phosphorus and potassium content) may allow this waste material (currently landfilled) to be used as a fertiliser, but no information exists on the effect of the ash on the biological properties of soil. The main aim of this study was to determine the potential impact of Miscanthus ash on earthworms by assessing the effect on survival, change in biomass, reproduction and avoidance behaviour of the geophagous, soil dwelling earthworm, Aporrectodea caliginosa. Tests utilised a range of Miscanthus ash doses from 0 to 50 t ha-1 (0, 1, 2.5, 5, 10, 25, 50). Results showed that Miscanthus ash had no significant impact on A. caliginosa survival, biomass and reproduction, but negative trends were observed for biomass from 2.5 t ha-1 and for reproduction from 10 t ha-1. In contrast, a significant avoidance response was observed in the 25 and 50 t ha-1 treatment and according to ISO guideline 17512 there is a negative impact of the Miscanthus ash on soil habitat function at 25 t ha-1 and above as more than 80% of earthworms were in the control soil. It is suggested that this negative effect on soil habitat function could be attributed to a range of factors including the presence of heavy metals in the ash and a change in substrate pH, texture and/or osmotic stress. Further laboratory-based studies conducted over extended time periods with a more refined range of ash doses and associated field-based studies are required to validate the results and determine a more precise assessment of the threshold ash value inducing a loss of soil habitat function.

Tillage intensity and pasture in rotation effectively shape soil microbial communities at a landscape scale.

Soil microorganisms are essential to agroecosystem functioning and services. Yet, we still lack information on which farming practices can effectively shape the soil microbial communities. The aim of this study was to identify the farming practices, which are most effective at positively or negatively modifying bacterial and fungal diversity while considering the soil environmental variation at a landscape scale. A long-term research study catchment (12 km2 ) representative of intensive mixed farming (livestock and crop) in Western Europe was investigated using a regular grid for soil sampling (n = 186). Farming systems on this landscape scale were described in terms of crop rotation, use of fertilizer, soil tillage, pesticides treatments, and liming. Molecular microbial biomass was estimated by soil DNA recovery. Bacterial and fungal communities were analyzed by 16S and 18S rRNA gene pyrosequencing. Microbial biomass was significantly stimulated by the presence of pasture during the crop rotation since temporary and permanent pastures, as compared to annual crops, increased the soil microbial biomass by +23% and +93% respectively. While soil properties (mainly pH) explained much of the variation in bacterial diversity, soil tillage seemed to be the most influential among the farming practices. A 2.4% increase in bacterial richness was observed along our gradient of soil tillage intensity. In contrast, farming practices were the predominant drivers of fungal diversity, which was mainly determined by the presence of pastures during the crop rotation. Compared to annual crops, temporary and permanent pastures increased soil fungal richness by +10% and +14.5%, respectively. Altogether, our landscape-scale investigation allows the identification of farming practices that can effectively shape the soil microbial abundance and diversity, with the goal to improve agricultural soil management and soil ecological integrity.

Soil C and N models that integrate microbial diversity.

Industrial agriculture is yearly responsible for the loss of 55-100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.

Microbial Diversity Indexes Can Explain Soil Carbon Dynamics as a Function of Carbon Source.

Mathematical models do not explicitly represent the influence of soil microbial diversity on soil organic carbon (SOC) dynamics despite recent evidence of relationships between them. The objective of the present study was to statistically investigate relationships between bacterial and fungal diversity indexes (richness, evenness, Shannon index, inverse Simpson index) and decomposition of different pools of soil organic carbon by measuring dynamics of CO2 emissions under controlled conditions. To this end, 20 soils from two different land uses (cropland and grassland) were incubated with or without incorporation of 13C-labelled wheat-straw residue. 13C-labelling allowed us to study residue mineralisation, basal respiration and the priming effect independently. An innovative data-mining approach was applied, based on generalized additive models and a predictive criterion. Results showed that microbial diversity indexes can be good covariates to integrate in SOC dynamics models, depending on the C source and the processes considered (native soil organic carbon vs. fresh wheat residue). Specifically, microbial diversity indexes were good candidates to help explain mineralisation of native soil organic carbon, while priming effect processes seemed to be explained much more by microbial composition, and no microbial diversity indexes were found associated with residue mineralisation. Investigation of relationships between diversity and mineralisation showed that higher diversity, as measured by the microbial diversity indexes, seemed to be related to decreased CO2 emissions in the control soil. We suggest that this relationship can be explained by an increase in carbon yield assimilation as microbial diversity increases. Thus, the parameter for carbon yield assimilation in mathematical models could be calculated as a function of microbial diversity indexes. Nonetheless, given limitations of the methods used, these observations should be considered with caution and confirmed with more experimental studies. Overall, along with other studies on relationships between microbial community composition and SOM dynamics, this study suggests that overall measures of microbial diversity may constitute relevant ways to include microbial diversity in models of SOM dynamics.

Numerical simulation of organic waste aerobic biodegradation: a new way to correlate respiration kinetics and organic matter fractionation.

Composting wastes permits the reuse of organic matter (OM) as agricultural amendments. The fate of OM during composting and the subsequent degradation of composts in soils largely depend on waste OM quality. The proposed study aimed at developing a model to predict the evolution in organic matter quality during the aerobic degradation of organic waste, based on the quantification of the various OM fractions contained in the wastes. The model was calibrated from data gathered during the monitoring of four organic wastes (two non-treated wastes and their digestates) exposed to respirometric tests. The model was successfully fitted for all four wastes and permitted to predict respiration kinetics, expressed as CO2 production rates, and the evolution of OM fractions. The calibrated model demonstrated that hydrolysis rates of OM fractions were similar for all four wastes whereas the parameters related to microbial activity (eg. growth and death rates) were specific to each substrate. These later parameters have been estimated by calibration on respirometric data, thus demonstrating that coupling analyses of OM fractions in initial wastes and respirometric tests permit the simulation of the biodegradation of various type of waste. The biodegradation model presented in this paper could thereafter be integrated in a composting model by implementing mass and heat balance equations.