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Projected climate change and rainfall variability will affect soil microbial communities, biogeochemical cycling and agriculture. Nitrogen (N) is the most limiting nutrient in agroecosystems and its cycling and availability is highly dependent on microbial driven processes. In agroecosystems, hydrolysis of organic nitrogen (N) is an important step in controlling soil N availability. We analyzed the effect of management (ecological intensive vs. conventional intensive) on N-cycling processes and involved microbial communities under climate change-induced rain regimes. Terrestrial model ecosystems originating from agroecosystems across Europe were subjected to four different rain regimes for 263 days. Using structural equation modelling we identified direct impacts of rain regimes on N-cycling processes, whereas N-related microbial communities were more resistant. In addition to rain regimes, management indirectly affected N-cycling processes via modifications of N-related microbial community composition. Ecological intensive management promoted a beneficial N-related microbial community composition involved in N-cycling processes under climate change-induced rain regimes. Exploratory analyses identified phosphorus-associated litter properties as possible drivers for the observed management effects on N-related microbial community composition. This work provides novel insights into mechanisms controlling agro-ecosystem functioning under climate change.

Soil nematode communities and food web indices can inform about the complexity, nutrient flows and decomposition pathways of soil food webs, reflecting soil quality. Relative abundance of nematode feeding and life-history groups are used for calculating food web indices, i.e., maturity index (MI), enrichment index (EI), structure index (SI) and channel index (CI). Molecular methods to study nematode communities potentially offer advantages compared to traditional methods in terms of resolution, throughput, cost and time. In spite of such advantages, molecular data have not often been adopted so far to assess the effects of soil management on nematode communities and to calculate these food web indices. Here, we used high-throughput amplicon sequencing to investigate the effects of tillage (conventional vs. reduced) and organic matter addition (low vs. high) on nematode communities and food web indices in 10 European long-term field experiments and we assessed the relationship between nematode communities and soil parameters. We found that nematode communities were more strongly affected by tillage than by organic matter addition. Compared to conventional tillage, reduced tillage increased nematode diversity (23% higher Shannon diversity index), nematode community stability (12% higher MI), structure (24% higher SI), and the fungal decomposition channel (59% higher CI), and also the number of herbivorous nematodes (70% higher). Total and labile organic carbon, available K and microbial parameters explained nematode community structure. Our findings show that nematode communities are sensitive indicators of soil quality and that molecular profiling of nematode communities has the potential to reveal the effects of soil management on soil quality., (© 2019 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

Ecosystem services (ES) are the benefits that people obtain from ecosystems. Investigating the environment through an ES framework has gained wide acceptance in the international scientific community and is applied by policymakers to protect biodiversity and safeguard the sustainability of ecosystems. This approach can enhance the ecological and societal relevance of pre-market/prospective environmental risk assessments (ERAs) of regulated stressors by: (1) informing the derivation of operational protection goals; (2) enabling the integration of environmental and human health risk assessments; (3) facilitating horizontal integration of policies and regulations; (4) leading to more comprehensive and consistent environmental protection; (5) articulating the utility of, and trade-offs involved in, environmental decisions; and (6) enhancing the transparency of risk assessment results and the decisions based upon them. Realisation of these advantages will require challenges that impede acceptance of an ES approach to be overcome. Particularly, there is concern that, if biodiversity only matters to the extent that it benefits humans, the intrinsic value of nature is ignored. Moreover, our understanding of linkages among ecological components and the processes that ultimately deliver ES is incomplete, valuing ES is complex, and there is no standard ES lexicon and limited familiarity with the approach. To help overcome these challenges, we encourage: (1) further research to establish biodiversity-ES relationships; (2) the development of approaches that (i) quantitatively translate responses to chemical stressors by organisms and groups of organisms to ES delivery across different spatial and temporal scales, (ii) measure cultural ES and ease their integration into ES valuations, and (iii) appropriately value changes in ES delivery so that trade-offs among different management options can be assessed; (3) the establishment of a standard ES lexicon; and (4) building capacity in ES science and how to apply ES to ERAs. These development needs should not prevent movement towards implementation of an ES approach in ERAs, as the advantages we perceive of using this approach render it more than worthwhile to tackle those challenges. Society and the environment stand to benefit from this shift in how we conduct the ERA of regulated stressors., (© 2019 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.)

Concentrating nutrients on biochar and clinoptilolite and subsequently using the nutrient-enriched sorbents as a fertiliser could be an alternative way to manage nutrients in digestate. In this study, we investigated the use of biochar and clinoptilolite columns in removing ammonium, potassium, orthophosphate and dissolved organic carbon (DOC) from the liquid fraction of digestate. Our objectives were to investigate the effect of the initial loading ratio between liquid and biochar on nutrient removal, and to investigate the effect of combining biochar with clinoptilolite on nutrient and DOC removal efficiency. Increasing the initial loading ratios increased nutrient concentrations on biochar to 8.61 mg NH 4 -N g -1 , 1.95 mg PO 4 -P g -1 and 13.01 mg DOC g -1 , but resulted in decreasing removal efficiencies. The combination of biochar and clinoptilolite resulted in improved ammonium, potassium and DOC removal efficiencies compared to biochar alone, but did not significantly change PO 4 -P removal efficiencies. Removal efficiencies with combined sorbents were up to 67% for ammonium, 58% for DOC and 58% for potassium. Clinoptilolite showed higher removal efficiencies compared to biochar alone, and combining clinoptilolite with biochar improved only total P removal efficiency. Concentrating nutrients with clinoptilolite and biochar may be an option when both sorbents are available at low cost.

Concerns about rising greenhouse gas (GHG) concentrations have spurred the promotion of no-tillage practices as a means to stimulate carbon storage and reduce CO2 emissions in agro-ecosystems. Recent research has ignited debate about the effect of earthworms on the GHG balance of soil. It is unclear how earthworms interact with soil management practices, making long-term predictions on their effect in agro-ecosystems problematic. Here we show, in a unique two-year experiment, that earthworm presence increases the combined cumulative emissions of CO2 and N2O from a simulated no-tillage (NT) system to the same level as a simulated conventional tillage (CT) system. We found no evidence for increased soil C storage in the presence of earthworms. Because NT agriculture stimulates earthworm presence, our results identify a possible biological pathway for the limited potential of no-tillage soils with respect to GHG mitigation.

Belowground organisms often display a shift in their mass-abundance scaling relationships due to environmental factors such as soil chemistry and atmospheric deposition. Here we present new empirical data that show strong differences in allometric scaling according to whether the resolution at the local scale is based on a taxonomic or a functional classification, while only slight differences arise according to soil environmental conditions. For the first time, isometry (an inverse 1:1 proportion) is recognized in mass-abundance relationships, providing a functional signal for constant biomass distribution in soil biota regardless of discrete trophic levels. Our findings are in contrast to those from aquatic ecosystems, in that higher trophic levels in soil biota are not a direct function of increasing body mass.

DIVERSITAS, the international programme on biodiversity science, is releasing a strategic vision presenting scientific challenges for the next decade of research on biodiversity and ecosystem services: "Biodiversity and Ecosystem Services Science for a Sustainable Planet". This new vision is a response of the biodiversity and ecosystem services scientific community to the accelerating loss of the components of biodiversity, as well as to changes in the biodiversity science-policy landscape (establishment of a Biodiversity Observing Network - GEO BON, of an Intergovernmental science-policy Platform on Biodiversity and Ecosystem Services - IPBES, of the new Future Earth initiative; and release of the Strategic Plan for Biodiversity 2011-2020). This article presents the vision and its core scientific challenges.

Understanding the impacts of agricultural intensification and extensification on soil biota communities is useful in order to preserve and restore biological diversity in agricultural soils and enhance the role of soil biota in agroecosystem functioning. Over four consecutive years, we investigated the effects of agricultural intensification and extensification (including conversion of grassland to arable land and vice versa, increased and decreased levels of mineral fertilization, and monoculture compared to crop rotation) on major soil biota group abundances and functional diversity. We integrated and compared effects across taxonomic levels to identify sensitive species groups. Conversion of grassland to arable land negatively affected both abundances and functional diversity of soil biota. Further intensification of the cropping system by increased fertilization and reduced crop diversity exerted smaller and differential effects on different soil biota groups. Agricultural intensification affected abundances of taxonomic groups with larger body size (earthworms, enchytraeids, microarthropods, and nematodes) more negatively than smaller-sized taxonomic groups (protozoans, bacteria, and fungi). Also functional group diversity and composition were more negatively affected in larger-sized soil biota (earthworms, predatory mites) than in smaller-sized soil biota (nematodes). Furthermore, larger soil biota appeared to be primarily affected by short-term consequences of conversion (disturbance, loss of habitat), whereas smaller soil biota were predominantly affected by long-term consequences (probably loss of organic matter). Reestablishment of grassland resulted in increased abundances of soil biota groups, but since not all groups increased in the same measure, the community structure was not completely restored. We concluded that larger-sized soil biota are more sensitive to agricultural intensification than smaller-sized soil biota. Furthermore, since larger-sized soil biota groups had lower taxonomic richness, we suggest that agricultural intensification exerts strongest effects on species-poor soil biota groups, thus supporting the hypothesis that biodiversity has an "insurance" function. As soil biota play an important role in agroecosystem functioning, altered soil biota abundances and functional group composition under agricultural intensification are likely to affect the functioning of the agroecosystem.

Soil quality, as a measure of the soil's capacity to function, can be assessed by indicators based on physical, chemical, and biological properties. Here we report on the assessment of soil quality in 21 rice (Oryza sativa) fields under three rice production systems (semi-direct, pre-germinated, and conventional) on four soil textural classes in the Camaquã region of Rio Grande do Sul, Brazil. The objectives of our study were: (i) to identify soil quality indicators that discriminate both management systems and soil textural classes, (ii) to establish a minimum data set of soil quality indicators and (iii) to test whether this minimum data set is correlated with yield. Twenty-nine soil biological, chemical, and physical properties were evaluated to characterize regional soil quality. Soil quality assessment was based on factor and discriminant analysis. Bulk density, available water, and micronutrients (Cu, Zn, and Mn) were the most powerful soil properties in distinguishing among different soil textural classes. Organic matter, earthworms, micronutrients (Cu and Mn), and mean weight diameter were the most powerful soil properties in assessing differences in soil quality among the rice management systems. Manganese was the property most strongly correlated with yield (adjusted r2 = 0.365, P = 0.001). The merits of sub-dividing samples according to texture and the linkage between soil quality indicators, soil functioning, plant performance, and soil management options are discussed in particular.

This work comprises calculations using the Frenkel-Kontorova and double-chain models, which led to new results explaining the experimental diffraction pattern of K-hollandite. The use of a deformable host chain and a Lennard-Jones-like interchain interaction gives the best results. From these calculations, it can also be concluded that the guest as well as the host are deformed and that the system is pinned. The inclusion of Debye-Waller factors as fitting parameters is also discussed, with the conclusion they should not be used in the case of the double-chain model.