In this technical note, we introduce a web-based application, the BonaRes Knowledge Library (KLIB, https://klibrary.bonares.de, last access: 26 July 2023), for the compilation and classification of scientific publications on soil processes according to the specific site conditions and experimental boundary conditions. The tool was developed based on the understanding that experimental findings in soil science are highly dependent on soil type, land use, and climate. The KLIB, therefore, goes beyond other available digital libraries by providing metadata on the site conditions and experimental settings for each publication. A number of visualization tools have been developed in the form of graphical networks to illustrate, for example, publications sharing the same type of scientific questions or soil properties that are affected by different types of drivers. This should help to explore the contents of the literature database more efficiently in order to support and facilitate the literature search efforts of the users. The KLIB is designed as a collaborative effort to encourage soil scientists to participate by entering their own studies and extending the existing database.

The increasing demand for biomass for food, animal feed, fibre and bioenergy requires optimization of soil productivity, while at the same time, protecting other soil functions such as nutrient cycling and buffering, carbon storage, habitat for biological activity and water filter and storage. Therefore, one of the main challenges for sustainable agriculture is to produce high yields while maintaining all the other soil functions. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soils that generate those functions. We developed a soil model to simulate the impact of various agricultural management options and climate change on soil functions by integrating the relevant processes mechanistically and in a systemic way. As a special feature, we include the dynamics of soil structure induced by tillage and biological activity, which is especially relevant in arable soils. The model operates on a 1D soil profile consisting of a number of discrete layers with dynamic thickness. We demonstrate the model performance by simulating crop growth, root growth, nutrient and water uptake, nitrogen cycling, soil organic matter turnover, microbial activity, water distribution and soil structure dynamics in a long-term field experiment including different crops and different types and levels of fertilization. The model is able to capture essential features that are measured regularly including crop yield, soil organic carbon, and soil nitrogen. In this way, the plausibility of the implemented processes and their interactions is confirmed. Furthermore, we present the results of explorative simulations comparing scenarios with and without tillage events to analyse the effect of soil structure on soil functions. Since the model is process-based, we are confident that the model can also be used to predict quantities that have not been measured or to estimate the effect of management measures and climate states not yet been observed. The model thus has the potential to predict the site-specific impact of management decisions on soil functions, which is of great importance for the development of a sustainable agriculture that is currently also on the agenda of the 'Green Deal' at the European level.

Soil organisms and their interactions play a key role in various ecosystem processes and functions, such as the provision of nutrients. The main actors in nitrogen transformation processes are microorganisms, but earthworms affect these processes as their activity results in changes of the microhabitat and microbial community. Studies have shown that nitrogen content is higher in earthworm casts than in bulk soil, and that earthworm invasion affects soil mineral nitrogen. However, we still lack a quantitative synthesis of earthworm effects on soil nitrogen in bulk soil that integrates the influence of potential controlling factors (i.e., soil properties, climatic conditions and experimental parameters). Here, we investigated the impact of earthworms on soil ammonium (NH4+), nitrate (NO3-) and total mineral nitrogen (ammonium + nitrate, Nmin) using meta-analytic techniques. Earthworms generally increased NO3- (+ 88%) and Nmin (+ 63%), but did not affect NH4+. We assume that earthworms affect total mineral nitrogen mainly by their impact on NO3-. Endogeic and epigeic earthworms significantly increased NO3- and Nmin, whereas no clear effect of anecic earthworms was found. This result is presumably caused by diverse effects of the different ecological groups on the microbial community composition. Our results for mixed ecological groups (i.e., anecic + endogeic earthworms) reveal potentially antagonistic effects of ecological groups. The impact of earthworm presence on NO3- and Nmin increased when experiments lasted longer than one week. The effect of earthworms on NH4+, NO3- or Nmin was not influenced by earthworm abundance and biomass, soil organic carbon, soil C/N ratio, litter C/N ratio, the initial amount of NH4+, NO3- or Nmin, total soil nitrogen or temperature. However, as data availability or replication across factor categories was low for some of these moderators, the non-significant results should be interpreted with caution. Also, we could not investigate interactions among the controlling factors due to paucity of data. Our study thus reveals important knowledge gaps regarding earthworm effects on soil nitrogen. Overall, our results highlight the importance of earthworms for soil nitrogen cycling and strengthen the call for soil-functional models to incorporate soil faunal effects.

The provisioning of nitrogen for plant growth is a key function of soils. Soil fauna primarily affect nitrogen mineralization through their interactions with microorganisms, but the excretion of feces and nitrogenous waste products can also supply plants with a considerable amount of their nitrogen requirements. The influence of soil fauna on soil nitrogen is rarely considered in agricultural soils. High amounts of mineral fertilizers are often applied, which are likely to be leached or denitrified from the soil if the amount of plant-available nitrogen exceeds crop requirements. This has profound consequences for the environment. Thus, we require a better understanding of the role of soil fauna in nutrient cycling to improve fertilizer management and agricultural sustainability. To this end, we review the current state of knowledge on the excretion of nitrogenous waste by soil fauna, focusing on earthworms, enchytraeids, nematodes, springtails, mites, isopods and myriapods. This includes an overview on excretory organs and products, a summary of quantitative measurements of nitrogen excretion and the factors that influence nitrogen excretion. Furthermore, we assess the contribution of soil faunal nitrogen excretion to nitrogen pools in agricultural fields based on mean nitrogen excretion rates and common soil invertebrate biomasses. Our results show that earthworms and nematodes are most likely to contribute agronomically-relevant quantities of nitrogen via excretion. Despite the very preliminary nature of our calculations, our results stress the importance of a better understanding of the role of soil fauna in nitrogen cycling in order to reduce soil-nitrogen losses and improve agricultural sustainability.

Soil fauna drives crucial processes of energy and nutrient cycling in agricultural systems, and influences the quality of crops and pest incidence. Soil tillage is the most influential agricultural manipulation of soil structure, and has a profound influence on soil biology and its provision of ecosystem services. The objective of this study was to quantify through meta‐analyses the effects of reducing tillage intensity on density and diversity of soil micro‐ and mesofaunal communities, and how these effects vary among different pedoclimatic conditions and interact with concurrent management practices. We present the results of a global meta‐analysis of available literature data on the effects of different tillage intensities on taxonomic and functional groups of soil micro‐ and mesofauna. We collected paired observations (conventional vs. reduced forms of tillage/no‐tillage) from 133 studies across 33 countries. Our results show that reduced tillage intensity or no‐tillage increases the total density of springtails (+35%), mites (+23%), and enchytraeids (+37%) compared to more intense tillage methods. The meta‐analyses for different nematode feeding groups, life‐forms of springtails, and taxonomic mite groups showed higher densities under reduced forms of tillage compared to conventional tillage on omnivorous nematodes (+53%), epedaphic (+81%) and hemiedaphic (+84%) springtails, oribatid (+43%) and mesostigmatid (+57%) mites. Furthermore, the effects of reduced forms of tillage on soil micro‐ and mesofauna varied with depth, climate and soil texture, as well as with tillage method, tillage frequency, concurrent fertilisation, and herbicide application. Our findings suggest that reducing tillage intensity can have positive effects on the density of micro‐ and mesofaunal communities in areas subjected to long‐term intensive cultivation practices. Our results will be useful to support decision making on the management of soil faunal communities and will facilitate modelling efforts of soil biology in global agroecosystems.

Soil fauna plays an essential role in agricultural productivity as it mediates nutrient cycling and soil organic matter dynamics, alters soil physicochemical properties and supports plant growth. Nitrogen fertilization may have a positive or negative influence on soil fauna in a manner that alters ecosystem functioning, but these links have not yet been quantified. We present the results of a global meta-analysis of available literature data on the effects of N fertilization on taxonomic and ecological groups of soil fauna. Our results show that organic N fertilization increases the density of springtails, mites and earthworms, as well as the biomass of earthworms compared to when no fertilizer is applied. The meta-analysis for different nematode feeding groups and ecological categories of springtails and earthworms as well as different mite orders showed that organic fertilization has an overall positive effect on most groups as opposed to inorganic fertilization, which has neutral or negative effects on most groups, alone or in combination with organic fertilizers. Additional meta-analyses showed that the effects of N fertilization on soil fauna depend on the N application rate, on soil texture and on climatic conditions. Our findings suggest that the adoption of less intense farming practices such as organic fertilization combined with site-specific N fertilization regimes is a suitable strategy for protecting and enhancing functional communities of soil fauna.

We developed an integrated model of soil processes – the Bodium – that enables us to predict possible changes in soil functions under varying agricultural management and climatic change. The model combines current knowledge on soil processes by integrating state-of-the-art modules on plant growth, root development, soil carbon and matter turnover with new concepts with respect to soil hydrology and soil structure dynamics. The model domain is at profile scale, with 1D nodes of variable thickness and weight. It is tested with long-term field experiments to ensure a consistent output of the combined modules. The model is site-specific and works with different soil types and climates (weather scenarios). The output can be interpreted towards a broad spectrum of soil functions. Plant production and nutrient balances can be determined directly. The same is possible for water dynamics, with potential surface runoff (as infiltration surplus), storage and percolation together with travel time and groundwater recharge. In addition, nitrate losses are calculated, and the travel time distribution can help with the evaluation of pesticide percolation risk. To evaluate the habitat for biological activity, the activity is calculated in terms of carbon turnover, and the state variables carbon availability, water, air and temperature for the are accessible. Also, for macrofauna the earthworm activity is included. The comparison of scenario runs can be evaluated quantitatively in terms of potential developments of soil functions. The model is work in progress. Further modules that will be implemented are pH dynamics, more explicit microbial activity, and a more complete set of effects of agricultural management on soil structure are integrated.

The impact of agricultural activities on soil fauna can be highly variable, depending on the management options adopted. High-input agricultural practices can promote a reduction in diversity of soil microarthropod communities but, at the same time can also favor bacterial-feeding fauna through the increase of bacterial foodweb pathways. In contrast, low-input practices can increase the dominance of fungal-feeding fauna through the promotion of fungal pathways. Responses also vary with time after fertilizer application and are strongly dependent on crop species or shifts in plant species composition due to fertilization. The type of fertilizer, organic or inorganic, can also have diverse effects on soil organisms. Organic fertilizers can increase the population of soil decomposers serving as nutrient sources for other soil organisms. Inorganic fertilizers can indirectly affect the soil organisms by increasing crop growth, potentially leading to higher soil organic matter generation. However, inorganic fertilizers can also reduce species richness and abundance of microarthropods and earthworms due to acidification. Other soil fauna such as collembolan may not be particularly sensitive to nitrogen fertilization types. Nitrogen fertilization may disturb soil organisms in a manner that affects ecosystem functioning, but the links are not yet well quantified. Therefore, a compilation of available experimental field data on the effects of nitrogen fertilization on taxonomic and functional groups of soil fauna is needed to clarify the patterns and mechanisms of responses. We are currently working on a quantitative review based on a global meta-analysis that will use paired observations from studies published across several countries. With this review, we aim to synthesize and discuss the current global knowledge on the effects of nitrogen organic and inorganic fertilization on soil fauna. Depending on data availability, we aim to quantify the responses of several groups of soil organisms to synthetic and organic nitrogen inputs, considering factors such as application rate or crop type. Our findings will be used for the development of modeling tools for the prediction of the impacts of agricultural management practices on soil functions.

Mechanistic simulation models are an essential tool for predicting soil functions such as nutrient cycling, water filtering and storage, productivity and carbon storage as well as the complex interactions between these functions. Most soil functions are driven or affected by soil organisms. Yet, biological processes are often neglected in soil function models or implicitly described by rate parameters. This can be explained by the high complexity of the soil ecosystem with its dynamic and heterogeneous environment, and by the range of temporal and spatial scales these processes are taking place at. On the other hand, the technical capabilities to explore microbial activity and communities in soil has greatly improved, resulting in new possibilities to understand soil microbial processes on various scales. However, to integrate such biological processes in soil modelling, we need to find the right level of detail. Here, we present a systemic soil model approach to simulate the impact of different management options and changing climate on soil functions integrating biological activity on the profile scale. We use stoichiometric considerations to simulate microbial processes involved in different soil functions without explicitly describing community dynamics or functional groups. With this approach we are able to mechanistically describe microbial activity and its impact on the turnover of organic matter and nutrient cycling as driven by agricultural soil management. Further, we discuss general challenges and ongoing developments to additionally consider, e.g., microbe-fauna-interactions or microbial feedback with soil structure dynamics.

Although a comprehensive understanding of soil systems is needed to sustain soil functioning, our scientific knowledge of the underlying processes, for example, on the impact of earthworm activity on bulk density, is still limited. Using meta-analysis, we quantified earthworm effects on bulk density and investigated the influence of driving factors. Earthworm effect sizes were species-specific and depended on soil texture and earthworm body mass. Effect sizes were not unambiguously dependent on ecological groups, land use, experimental duration, abundance or initial bulk density. The paucity of data did not allow testing of interactive influences through meta-analysis. Consequently, this study reveals important knowledge gaps in our understanding of earthworm effects on bulk density. Comparative studies taking the soil's complexity into account are still highly necessary to further our understanding of biotic interactions with soil-structure dynamics. Highlights The effects of earthworms on bulk density were evaluated by meta-analysis. Earthworm effects are species-specific and depend on soil texture and earthworm body mass. Effects do not unambiguously depend on land use, duration, abundance and initial bulk density. Knowledge gaps regarding species, soil characteristics and interactive effects are identified.

While the change of soil functions under different management is important in the evaluation of long term strategies in agriculture, they are often difficult to be quantified. The obstacles are measurement problems on one hand, and on the other hand predictions for new management strategies and changing climate scenarios require estimates for yet unknown conditions. Comprehensive modeling of soil processes provides a road to both: Soil properties and processes that are per se difficult to measure can be included in a model to derive suitable indicators for soil unions. In this way, also, predicitons in the future for different climate scenarios and management strategies are possible. In this presentation we give definitions for a limited set of indicators to quantify the most important soil functions in terms of both the current soil state and the soils’ potential to fulfill these functions. This includes the production of biomass, storage of carbon, storage and filtering of ground water, nutrient cycling, and habitat for biodiversity. The quantitative evaluation of soil functions byel based indicators and their dynamics facilitates further socio-economic assessment and the development tools for governance.

The increasing demand for food and bio-energy gives need to optimize soil productivity, while securing other soil functions such as nutrient cycling and buffer capacity, carbon storage, biological activity, and water filter and storage. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soil with those functions, as well as the feedbacks between these functions. We developed a systemic soil model to simulate the impact of different management options and changing climate on the named soil functions by integrating them within a simplified system. The model operates on a 1d soil profile consisting of dynamic nodes, which may represent the different soil horizons, and integrates different processes including dynamic water distribution, soil organic matter turnover, crop growth, nitrogen cycling, and root growth. We present the main features of our model by simulating crop growth under various climatic scenarios on different soil types including management strategies affecting the soil structure. We show the relevance of soil structure for the main soil functions and discuss different model outcome variables as possible measures for these functions. Further, we discuss ongoing model extensions, especially regarding the integration of biological processes, and possible applications.

Soils play a key role for the functioning of terrestrial ecosystems. Thus, soils are essential for human society not only because they form the basis for the production of food. This has long been recognized, and during the last three decades the need to establish methods to evaluate the ability of soils to provide soil functions has moved toward the top of the agenda in soil science. Quantitative evaluation schemes are indispensable to adequately include soils into strategies to reach sustainable development targets. In this paper we build upon existing approaches and propose a concept to evaluate individual soil functions with respect to the soil's intrinsic potential in contrast to its actual state. This leads to a separation of indicator variables and allows for conclusions on the structure of appropriate models that are required to predict the dynamics of soil functions in response to external perturbation. This concept is demonstrated for the production function, carbon storage and water storage which are evaluated exemplarily for different plots of a long-term field experiment. It is discussed for nutrient cycling and habitat function, where evaluation schemes are still less obvious.

The capacity of soils to store organic carbon represents a key function of soils that is not only decisive for climate regulation but also affects other soil functions. Recent efforts to assess the impact of land management on soil functionality proposed that an indicator- or proxy-based approach is a promising alternative to quantify soil functions compared to time- and cost-intensive measurements, particularly when larger regions are targeted. The objective of this review is to identify measurable biotic or abiotic properties that control soil organic carbon (SOC) storage at different spatial scales and could serve as indicators for an efficient quantification of SOC. These indicators should enable both an estimation of actual SOC storage as well as a prediction of the SOC storage potential, which is an important aspect in land use and management planning. There are many environmental conditions that affect SOC storage at different spatial scales. We provide a thorough overview of factors from micro-scales (particles to pedons) to the global scale and discuss their suitability as indicators for SOC storage: clay mineralogy, specific surface area, metal oxides, Ca and Mg cations, microorganisms, soil fauna, aggregation, texture, soil type, natural vegetation, land use and management, topography, parent material and climate. As a result, we propose a set of indicators that allow for time- and cost-efficient estimates of actual and potential SOC storage from the local to the regional and subcontinental scale. As a key element, the fine mineral fraction was identified to determine SOC stabilization in most soils. The quantification of SOC can be further refined by including climatic proxies, particularly elevation, as well as information on land use, soil management and vegetation characteristics. To enhance its indicative power towards land management effects, further “functional soil characteristics”, particularly soil structural properties and changes in the soil microbial biomass pool should be included in this indicator system. The proposed system offers the potential to efficiently estimate the SOC storage capacity by means of simplified measures, such as soil fractionation procedures or infrared spectroscopic approaches.

The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.