The concept of ecosystem services, especially in combination with economic valuation, can illuminate trade-offs involved in soil management, policy and governance, and thus support decision making. In this paper, we investigate and highlight the potential and limitations of the economic valuation of soil-based ecosystem services to inform sustainable soil management and policy. We formulate a definition of soil-based ecosystem services as basis for conducting a review of existing soil valuation studies with a focus on the inclusion of ecosystem services and the choice of valuation methods. We find that, so far, the economic valuation of soil-based ecosystem services has covered only a small number of such services and most studies have employed cost-based methods rather than state-of-the-art preference-based valuation methods, even though the latter would better acknowledge the public good character of soil related services. Therefore, the relevance of existing valuation studies for political processes is low. Broadening the spectrum of analyzed ecosystem services as well as using preference-based methods would likely increase the informational quality and policy relevance of valuation results. We point out options for improvement based on recent advances in economic valuation theory and practice. We conclude by investigating the specific roles economic valuation results can play in different phases of the policy-making process, and the specific requirements for its usefulness in this context.

Potential of the economic valuation of soil-based ecosystem services to inform sustainable soil management and policy.

Agricultural management is a key force affecting soil processes and functions. Triggered by biophysical constraints as well as rapid structural and technological developments, new management practices are emerging with largely unknown impacts on soil processes and functions. This impedes assessments of the potential of such emerging practices for sustainable intensification, a paradigm coined to address the growing demand for food and nonfood products. In terms of soil management, sustainable intensification means that soil productivity is increased while other soil functions and services, such as carbon storage and habitat for organisms, are simultaneously maintained or even improved. In this paper we provide an overview of research challenges to better understand how emerging soil management practices affect soil processes and functions. We distinguish four categories of soil management practices: spatial arrangements of cropping systems, crops and rotations, mechanical pressures, and inputs into the soil. Key research needs identified for each include nutrient efficiency in agroforestry versus conventional cropping systems, soil-rhizosphere microbiome elucidation to understand the interacting roles of crops and rotations, the effects of soil compaction on soil–plant–atmosphere interactions, and the ecotoxicity of plastics, pharmaceuticals and other pollutants that are introduced into the soil. We establish an interdisciplinary, systemic approach to soil science and include cross-cutting research activities related to process modeling, data management, stakeholder interaction, sustainability assessment and governance. The identification of soil research challenges from the perspective of agricultural management facilitates cooperation between different scientific disciplines in the field of sustainable agricultural production.

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Soil research challenges in response to emerging agricultural soil management practices

The globally increasing demand for food, fiber, and bio-based products interferes with the ability of arable soils to perform their multiple functions and support sustainable development. Sustainable soil management under high production conditions means that soil functions contribute to ecosystem services and biodiversity, natural and economic resources are utilized efficiently, farming remains profitable, and production conditions adhere to ethical and health standards. Research in support of sustainable soil management requires an interdisciplinary approach to three interconnected challenges: (i) understanding the impacts of soil management on soil processes and soil functions; (ii) assessing the sustainability impacts of soil management, taking into account the heterogeneity of geophysical and socioeconomic conditions; and (iii) having a systemic understanding of the driving forces and constraints of farmers’ decision-making on soil management and how governance instruments may, interacting with other driving forces, steer sustainable soil management. The intention of this special issue is to take stock of an emerging interdisciplinary research field addressing the three challenges of sustainable soil management in various geographic settings. In this editorial, we summarize the contributions to the special issue and place them in the context of the state of the art. We conclude with an outline of future research needs.

Assessment and Governance of Sustainable Soil Management

A good understanding of the levels and distribution patterns of soil properties and/or quality indicators is a prerequisite for developing sustainable agricultural land management programs. Traditional assessments of these parameters of soil fertility status are somewhat costly, in both economics and time aspects. Different modelling techniques have been proposed as a useful tool for determination of soil quality indicators and development of soil fertility maps, but to what extent these results are reliable remains under-quantified in many regions worldwide. To address this uncertainty, Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) and Parametric analyses were conducted to ascertain the soil fertility status of a semiarid region in the Northeast of Iran for some selected crops: alfalfa, corn silage, potato, sugar beet, tomato and wheat. The Fuzzy-AHP and Parametric techniques using soil suitability indices were estimated for each crop and each soil delineation was achieved by Ordinary Kriging. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used as a compensatory method to allow tradeoffs among the selected criteria. Our results demonstrated that from the Fuzzy-AHP analysis, the soil fertility indices ranged from moderate to high for production of alfalfa; from low to high for production of corn silage and sugar beet; moderate to high for production of potato and tomato; and from low to moderate for production of wheat. However, the parametric analysis showed soil fertility classes ranging from very low to high for production of all the selected crops. High correlations were also observed between soil fertility indices predicted by both models. Similarly, the capacities of both models to predict soil fertility status for production of the selected crops were also highly correlated. The preference for the cultivation of the selected crops based on the Fuzzy-AHP analysis was sugar beet > corn silage > wheat > alfalfa > tomato > potato. On the other hand, using Parametric techniques, the crops preferences for cultivation ranked as corn silage > wheat > alfalfa > sugar beet > tomato > potato. We concluded that the findings would help to develop sustainable plans of cultivation based on patterns related to soil fertility classes depending on each crop’s requirement.

Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran

 The collective analysis of long-term field experiments (LTFEs), here defined as agricultural
experiments with a minimum duration of 20 years and research in the context of sustainable
soil use and yield, can be used for detecting changes in soil properties and yield such as those induced
by climate change However, information about existing LTFEs is scattered, and the research data
are not easily accessible In this study, meta-information on LTFEs in Germany is compiled and
their spatial representation is analyzed The study is conducted within the framework of the
BonaRes project, which, inter alia, has established a central access point for LTFE information
and research data A total of 205 LTFEs which fit to the definition above are identified Of these,
140 LTFEs are ongoing The land use in 168 LTFEs is arable field crops, in 34 trials grassland, in
2 trials vegetables and in 1 trial pomiculture Field crop LTFEs are categorized into
fertilization ( n=158 ), tillage ( n=38 ) and crop rotation ( n=32 ; multiple nominations
possible) experiments, while all grassland experiments ( n=34 ) deal with fertilization The
spatial representation is analyzed according to the climatic water balance of the growing season
(1 May to 31 October) (CWBg), the Muncheberg Soil Quality Rating (MSQR) and clay content The
results show that, in general, the LTFEs well represent the area shares of both the CWBg and the
MSQR classes Eighty-nine percent of the arable land and 65 % of the grassland in Germany are covered by
the three driest CWBg classes, hosting 89 % and 71 % of the arable and grassland LTFEs,
respectively LTFEs cover all six MSQR classes but with a bias towards the high and very high
soil quality classes LTFEs on arable land are present in all clay content classes according to
the European Soil Data Centre (ESDAC) but with a bias towards the clay content class 4 Grassland LTFEs show a bias towards
the clay content classes 5, 6 and 7, while well representing the other clay content classes,
except clay content class 3, where grassland LTFEs are completely missing The results confirm
the very high potential of LTFE data for spatially differentiated analyses and modeling
However, reuse is restricted by the difficult access to LTFE research data The common database
is an important step in overcoming this restriction

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Long-term Field Experiments in Germany: Classification and spatial Representation

Soils are under increasing utilization pressure, and soil governance is an important element to maintain soil functions and prevent the degradation of soil quality. However, scientific studies about soil governance are rare. In this paper, we focus on the governance mechanism of land rent. Here, a major theoretical assumption is that landowners have higher incentives to maintain soil quality than leaseholders. By using data for German arable land at the county level, we contrast theoretical assumptions about the relationships between landowners, leaseholders and soil quality with empirical evidence based on correlations between arable land rent prices, rent proportions and yield potential. The main finding is that the empirical data contradict the theoretical assumptions to a large degree, i.e., no clear relationship could be discerned between the three parameters of arable land soil quality, rent price and rent proportion. We discuss possible explanations for the revealed contradictions based on the state of research and highlight the need for future research to better understand the potential of arable land tenancy as a governance mechanism for sustainable soil management.

Arable Land Tenancy and Soil Quality in Germany: Contesting Theory with Empirics

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands. 

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

Nahleen Lemke

Papers

Arable Land Tenancy and Soil Quality in Germany: Contesting Theory with Empirics

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems