The proposed system of evaluating ecosystem services in line with the SDGs can be the basis for an attractive and relatively simple regulatory system based on comparing indicator values, as discussed above, with thresholds that still need to be developed in most cases. Such a system should be based on measurements in system experiments on experimental farms and in “Living Labs”, applying relatively simple field methods, which farmers will welcome, as they complain about the current complex systems. This requires the development of new measuring methods that can produce a lot of data in a short period of time, allowing a scientifically sound evaluation of spatial variability. Soil health studies are important as soil health makes major contributions to achieving ecosystem services, as was shown with modeling studies for some Italian soils ^{[12][13][14][15]}.

Of particular interest is a link with the future Common Agricultural Policy (2021–2027) where payments for ecosystem services are now one of the options being discussed. This could mean a substantial payment when all ecosystem services have a sufficiently high level. If one or more of the services are inadequate, a focused subsidy on the lacking services can be considered, as a case study in Switzerland has shown, where subsidies were based on introducing cover crops and on applying minimum tillage to enhance carbon sequestration. This program turned out to be highly successful ^[16].

The system presented in this entry is based on the selection of a limited set of relatively simple indicators directly coupled to an ecosystem service linked to SDGs or, separately, to soil health contributing to ecosystem services. Along these lines, the application of a soil indicator set is being explored in the Netherlands ^[17].

As discussed, production levels were well-documented and can be supported by modeling the soil–water–atmosphere–plant system. Several well-tested models are available ^[18][19][20]. Basic soil data, such as texture, bulk density and organic matter content, are used in so-called pedotransfer functions to predict hydraulic soil characteristics needed for modeling such as hydraulic conductivity and moisture retention ^[21][22]. However, aside from modeling, measurements of real yields are still also necessary to validate the models. Researchers advocate for attention to climate change, which will have major effects on food production. Obviously, only modelling can handle future climate scenarios (SDG2). Healthy food, based on healthy crops, can be assessed by existing health regulations’ defining thresholds. This is, however, a highly dynamic field of study as new pollutants arrive (SDG3). The quality of ground and surface waters (SDG6) could only be derived from national monitoring systems and are not yet part of monitoring systems at the farm level. This would be required when assessing “Living Labs” in future. Modern automated monitoring systems are available to obtain hard data that do not depend on debatable interpolations from current, often far-away, measurement locations. Energy use (SDG7) is less relevant from a national point of view but is important for individual farmers as a cost item to be reduced. The emission of greenhouse gases (SDG13) is important and is now being estimated by modeling, even though the particular soil being considered here was not yet covered. However, modeling is only justified when the models are properly validated with measured data. This validation process is still rather undefined, and direct measurements are therefore needed. The available measurement methods using small on-site chambers are cumbersome and costly while only providing point data at specific moments in time. Applying frequent satellite images would be highly attractive, as is being explored now by the European Space Agency (https://www.esa.int, assessed on 20 February 2022). This type of work needs a high priority and strong support. (SDG15) refers to land degradation, where the indicators for soil health are relevant to assess soil degradation. Biodiversity is, however, still undefined in terms of specific indicators for the entire farming system. Policy decisions on future land-use scenarios are therefore urgently needed. Innovative methods for measuring ecosystem services are summarized in Table 1.

Soil contributions to ecosystem services can be framed in terms of soil health, for which several indicators have been defined as discussed in this entry. Soil as a favorable environment for root growth is key for all ecosystem services contributing to the five SDGs being considered. Soil structure, the organic matter content and soil moisture regimes are key indicators for soil health, assuming a lack of pollutants and adequate levels of nutrients by fertilization. The current standard methods assessing soil structure, as reviewed above for bulk density, use relatively small soil samples and are costly and laborious as they require laboratory analysis, not providing instant data. Standard deviations among replicate measurements are relatively high due to small sample volumes and, considering 95% confidence intervals, hardly allow the distinction of differences among treatments, let alone among different soils. Measuring the penetration resistance is attractive, as many observations can be instantly made. An important factor causing variation among measurements is moisture content; so, measurements will have to be made at certain periods only, preferably only when the soil is at field capacity. Innovative techniques are available to allow rapid, multiple and cheap measurements for both organic matter content and bulk density once equipment has been obtained. The application of proximal sensing for organic matter ^[23][24][25] and further testing of radiation techniques for measuring bulk density (e.g., ^[26]) are highly recommended. Field research on the impact of present and past soil management on the organic matter content of a given type of soil can provide valuable insights on the effects of management that differ significantly among soils. Organic matter contents were sampled at fifty farms on two prominent Dutch soil types, and the study could relate actual organic matter content very well (R² > 0.8) with current and past management, providing valuable suggestions for future management practices ^[27][28]. There are thousands of experiments out there in the field waiting to be discovered! Soil biodiversity is being studied widely, but so far, standard techniques have not been suggested or approved. Doing so is a high priority as soil biodiversity plays a key role in soil functioning. Applying proxies, such as the organic matter content, as in this study, needs improvement.

The simulation of soil moisture regimes combined with nutrient dynamics in the soil–water–atmosphere–plant system can provide important information for precision agriculture where nutrient inputs are fine-tuned to the needs of plants, optimizing the soil fertility regime. This can result in substantial savings of fertilizer input and costs of up to at least 10%, thereby also reducing leaching and groundwater pollution by excess nutrients. A study on precision fertilization consisted of the preparation of a functional soil map with four different soil units, derived from the interpolation of point data, with a distinct behavior in terms of water regimes and nitrogen dynamics. Modeling was applied to determine the critical moment when the available nitrogen reached a threshold. Then, fertilization was needed. This moment was different for the different soil units, providing a basis for applying precision techniques ^[29]. Again, robots can in future perform the task of fertilization, strongly reducing labor demand and reducing pressures on soil by traditional fertilization equipment.