1 of 15European Journal of Soil Science, 2025; 76:e70163 https://doi.org/10.1111/ejss.70163 European Journal of Soil Science SURVEY ARTICLE OPEN ACCESS Monitoring Systems of Agricultural Soils Across Europe Regarding the Upcoming European Soil Monitoring Law Eloïse Mason1,2   | Sophie Cornu3   | Dominique Arrouays1   | Maria Fantappiè4  | Arwyn Jones5  | Sophia Götzinger6  | Heide Spiegel6   | Katrien Oorts7  | Caroline Chartin8  | Luboš Borůvka9   | Evelin Pihlap10  | Elsa Putku10  | Jaakko Heikkinen11   | Line Boulonne1   | Christopher Poeplau12   | Marc Marx13  | Elisa Tagliaferri14  | Ialina Vinci15   | Lauris Leitāns16  | Kęstutis Armolaitis17  | Fenny van Egmond18  | Jozef Kobza19  | Johanna Wetterlind20   | Thomas Drobnik21  | Juliane Hirte22   | József Hefler23  | Bożena Smreczak24  | Lucas Carvalho Gomes25   | Mogens Humlekrog Greve25  | Antonio Bispo1 1INRAE, UR 1508 Info&Sols, Orléans, France  |  2Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, Palaiseau, France  |  3Aix Marseille Univ, CNRS, IRD, Coll de France, INRAE, CEREGE, Aix-en-Provence, France  |  4Consiglio per la Ricerca in Agricoltura e l'analisi dell'Economia Agraria, Centro di ricerca Agricoltura e Ambiente, Florence, Italy  |  5European Commission, Joint Research Centre (JRC), Ispra, Italy  |  6Department for Soil Health and Plant Nutrition, Austrian Agency for Health and Food Safety, Vienna, Austria  |  7Department of Environment & Spatial Development, Government of Flanders, Brussels, Belgium  |  8Department of Sustainability, Systems & Prospective – Unit of Soil, Water and Integrated Crop Production, Walloon Agricultural Research Centre, Gembloux, Belgium  |  9Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Suchdol, Czech Republic  |  10Department of Agricultural Research, Centre of Estonian Rural Research and Knowledge (METK), Jõgeva, Estonia  |  11Natural Resources Institute Finland Luke, Jokioinen, Finland  |  12Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany  |  13German Environment Agency, Dessau-Roßlau, Germany  |  14Ente Regionale per i Servizi all'Agricoltura e alle Foreste (ERSAF), Milano, Italy  |  15Environmental Protection Agency of the Veneto Region (ARPAV), Veneto, Italy  |  16State Plant Protection Service, Riga, Latvia  |  17Lithuanian Research Centre for Agriculture and Forestry (LAMMC), Instituto al. 1, Akademija, Kėdainiai, Lithuania  |  18Wageningen Environmental Research, Wageningen, the Netherlands  |  19National Agricultural and Food Centre, Soil Science and Conservation Research Institute, Bratislava, Slovakia  |  20Department of Soil and Environment, Swedish University of Agricultural Sciences, Skara, Sweden  |  21Federal Office for the Environment (FOEN), Berne, Switzerland  |  22Agroscope, Agroecology and Environment, Soil Quality and Soil Use, Zurich, Switzerland  |  23National Food Chain Safety Office, Directorate of Agricultural Genetic Resources, Budapest, Hungary  |  24Institute of Soil Science and Plant Cultivation – State Research Institute, Pulawy, Poland  |  25Department of Agroecology, Aarhus University, Tjele, Denmark Correspondence: Antonio Bispo (antonio.bispo@inrae.fr) Received: 23 April 2025  |  Revised: 4 July 2025  |  Accepted: 10 July 2025 Funding: This research was developed in the framework of the European Joint Program for SOIL “Towards Climate-Smart Sustainable Management of Agricultural Soils” (EJP SOIL) funded by the European Union Horizon 2020 Research and Innovation Program (Grant agreement no. 862695). Sophia Götzinger acknowledges the European Union's Horizon Europe Research and Innovation Program funding for the BENCHMARKS project (Grant agree- ment: 101091010). Keywords: EJPSOIL | harmonization | LUCAS | monitoring networks | soil health | web-based survey ABSTRACT In Europe, 60%–70% of soils are considered degraded, underscoring the urgent need for consistent monitoring to prevent further degradation and support evidence-based policies for sustainable soil management. Many countries in Europe have implemented one or more soil monitoring systems (SMSs), often established long before the EU-wide “Land Use/Cover Area frame statistical Survey Soil”, LUCAS Soil program. As a result, their sampling strategies and analytical methodologies vary significantly. The proposed EU Directive on Soil Monitoring and Resilience (Soil Monitoring Law, SML) aims to address these differences by estab- lishing a unified framework for systematic soil health monitoring across the EU. This paper assesses the compatibility of the 25 identified SMSs from countries participating in the EJP SOIL Program with the anticipated requirements of the SML. The analy- sis focuses on critical aspects, including sampling strategies, analytical methods, and data accessibility. Results show significant This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2025 The Author(s). European Journal of Soil Science published by John Wiley & Sons Ltd on behalf of British Society of Soil Science. https://doi.org/10.1111/ejss.70163 https://doi.org/10.1111/ejss.70163 https://orcid.org/0000-0002-3537-6900 https://orcid.org/0000-0002-2433-5898 https://orcid.org/0000-0002-6878-6498 https://orcid.org/0000-0003-1285-8509 https://orcid.org/0000-0001-5317-0933 https://orcid.org/0000-0002-6837-1057 https://orcid.org/0000-0002-5789-6691 https://orcid.org/0000-0003-3108-8810 https://orcid.org/0009-0001-9396-6423 https://orcid.org/0000-0003-2821-2999 https://orcid.org/0000-0002-8873-955X https://orcid.org/0000-0002-2105-2470 mailto: mailto:antonio.bispo@inrae.fr http://creativecommons.org/licenses/by/4.0/ http://crossmark.crossref.org/dialog/?doi=10.1111%2Fejss.70163&domain=pdf&date_stamp=2025-08-05 2 of 15 European Journal of Soil Science, 2025 variability in SMS approaches, including sampling depth, monitored land uses, and analytical methods, which limit cross-system comparability. Despite challenges, opportunities for harmonization include aligning SMSs with the LUCAS Soil methodology, developing transfer functions, and adopting scoring systems for soil health evaluation. Enhanced collaboration and data acces- sibility are also emphasized as critical for achieving the SML's objectives. This research provides actionable recommendations to harmonise SMSs with the SML framework, promoting coordinated soil monitoring efforts across Europe to support the EU's goal of achieving healthy soils by 2050. 1   |   Introduction Life on Earth fundamentally relies on healthy soils. Soil health—defined as “the physical, chemical, and biological condition of the soil determining its capacity to function as a vital living system and to provide ecosystem services” (European Commission 2023)—is crucial for maintaining eco- logical balance and supporting human well-being (Veerman et  al. 2020). However, soils are increasingly under threat in Europe, with an estimated 60%–70% of European soils clas- sified as somewhat degraded or unhealthy by 2020 (Panagos, Borrelli, et al. 2024). This highlights an urgent need for reli- able and consistent data on soil to evaluate soil health, par- ticularly for practitioners and policymakers striving to detect soil degradation at an early stage and promote sustainable soil management practices (De Richer Forges and Arrouays 2010). While a qualitative definition of soil health exists, the lack of a widely accepted quantitative framework—such as mea- surable indicators with respective threshold values—poses a significant challenge (Lehmann et al. 2020). This gap compli- cates the translation of the concept into actionable criteria for monitoring and management. Soil monitoring systems (SMSs) are essential for the systematic assessment of soil properties, enabling the detection of spatial and temporal changes (FAO/ ECE  1994). The design of a SMS involves several key deci- sions: (i) determining the appropriate timing and frequency of sampling; (ii) selecting sampling locations in order to well represent the soil variability, land uses and land management; (iii) specifying the sampling depth and methodology, includ- ing whether to sample by pedogenic horizons or fixed depth increments, the tools used, and the collection of a single or composite sample; (iv) deciding which soil properties to ana- lyze and the methods for sample preparation and laboratory analysis; and (v) defining the relevant metadata (e.g., climate and land management) and data to be collected to allow for the accurate interpretation of the results. Most EU Member States have designed and established one or more SMSs within their countries, though the specifics of these SMSs differ between countries. Several studies under- lined the challenges in comparing and sharing data between SMSs, either due to technical discrepancies (e.g., differences in sampling strategies, analytical methods, and data for- mat) but also due to costs and legal requirements (Morvan et al. 2008; van Leeuwen et al. 2017; Cornu et al. 2023; Froger et al. 2024; Meurer et al. 2024). In parallel, the Joint Research Centre of the European Commission (EU-JRC) developed its own SMS, LUCAS Soil, to report on the state of soils across Europe (Orgiazzi et  al.  2018). LUCAS Soil was designed to offer a unified, standardized approach to the collection and analysis of topsoil samples throughout the EU, with results now displayed on the EU Soil Observatory (EUSO) Soil Health Dashboard accessible through the European Soil Data Centre (ESDAC) (Panagos, Broothaerts, et al. 2024). However, recent findings by Froger et al. (2024) reveal significant differences between LUCAS Soil and national SMSs, with the latter gen- erally covering a broader range of land covers, soil types, and regions. Key soil properties, including pH, soil organic carbon, nutrients, and clay content, also showed marked differences between data from LUCAS Soil and national SMSs when an- alyzed on a national scale. Therefore, LUCAS Soil cannot be used as the only EU SMS but should be complemented by na- tional SMSs, which underscores the critical need for harmo- nizing SMSs across EU Member States to achieve comparable evaluations of soil health at the European level. This need for harmonization aligns with broader European objectives to safeguard soil. Central to these efforts is the EU Soil Strategy for 2030 (European Commission  2021), which aims to ensure that all EU soils are in healthy condition by 2050. To support this goal, the European Commission pro- posed the Soil Monitoring and Resilience Directive (European Commission 2023), commonly referred to as the Soil Monitoring Law (SML). This directive aims to establish a unified legal framework to enable systematic monitoring of soil health on all land uses across Member States while promoting sustain- able soil management practices. One objective is to achieve a coordinated and standardized soil monitoring approach across Europe, enabling consistency, comparability, and transparency in soil data collection. The proposed directive sets forth specific requirements for soil sampling and analysis to address existing differences and enable harmonized soil health assessments in all Member States (European Commission 2023). This raises a critical challenge: how do current SMSs reflect the principles outlined in the SML? Additionally, what updates are needed to further enhance their contribution to a unified European soil monitoring framework, having in mind that most Member States have indicated that they do not want to significantly mod- ify their current SMSs (Bispo et al. 2021). By examining 25 SMSs from 24 countries participating in the European Joint Program for Soil (EJP SOIL; www.​ejpso​il.​eu), and the EU-level LUCAS Soil, this research aims to: (i) com- pare existing SMSs focused on agricultural soils; (ii) examine the extent to which these SMSs reflect the proposed SML's objectives; (iii) identify potential challenges or areas where current SMSs could evolve to support the SML's implemen- tation; and (iv) evaluate the feasibility of standardization (all countries apply the same protocols) or harmonization (a way to stitch varying practices together) of SMSs across the EU, and propose actionable recommendations. Although LUCAS Soil is included in the analysis to illustrate technical aspects 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense http://www.ejpsoil.eu 3 of 15 or existing collaborations, it is not used as a benchmark. This paper provides a foundation for guiding the implementation of the SML and advancing coordinated soil monitoring practices across Europe. 2   |   Materials and Methods 2.1   |   Design and Implementation of a Survey to Report SMSs A web-based survey was conducted to review SMSs focusing on agricultural soils (other land uses being potentially also included) across the EJP SOIL countries (Bispo et  al.  2021). Experts from each of the 24 participating countries (Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Italy, Latvia, Lithuania, the Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, and United Kingdom), as well as the EU-JRC, were invited to complete the online survey. The survey was designed to gather detailed information about the agricultural or general SMSs present in each of the EJP SOIL countries, focusing on the sampling protocols and the soil ana- lytical methods, to identify similarities and differences. The sur- vey started with questions to identify the name, objectives, and land-use scope of each SMS. Second, experts were asked for in- formation on the temporal and spatial sampling protocols used in the SMSs. Third, details on the properties measured and the soil analysis methods employed were asked for. Fourth, stake- holders familiar with the topic were asked to provide insights into potential harmonization options, indicating which aspects of their protocols could be adapted or modified. Finally, experts were asked to indicate their willingness to collaborate with LUCAS Soil, to modify their existing SMS protocols, or to add new monitoring sites. It is important to note that these experts were scientists. Their views, therefore, do not represent official national positions. Following a pretest phase and subsequent adjustments, the survey was launched in April 2021 and remained open for 2 months, closing in June 2021. It was administered via an online survey platform. After data collection, thorough data cleaning was conducted to identify and correct any errors or omissions. Clarifications were sought from country experts when needed, and terminologies were standardized to ensure comparability across SMSs. In August 2024, the survey was newly expanded to allow countries to verify and complete any missing informa- tion related to their SMS. Additional questions were included to gather details on the methods used to measure soil prop- erties and to determine whether any new or previously over- looked SMS should be added. In addition to survey responses, Summary • Identifies gaps between EU soil monitoring systems (SMS) and upcoming Soil Monitoring Law (SML). • Provides the first comparative analysis of 25 SMSs vs. proposed SML criteria. • Reveals key differences in sampling strategies, meas- ured parameters, and data access across SMSs. • Proposes practical solutions for harmonizing SMSs while respecting national contexts. FIGURE 1    |    Geographical distribution of SMSs included in the survey conducted across EJP SOIL countries. LUCAS Soil for the EU is not represented. 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 4 of 15 European Journal of Soil Science, 2025 complementary information was extracted from existing sources (Froger et al. 2024; Götzinger and Sandén 2024). 2.2   |   Reported SMSs A total of 29 existing SMSs, including LUCAS Soil for the EU, were reported across 18 countries and the EU (Figure  1). These countries include Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, Latvia, Lithuania, the Netherlands, Poland, Slovakia, Spain, Sweden, and Switzerland. To be included in this study, each SMS had to meet specific criteria. While the SML addresses all types of land use, EJP SOIL narrows its scope to agricultural soils. Consequently, this study excludes SMSs that focus solely on other land uses (e.g., the Swedish Forest Soil Inventory and the Forest Soil Monitoring in Estonia). However, it is important to note that some of the reported SMSs encompass multiple land uses, including but not limited to agricultural soils, as certain countries' SMSs (e.g., France) do not have separate surveys for different land uses. For such SMSs, the reported data (e.g., mon- itored surface area per site) refer to the entire monitoring net- work, not exclusively to agricultural soils. Additionally, at least one monitoring campaign must have been conducted, with fu- ture measurements planned if only one campaign has occurred (excluding Spain due to a lack of follow-up measurements) (Morvan et al. 2008). It is important to note that Portugal, Turkey, Norway, and Slovenia reported not having an SMS in place, though ne- gotiations are ongoing to establish one (e.g., in Portugal and Norway). Similarly, Ireland has initiated a national inventory but has yet to fully implement an SMS. No data were collected from the United Kingdom. Additionally, in some countries, soil monitoring is conducted at the sub-national level under the jurisdiction of regional authorities (e.g., Austria, Belgium, Germany, and Italy). Some countries also operate multiple SMSs focused on different soil properties, as is the case in the Czech Republic, Germany, Belgium, and Latvia. After apply- ing the inclusion and exclusion criteria, we were left with 25 SMSs from 17 of the 24 countries participating in EJP SOIL, along with LUCAS Soil at the EU level. Since not all SMSs responded to every question in the survey, the number of SMSs considered in the analysis may vary between questions. Percentages are therefore calculated based on the subset of SMSs that provided relevant answers. 3   |   Results 3.1   |   Comparative Analysis of Sampling Strategies in Relation to the SML 3.1.1   |   Sampling Design The spatial distribution of sampling sites is a critical component in the design of SMSs. One of the adjusted proposals for the SML specifies that the sampling approach should follow a stratified random scheme, where the strata are defined as soil units, being the combination of soil type and land use. These soil units are sampled, and the results have to be reported at the soil district level, which is are operational or administrative strata consist- ing of multiple soil units. These soil districts are to be defined by each Member State. They could, for example, correspond to Nomenclature of Units for Territorial Statistics (NUTS) level 1 or 2. In addition, “the number and location of the sampling points shall represent the variability of the chosen soil parameters within the soil units with a maximum percent error of 5%”. An analysis of the reported SMSs reveals varying levels of compati- bility with these sampling design requirements: 1. The sampling design of the different SMSs follows either a grid-based design, a stratified approach, or a combi- nation of both. The stratified approach is used by 61% of SMSs (14 out of 23) (Table 1). In these cases, site selection is primarily based on soil-related characteristics (such as soil type, texture, classification, and pedological regions), often in combination with other criteria. For example, site selection considers land use and climatic conditions (Czech Republic_BMP); geographical and soil characteristics (e.g., parent material, soil types and formation) (Hungary), as well as land use (Germany_BD); soil types and texture (Poland and Latvia_nitrogen); soil type, farming type (bio- logical, conventional) and production (horticulture, arbori- culture, animal), and territorial division (Latvia_agro and Latvia_carbon); with the notable exception of Belgium_ Flanders that is only based on land use. A regular grid sampling approach is used by 26% (6 out of 23) of the SMSs, with cell sizes varying between SMSs, ranging from 4 km × 4 km (Austria) to 16 km × 16 km (France). Finally, 13% (3 out of 23) of the SMSs (LUCAS Soil, Finland, and Slovakia) have a combination of both designs. In LUCAS Soil, site selection is first based on a regular grid, but the choice of the cells within that grid to be sampled is then stratified according to land cover type, defined by the area-frame, and does not consider soil type. This raises the question of whether the number of samples is sufficient to accurately represent/cover the diversity of soil units within each SMS. There is no universally optimal design; sampling strategies should be adapted to the indicators, expected outputs, and required precision. Within the SML framework, which relies on soil units, stratified sampling is generally more appropriate, though its advantage diminishes with increas- ing sampling density. 2. The SML mandates soil monitoring across all land use types, including agricultural, forested, natural, and urban areas. Based on the scope of this study, which focuses on SMSs related to agricultural soils, 48% of the current SMSs monitor a large range of land uses, while 52% (13 out of 25) focus exclusively on agricultural soils (Table 1). It is impor- tant to note that this analysis does not account for SMSs dedicated solely to other land uses, such as forest soils (e.g., BZE-Forest in Germany or the Swedish Forest Soil Inventory). While some countries operate separate SMSs for different land uses, this separation can lead to greater heterogeneity in soil health assessment and complicate comparisons across land uses, even within a country. 3. Our analysis reveals a significant variation in the number of sampling sites per SMS, ranging from 30 sites in Estonia to 420,000 in the Czech Republic_AZZP (Table 1). To en- able comparisons, the number of sites was normalized to 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 5 of 15 T A B L E 1      |     D es cr ip tio n of th e re po rt ed S M Ss , c at eg or iz ed b y th e: (i ) m on ito ri ng o bj ec tiv es , w he re p H re pr es en ts p H a nd n ut ri en ts m on ito ri ng , S O C so il or ga ni c ca rb on m on ito ri ng , a nd O o ve ra ll st at e of th e so il (in cl ud in g SO C , p H , a nd n ut ri en ts ); (ii ) a gg re ga te d da ta a cc es si bi lit y, w he re Y es in di ca te s d at a fr ee ly a va ila bl e, N o in di ca te s d at a no t y et a va ila bl e or re st ri ct ed , a nd R eq in di ca te s d at a av ai la bl e up on re qu es t; (ii i) av ai la bi lit y of s oi l m an ag em en t d at a; (i v) te m po ra l s am pl in g, in cl ud in g th e st ar tin g ye ar , w he th er th e SM S is s til l o pe ra tio na l, an d th e in te rv al b et w ee n ca m pa ig ns (i n ye ar s) ; a nd (v ) s pa tia l sa m pl in g, in cl ud in g th e nu m be r o f s am pl in g si te s, th e sa m pl in g de si gn ty pe (S tr at  =  st ra tif ie d re pr es en ta tiv e si te s, G ri d  =  sa m pl in g ba se d on a re gu la r g ri d, M ix  =  co m bi ni ng b ot h st ra tif ie d an d gr id -b as ed ap pr oa ch es ), th e m on ito re d la nd u se s (A ll  =  se ve ra l o r A gr i =  ag ri cu ltu ra l), th e sa m pl in g de pt h ty pe (o ne o r se ve ra l f ix ed , o r de pt h ac co rd in g to s oi l h or iz on s) , a nd th e nu m be r of s am pl es p er d ep th in a co m po si te sa m pl e. C ou nt ri es /S M Ss G en er al d es cr ip ti on Te m po ra l s am pl in g Sp at ia l s am pl in g N am e of th e SM S A im D at a ac ce ss M an ag e- m en t da ta St ar ti n g ye ar St il l ru n n in g In te rv al (y ea rs ) N um be r of s it es D es ig n ty pe L an d us es D ep th ty pe N um be r sa m pl es A us tr ia So il in ve nt or ie s of th e A us tr ia n fe de ra l p ro vi nc es (B ZI s) O R eq N o 19 90 Ye s ≈1 0 20 00 G ri d A ll Se ve ra l 12 –2 0 Be lg iu m _F la nd er s Fl em is h so il or ga ni c ca rb on m on ito ri ng ne tw or k (C m on ) SO C N o Ye s 20 21 Ye s 10 25 94 St ra t A ll Se ve ra l 7– 16 Be lg iu m _W al lo ni a To ta l s oi l or ga ni c ca rb on (C A R BI O SO L) SO C Ye s Ye s 20 04 N o 10 59 0 St ra t A gr i H or iz on s 5 Be lg iu m _r eq ua R EQ U A SU D O Ye s Ye s 20 05 Ye s A ll H or iz on s 25 C ze ch R ep ub lic _A ZZ P A gr oc he m ic al so il te st in g ne tw or k (A ZZ P) O R eq N o 19 62 Ye s ≈ 6 42 0, 00 0 A gr i O ne 30 C ze ch R ep ub lic _B M P Ba sa l s oi l m on ito ri ng (B M P) O R eq N o 19 92 Ye s 6 21 4 St ra t A gr i Se ve ra l 6 D en m ar k D an is h na tio na l sq ua re g ri d (N SG _a gr o) SO C N o Ye s 19 86 Ye s ≈1 0 57 3 G ri d A ll Se ve ra l 10 Es to ni a A gr ic ul tu ra l s oi l m on ito ri ng O Ye s Ye s 19 83 a Ye s 5 30 Tr an se ct A ll H or iz on s Fi nl an d M on ito ri ng of a ra bl e so il ch em ic al q ua lit y (V al se ) O N o Ye s 19 74 Ye s ≈1 0 63 0 M ix A gr i O ne 10 –2 0 (C on tin ue s) 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 6 of 15 European Journal of Soil Science, 2025 C ou nt ri es /S M Ss G en er al d es cr ip ti on Te m po ra l s am pl in g Sp at ia l s am pl in g N am e of th e SM S A im D at a ac ce ss M an ag e- m en t da ta St ar ti n g ye ar St il l ru n n in g In te rv al (y ea rs ) N um be r of s it es D es ig n ty pe L an d us es D ep th ty pe N um be r sa m pl es Fr an ce So il Q ua lit y m on ito ri ng ne tw or k (R M Q S) O Ye s Ye s 20 00 Ye s ≈1 5 22 41 G ri d A ll Se ve ra l 25 G er m an y_ BZ E- LW A gr ic ul tu ra l s oi l co nd iti on su rv ey (B ZE -L W ) SO C Ye s Ye s 20 11 Ye s ≈1 0 31 04 G ri d A gr i Se ve ra l 30 G er m an y_ BD Pe rm an en t s oi l m on ito ri ng in G er m an y (B D ) O N o Pa rt ly 19 85 Ye s 4– 5 80 0 St ra t A ll H or iz on s 15 –2 0 H un ga ry H un ga ri an so il in fo rm at io n an d m on ito ri ng sy st em (T IM ) O Ye s 19 92 Ye s 1 12 36 St ra t A ll Se ve ra l 1 It al y_ Lo m ba rd ia R eg io na l s oi l nu tr ie nt s m on ito ri ng ne tw or k pH R eq N o 20 10 Ye s 1 12 0 St ra t A gr i Se ve ra l 5 It al y_ Ve ne to A R PA V_ U O Q S O Ye s Ye s 20 12 Ye s 5 or 1 b 10 0 St ra t A ll O ne 3 or 1 6b La tv ia _a gr o So il ag ro ch em ic al re se ar ch — re pr es en ta tiv e sa m pl e fr am e O Ye s Ye s 20 18 Ye s 1 62 50 St ra t A gr i O ne 10 –2 0 La tv ia _n itr og en M in er al n itr og en m on ito ri ng pH Ye s Ye s 20 06 Ye s 1 48 St ra t A gr i Se ve ra l 10 La tv ia _c ar bo n SO C m on ito ri ng in re pr es en ta tiv e sa m pl e fr am e SO C Ye s Ye s 20 18 Ye s 1 10 0 St ra t A gr i Se ve ra l 5 Li tu an ia M on ito ri ng o f so il ag ro ch em ic al pr op er tie s O Ye s Ye s 19 93 N o 10 10 ,0 00 St ra t A gr i O ne 15 –2 0 (C on tin ue s) T A B L E 1      |     (C on tin ue d) 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 7 of 15 C ou nt ri es /S M Ss G en er al d es cr ip ti on Te m po ra l s am pl in g Sp at ia l s am pl in g N am e of th e SM S A im D at a ac ce ss M an ag e- m en t da ta St ar ti n g ye ar St il l ru n n in g In te rv al (y ea rs ) N um be r of s it es D es ig n ty pe L an d us es D ep th ty pe N um be r sa m pl es N et he rl an ds N et he rl an ds So il Sa m pl in g Pr og ra m (C C -N L) O N o N o 19 98 Ye s 6 13 92 St ra t A ll Se ve ra l 5 Po la nd M on ito ri ng o f A ra bl e so ils o f Po la nd (M C hG ) O N o 19 95 Ye s 5 21 6 St ra t A gr i O ne 20 Sl ov ak ia Pa rt ia l s oi l m on ito ri ng sy st em (Č M S- P) O Ye s N o 19 93 Ye s 5 31 8 M ix A gr i Se ve ra l 3 or 5 c Sw ed en Sw ed is h so il & cr op in ve nt or y O Ye s Ye s 19 95 a Ye s 10 20 00 G ri d A gr i O ne 10 Sw itz er la nd Sw is s S oi l M on ito ri ng N et w or k (N A BO ) O R eq Ye s 19 84 Ye s 5 11 4 St ra t A ll O ne 25 LU C A S So il La nd U se / C ov er A re a fr am e st at is tic al Su rv ey S oi l O Ye s/ N od N o 20 09 Ye s 3– 4 25 ,0 00 M ix A ll O ne 5 a S ta rt ed in 1 98 3 un til 1 99 2, w as re -e st ab lis he d in 2 00 2. b O ne -y ea r i nt er va l a nd 3 sa m pl es p er d ep th fo r b io lo gi ca l q ua lit y/ 5- ye ar in te rv al a nd 1 6 sa m pl es p er d ep th fo r n itr at es a nd h ea vy m et al s. c F iv e sa m pl es fo r c he m ic al a na ly si s a nd th re e sa m pl es fo r p hy si ca l a na ly si s. d W hi le m os t d at a ar e fr ee ly a cc es si bl e, a cc es s t o co nt am in an t-r el at ed d at a is re st ri ct ed . T A B L E 1      |     (C on tin ue d) 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 8 of 15 European Journal of Soil Science, 2025 the monitored area, using agricultural land for SMSs fo- cused on agricultural soils and total country surface area for SMSs covering all land uses (Figure 2). It is important to note that the monitored area may exclude non-soil- covered surfaces, such as bare rock or water bodies, which can represent a non-negligible part of a country (e.g., 17% in Switzerland). The number of sampling sites per unit area varies widely among SMSs, ranging from one site per 0.1 km2 in the Czech Republic_AZZP to one site for over 400 km2 in Poland, Latvia_nitrogen, or Germany_BD. This potentially depends on the aim of the SMS, for example, if results are only meant to be interpreted at the national or at subnational/regional level. According to Morvan et al. (2008), a density of one sampling site per 300 km2 is recommended for a good coverage of a country's soil var- iability. However, this reference value may no longer be applicable when considering soil units as the basis, as re- quested by the SML. 3.1.2   |   Sample Collection The SML specifies that at least five subsamples should be col- lected to a depth of at least 30 cm, homogenized to create a com- posite sample, and data reported by fixed depth. Additionally, the SML requires that “exact sampling locations should be sam- pled”. An analysis of the reported SMSs reveals varying levels of compatibility with these requirements: 1. Composite sampling is performed in all SMSs except in Estonia, where composite sampling is applied only for heavy metals and pesticide residues, while the main sample collection is done in soil pits. Among the SMSs conducting composite sampling, the majority (88%, 21 out of 24) col- lect at least five subsamples (Table 1). Exceptions include Hungary, which collects fewer subsamples, and Slovakia and Italy_Veneto, where the number depends on the soil property analyzed. 2. About half of the SMSs (12 out of 25) use multiple fixed- depth intervals, while nine SMSs sample only at one fixed depth (the topsoil), and four SMSs rely on pedo- genic horizons (Table  1). For comparison issues, it is recommended to use fixed depths in order to avoid sub- jectivity in sampling, harmonize sampling protocols, and facilitate comparisons between SMSs and over time (Arrouays et al. 2012). However, sampling based on pe- dogenic horizons may better reflect soil formation pro- cesses. Ideally, both approaches should be combined, sampling by fixed depth increments in the site, and by pedogenetic horizons in soil pits dug close to the mon- itoring area. Among SMSs with fixed depths, sampling ranges from shallow layers (e.g., 0–10 cm) to deeper pro- files up to 100 cm (Figure  3). Eleven of these SMSs are currently sampled to a depth of 30 cm, as specified in the SML. Three SMSs (both Czech Republic SMSs and Italy_ Veneto) apply this depth for specific crops or soil proper- ties, while seven SMSs (Finland, Latvia_agro, Lithuania, Poland, Slovakia, Sweden, Switzerland) use shallower sampling depths. It is worth noting that LUCAS Soil used a sampling depth of 20 cm until 2022, when it was in- creased to 30 cm. 3. In terms of sampling geolocation, all SMSs in this study now use GPS coordinates to ensure precise geolocation, FIGURE 2    |    Distribution of monitored surface area (km2) per sampling sites across SMSs, normalized by agricultural land area for SMSs targeting agricultural soils (green) or by total surface area for SMSs with all land uses (blue). 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 9 of 15 with two exceptions: in Germany-BD, GPS use is rec- ommended but not mandatory in all cases, and in the Netherlands, it was implemented only since the 2018 cam- paign, not in 1998. 3.1.3   |   Sampling Time Interval Among the 25 reported SMSs, 23 remain operational. The ma- jority (54%, 13 out of 24) were established in or before 1995, demonstrating a long-standing commitment to soil monitoring. Two (Lithuania and Belgium_Wallonia) have however been discontinued (Table 1). Lithuania is re-establishing monitoring in 2025, and Belgium–Wallonia is developing a new SMS aligned with the SML. The proposed SML specifies that “new soil measurements are performed every six years, within one sampling campaign or as part of a continuous sampling scheme during the indi- cated period of time”. Sampling time intervals between re- peated measurements on the same sites vary widely among the SMSs, ranging from annual to more than 15 years. Most SMSs (63%, 15 out of 24) operate within the 6-year interval suggested by the SML, including LUCAS Soil, which samples FIGURE 3    |    Soil sampling depth intervals by country and land use for SMSs reporting one or more fixed soil depths. Each horizontal line rep- resents the depth intervals specific to a given SMS, with distinctions made for different land uses where applicable. The red dashed line indicates the SML's recommended sampling depth of 30 cm. For Italy_Veneto, the one fixed depth varies: 0–10 cm for biological quality assessments, and 0–30 cm for nitrates and heavy metals. In France, for agricultural tilled or ploughed soils, the upper layer limits depend on ploughing or tilling depths; other- wise, the fixed depth is 0–30 cm. SMSs relying on pedogenic horizons are not represented in this figure. 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 10 of 15 European Journal of Soil Science, 2025 every 3–4 years. However, nine SMSs (Austria, Belgium_ Wallonia, and Belgium_Flanders, Denmark, France, Finland, Germany_BZE-LW, Lithuania, and Sweden) return to the same sampling sites less frequently than every 6 years. The lack of consensus in the literature on optimal sampling in- tervals likely explains the variation observed between SMSs. Some (e.g., Bellamy et al. 2005) suggest reducing the interval to improve the detection of short-term changes, while others (e.g., Desaules et  al.  2010) recommend adapting it to ensure that observed trends exceed methodological uncertainties. One option could be to shorten the interval but avoid analys- ing all soil properties in every campaign. 3.1.4   |   Additional Information In terms of field data, the SML emphasises the importance of closely monitoring the impact of soil management practices and recording the soil type. 68% of SMSs (17 out of 25) collect data on soil management practices (Table 1). This includes in- formation gathered through interviews or surveys with farm- ers or land planners, covering aspects such as inter-campaign periods, the history and evolution of land use, and land man- agement practices including crop rotations, crop manage- ment, and tillage practices. Additionally, 56% of SMSs (14 out of 25) record soil type. Among these, 11 SMSs (79%) rely on national classification standards (Belgium_Wallonia, Czech Republic_BMP, France, Germany_BZE-LW, Germany_BD, Hungary, Italy_Veneto, Lithuania, Netherlands, Slovakia, and Switzerland), 2 (14%) use the World Reference Base for Soil Resources (WRB) classification (LUCAS Soil and Denmark), and 1 (7%) records both the national standard and the WRB results (Estonia). Note that Lithuania's soil classification was harmonized with the WRB classification. This issue is particularly important, as there is no direct correspondence between national soil classification systems and the WRB. Harmonization therefore requires either extensive training of soil surveyors in the WRB or post-processing efforts to con- vert, when feasible, as some information may be missing. 3.2   |   Comparative Analysis of Measured Soil Properties and Corresponding Analytical Methods in Relation to the SML The list of measured soil properties varies among SMSs, re- flecting their diverse objectives (Table 1). The majority (72%, 18 out of 25) aim to assess the overall state of the soil. Some SMSs (20%, 5 out of 25), such as Belgium's (Flanders and Wallonia), Denmark's, Latvia's (carbon), and Germany's (BZE-LW), par- ticularly focus on monitoring soil organic carbon (SOC), al- though other soil properties are also measured. Additionally, 8% (2 out of 25) of the SMSs, namely in Latvia (nitrogen) and Italy (Lombardia), primarily monitor different forms of soil nitrogen in relation to the Nitrate Directive. However, the SML proposes a list of specific soil properties to be analyzed, including physical, chemical, and biological properties (Table  2). Among these, soil organic carbon, particle size distri- bution, extractable phosphorus, carbonate content, total nitro- gen content, effective cation exchange capacity, bulk density, and heavy metals are widely measured. In contrast, properties such as electrical conductivity, pH, soil organisms, and organic contami- nants are only moderately measured, while soil water holding ca- pacity and saturated hydraulic conductivity are rarely measured. Even among the widely measured soil properties, significant vari- ability exists in the laboratory analysis methodologies applied across SMSs, which complicates the comparison of soil health assessments. To address these differences, the SML recommends specific reference methodologies for measuring these proper- ties, most of which are ISO-based, although alternative methods are specified in some cases, such as for extractable phosphorus. Methodologies applied to widely monitored soil properties across SMSs are examined (Table 3). Overall, properties such as organic carbon, bulk density in topsoil, bulk density in subsoil, total nitro- gen content, particle size distribution, and carbonate content show broader adoption of ISO standards compared to others, like heavy metals, effective cation exchange capacity (ECEC), and extractable TABLE 2    |    Soil properties recommended by the SML and number of SMS measuring each parameter (n = 25). We considered as widely measured those properties assessed by more than half of the SMSs, and as rarely measured those included in fewer than 10% of SMSs. Soil properties monitored Number of SMSs measuring each parameter Frequency of measurements pH Water: 13, KCl: 8, CaCl2: 9 Moderately Particle size distribution 20 Widely Effective cation exchange capacity (ECEC) 16 Widely Electrical conductivity 9 Moderately Bulk density Topsoil: 15, Subsoil: 16 Widely Soil water holding capacity 2 Rarely Saturated hydraulic conductivity (Ksat) 2 Rarely Organic carbon 24 Widely Carbonate content 16 Widely Soil organisms 8 Moderately Heavy metals 15 Widely Organic contaminants 6 Moderately Total nitrogen content 16 Widely Extractable phosphorus 18 Widely 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 11 of 15 phosphorus. These results indicate that while the SML has chosen the use of one or two ISO methods to standardise soil data collec- tion across Europe, many SMSs rely on alternative methods. While the SML has chosen the use of one or two ISO methods per prop- erty to standardise data collection across Europe, many SMSs rely on national alternative protocols. These methods should now be compared to evaluate their degree of comparability. 3.3   |   Comparative Analysis of Data Accessibility in Relation to the SML The SML requires Member States to make monitoring results publicly accessible as aggregated data. Among the reported SMSs, 54% (12 out of 22) of the reported SMSs currently provide freely accessible data as aggregated data (Table 1). Data from five SMSs (Austria, both Czech Republic SMSs, Italy_Lombardia, and Switzerland) can be obtained upon request, while five SMSs (Belgium_Flanders, Denmark, Finland, Germany_BD, and the Netherlands) either restrict access or do not offer it at all. Notably, LUCAS Soil offers free access to most data, though access to contaminant-related data remains restricted. 3.4   |   Experts' Feedback on SMS Adaptation and Collaboration Most experts (with the exception of three) were unwilling to make substantial changes to their established SMS protocols, citing the rigidity of long-standing SMSs and the need to preserve historical data comparability. However, 20 out of 21 experts agreed to carry out double sampling exercises to compare their national proto- cols with LUCAS Soil, and 11 indicated openness to adding new monitoring sites (e.g., to improve spatial coverage) or including new measurements (e.g., biodiversity). Such actions would in- crease costs, and as highlighted by seven experts, it is already difficult to maintain existing SMSs due to budgetary constraints. 4   |   Discussion 4.1   |   Current SMS Practices vs. SML Requirements Most European countries have established one or more SMSs, but significant differences in sampling strategies and protocols make results difficult to compare between countries (Bispo TABLE 3    |    Overview of methodologies used to measure soil properties widely monitored across the SMSs, showing their alignment with ISO- recommended methods outlined in the SML. SMSs are categorized by ISO-recommended, comparable, or alternative methods, with parentheses indicating the number of SMSs per category. Properties monitored ISO recommended methods SMSs using The recommended ISO methods Comparable methods Alternative methods Particle size distribution 11277 BE3, DE1, DE2, DK, EE, EU, SE IT2 AT, BE1, CH, CZ2, FI, FR, HU, IT1, LT, NL, PL, SK ECEC 11260 DE1, EU, SE AT, CH, IT2 BE3, CZ1, CZ2, DE2, FR, HU, IT1, NL, PL, SK Bulk density (Topsoil) 11272 BE1, BE2, DE1, DE2, DK, EE, FR, IT2, LT, LV3 EU AT, CH, HU, NL Bulk density (Subsoil) 11272 BE1, BE2, DE1, DE2, DK, FR, IT2, LT, LV3 EU AT, CH, CZ2, HU, NL, SK Organic carbon 10694 BE1, BE2, BE3, CH, DE1, DK, EE, EU, FR, LT, LV3, NL, SE IT2 AT, CZ1, CZ2, DE2, FI, HU, IT1, LV1, PL, SK Carbonate content 10693 BE3, CH, EU, DE2, FR, NL, SK IT2 AT, BE2, CZ1, DE1, DK, HU, PL, SE Heavy metals 54321a AT, BE3, IT2 CH, CZ2, DE2, EE, EU, FI, FR, HU, IT1, PL, SE, SK Total nitrogen content 11261/13878 BE1, BE3, CH, DK, EU, FR, IT2, SE AT, DE1, DE2 CZ2, FI, HU, IT1, NL Extractable phosphorus 11263b EU, FR, IT2 AT, BE3, CH, CZ1, CZ2, DE2, EE, FI, IT1, LT, LV1, NL, PL, SE, SK Abbreviations: AT, Austria; BE1, Belgium_Flanders; BE2, Belgium_Wallonia; BE3, Belgium_requa; CH, Switzerland; CZ1, Czech Republic_AZZP; CZ2, Czech Republic_BMP; DE1, Germany_BZE-LW; DE2, Germany_BD; DK, Denmark; EE, Estonia; EU, LUCAS Soil; FI, Finland; FR, France; HU, Hungary; IT1, Italy_ Lombardia; IT2, Italy_Veneto; LT, Lithuania; LV1, Latvia_agro; LV2, Latvia_nitrogen; LV3, Latvia_carbon; NL, Netherlands; PL, Poland; SE, Sweden; SK, Slovakia. aHeavy metals (As, Sb, Cd, Co, Cr (total), Cu, Hg, Pb, Ni, Tl, V, and Zn) should be measured using ISO 54321 digestion (with Aqua Regia), with optional analysis of bioavailable fractions using ISO 17586 (dilute nitric acid). bISO 11263 is the preferred method; nevertheless, other methods can be used as an alternative. 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 12 of 15 European Journal of Soil Science, 2025 et al. 2021). These differences are shaped by national priorities, environmental conditions, different opinions on the scientifi- cally best sampling design and analytical methods, and resource constraints, reflecting the unique contexts of each SMS design. While some SMSs monitor a broad range of soil properties, oth- ers are limited to specific properties, such as soil organic carbon, pH, or nutrients, leaving other critical soil health aspects unad- dressed. This variability highlights disparities in priorities and capabilities among SMSs, as well as potential gaps in monitoring soil health. The extent to which SMSs reflect the principles proposed in the SML varies depending on the specific criteria evaluated (Figure 4), with LUCAS Soil being the SMS most comparable to the SML framework. This similarity is unsurprising, given that the SML was partially built upon the methodology developed by LUCAS Soil. Other SMSs show greater or lesser divergence from the SML framework, depending on the criteria. For instance, within sam- pling strategies, the highest similarity is observed for composite sampling and information to be recorded, with most SMSs already meeting or exceeding the SML's requirements. However, chal- lenges are more apparent for sampling depth, with many SMSs not sampling the proposed depth of 30 cm. This issue could be ad- dressed if countries agree to sample an additional depth to reach 30 cm (e.g., by collecting both 0–20 and 20–30 cm layers). For soil properties measured, while certain key indicators like soil organic carbon are widely monitored, most SMSs do not measure all re- quired properties, or do not fully use the SML's recommended methods. The observed variability highlights the need to address key gaps and inconsistencies between SMSs and the upcoming SML. Harmonizing will require balancing the development of common monitoring approaches with the need to respect and adapt existing SMSs, as only 3 out of 21 experts expressed willing- ness to make substantial changes to their current protocols. 4.2   |   Spatial Coverage Challenges To improve spatial coverage, many experts showed openness to adding new monitoring sites. The spatial distribution of sam- pling sites is crucial for capturing representative soil health data (Wadoux et al. 2024). The SML requires sampling points to reflect the variability of soil properties within soil units, which are subsets of broader soil districts. However, while the SML also limits error to 5%, it provides no specific guidance on the number of points required per soil unit. This is understandable, as such guidance would need to account for soil and land use variability, which can differ significantly between regions and countries. Given the vari- ability in soil unit and soil district sizes across countries, setting a universal threshold may not be practical or meaningful. Grid-based sampling approaches, employed by several coun- tries, raise further questions about whether such designs can be adapted to meet the SML's stratification requirements. The example of France and the Czech Republic illustrates these challenges, with France highlighting the difficulties posed by high pedo-climatic diversity (Minasny et al. 2010) and the Czech Republic demonstrating the benefits of a dense sampling net- work. France's RMQS network currently monitors 2241 points across 13 administrative regions (NUTS level 1, considered here as soil districts). Assuming an average stratification of 14 soil types and 3 major land uses, this results in: Number of soil units = 13 × 14 × 3 = 546 FIGURE 4    |    Similarities of SMSs with the SML across sampling strategies, soil properties monitored, methods, and data accessibility. Colours indicate levels of similarity: Green (very high similarity), yellow (high similarity), orange (moderate similarity), red (low similarity), and gray (no information). 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 13 of 15 Given 2241 total points, this corresponds to an average of just 4 points per soil unit, which is insufficient to adequately capture soil variability. In contrast, the Czech Republic's Agrochemical Soil Testing Network, focused on agricultural soils, samples approx- imately 420,000 points across 14 administrative regions. With 6 soil types and 1 primary land use per region, the Czech Republic's SMS supports 84 soil units, averaging over 5000 points per unit. In Denmark, the national SMS is based on a 7 × 7 km grid cover- ing the entire country, yet it does not incorporate the stratification principles required by the SML. Greve et al. (2024) evaluated its suitability under several stratification scenarios, revealing that only 30% of national sites and 21% of LUCAS Soil 2018 samples meet the SML's criteria. Addressing these gaps could follow two complementary approaches: adding new points to improve the representation of soil units, integrating LUCAS points to support harmonization efforts, or a combination of both. 4.3   |   Harmonization Opportunities Most SMSs differ from the proposed SML guidelines in terms of sampling procedures, parameter selection, and measurement methods, making it challenging to compare results across SMSs. One way to address this challenge is through the development of transfer functions between laboratory methods of the same soil property and between sampling protocols. These can be derived by a double sampling campaign, where soil samples are collected and analyzed following both the LUCAS protocol and (if differ- ent) the SMS-specific protocol, as already done in Switzerland and Austria (Fernández-Ugalde et  al.  2020; Baumgarten et al. 2021). This is complemented by double analysis, in which the samples are analyzed using both the SMS-specific methods and the LUCAS methods for the various properties. This ap- proach enables the derivation, testing, and validation of transfer functions, which can be used to convert results obtained with one method into an equivalent result for another. Transfer func- tions were established for several properties, for example, pH, or- ganic carbon content, particle size distribution, and phosphorus levels (Arrouays et al. 2015; Kabała et al. 2016; Hu et al. 2021). Note that such transfer functions may also introduce substantial uncertainties in the results, depending on the chosen equations (Steinfurth et al. 2021). The variation in laboratory quality across the EU further complicates the comparability of soil data. To ad- dress this, the SML proposes the inclusion of minimum require- ments for quality control in laboratories analysing soil samples. Another potential method to harmonise soil health assessments across SMSs, even if not yet included in the SML requirements, is the use of scores. This approach, used in countries like the United States and Canada, involves translating soil measurements into scores based on the relationship between the soil indicators and relevant soil functions (Fine et al. 2017; Amgain et al. 2022; Gauthier et al. 2023; Poppiel et al. 2025). These individual scores are then aggregated into an overall soil health score, providing an evaluation of soil health. Importantly, scoring systems can be adapted to local contexts by incorporating regional variations in soil types, pedo-climatic conditions, land use, and management practices. In Europe, initiatives like EJP SOIL are testing data- driven scoring systems based on the statistical distribution of soil data at national and regional scales. While still under evaluation, this approach holds potential for improving comparability across SMSs, aligning with the SML's requirements, and accommodating local specificities. However, scoring functions can also introduce more discrepancies among different datasets. 4.4   |   Balancing Data Availability and Privacy Data accessibility remains a significant challenge, with limited consensus on standards for ensuring interoperability and broad availability. This issue is compounded by the fact that much of the data is georeferenced and, in several countries, can be classified as personal data subject to General Data Protection Regulation (GDPR) constraints (Fantappiè et  al.  2021; Cornu et  al.  2023). While such restrictions could be avoided by aggregating and dis- seminating data at the soil unit level (e.g., reporting a mean value for a whole soil unit instead of all georeferenced individual mea- surements) to ensure both privacy and accessibility, as proposed in the SML, it is important to note that many applications of soil monitoring data require access to geographically precise, non- aggregated data (e.g., for digital soil mapping application). An option could be to provide the data with approximate coordinates and an uncertainty on these coordinates, making sure that the level of uncertainty is sufficient for the sampling location not to be identified. 5   |   Conclusion This study highlights the significant variability in the design and implementation of SMSs across countries participating in EJP SOIL. While this diversity reflects national priorities, en- vironmental conditions, different scientific opinions on the most appropriate sampling design and analytical methods, and resource constraints, it also poses challenges for harmonizing soil monitoring efforts and addressing the requirements of the upcoming SML. Key differences were identified in the sampling design and monitored properties, which hamper the compara- bility of results and the ability to monitor soil health effectively at the EU level (Froger et al. 2024). Despite these challenges, several opportunities exist to harmo- nise SMS with the upcoming SML. For existing SMSs, harmo- nization can be pursued by adding new monitoring points to address gaps in spatial coverage, integrating scoring systems for soil health evaluation, or developing transfer functions to recon- cile methodological differences. For new descriptors included in the SML but not yet routinely measured in existing SMSs (e.g., biodiversity indicators, pesticides, PFAS, and microplastics), there is a clear opportunity to define standard sampling and measurement protocols from the outset. Finally, the same oc- curs for countries where no SMS currently exists; the SML can serve as a standard for designing new systems. This study focuses on SMSs primarily targeting agricultural soils. However, some countries have additional monitoring net- works dedicated to other land uses and soil-related processes. Including these SMSs, as well as SMSs from EU Member States outside EJP SOIL, will enhance the complexity of harmonizing existing data to meet the requirements of the SML framework. Additionally, although this study evaluates several key soil properties monitored by SMSs, it does not cover certain aspects 13652389, 2025, 4, D ow nloaded from https://bsssjournals.onlinelibrary.w iley.com /doi/10.1111/ejss.70163 by L uonnonvarakeskus, W iley O nline L ibrary on [25/08/2025]. See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense 14 of 15 European Journal of Soil Science, 2025 explicitly recommended by the SML, such as soil erosion and soil sealing. These soil threats are crucial for meeting the com- prehensive objectives set by the SML. Future research should assess the capacity of existing SMSs to monitor these processes. Author Contributions Eloïse Mason: writing – original draft, writing – review and editing, data curation, investigation, formal analysis, visualization, methodol- ogy, project administration, validation. Sophie Cornu: validation, writ- ing – original draft, writing – review and editing, methodology, formal analysis. Dominique Arrouays: writing – original draft, writing – re- view and editing, methodology, investigation. Maria Fantappiè: con- ceptualization, writing – original draft, writing – review and editing, methodology. Arwyn Jones: methodology, conceptualization, investi- gation. Sophia Götzinger: writing – original draft, writing – review and editing, investigation. Heide Spiegel: investigation, writing – original draft, writing – review and editing. Katrien Oorts: investigation, writ- ing – original draft, writing – review and editing. Caroline Chartin: in- vestigation, writing – original draft, writing – review and editing. Luboš Borůvka: investigation, writing – original draft, writing – review and editing. Evelin Pihlap: investigation, writing – original draft, writing – review and editing. Elsa Putku: investigation, writing – original draft, writing – review and editing. Jaakko Heikkinen: investigation, writing – original draft, writing – review and editing. Line Boulonne: investiga- tion, writing – original draft, writing – review and editing. Christopher Poeplau: investigation, writing – original draft, writing – review and editing. Marc Marx: investigation, writing – original draft, writing – review and editing. Elisa Tagliaferri: investigation, writing – original draft, writing – review and editing. Ialina Vinci: investigation, writing – original draft, writing – review and editing. Lauris Leitāns: investi- gation, writing – original draft, writing – review and editing. Kęstutis Armolaitis: investigation, writing – review and editing, writing – orig- inal draft. Fenny van Egmond: investigation, writing – original draft, writing – review and editing. Jozef Kobza: investigation, writing – orig- inal draft, writing – review and editing. Johanna Wetterlind: investi- gation, writing – original draft, writing – review and editing. Thomas Drobnik: investigation, writing – original draft, writing – review and editing. Juliane Hirte: investigation, writing – original draft, writing – review and editing. József Hefler: investigation, writing – original draft, writing – review and editing. Bożena Smreczak: investigation, writing – review and editing, writing – original draft. Lucas Carvalho Gomes: investigation, writing – original draft, writing – review and editing. Mogens Humlekrog Greve: investigation, writing – original draft, writing – review and editing. 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