BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//pretalx.earthmonitor.org//soil-health-now-2025//ZDK39Z BEGIN:VEVENT UID:pretalx-soil-health-now-2025-SCYMZE@pretalx.earthmonitor.org DTSTART:20250408T191000Z DTEND:20250408T191400Z DESCRIPTION:Biological indicators play a critical role in assessing soil fu nctions and overall soil health\, yet they remain underrepresented compare d to chemical and physical indicators. Soil health is strongly influenced by biological activity\, which is essential for nutrient cycling\, organic matter decomposition\, and overall ecosystem productivity. Extracellular enzymatic activities (EEA)\, in particular\, provide valuable insights int o how soil biological activity responds to external factors such as manage ment practices\, climatic changes\, or pollutants. However\, traditional m ethods for measuring EEA typically require complex laboratory setups\, whi ch limits their application in real-time field assessments.\nIn this study \, we introduce a novel\, laboratory-independent soil enzyme activity read er (SEAR). SEAR utilizes an approach where soil enzymes react with fluorog enic substrates embedded in a transparent gel. Upon contact\, the enzymes catalyze a reaction\, producing fluorescent products that are detected on the opposite side of the gel. This enables a rapid and efficient assessmen t of multiple enzymatic activities\, with the potential for analytical rep licates and controls through the use of reaction plates with multiple gel compartments.\nWe validated SEAR by spiking sand samples with varying conc entrations of different enzymes\, thereby establishing operational limits for rate detection\, precision\, and substrate concentration ranges. Our r esults demonstrate that SEAR performs reliably across a wide range of soil types\, including sandy to silty clay loam soils\, acid forest soils (pH < 4)\, carbonate-containing agricultural soils\, and soils with up to 18% organic carbon content. Furthermore\, the device was tested under various environmental conditions\, including soil moistures ranging from 2% to 173 % of water holding capacity and temperatures from 6°C to 50°C\, successf ully demonstrating its versatility for field applications.\nWith SEAR\, so il EEA measurements can be conducted quickly in the field\, eliminating th e need for laboratory access\, sample storage\, or pretreatment\, which ca n alter results. The use of industrially manufactured reaction plates with strict specifications\, combined with an automated data analysis pipeline \, ensures standardized measurements without requiring specialized laborat ory skills.\nIn conclusion\, SEAR represents a significant advancement in soil biological assessment by enabling fast\, accurate\, and field-ready m easurements of EEA. Its potential for standardization and ease of use posi tions it as a powerful tool for soil scientists and environmental managers to assess soil health and functionality in real time across diverse lands capes and conditions. SEAR will also enable ongoing monitoring of soil bio logical activity\, supporting long-term studies and adaptive management pr actices for sustainable land use. DTSTAMP:20260807T120752Z LOCATION:W - Invite SUMMARY:Novel\, laboratory-independent device to measure extracellular enzy matic activity in soils - Jasmin Fetzer URL:https://pretalx.earthmonitor.org/soil-health-now-2025/talk/SCYMZE/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2025-VBMNHA@pretalx.earthmonitor.org DTSTART:20250408T183500Z DTEND:20250408T183900Z DESCRIPTION:Policy demands for robust soil health monitoring are steadily g rowing. Given that soil biota are critical to the ecosystem services soils provide\, biological properties are well-suited as relevant indicators\, complementing physicochemical characteristics. However\, biological proper ties are highly dynamic across spatial and temporal scales\, which present s a challenge when using them for monitoring purposes.\nAs part of AI4Soil Health project\, we conducted a comprehensive soil health assessment in th e experimental grasslands of NEIKER\, where a rotational grazing system ha s been in place since 2013\, compared to a free grazing system. Our object ives were to test innovative methods for measuring soil health and to anal yze the temporal dynamics of soil biological properties in relation to cli matic and pasture conditions.\nPlant and soil samples were collected every three weeks from April to November 2024 at two depths (0-20 cm and 20-50 cm). A broad array of descriptors related to pasture quality\, production\ , and soil physicochemical and biological properties were assessed. Novel methods tested and compared to conventional approaches included: (i) Digit Soil – a tool that measures enzymatic activity\, providing real-time dat a on organic matter decomposition and other key biological processes\; (ii ) microBIOMETER – a portable kit measuring microbial biomass and the fun gi-to-bacteria ratio\; (iii) Slakes – assessing aggregate stability thro ugh a mobile app\; (iv) eDNA and eRNA metabarcoding of 16S rRNA and ITS\, to differentiate total and active prokaryotic and fungal communities\; (v) remote sensing from Planet to provide data on vegetation growth and green ness.\nThe novel diagnostic tools provided cost-effective and high quality soil health assessments. Nevertheless\, preliminary results suggest that differences in soil biological properties were more pronounced across soil depths and over time than between grazing types. Therefore\, their spatia l and temporal variability must be considered when designing a soil health monitoring program. DTSTAMP:20260807T120752Z LOCATION:W - Invite SUMMARY:Novel diagnostic tools for studying the dynamics of soil biological properties under different grazing systems - Lur Epelde\, Sonia Meller\, Lexy Ratering Arntz\, Asier Uribeetxebarria\, Jasmin Fetzer URL:https://pretalx.earthmonitor.org/soil-health-now-2025/talk/VBMNHA/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2025-ACN3EW@pretalx.earthmonitor.org DTSTART:20250408T163000Z DTEND:20250408T164500Z DESCRIPTION:Soils are increasingly rediscovered as a vital resource that un derpins many natural and societal services. Over more than half a century\ , agricultural mechanization and a singular focus on plant production\, su pported by chemical fertilizers\, have led to widespread soil degradation. This reductionistic perspective has relied on soil observations focused o n physico-chemical properties\; properties that can be boosted by chemical additions but ignore the biological and ecological status and functions o f the soil. Recognizing the importance of natural soil processes\, which h ave evolved and been fine-tuned over billions of years\, a new set of indi cators for describing soil health beyond the physico-chemical properties i s required. These indicators should preferably be observable and analyzabl e by farmers\, advisors\, extension workers and other citizen scientists. Methods that directly or indirectly capture the biological and ecological functions include\, for instance i) environmental DNA (eDNA) metabarcoding to characterize the diversity and composition of soil microbial communiti es\, ii) activity rates of key enzymes involved in the main biogeochemical cycles\, iii) the ratio of soil fungi to bacteria\, an indicator of the e xtent of disturbance in soil ecosystems\, iv) aggregate stability\, which is important for soil erosion resistance\, and water and nutrient holding capacity\, and v) water infiltration capacity as a key measure of the soil water absorption\, holding and release potentials. While eDNA requires sp ecialist laboratories and databases\, the other methods are currently avai lable for “Do-It-Yourself” (DIY) testing. In this study\, as part of t he EU-funded project AI4SoilHealth (https://ai4soilhealth.eu) we sampled s oils in Greece\, Sweden\, Finland\, Croatia and Denmark. We applied the ou tlined methods alongside traditional wet chemistry analysis of properties such as carbon\, pH and electrical conductivity\, and the particle size di stribution. These properties were also estimated by leveraging their corre lations with diffuse reflectance Near InfraRed (NIR) spectra and applying machine learning models. We are testing both the robustness of the novel m ethods and their interdependence with more traditional physico-chemical pr operties and soil spectroscopy. We hypothesize that there is a significant positive correlation between novel indicators (e.g. eDNA richness is corr elated to enzymatic activity\, which is correlated to aggregate stability\ , which in turn is correlated to infiltration capacity) and that high scor es of the biological and ecological properties are correlated with\, for i nstance\, soil carbon content. This study explores the potential of these novel methods for more holistic understanding of soil health. DTSTAMP:20260807T120752Z LOCATION:HugoTECH SUMMARY:In-situ soil health indicators beyond physico-chemical properties - Lur Epelde\, Sonia Meller\, Fatemeh Hateffard\, Peter Lehmann\, Jasmin Fe tzer\, Konstantinos Karyotis\, Hsiang-Ju Fan\, Robert Minarik\, Thomas Gum bricht URL:https://pretalx.earthmonitor.org/soil-health-now-2025/talk/ACN3EW/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2025-H3LSEN@pretalx.earthmonitor.org DTSTART:20250408T143000Z DTEND:20250408T144500Z DESCRIPTION:Most soil properties are continuously varying over different sc ales in both space and time. An analysis of field sampled soil is the most accurate method for estimating the spatial distribution of soil propertie s and health indicators at field scale. The field scale spatiotemporal var iation in properties\, however\, requires an effective\, well selected and unbiased probability distribution based sampling framework leveraging the in-situ variability of the relevant environmental covariates. Covariates that can be used for modeling the soil properties over the entire study ar ea. Typically such covariates are represented at spatial rasters derived f rom e.g. topographic data and satellite imagery. In this work\, we introdu ce the probability based balanced stratified sampling algorithm compatible with the proposed European Soil Monitoring law. The algorithm distributes doubly balanced sampling locations over both geographical and feature spa ce constrained by a maximum allowed error – in our case the coefficients of variation. The geographical feature space input data are selected cova riates from the Soil Health Data Cube (https://shdc.ai4soilhealth.eu/). We target the covariates that reflect the distribution of soil health indica tors tested or developed by the EU funded project AI4SoilHealth (https://a i4soilhealth.eu). To begin this process\, a Bethel-inspired optimization a pproach is applied to stratify the study areas. The strata are then used f or computing the approximately equal inclusion probabilities for all units and the number of samples for each strata allocated based on the availabl e auxiliary information. The second stage of the process involves doubly b alancing the algorithm\, with the aim to select the optimal sampling locat ions over geographical and feature space with respect to the stratificatio n. In our study\, we compare the algorithm with 1) simple random sampling\ , 2) feature space coverage sampling and\, 3) the EU wide Land Use and Cov er Area frame Survey (LUCAS) algorithm using legacy data. The advantages o f the novel algorithm are demonstrated in the optimized number of samples while preserving the accuracy of target estimates and mapping accuracy. In the first experiment\, we subsample the legacy random grid samplings. In the second (numerical) experiment\, we use the soil property maps of the S oil Health Data Cube as observed values to design new optimized sampling n etworks with no gridded location constraints. DTSTAMP:20260807T120752Z LOCATION:Expert Room 11 SUMMARY:Probability based stratified sampling for both mapping and estimati ng the population parameters of the soil health indicators at field scale - Thomas Gumbricht\, Jasmin Fetzer\, Konstantinos Karyotis\, Robert Minari k\, Thomas Gumbricht\, Monika Zovko URL:https://pretalx.earthmonitor.org/soil-health-now-2025/talk/H3LSEN/ END:VEVENT END:VCALENDAR