BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//pretalx.earthmonitor.org//soil-health-now-2026//KXWYW8 BEGIN:VTIMEZONE TZID:Europe/Athens BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET TZOFFSETFROM:+0300 TZOFFSETTO:+0200 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST TZOFFSETFROM:+0200 TZOFFSETTO:+0300 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-soil-health-now-2026-FSMT7Z@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261208T160000 DTEND;TZID=Europe/Athens:20261208T161500 DESCRIPTION:Soil biodiversity plays a central role in regulating ecosystem functioning and maintaining soil health through its influence on nutrient cycling\, carbon dynamics\, soil structure formation and water regulation. At the same time\, environmental change and land-use intensification alte r soil physicochemical conditions and vegetation dynamics\, with cascading consequences for belowground communities and ecosystem functioning. Despi te increasing recognition of the importance of soil biodiversity within Eu ropean soil health initiatives\, identifying scalable and operational indi cators capable of capturing soil ecological responses across contrasting p edoclimatic regions remains a major challenge.\nUsing harmonized datasets generated within the SOB4ES project\, we integrated soil biodiversity indi cators\, soil physicochemical properties\, land-use information and Earth Observation-derived climatic\, vegetation and topographic variables across European sites. The analyses employed machine-learning approaches and exp lainable artificial intelligence methods to investigate large-scale relati onships among soil biodiversity\, environmental gradients and ecosystem se rvice-related functions under different climatic and land-use contexts.\nA cross multiple organism groups\, diversity-based metrics generally showed stronger and more consistent relationships with environmental gradients th an abundance- or density-based indicators\, supporting their relevance for large-scale soil health assessment frameworks. Soil pH\, soil organic car bon\, moisture conditions and soil texture parameters emerged as dominant cross-taxa predictors\, while climatic and vegetation-related variables de rived from Earth Observation data explained a substantial proportion of sp atial variation in belowground biodiversity patterns. However\, the influe nce of environmental predictors frequently differed among land-use types\, indicating that biodiversity responses are strongly context-dependent and shaped by interactions among soil conditions\, vegetation structure and m anagement intensity. \n\nOverall\, the integration of harmonized biodivers ity observations\, remote-sensing data and machine-learning approaches dem onstrated strong potential for supporting spatially explicit soil health m onitoring and the identification of robust biological indicators under glo bal change and land-use pressures across Europe.\n\nAcknowledgments: The w ork and all the authors were supported by the Horizon Europe project SOB4E S under Grant Agreement No. 101112831. We acknowledge all participating in vestigators from the SOB4ES consortium who contributed to the existing sam ple collection and the field sampling for the generation of the spatial da tabase used in the current analysis. Partners from KNAW\, UVIGO\, NUID UCD \, UNICT\, KU Leuven\, CU\, ARO\, IBB\, UL\, UoC\, SLU\, EFWSL\, Airfield\ , MFO\, and INRAe provided these contributions. DTSTAMP:20260825T180211Z LOCATION:Amphitheater II SUMMARY:Using earth observation and machine learning to identify environmen tal drivers and land-use pressures of soil biodiversity across European la ndscapes - Maria Marily Christou\, Snezhana Mourouzidou URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/FSMT7Z/ END:VEVENT BEGIN:VEVENT UID:pretalx-soil-health-now-2026-TZFHT8@pretalx.earthmonitor.org DTSTART;TZID=Europe/Athens:20261207T170000 DTEND;TZID=Europe/Athens:20261207T180000 DESCRIPTION:Extreme weather events\, including droughts\, heatwaves\, inten se rainfall and episodic non-seasonal frosts\, are increasingly disrupting soil functionality and agricultural production stability. In Mediterranea n agricultural landscapes\, these pressures interact with long-standing so il degradation processes such as declining organic matter\, erosion\, sali nisation\, compaction and reduced biological activity\, creating new risks for food security and land management. There is therefore a growing need for integrated\, spatially explicit tools that can assess not only the cur rent condition of soils\, but also their capacity to buffer climatic stres s\, recover after disturbance and support stable crop production over time . \n\nThe Soil Resilience and Food Security Index (SRFSI) is proposed as a composite framework for evaluating the resilience of agricultural landsca pes under climate-extreme conditions. The index integrates four complement ary dimensions: Soil Resilience Capacity\, representing the ability of soi ls to sustain carbon storage\, water regulation\, nutrient cycling\, struc tural stability and biological functioning\; Biological and Agroecological Management\, capturing the contribution of practices such as compost and manure application\, biofertilisers\, microbial inoculants\, cover crops\, crop-residue retention\, reduced tillage\, diversified rotations and land scape elements that enhance biodiversity and water regulation\; Climate-Ex treme Resilience\, assessing exposure and response to drought\, heatwaves\ , heavy rainfall\, erosion risk\, salinity stress and crop-relevant non-se asonal frosts\; and Food Security Stability\, reflecting yield stability\, stress-year yield retention\, production reliability and post-event recov ery. \n\nThrough SRFSI\, a framework is proposed that can function both as a baseline diagnostic approach and as a scenario-based tool for assessing soil and production resilience. By comparing index scores under current c onditions\, climate-extreme scenarios and post-intervention conditions\, r esilience loss and adaptation gain can be quantified across different crop s\, soil types and management systems. Remote-sensing proxies\, open soil and climate datasets\, field measurements and farm-management information are combined to support implementation at field\, farm\, municipal and reg ional scales. This approach is intended to support the identification of v ulnerable agricultural areas\, the evaluation of biological and agroecolog ical soil-management interventions\, and the design of strategies that hel p maintain productive\, resilient and food-secure agricultural systems und er increasing climate uncertainty. DTSTAMP:20260825T180211Z LOCATION:Basement (Foyer) SUMMARY:Towards a Soil Resilience and Food Security Index for Climate-Resil ient Agricultural Landscapes - Konstantinos Karyotis\, Maria Marily Christ ou URL:https://pretalx.earthmonitor.org/soil-health-now-2026/talk/TZFHT8/ END:VEVENT END:VCALENDAR