Description
From field data to forecasts: tools, models, and databases supporting predictive understanding of ecosystem responses.
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Dr Alessandro Oggioni (National Research Council of Italy (CNR))01/10/2026, 08:30Oral
From field data to forecasts: tools, models, and databases supporting predictive understanding of ecosystem responses.
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Augustin de la Brosse (CNRS)01/10/2026, 09:00Session 7: Digital Ecosystems – Data Integration and ModelingOral
Adult emerging aquatic insects provide ecosystem services at the landscape scale. Their emergence from water areas represents a transfer of energy from aquatic to terrestrial ecosystems. In particular, their carcasses and excreta subsidize terrestrial systems with organic matter. Agricultural intensification is reshaping aquatic and terrestrial ecosystems, impacting sensitive taxa, such as...
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Marco Bascietto (CREA - Council for Agricultural Research and Economics)01/10/2026, 09:15Session 7: Digital Ecosystems – Data Integration and ModelingOral
Ecological research infrastructures increasingly require environmental context to support ecosystem experiments, biodiversity analyses and cross-site syntheses. Open satellite archives and cloud platforms now provide unprecedented access to Earth Observation (EO) data. However, these products often remain difficult to integrate into ecological workflows because they require substantial...
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Dr Glory Oden (North West University Potchefstroom)01/10/2026, 09:30Session 7: Digital Ecosystems – Data Integration and ModelingOral
Africa made significant advances in palynological research, spanning multiple research fields such as paleoecology, palaeoclimatology, archaeology, petroleum exploration, aerobiology, melissopalynology, biodiversity conservation, and environmental management. However, research capacity and disciplinary focus vary across the continent. In Southern Africa, South Africa hosts the most...
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Prof. Federica Mandreoli (University of Modena and Reggio Emilia)01/10/2026, 09:45Session 7: Digital Ecosystems – Data Integration and ModelingOral
Recent advances in manufacturing environments have stimulated the development of intelligent assistants that support human decision making through natural-language interaction, AI-assisted analytics, and seamless access to complex data ecosystems. Meanwhile, Research Infrastructures (RIs) and experimental ecosystem science are becoming increasingly data-intensive, generating large volumes of...
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Alexis Comar (Hiphen)01/10/2026, 10:00Session 7: Digital Ecosystems – Data Integration and ModelingOral
High-throughput plant phenotyping has generated unprecedented volumes of heterogeneous data originating from field platforms, drones, proximal sensors and controlled-environment facilities. While research infrastructures have made remarkable progress in developing standards, data management practices and interoperable digital ecosystems, an important challenge remains: transforming these...
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Laura Miketin (Faculty of Forestry and Wood Technology)01/10/2026, 10:15Session 7: Digital Ecosystems – Data Integration and ModelingOral
This contribution presents a digital biomonitoring network developed to monitor forest growth dynamics in the Dinaric Alps, a mountain region of the Western Balkans where Adriatic, montane and continental climatic influences meet over short distances. This strong spatial heterogeneity makes the region suitable for studying how forest ecosystems respond to local differences in temperature,...
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Nicola D'Ascenzo (RE IMAGING)01/10/2026, 10:30Session 7: Digital Ecosystems – Data Integration and ModelingOral
Background and Objectives - Crop growth models are essential for modern Decision Support Systems (DSS) to optimize water and nitrogen (N) management. However, conventional models rely strictly on macro-scale inputs (weather, soil, and satellite imaging), ignoring the rapid metabolic and biophysical pathways that trigger within 5 to 120 minutes of fertilizer application. This research aims to...
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Prof. Jayaraju Nadimikeri (Yogi Vemana University, KADAPA)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
India has 7,516 km of coastline, of which the mainland accounts for 5,422 km. The shoreline is one of the rapidly changing linear features of the coastal zone which is dynamic in nature. The issue of shoreline changes due to sea level rise over the next century has increasingly become a major social, economic and environmental concern to a large number of countries along the coast, where it...
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S. Monaco (CREA-IT Research Centre for Engineering and Agro-Food Processing, Turin, Italy)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
Introduction
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The EU Carbon Removals and Carbon Farming (CF) Certification Framework (Reg. EU/2024/3012) demands transparent methodologies to quantify net carbon benefits. Tier-3 Monitoring, Reporting, and Verification (MRV) systems are required for CF practices, but data scarcity limits model scalability across heterogeneous, fragmented agricultural landscapes. Within the MRV4SOC project,... -
Riaz Ali (Minhaj University Lahore)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
A simple and reliable RP-HPLC-DAD method was developed and validated for the simultaneous determination of seventeen β-lactam and non-β-lactam active pharmaceutical ingredients (APIs) using a single chromatographic system. Separation was achieved on a Phenosphere C18 column (100 mm × 4.6 mm, 5 μm) employing tetraheptylammonium bromide (THAB) aqueous solution and acetonitrile as the mobile...
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Prof. Björm Klöve (University of Oulu)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
DIWA (Digital Waters) Flagship is Finland’s national flagship programme for water research and digitalization, bringing together the University of Oulu, University of Turku, Aalto University, Finnish Environment Institute (SYKE), Finnish Geospatial Research Institute (FGI), and Finnish Meteorological Institute (FMI). Through its source-to-sea and critical-zone research framework, DIWA...
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Omobola Eko (University of Tuscia)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
Environmental research infrastructures (RIs) generate extensive datasets on ecosystem processes, biodiversity, and climate dynamics. However, despite major advancements in open data accessibility and FAIR principles, translating these data into actionable knowledge for planners, policymakers, and land managers remains a critical challenge. This study aims to identify key barriers to the...
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91. From Field to Region: Digital Research Infrastructures for Multi-Scale Agro-Ecosystem MonitoringMargot Verhulst (VITO)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
Understanding agro-ecosystem dynamics across spatial and temporal scales remains a major challenge in agricultural and environmental research. Experimental facilities and phenotyping platforms provide detailed observations of ecosystem processes and crop performance, while Earth Observation (EO) systems enable continuous monitoring across larger spatial extents. VITO has developed and operates...
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Marco Sozzi (Università di Padova)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
Background and objectives
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Digital characterization of agricultural spraying can provide high-resolution data to support more precise and predictive management of pesticide application in agroecosystems. Pulse Width Modulation (PWM) systems are increasingly used in variable-rate spraying because they regulate flow rate while maintaining a relatively stable operating pressure. However,... -
Florent Massol (CNRS)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
The ISIA web application is a project management tool designed for research teams and staff at our experimental facilities.
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ISIA enables the networking of research infrastructure installations and offers a wide range of features, from a service catalog to the collection of FAIR metadata. -
François Rincon (SETE, CNRS)Session 7: Digital Ecosystems – Data Integration and ModelingPoster
There is a pressing need for a quantitative understanding of how biodiversity reacts in space and time to strong anthropogenic and global warming pressures, and for innovative large-scale ecological conservation strategies integrating the strongly-coupled, collective (many-species), multi-scale character (in space and time) of the problem at hand. A prerequisite for this however is to gain...
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