(Press-News.org) Scientists are invited to submit their latest research to a new special issue focusing on the intersection of artificial intelligence (AI) and biochar for sustainable land management. The special issue, titled "Artificial Intelligence in Biochar Ecological Applications: Advances for Soil Carbon and Sustainability in Agricultural, Forest, and Grassland Ecosystems," will be published in the journal Biochar.
Agricultural land, forests, and grasslands cover most of the Earth's terrestrial surface, playing a central role in the global carbon cycle, ecosystem services, and human well-being. Biochar, a charcoal-like substance produced from plant matter, is a promising nature-based solution. It can improve soil fertility, boost carbon storage, and help restore degraded land across these vital ecosystems.
However, predicting and optimizing biochar's effects remains challenging due to complex environmental processes and differences across landscapes. The rapid advancement of AI, remote sensing, and big data analytics now offers unprecedented tools to tackle these challenges. AI-driven approaches can help identify mechanisms, create predictive models, and support smarter land management decisions.
This special issue aims to gather cutting-edge research at the crossroads of AI, biochar, and terrestrial ecosystem management. It will highlight work that uses intelligent technologies to monitor, quantify, and enhance the benefits of biochar application.
Topics of interest include, but are not limited to:
AI + Remote/Proximal Sensing
Remote sensing, proximal sensing, and machine learning approaches for monitoring soil carbon, nutrients, and vegetation responses to biochar applications across agricultural, forest, and grassland ecosystems.
Carbon Cycling and Ecosystem Sustainability
AI-driven assessments of biochar impacts on soil carbon sequestration, greenhouse gas emissions, and carbon neutrality across agro–forest–grassland systems.
Land Degradation and Ecosystem Restoration
Applications of intelligent algorithms in biochar-based restoration of degraded soils and ecosystems in croplands, forests, and grasslands.
Multi-source Data Integration and Modelling
AI models integrating climate, soil, vegetation, management, and socio-economic data to predict long-term ecological impacts of biochar across terrestrial ecosystems.
Intelligent Decision Support and Policy Evaluation
AI-assisted frameworks for optimizing biochar management, evaluating ecosystem service trade-offs, and supporting sustainable land-use and climate policies.
Case Studies and Methodological Innovations
Empirical studies and novel methodologies for AI–biochar applications in representative systems, including croplands, agroforestry systems, alpine grasslands, agro-pastoral ecotones, and arid ecosystems.
The special issue welcomes submissions in the form of Reviews, Original Research, Letters, Short Communications, and Perspectives.
Submissions are now open. The deadline for submissions is October 31, 2026.
For more information and to submit a manuscript, please visit the special issue homepage:
https://link.springer.com/journal/42773/updates/27838604
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About Biochar
Biochar (e-ISSN: 2524-7867) is the first journal dedicated exclusively to biochar research, spanning agronomy, environmental science, and materials science. It publishes original studies on biochar production, processing, and applications—such as bioenergy, environmental remediation, soil enhancement, climate mitigation, water treatment, and sustainability analysis. The journal serves as an innovative and professional platform for global researchers to share advances in this rapidly expanding field.
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Call for papers: AI in biochar research for sustainable land ecosystems
Special issue explores how artificial intelligence can enhance soil carbon storage and ecosystem health in farmlands, forests, and grasslands
2026-01-23
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[Press-News.org] Call for papers: AI in biochar research for sustainable land ecosystemsSpecial issue explores how artificial intelligence can enhance soil carbon storage and ecosystem health in farmlands, forests, and grasslands