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Prediction of Carbon and Nitrogen Cycles and Soil Functions in Forest Ecosystems: From Molecular Mechanisms to Landscape Management
This special issue belongs to the section “Forest Soil“.
Special Issue Information
Dear Colleagues,
Forest ecosystems, serving as the largest carbon sink and nitrogen reservoir within terrestrial ecosystems, play a pivotal role in global biogeochemical cycles and climate regulation. However, in recent years, these ecosystems have encountered unprecedented pressures due to the combined effects of global climate change and anthropogenic activities. Studies indicate that over the past two decades, the global forest soil carbon pool has experienced a loss of approximately 12%, while nitrogen cycling efficiency has decreased by 15–20%. These changes not only compromise the productivity of forest ecosystems but also diminish their capacity for climate regulation. Furthermore, alterations in the soil carbon-to-nitrogen ratio (C/N) significantly influence the structure and function of microbial communities, thereby modifying nutrient cycling dynamics. In response to this context, understanding the molecular mechanisms underlying carbon and nitrogen cycling in forest soils, developing accurate predictive models, and formulating conservation strategies grounded in ecological processes have emerged as key interdisciplinary research priorities in ecology, soil science, and environmental science. Such efforts are not only essential for providing a scientific foundation to achieve the goal of "carbon neutrality", but also critical for preserving the multifunctionality of forest ecosystems.
This Special Issue aims to collect original research covering the fields of forest ecosystem protection and soil carbon and nitrogen cycling, with a focus on the full-chain research from mechanism analysis to technological innovation and management application, which is in line with the aims of Forests.
For this research topic, original research articles and reviews are welcome. Potential research areas may include (but are not limited to) the following:
- The biogeochemical processes of carbon and nitrogen cycling in forest soils and their microbial driving mechanisms.
- Development and validation of multi-scale (molecular to landscape) soil property prediction models.
- Strategies for carbon and nitrogen regulation in forest conservation and restoration under climate change.
- Application of emerging remote sensing technologies and machine learning in the assessment of soil functions.
- Long-term assessment of forest management practices on soil carbon and nitrogen cycles.
Dr. Shuai Wang
Prof. Dr. Qianlai Zhuang
Prof. Dr. Fengkui Qian
Dr. Hui Li
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- forest ecosystem
- carbon–nitrogen cycle
- soil function prediction
- biogeochemical processes
- machine learning
- landscape management
- adaptation to climate change
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