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Assessing Ecosystem Respiration in Global Carbon Cycle: Digital Application in...
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Assessing Ecosystem Respiration in Global Carbon Cycle: Digital Application in Agriculture

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Ecosystem, Environment and Climate Change in Agriculture".

Deadline for manuscript submissions: 25 February 2026 | Viewed by 982

Special Issue Editors

Prof. Dr. Jinshi Jian

E-Mail Website
Guest Editor
College of Soil and Water Conservation Science and Engineering, Northwest A&F University, Xianyang 712100, China
Interests: soil respiration; soil health; soil erosion; global climate change; soil carbon cycle
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qianfeng Wang

E-Mail Website
Guest Editor
College of Environment & Safety Engineering, Fuzhou University, Fuzhou 350108, China
Interests: climate change; drought; remote sensing; vegetation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ecosystem respiration (Reco), a critical flux of carbon from terrestrial ecosystems to the atmosphere, plays a key role in the global carbon cycle. Although agricultural landscapes are major contributors to carbon exchange, quantifying Reco in these systems remains challenging due to their high spatiotemporal variability. The emergence of digital technologies now offers promising avenues to overcome these limitations and enhance the accuracy of Reco estimation in agriculture.

This Special Issue aims to highlight innovative research on the assessment of ecosystem respiration in agricultural systems and its implications for the global carbon cycle. We are particularly interested in the application of digital technologies, including remote sensing, data synthesis, and artificial intelligence, to advance the monitoring, modeling, and understanding of Reco in agricultural landscapes. The scope of this Special Issue encompasses studies that leverage digital tools to enhance the spatiotemporal resolution, accuracy, and scalability of Reco estimates.

We will emphasize research that integrates multi-source data (e.g., from flux towers, satellites, and drones), employs machine learning and AI techniques, and develops novel digital approaches for quantifying Reco and its drivers. Key themes for consideration include the use of remote sensing to derive respiration-related proxies, the application of big data analytics for pattern recognition in heterogeneous agricultural systems, and the fusion of digital data with process-based models to improve predictions of carbon cycling under changing climate conditions.

We invite original research articles, reviews, and methodological papers. Topics of interest include, but are not limited to, the following: digital mapping of Reco using remote sensing; AI/ML applications for Reco prediction; data-model integration in agricultural carbon cycling; the impact of management practices on respiration; and the regional- and global-level scalability of field measurements. Interdisciplinary studies combining agronomy, ecology, data science, and remote sensing are particularly encouraged.

Prof. Dr. Jinshi Jian
Prof. Dr. Qianfeng Wang
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. Agriculture is an international peer-reviewed open access semimonthly 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

  • ecosystem respiration
  • soil respiration
  • global change
  • machine learning application
  • remote sensing
  • agriculture

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Published Papers (1 paper)

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Review

29 pages, 6548 KB  
Review
Remote Sensing-Based Advances in Climate Change Impacts on Agricultural Ecosystem Respiration
by Xingshuai Mei, Tongde Chen, Jianjun Li, Fengqiuli Zhang, Jiarong Hou and Keding Sheng
Agriculture 2025, 15(23), 2509; https://doi.org/10.3390/agriculture15232509 - 3 Dec 2025
Viewed by 657
Abstract
Global climate change is exerting a growing impact on agricultural ecosystems. Accurately assessing the spatiotemporal dynamics of agricultural ecosystem respiration and its response mechanisms to climate has therefore emerged as a critical issue in agricultural carbon cycle research and climate change response. It [...] Read more.
Global climate change is exerting a growing impact on agricultural ecosystems. Accurately assessing the spatiotemporal dynamics of agricultural ecosystem respiration and its response mechanisms to climate has therefore emerged as a critical issue in agricultural carbon cycle research and climate change response. It should be noted that the ‘agro-ecosystem’ referred to in this study covers two major types: one is the farmland agro-ecosystem dominated by crop planting (such as farmland, orchard and other artificial management systems), and the other is the grassland agro-ecosystem dominated by herbaceous plants and managed by humans (such as grazing grassland and mowing grassland). Remote sensing technology provides a new way to break through the limitations of traditional ground observation by virtue of its advantages of large-scale and continuous monitoring. Based on the CiteSpace bibliometric method, this study focused on the key time window of 2021–2025, systematically searched the core collection of Web of Science, and finally included 222 related literature. This period marks the initial stage of the rise and rapid development of this interdisciplinary field, enabling us to capture the formation of its knowledge structure and the evolution of its research paradigm from the source. Through the quantitative analysis of this literature, it aims to reveal the research hotspots, development paths and frontier trends in this field. The results show that China occupies a dominant position in this field (135 articles). The evolution of research shows a three-stage development characterized by “technology-driven-method fusion-system coupling,” which is divided into the initial development period (2021–2022), the rapid growth period (2023–2024) and the deepening development period (2025) (because 2025 has not yet ended, this stage is a preliminary discussion). Keyword clustering analysis identified 13 important research directions, including machine learning (# 0 clustering), permafrost (# 1 clustering) and carbon flux (# 2 clustering). It is found that the deep integration of artificial intelligence and remote sensing data is promoting the transformation of research methods from traditional inversion to intelligent modeling. At the same time, the attention to alpine grassland and other ecosystems also reflects the trend that the research frontier extends to the interaction zone between the agricultural ecosystem and the natural environment. Future research should prioritize three key directions: building multi-scale monitoring networks, developing “grey box” models that integrate mechanisms and data fusion, and evaluating the carbon emission reduction efficiency of agricultural management practices. These efforts will provide a theoretical basis for carbon management and climate adaptation in agricultural ecosystems, as well as scientific and technological support for achieving global agricultural sustainable development goals (specifically, SDG13 on climate action and SDG15 on terrestrial ecosystem conservation). Full article
(This article belongs to the Special Issue Assessing Ecosystem Respiration in Global Carbon Cycle: Digital Application in Agriculture)
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