Feature Papers in Ecosystem, Environment and Climate Change 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: 31 December 2025 | Viewed by 555

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Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
Interests: carbon and nitrogen cycling; carbon sequestration; greenhouse gas emission; non-point source pollution; nitrogen deposition; biochar
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Special Issue Information

Dear Colleagues,

Nutrients cycling in farmlands has significant effects on global warming, water eutrophication as well as food security. Unreasonable fertilizer application, inefficient irrigation, and soil erosion in farmlands have driven carbon, nitrogen and phosphorus in soil leaching into water systems, causing eutrophication, groundwater contamination, and greenhouse gas emissions. It is important to clarify the nutrients cycling processes in farmlands, and to manage the nutrients for enhancing use efficiency, reducing losses to the environment, and improve soil health.

This Special Issue, entitled "Feature Papers in Ecosystem, Environment and Climate Change in Agriculture", aims to publish high-quality papers that advance understanding of nutrient migration processes, mechanisms, their environmental impacts, and mitigation strategies for green production in farmlands. It focuses on the new mechanisms of nutrient cycling, responses of nutrient cycling to climate change, the measurements of nutrient migration fluxes under air–soil–water interface, prediction of nutrient losses using machine learning, and new techniques for managing nutrients cycling to reduce losses and improve soil health in farmlands. The Special Issue also welcomes critical reviews and syntheses of the current state of affairs and emerging themes in ecosystem, environment and climate change in agriculture.

Prof. Dr. Jianlin Shen
Guest Editor

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Keywords

  • ecological process
  • nutrient cycling
  • greenhouse gases emissions
  • non-point source pollution
  • climate change
  • soil health
  • green agriculture
  • pollution mitigation
  • environmental impact
  • machine learning
  • isotope tracing

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Published Papers (1 paper)

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Research

26 pages, 5190 KB  
Article
Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China
by Hao Tang, Qiao Li, Hongfei Tao, Pingan Jiang, Congcang Tang and Xiangzhi Kong
Agriculture 2025, 15(19), 2016; https://doi.org/10.3390/agriculture15192016 - 26 Sep 2025
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Abstract
With global warming, the increasing frequency of drought events threatens the stability of ecosystems, so the development of a rational ecological drought monitoring and assessment model is urgently needed. In this study, an evapotranspiration deficit (ED) was added for the first time into [...] Read more.
With global warming, the increasing frequency of drought events threatens the stability of ecosystems, so the development of a rational ecological drought monitoring and assessment model is urgently needed. In this study, an evapotranspiration deficit (ED) was added for the first time into the construction of an ecological drought index. Considering atmospheric water deficit (WD), soil moisture (SM) and runoff (RF), both the Copula method and a nonparametric method were used to construct a multivariate comprehensive drought index (MCDI) to monitor ecological drought. The MCDI was evaluated using Pearson, actual drought validation, Theil–Sen, Mann–Kendall and ExtraTrees+SHAP methods, in order to assess differences between construction methods, analyze the drivers and sensitivities of ecological drought in Xinjiang, China, and specifically explore the role of ED in ecological drought. The results showed that (1) ED based on the ratio form is more suitable for capturing SM changes; (2) the performance of the composite drought index was improved in all aspects when cumulative effects were considered, and the ecological drought index based on the nonparametric method was superior to the index using the Copula method; (3) soil moisture was identified as the main contributor to ecological drought in Xinjiang, with the strongest synergistic effect occurring between SM and ED; and (4) the sensitivity of ecological drought to soil moisture within the arid regions increased nonlinearly along the decreasing SM gradient. In addition, the sensitivity to all drivers increased over time, with the largest increase observed for RF, followed by SM and then ED. The findings of this paper provide a useful reference for constructing a comprehensive drought index at the global scale, since the nonparametric method requires considerably fewer computational resources compared with the Copula method. In addition, the identified synergistic effect of ED and SM offers a new theoretical basis for ecological drought prevention and management in arid regions. Full article
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