Forest/Urban Forest Systems under Climate Change: Carbon Dynamics, Ecological Functions, and Sustainable Management

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Meteorology and Climate Change".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 962

Special Issue Editors


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Guest Editor
College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China
Interests: ecological restoration; wastewater treatment; soil remediation
Special Issues, Collections and Topics in MDPI journals
College of Environmental Science and Technology, Central South University of Forestry and Technology, Changsha, China
Interests: heavy metals; microbiology; ecosystem restoration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, the impact of climate change (like global warming, changes in precipitation regime, and an extreme global climate) on plant communities is a major potential threat to global forest plant biodiversity and plant ecological functions. However, the distribution and survival of species and ecological functions of forest/urban forest ecosystems under climate change have not been closely studied. Under climate change, forest plants can survive, adapt, or die, and the response of plant communities to climate change may be the comprehensive result of the interaction of various components of the forest ecosystem, and the study of this response can help predict and manage the continuous evolution of forest ecosystems. Global climate change makes forests more important than ever before. Restoring forest ecosystems and building new plantations can mitigate climate change by slowing the accumulation of carbon dioxide in the atmosphere. Forest systems can absorb atmospheric carbon dioxide, producing large carbon sinks and having low costs to maintain. Accurate estimation of forest biomass/carbon storage and monitoring of carbon dynamics are essential to simulate the global carbon cycle, quantify carbon flux, and achieve carbon neutrality goals. Advanced artificial intelligence (machine learning, deep learning, transfer learning) and large amounts of remote sensing data provide powerful tools for accurately estimating forest biomass/carbon stocks and monitoring carbon dynamics. The fixation, transport, distribution, stabilization, and storage of carbon in forest/urban forest ecosystems has received much attention due to climate change. A deeper understanding of these relationships with environmental factors will help to understand the complex responses of forest ecosystems to projected succession changes caused by climate fluctuations. Therefore, it is extremely necessary to study forest ecosystems (growth models), develop forest plant growth models to adapt to climate change, and provide ecosystem service analysis. Economic and policy analysis is essential for forest management, coordinated economic growth, and environmental protection. Innovative approaches, policy tools, and innovative digital approaches that explore the ecosystem services and economic value provided by forests are highly effective in achieving the sustainable development of forest ecosystems and can influence forest growth trajectories, promoting resilience and diversity.

Submissions may cover, but should not be limited to: the responses of forest plant species and plant communities to climate change; carbon fixation, transport, and storage in forest ecosystems and the economic value of forest carbon sinks; the application of remote sensing and related technologies in assessing forest biomass and monitoring carbon dynamics; the development of biomass carbon assessment methods and modelling, and the use of all remote sensing platforms to analyze or monitor changes in forest ecosystem types; and the interaction between economics and policy in sustainable forest management. In the meantime, contributions to this Special Issue are encouraged using any software or application, including traditional and advanced machine learning methods.

Dr. Junyuan Guo
Dr. Chao Huang
Guest Editors

Manuscript Submission Information

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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
  • ecosystem services
  • sustainable forest management
  • climate change
  • green policies
  • multi-source remote sensing
  • artificial intelligence
  • carbon dynamic
  • carbon allocation
  • carbon transport
  • carbon storage
  • carbon sinks
  • GIS

Published Papers (1 paper)

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Research

19 pages, 5290 KiB  
Article
The Application of Geographic Information System in Urban Forest Ecological Compensation and Sustainable Development Evaluation
by Liwei An, Guifeng Liu and Meiling Hou
Forests 2024, 15(2), 285; https://doi.org/10.3390/f15020285 - 02 Feb 2024
Viewed by 714
Abstract
Urban forests can alleviate the urban heat island effect, improve air quality, and improve residents’ mental health. By studying urban forests, these resources can be better used and managed to create more livable urban environments. Therefore, the urban forest in the Taishan region [...] Read more.
Urban forests can alleviate the urban heat island effect, improve air quality, and improve residents’ mental health. By studying urban forests, these resources can be better used and managed to create more livable urban environments. Therefore, the urban forest in the Taishan region is taken as the research object, and the ecological compensation and sustainable development of urban forest in Tai’an City are deeply analyzed by GIS. It divided the area into forest land, water bodies, wetlands, grasslands, and shrubs as the basic ecosystem types. And through secondary interpretation and combination, a complete urban forest information database was established. To evaluate the comprehensive benefits of urban forests, the analytic hierarchy process was utilized to establish a corresponding evaluation index system. Based on the assessment outcomes of the comprehensive benefits of urban forests in the area, a standard accounting method for urban forest ecological compensation was proposed. The results showed that each index of the comprehensive benefits of urban forests and the random consistency ratio were both less than 0.1. This indicated that the matrix calculation results of various indicators of urban forest comprehensive benefits had good consistency. At the target level, the comprehensive evaluation score of urban forests in the study area was 7.69. At the factor level, the weight value of the urban forest landscape structure was 0.675, and the comprehensive score was 7.62. The weight value of urban forest comprehensive benefits was 0.325, and the comprehensive score was 7.82. The quantitative weight value of urban forest greening in the study area was 0.6138, with a comprehensive score of 7.57. Based on the analysis of the issues in urban forests and ecological compensation in the research area of Tai’an City, corresponding ecological compensation strategies have been proposed. It is of great value to study the urban forest of Tai’an city, which can help to formulate more effective urban planning and sustainable development strategies. The research results can also provide a valuable reference and inspiration for the improvement of urban forest ecological environment and biodiversity protection in other areas. Full article
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